tangyx/MetaQA_overall · Datasets at Hugging Face

data_source stringclasses 1 value	prompt stringlengths 1.02k 13.9k	ability stringclasses 1 value	reward_model dict	extra_info dict
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36212, DRAMA 16138, JACOB GENTRY 6180, LOVE STORY 19613, MICHAEL HALL D'ADDARIO 19916, MONSIEUR LAZHAR 31312, PEOPLE LIKE US 28095, THE SIGNAL src, edge_attr, dst 6180, has_genre, 36212 19916, has_genre, 36212 31312, has_genre, 36212 31312, has_tags, 36212 31312, starred_actors, 19613 28095, directed_by, 16138 28095, has_tags, 6180 28095, written_by, 16138 Question: For what reason are JACOB GENTRY, MICHAEL HALL D'ADDARIO, and MONSIEUR LAZHAR associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JACOB GENTRY", "MICHAEL HALL D'ADDARIO", "MONSIEUR LAZHAR" ], "valid_edges": [ [ "LOVE STORY", "has_genre", "DRAMA" ], [ "MONSIEUR LAZHAR", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_tags", "DRAMA" ], [ "PEOPLE LIKE US", "starred_actors", "MICHAEL HALL D'ADDARIO" ], [ "THE SIGNAL", "directed_by", "JACOB GENTRY" ], [ "THE SIGNAL", "has_tags", "LOVE STORY" ], [ "THE SIGNAL", "written_by", "JACOB GENTRY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 17254, AMERICAN BEAUTY 30463, COMEDY 7373, DALE VAN EVERY 36212, DRAMA 9624, IT'S A BOY GIRL THING 1555, LITTLE BLACK BOOK 5252, MID-LIFE CRISIS 37544, NICK HURRAN 3627, THE TALK OF THE TOWN 5147, VIRTUAL SEXUALITY src, edge_attr, dst 17254, has_genre, 36212 17254, has_tags, 36212 17254, has_tags, 5252 17254, release_year, 8486 9624, directed_by, 37544 9624, has_genre, 30463 1555, directed_by, 37544 1555, has_genre, 30463 3627, has_genre, 30463 3627, has_genre, 36212 3627, written_by, 7373 5147, directed_by, 37544 5147, release_year, 8486 Question: How are DALE VAN EVERY, MID-LIFE CRISIS, and NICK HURRAN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DALE VAN EVERY", "MID-LIFE CRISIS", "NICK HURRAN" ], "valid_edges": [ [ "AMERICAN BEAUTY", "has_genre", "DRAMA" ], [ "AMERICAN BEAUTY", "has_tags", "DRAMA" ], [ "AMERICAN BEAUTY", "has_tags", "MID-LIFE CRISIS" ], [ "AMERICAN BEAUTY", "release_year", "1999" ], [ "IT'S A BOY GIRL THING", "directed_by", "NICK HURRAN" ], [ "IT'S A BOY GIRL THING", "has_genre", "COMEDY" ], [ "LITTLE BLACK BOOK", "directed_by", "NICK HURRAN" ], [ "LITTLE BLACK BOOK", "has_genre", "COMEDY" ], [ "THE TALK OF THE TOWN", "has_genre", "COMEDY" ], [ "THE TALK OF THE TOWN", "has_genre", "DRAMA" ], [ "THE TALK OF THE TOWN", "written_by", "DALE VAN EVERY" ], [ "VIRTUAL SEXUALITY", "directed_by", "NICK HURRAN" ], [ "VIRTUAL SEXUALITY", "release_year", "1999" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 20719, A TIME FOR DRUNKEN HORSES 23160, BELLY 32815, BLACKBOARDS 36212, DRAMA 35079, HYPE WILLIAMS 15321, JUN FALKENSTEIN 13725, KURDISH 37753, THE TIGGER MOVIE 23247, TRIAGE 29947, TURTLES CAN FLY 22214, WAR src, edge_attr, dst 20719, has_genre, 22214 20719, in_language, 13725 20719, release_year, 6776 23160, directed_by, 35079 23160, has_genre, 36212 23160, written_by, 35079 32815, has_genre, 22214 32815, in_language, 13725 32815, release_year, 6776 37753, directed_by, 15321 37753, release_year, 6776 37753, written_by, 15321 23247, has_genre, 36212 23247, has_genre, 22214 23247, in_language, 13725 29947, has_genre, 36212 29947, has_genre, 22214 29947, in_language, 13725 Question: For what reason are HYPE WILLIAMS, JUN FALKENSTEIN, and KURDISH associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HYPE WILLIAMS", "JUN FALKENSTEIN", "KURDISH" ], "valid_edges": [ [ "A TIME FOR DRUNKEN HORSES", "has_genre", "WAR" ], [ "A TIME FOR DRUNKEN HORSES", "in_language", "KURDISH" ], [ "A TIME FOR DRUNKEN HORSES", "release_year", "2000" ], [ "BELLY", "directed_by", "HYPE WILLIAMS" ], [ "BELLY", "has_genre", "DRAMA" ], [ "BELLY", "written_by", "HYPE WILLIAMS" ], [ "BLACKBOARDS", "has_genre", "WAR" ], [ "BLACKBOARDS", "in_language", "KURDISH" ], [ "BLACKBOARDS", "release_year", "2000" ], [ "THE TIGGER MOVIE", "directed_by", "JUN FALKENSTEIN" ], [ "THE TIGGER MOVIE", "release_year", "2000" ], [ "THE TIGGER MOVIE", "written_by", "JUN FALKENSTEIN" ], [ "TRIAGE", "has_genre", "DRAMA" ], [ "TRIAGE", "has_genre", "WAR" ], [ "TRIAGE", "in_language", "KURDISH" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "has_genre", "WAR" ], [ "TURTLES CAN FLY", "in_language", "KURDISH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4981, 1965 11832, A CHARLIE BROWN CHRISTMAS 6718, A FAREWELL TO ARMS 12649, A LITTLE ROMANCE 8221, A MAN ESCAPED 24319, A PASSAGE TO INDIA 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 10341, ADVENTURES OF DON JUAN 28463, AFTER THE FOX 26641, ALBERT CAMUS 29638, ALICE IN WONDERLAND 13573, ANNA CHRISTIE 17157, ARABIAN NIGHTS 34734, BATTLE OF THE BULGE 10045, BD-R 38657, BEAT THE DEVIL 4592, BEAU TRAVAIL 15771, BENGAZI 27938, BRIGITTE BARDOT 21584, BUNNY LAKE IS MISSING 1040, CAPTAIN BLOOD 5840, CERTIFIED COPY 6903, CHARIOTS OF FIRE 25344, CONFIDENTIALLY YOURS 34792, CONTEMPT 16536, CYRANO DE BERGERAC 23205, DARLING 21286, DAVID COPPERFIELD 23396, DIAL M FOR MURDER 11249, DIARY OF A COUNTRY PRIEST 16041, DJANGO UNCHAINED 5881, ELEPHANT BOY 31783, ENGLISH 24540, EYES WITHOUT A FACE 819, FIST OF THE NORTH STAR 26308, FLIPPER 6012, FRENCH 9003, FUNNY GAMES 5527, GIGI 17384, GUNGA DIN 20941, HAMLET 15896, HOW TO STUFF A WILD BIKINI 12087, HOWL'S MOVING CASTLE 26383, I CONFESS 27285, I WAS A MALE WAR BRIDE 7539, IVANHOE 847, JACK THE GIANT KILLER 21922, JANE EYRE 2527, JEANNE MOREAU 803, JERRY LEWIS 20567, JOHN CARTER 35705, JOURNEY TO THE CENTER OF THE EARTH 38986, JUNGLE BOOK 19098, KING KONG 14209, KING OF HEARTS 14156, KING SOLOMON'S MINES 26649, KISMET 37100, KNIGHTS OF THE ROUND TABLE 33519, LA HAINE 36940, LABYRINTH 30029, LAWRENCE OF ARABIA 35149, LE BEAU SERGE 39572, LES COUSINS 30157, LOLA 32275, LORD OF THE FLIES 14433, LOUIS MALLE 27050, MAN OF LA MANCHA 20579, MARAT/SADE 16925, MAYERLING 6543, MODEL SHOP 31657, MON ONCLE 31661, MY FAIR LADY 12358, MY FAVORITE SEASON 14797, O BROTHER, WHERE ART THOU? 27496, ONE MILLION YEARS B.C. 36988, OPERATION CROSSBOW 29693, PICKPOCKET 33032, PORT OF SHADOWS 15651, PREHISTORIC WOMEN 24745, PURPLE NOON 5897, REPULSION 15938, RIFIFI 15873, ROBIN AND MARIAN 2738, ROMEO AND JULIET 35586, SAHARA 6603, SEX IS COMEDY 27626, SHEENA 31316, SHERLOCK HOLMES AND THE SECRET WEAPON 8436, SPIRITS OF THE DEAD 15194, STORY OF WOMEN 11699, TARZAN THE APE MAN 18715, TARZAN'S NEW YORK ADVENTURE 21608, THE ADVENTURES OF HUCKLEBERRY FINN 24625, THE APARTMENT 15003, THE BATTLE OF ALGIERS 37980, THE BEDFORD INCIDENT 34737, THE BRIDE WORE BLACK 3354, THE BROTHERS GRIMM 18855, THE CADDY 14222, THE CANTERVILLE GHOST 7639, THE CHARGE OF THE LIGHT BRIGADE 18651, THE CORSICAN BROTHERS 21330, THE CRIMSON PIRATE 24990, THE CURSE OF FRANKENSTEIN 16800, THE DECEIVERS 39794, THE DISORDERLY ORDERLY 15154, THE FAMILY JEWELS 38631, THE FLAME AND THE ARROW 11635, THE FOUR FEATHERS 9166, THE GUNS OF NAVARONE 15600, THE HALLELUJAH TRAIL 38257, THE HAPPY TIME 15198, THE HUNCHBACK OF NOTRE DAME 25529, THE ILLUSIONIST 6836, THE IMMORTAL STORY 4091, THE LADY VANISHES 32231, THE LAND THAT TIME FORGOT 31569, THE LOVE PARADE 34018, THE LOVED ONE 4182, THE MAN IN THE IRON MASK 33513, THE MAN WHO LOVED WOMEN 13295, THE MARK OF ZORRO 4029, THE MASK OF FU MANCHU 2432, THE MASTER OF BALLANTRAE 32297, THE MERRY WIDOW 26820, THE MUMMY 1295, THE NUTTY PROFESSOR 5575, THE PEOPLE THAT TIME FORGOT 24512, THE PHANTOM TOLLBOOTH 22486, THE PRINCE AND THE PAUPER 31851, THE PRISONER OF ZENDA 18274, THE ROSE TATTOO 8477, THE SCARLET PIMPERNEL 11265, THE SEA HAWK 30746, THE SECRET LIFE OF WALTER MITTY 25495, THE SHOP ON MAIN STREET 8304, THE SILVER CHALICE 31647, THE SON OF THE SHEIK 34579, THE SPY WHO CAME IN FROM THE COLD 17143, THE STRANGER 7816, THE THREE MUSKETEERS 38808, THE TRAIN 983, THE TREASURE OF THE SIERRA MADRE 30491, THE TRIAL 13722, THE TRIAL OF JOAN OF ARC 29678, THE UMBRELLAS OF CHERBOURG 19255, THE VALACHI PAPERS 17568, THE VANISHING 12308, THE VIKINGS 27609, THE WIND AND THE LION 14471, THIS HAPPY BREED 24789, TO HAVE AND HAVE NOT 25443, TOM JONES 6724, TOM SAWYER 3029, TRIPLE CROSS 4378, VICTIM 30965, VILLAGE OF THE GIANTS 11659, VIVA MARIA! 22844, WENT THE DAY WELL? 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 6037, WITCHFINDER GENERAL 38760, Z 23675, ZERO FOR CONDUCT src, edge_attr, dst 11832, has_tags, 10045 11832, release_year, 4981 6718, has_tags, 10045 6718, in_language, 31783 12649, has_tags, 10045 12649, in_language, 6012 8221, has_tags, 10045 8221, has_tags, 6012 8221, in_language, 6012 24319, has_tags, 10045 24319, in_language, 31783 16054, has_genre, 4763 16054, has_tags, 4763 16054, has_tags, 10045 10341, has_genre, 4763 10341, has_tags, 10045 28463, has_tags, 10045 28463, in_language, 31783 29638, has_genre, 4763 29638, has_tags, 10045 29638, in_language, 31783 13573, has_tags, 10045 13573, in_language, 31783 17157, has_genre, 4763 17157, has_tags, 10045 34734, has_tags, 10045 34734, release_year, 4981 38657, has_genre, 4763 38657, has_tags, 10045 4592, has_tags, 10045 4592, in_language, 6012 15771, has_genre, 4763 15771, has_tags, 10045 21584, has_tags, 10045 21584, release_year, 4981 1040, has_genre, 4763 1040, has_tags, 4763 1040, has_tags, 10045 5840, in_language, 31783 5840, in_language, 6012 6903, has_tags, 10045 6903, in_language, 31783 25344, has_tags, 10045 25344, in_language, 6012 34792, has_tags, 10045 34792, starred_actors, 27938 16536, has_tags, 10045 16536, has_tags, 6012 16536, in_language, 31783 16536, in_language, 6012 23205, has_tags, 10045 23205, release_year, 4981 21286, has_genre, 4763 21286, has_tags, 10045 23396, has_tags, 10045 23396, in_language, 31783 11249, has_tags, 10045 11249, in_language, 6012 16041, has_tags, 10045 16041, in_language, 31783 5881, has_genre, 4763 5881, has_tags, 10045 24540, has_tags, 10045 24540, in_language, 6012 819, has_tags, 10045 819, in_language, 31783 26308, has_genre, 4763 26308, has_tags, 10045 9003, has_tags, 10045 9003, in_language, 31783 5527, has_tags, 10045 5527, in_language, 31783 5527, in_language, 6012 17384, has_genre, 4763 17384, has_tags, 10045 20941, has_tags, 10045 20941, in_language, 31783 15896, has_tags, 10045 15896, release_year, 4981 12087, has_genre, 4763 12087, has_tags, 4763 12087, has_tags, 10045 26383, has_tags, 10045 26383, in_language, 6012 27285, has_tags, 10045 27285, in_language, 6012 7539, has_genre, 4763 7539, has_tags, 10045 847, has_genre, 4763 847, has_tags, 10045 847, in_language, 31783 21922, has_tags, 10045 21922, in_language, 31783 21922, in_language, 6012 20567, has_genre, 4763 20567, has_tags, 10045 35705, has_genre, 4763 35705, has_tags, 4763 35705, has_tags, 10045 38986, has_genre, 4763 38986, has_tags, 10045 19098, has_genre, 4763 19098, has_tags, 4763 19098, has_tags, 10045 14209, has_tags, 10045 14209, in_language, 6012 14156, has_genre, 4763 14156, has_tags, 4763 14156, has_tags, 10045 26649, has_tags, 10045 26649, in_language, 31783 37100, has_genre, 4763 37100, has_tags, 10045 33519, has_tags, 10045 33519, has_tags, 6012 33519, in_language, 6012 36940, has_genre, 4763 36940, has_tags, 4763 36940, has_tags, 10045 30029, has_genre, 4763 30029, has_tags, 10045 35149, has_tags, 10045 35149, in_language, 6012 39572, has_tags, 10045 39572, in_language, 6012 30157, has_tags, 10045 30157, in_language, 6012 32275, has_tags, 10045 32275, in_language, 31783 27050, has_tags, 10045 27050, in_language, 31783 20579, has_tags, 10045 20579, in_language, 31783 16925, has_tags, 10045 16925, in_language, 31783 16925, in_language, 6012 6543, has_tags, 10045 6543, in_language, 31783 31657, has_tags, 10045 31657, in_language, 6012 31661, has_tags, 10045 31661, in_language, 31783 12358, has_tags, 10045 12358, in_language, 6012 14797, has_genre, 4763 14797, has_tags, 4763 14797, has_tags, 10045 27496, has_genre, 4763 27496, has_tags, 10045 36988, has_tags, 10045 36988, release_year, 4981 29693, has_tags, 10045 29693, in_language, 6012 33032, has_tags, 10045 33032, in_language, 6012 15651, has_genre, 4763 15651, has_tags, 10045 24745, has_tags, 10045 24745, in_language, 6012 5897, has_tags, 10045 5897, in_language, 31783 5897, release_year, 4981 15938, has_tags, 10045 15938, in_language, 6012 15873, has_genre, 4763 15873, has_tags, 10045 2738, has_tags, 10045 2738, in_language, 31783 35586, has_genre, 4763 35586, has_tags, 10045 6603, has_tags, 10045 6603, in_language, 6012 27626, has_genre, 4763 27626, has_tags, 10045 31316, has_genre, 4763 31316, has_tags, 10045 8436, directed_by, 14433 8436, has_tags, 10045 8436, in_language, 31783 8436, in_language, 6012 8436, starred_actors, 27938 8436, written_by, 14433 15194, has_tags, 10045 15194, in_language, 6012 11699, has_genre, 4763 11699, has_tags, 10045 18715, has_genre, 4763 18715, has_tags, 10045 21608, has_genre, 4763 21608, has_tags, 10045 24625, has_tags, 10045 24625, in_language, 6012 15003, has_tags, 10045 15003, has_tags, 6012 15003, in_language, 6012 37980, has_tags, 10045 37980, release_year, 4981 34737, has_tags, 10045 34737, in_language, 6012 34737, starred_actors, 2527 3354, has_genre, 4763 3354, has_tags, 4763 3354, has_tags, 10045 3354, in_language, 6012 18855, has_tags, 10045 18855, starred_actors, 803 14222, has_tags, 10045 14222, in_language, 31783 7639, has_genre, 4763 7639, has_tags, 10045 18651, has_tags, 10045 18651, in_language, 31783 21330, has_genre, 4763 21330, has_tags, 10045 24990, has_tags, 10045 24990, in_language, 31783 16800, has_genre, 4763 16800, has_tags, 10045 39794, starred_actors, 803 15154, directed_by, 803 15154, release_year, 4981 15154, starred_actors, 803 15154, written_by, 803 38631, has_genre, 4763 38631, has_tags, 10045 11635, has_genre, 4763 11635, has_tags, 10045 9166, has_genre, 4763 9166, has_tags, 10045 15600, has_tags, 10045 15600, release_year, 4981 38257, has_tags, 10045 38257, in_language, 6012 15198, has_tags, 10045 15198, in_language, 31783 15198, in_language, 6012 25529, has_tags, 10045 25529, in_language, 6012 6836, has_tags, 10045 6836, in_language, 6012 6836, starred_actors, 2527 4091, has_tags, 10045 4091, in_language, 31783 32231, has_genre, 4763 32231, has_tags, 4763 32231, has_tags, 10045 31569, has_tags, 10045 31569, in_language, 6012 34018, has_tags, 10045 34018, release_year, 4981 4182, has_genre, 4763 4182, has_tags, 4763 4182, has_tags, 10045 33513, has_tags, 10045 33513, in_language, 6012 13295, has_genre, 4763 13295, has_tags, 10045 4029, has_genre, 4763 4029, has_tags, 10045 2432, has_genre, 4763 2432, has_tags, 10045 32297, has_tags, 10045 32297, in_language, 6012 26820, has_genre, 4763 26820, has_tags, 4763 26820, has_tags, 10045 1295, directed_by, 803 1295, has_tags, 10045 1295, has_tags, 803 1295, starred_actors, 803 1295, written_by, 803 5575, has_genre, 4763 5575, has_tags, 10045 24512, has_genre, 4763 24512, has_tags, 10045 22486, has_genre, 4763 22486, has_tags, 10045 31851, has_genre, 4763 31851, has_tags, 10045 18274, has_tags, 10045 18274, in_language, 31783 8477, has_genre, 4763 8477, has_tags, 10045 8477, in_language, 31783 8477, in_language, 6012 11265, has_tags, 10045 11265, in_language, 31783 30746, has_genre, 4763 30746, has_tags, 10045 30746, in_language, 31783 25495, has_tags, 10045 25495, release_year, 4981 8304, has_tags, 10045 8304, in_language, 31783 31647, has_genre, 4763 31647, has_tags, 10045 34579, has_tags, 10045 34579, in_language, 31783 34579, release_year, 4981 17143, has_tags, 10045 17143, written_by, 26641 7816, has_genre, 4763 7816, has_tags, 10045 38808, has_tags, 10045 38808, starred_actors, 2527 983, has_genre, 4763 983, has_tags, 10045 983, in_language, 31783 30491, has_tags, 10045 30491, starred_actors, 2527 13722, has_tags, 10045 13722, in_language, 6012 29678, has_tags, 10045 29678, has_tags, 6012 29678, in_language, 6012 19255, has_tags, 10045 19255, in_language, 31783 17568, has_tags, 10045 17568, in_language, 31783 17568, in_language, 6012 12308, has_genre, 4763 12308, has_tags, 10045 27609, has_genre, 4763 27609, has_tags, 10045 14471, has_tags, 10045 14471, in_language, 31783 24789, has_genre, 4763 24789, has_tags, 10045 25443, has_genre, 4763 25443, has_tags, 10045 6724, has_genre, 4763 6724, has_tags, 10045 3029, has_tags, 10045 3029, in_language, 6012 4378, has_tags, 10045 4378, in_language, 31783 30965, has_tags, 10045 30965, release_year, 4981 11659, directed_by, 14433 11659, has_genre, 4763 11659, has_tags, 10045 11659, has_tags, 27938 11659, has_tags, 6012 11659, has_tags, 2527 11659, has_tags, 14433 11659, in_language, 31783 11659, in_language, 6012 11659, release_year, 4981 11659, starred_actors, 27938 11659, starred_actors, 2527 11659, written_by, 14433 22844, has_tags, 10045 22844, in_language, 31783 35212, has_tags, 10045 35212, in_language, 31783 6037, has_tags, 10045 6037, in_language, 31783 38760, has_tags, 10045 38760, in_language, 6012 23675, has_tags, 10045 23675, has_tags, 6012 23675, in_language, 6012 Question: In what context are ALBERT CAMUS, THE DISORDERLY ORDERLY, and VIVA MARIA! connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALBERT CAMUS", "THE DISORDERLY ORDERLY", "VIVA MARIA!" ], "valid_edges": [ [ "A CHARLIE BROWN CHRISTMAS", "has_tags", "BD-R" ], [ "A CHARLIE BROWN CHRISTMAS", "release_year", "1965" ], [ "A FAREWELL TO ARMS", "has_tags", "BD-R" ], [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "A LITTLE ROMANCE", "has_tags", "BD-R" ], [ "A LITTLE ROMANCE", "in_language", "FRENCH" ], [ "A MAN ESCAPED", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "FRENCH" ], [ "A MAN ESCAPED", "in_language", "FRENCH" ], [ "A PASSAGE TO INDIA", "has_tags", "BD-R" ], [ "A PASSAGE TO INDIA", "in_language", "ENGLISH" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "BD-R" ], [ "ADVENTURES OF DON JUAN", "has_genre", "ADVENTURE" ], [ "ADVENTURES OF DON JUAN", "has_tags", "BD-R" ], [ "AFTER THE FOX", "has_tags", "BD-R" ], [ "AFTER THE FOX", "in_language", "ENGLISH" ], [ "ALICE IN WONDERLAND", "has_genre", "ADVENTURE" ], [ "ALICE IN WONDERLAND", "has_tags", "BD-R" ], [ "ALICE IN WONDERLAND", "in_language", "ENGLISH" ], [ "ANNA CHRISTIE", "has_tags", "BD-R" ], [ "ANNA CHRISTIE", "in_language", "ENGLISH" ], [ "ARABIAN NIGHTS", "has_genre", "ADVENTURE" ], [ "ARABIAN NIGHTS", "has_tags", "BD-R" ], [ "BATTLE OF THE BULGE", "has_tags", "BD-R" ], [ "BATTLE OF THE BULGE", "release_year", "1965" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_tags", "BD-R" ], [ "BEAU TRAVAIL", "has_tags", "BD-R" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BENGAZI", "has_genre", "ADVENTURE" ], [ "BENGAZI", "has_tags", "BD-R" ], [ "BUNNY LAKE IS MISSING", "has_tags", "BD-R" ], [ "BUNNY LAKE IS MISSING", "release_year", "1965" ], [ "CAPTAIN BLOOD", "has_genre", "ADVENTURE" ], [ "CAPTAIN BLOOD", "has_tags", "ADVENTURE" ], [ "CAPTAIN BLOOD", "has_tags", "BD-R" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "in_language", "FRENCH" ], [ "CHARIOTS OF FIRE", "has_tags", "BD-R" ], [ "CHARIOTS OF FIRE", "in_language", "ENGLISH" ], [ "CONFIDENTIALLY YOURS", "has_tags", "BD-R" ], [ "CONFIDENTIALLY YOURS", "in_language", "FRENCH" ], [ "CONTEMPT", "has_tags", "BD-R" ], [ "CONTEMPT", "starred_actors", "BRIGITTE BARDOT" ], [ "CYRANO DE BERGERAC", "has_tags", "BD-R" ], [ "CYRANO DE BERGERAC", "has_tags", "FRENCH" ], [ "CYRANO DE BERGERAC", "in_language", "ENGLISH" ], [ "CYRANO DE BERGERAC", "in_language", "FRENCH" ], [ "DARLING", "has_tags", "BD-R" ], [ "DARLING", "release_year", "1965" ], [ "DAVID COPPERFIELD", "has_genre", "ADVENTURE" ], [ "DAVID COPPERFIELD", "has_tags", "BD-R" ], [ "DIAL M FOR MURDER", "has_tags", "BD-R" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DIARY OF A COUNTRY PRIEST", "has_tags", "BD-R" ], [ "DIARY OF A COUNTRY PRIEST", "in_language", "FRENCH" ], [ "DJANGO UNCHAINED", "has_tags", "BD-R" ], [ "DJANGO UNCHAINED", "in_language", "ENGLISH" ], [ "ELEPHANT BOY", "has_genre", "ADVENTURE" ], [ "ELEPHANT BOY", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "in_language", "FRENCH" ], [ "FIST OF THE NORTH STAR", "has_tags", "BD-R" ], [ "FIST OF THE NORTH STAR", "in_language", "ENGLISH" ], [ "FLIPPER", "has_genre", "ADVENTURE" ], [ "FLIPPER", "has_tags", "BD-R" ], [ "FUNNY GAMES", "has_tags", "BD-R" ], [ "FUNNY GAMES", "in_language", "ENGLISH" ], [ "GIGI", "has_tags", "BD-R" ], [ "GIGI", "in_language", "ENGLISH" ], [ "GIGI", "in_language", "FRENCH" ], [ "GUNGA DIN", "has_genre", "ADVENTURE" ], [ "GUNGA DIN", "has_tags", "BD-R" ], [ "HAMLET", "has_tags", "BD-R" ], [ "HAMLET", "in_language", "ENGLISH" ], [ "HOW TO STUFF A WILD BIKINI", "has_tags", "BD-R" ], [ "HOW TO STUFF A WILD BIKINI", "release_year", "1965" ], [ "HOWL'S MOVING CASTLE", "has_genre", "ADVENTURE" ], [ "HOWL'S MOVING CASTLE", "has_tags", "ADVENTURE" ], [ "HOWL'S MOVING CASTLE", "has_tags", "BD-R" ], [ "I CONFESS", "has_tags", "BD-R" ], [ "I CONFESS", "in_language", "FRENCH" ], [ "I WAS A MALE WAR BRIDE", "has_tags", "BD-R" ], [ "I WAS A MALE WAR BRIDE", "in_language", "FRENCH" ], [ "IVANHOE", "has_genre", "ADVENTURE" ], [ "IVANHOE", "has_tags", "BD-R" ], [ "JACK THE GIANT KILLER", "has_genre", "ADVENTURE" ], [ "JACK THE GIANT KILLER", "has_tags", "BD-R" ], [ "JACK THE GIANT KILLER", "in_language", "ENGLISH" ], [ "JANE EYRE", "has_tags", "BD-R" ], [ "JANE EYRE", "in_language", "ENGLISH" ], [ "JANE EYRE", "in_language", "FRENCH" ], [ "JOHN CARTER", "has_genre", "ADVENTURE" ], [ "JOHN CARTER", "has_tags", "BD-R" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_genre", "ADVENTURE" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_tags", "ADVENTURE" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_tags", "BD-R" ], [ "JUNGLE BOOK", "has_genre", "ADVENTURE" ], [ "JUNGLE BOOK", "has_tags", "BD-R" ], [ "KING KONG", "has_genre", "ADVENTURE" ], [ "KING KONG", "has_tags", "ADVENTURE" ], [ "KING KONG", "has_tags", "BD-R" ], [ "KING OF HEARTS", "has_tags", "BD-R" ], [ "KING OF HEARTS", "in_language", "FRENCH" ], [ "KING SOLOMON'S MINES", "has_genre", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KISMET", "has_tags", "BD-R" ], [ "KISMET", "in_language", "ENGLISH" ], [ "KNIGHTS OF THE ROUND TABLE", "has_genre", "ADVENTURE" ], [ "KNIGHTS OF THE ROUND TABLE", "has_tags", "BD-R" ], [ "LA HAINE", "has_tags", "BD-R" ], [ "LA HAINE", "has_tags", "FRENCH" ], [ "LA HAINE", "in_language", "FRENCH" ], [ "LABYRINTH", "has_genre", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "BD-R" ], [ "LAWRENCE OF ARABIA", "has_genre", "ADVENTURE" ], [ "LAWRENCE OF ARABIA", "has_tags", "BD-R" ], [ "LE BEAU SERGE", "has_tags", "BD-R" ], [ "LE BEAU SERGE", "in_language", "FRENCH" ], [ "LES COUSINS", "has_tags", "BD-R" ], [ "LES COUSINS", "in_language", "FRENCH" ], [ "LOLA", "has_tags", "BD-R" ], [ "LOLA", "in_language", "FRENCH" ], [ "LORD OF THE FLIES", "has_tags", "BD-R" ], [ "LORD OF THE FLIES", "in_language", "ENGLISH" ], [ "MAN OF LA MANCHA", "has_tags", "BD-R" ], [ "MAN OF LA MANCHA", "in_language", "ENGLISH" ], [ "MARAT/SADE", "has_tags", "BD-R" ], [ "MARAT/SADE", "in_language", "ENGLISH" ], [ "MAYERLING", "has_tags", "BD-R" ], [ "MAYERLING", "in_language", "ENGLISH" ], [ "MAYERLING", "in_language", "FRENCH" ], [ "MODEL SHOP", "has_tags", "BD-R" ], [ "MODEL SHOP", "in_language", "ENGLISH" ], [ "MON ONCLE", "has_tags", "BD-R" ], [ "MON ONCLE", "in_language", "FRENCH" ], [ "MY FAIR LADY", "has_tags", "BD-R" ], [ "MY FAIR LADY", "in_language", "ENGLISH" ], [ "MY FAVORITE SEASON", "has_tags", "BD-R" ], [ "MY FAVORITE SEASON", "in_language", "FRENCH" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "has_genre", "ADVENTURE" ], [ "ONE MILLION YEARS B.C.", "has_tags", "BD-R" ], [ "OPERATION CROSSBOW", "has_tags", "BD-R" ], [ "OPERATION CROSSBOW", "release_year", "1965" ], [ "PICKPOCKET", "has_tags", "BD-R" ], [ "PICKPOCKET", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "has_tags", "BD-R" ], [ "PORT OF SHADOWS", "in_language", "FRENCH" ], [ "PREHISTORIC WOMEN", "has_genre", "ADVENTURE" ], [ "PREHISTORIC WOMEN", "has_tags", "BD-R" ], [ "PURPLE NOON", "has_tags", "BD-R" ], [ "PURPLE NOON", "in_language", "FRENCH" ], [ "REPULSION", "has_tags", "BD-R" ], [ "REPULSION", "in_language", "ENGLISH" ], [ "REPULSION", "release_year", "1965" ], [ "RIFIFI", "has_tags", "BD-R" ], [ "RIFIFI", "in_language", "FRENCH" ], [ "ROBIN AND MARIAN", "has_genre", "ADVENTURE" ], [ "ROBIN AND MARIAN", "has_tags", "BD-R" ], [ "ROMEO AND JULIET", "has_tags", "BD-R" ], [ "ROMEO AND JULIET", "in_language", "ENGLISH" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SEX IS COMEDY", "has_tags", "BD-R" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SHEENA", "has_genre", "ADVENTURE" ], [ "SHEENA", "has_tags", "BD-R" ], [ "SHERLOCK HOLMES AND THE SECRET WEAPON", "has_genre", "ADVENTURE" ], [ "SHERLOCK HOLMES AND THE SECRET WEAPON", "has_tags", "BD-R" ], [ "SPIRITS OF THE DEAD", "directed_by", "LOUIS MALLE" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "in_language", "FRENCH" ], [ "SPIRITS OF THE DEAD", "starred_actors", "BRIGITTE BARDOT" ], [ "SPIRITS OF THE DEAD", "written_by", "LOUIS MALLE" ], [ "STORY OF WOMEN", "has_tags", "BD-R" ], [ "STORY OF WOMEN", "in_language", "FRENCH" ], [ "TARZAN THE APE MAN", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_tags", "BD-R" ], [ "TARZAN'S NEW YORK ADVENTURE", "has_genre", "ADVENTURE" ], [ "TARZAN'S NEW YORK ADVENTURE", "has_tags", "BD-R" ], [ "THE ADVENTURES OF HUCKLEBERRY FINN", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF HUCKLEBERRY FINN", "has_tags", "BD-R" ], [ "THE APARTMENT", "has_tags", "BD-R" ], [ "THE APARTMENT", "in_language", "FRENCH" ], [ "THE BATTLE OF ALGIERS", "has_tags", "BD-R" ], [ "THE BATTLE OF ALGIERS", "has_tags", "FRENCH" ], [ "THE BATTLE OF ALGIERS", "in_language", "FRENCH" ], [ "THE BEDFORD INCIDENT", "has_tags", "BD-R" ], [ "THE BEDFORD INCIDENT", "release_year", "1965" ], [ "THE BRIDE WORE BLACK", "has_tags", "BD-R" ], [ "THE BRIDE WORE BLACK", "in_language", "FRENCH" ], [ "THE BRIDE WORE BLACK", "starred_actors", "JEANNE MOREAU" ], [ "THE BROTHERS GRIMM", "has_genre", "ADVENTURE" ], [ "THE BROTHERS GRIMM", "has_tags", "ADVENTURE" ], [ "THE BROTHERS GRIMM", "has_tags", "BD-R" ], [ "THE BROTHERS GRIMM", "in_language", "FRENCH" ], [ "THE CADDY", "has_tags", "BD-R" ], [ "THE CADDY", "starred_actors", "JERRY LEWIS" ], [ "THE CANTERVILLE GHOST", "has_tags", "BD-R" ], [ "THE CANTERVILLE GHOST", "in_language", "ENGLISH" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_genre", "ADVENTURE" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_tags", "BD-R" ], [ "THE CORSICAN BROTHERS", "has_tags", "BD-R" ], [ "THE CORSICAN BROTHERS", "in_language", "ENGLISH" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "in_language", "ENGLISH" ], [ "THE DECEIVERS", "has_genre", "ADVENTURE" ], [ "THE DECEIVERS", "has_tags", "BD-R" ], [ "THE DISORDERLY ORDERLY", "starred_actors", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "directed_by", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "release_year", "1965" ], [ "THE FAMILY JEWELS", "starred_actors", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "written_by", "JERRY LEWIS" ], [ "THE FLAME AND THE ARROW", "has_genre", "ADVENTURE" ], [ "THE FLAME AND THE ARROW", "has_tags", "BD-R" ], [ "THE FOUR FEATHERS", "has_genre", "ADVENTURE" ], [ "THE FOUR FEATHERS", "has_tags", "BD-R" ], [ "THE GUNS OF NAVARONE", "has_genre", "ADVENTURE" ], [ "THE GUNS OF NAVARONE", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "release_year", "1965" ], [ "THE HAPPY TIME", "has_tags", "BD-R" ], [ "THE HAPPY TIME", "in_language", "FRENCH" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "ENGLISH" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "FRENCH" ], [ "THE ILLUSIONIST", "has_tags", "BD-R" ], [ "THE ILLUSIONIST", "in_language", "FRENCH" ], [ "THE IMMORTAL STORY", "has_tags", "BD-R" ], [ "THE IMMORTAL STORY", "in_language", "FRENCH" ], [ "THE IMMORTAL STORY", "starred_actors", "JEANNE MOREAU" ], [ "THE LADY VANISHES", "has_tags", "BD-R" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LAND THAT TIME FORGOT", "has_genre", "ADVENTURE" ], [ "THE LAND THAT TIME FORGOT", "has_tags", "ADVENTURE" ], [ "THE LAND THAT TIME FORGOT", "has_tags", "BD-R" ], [ "THE LOVE PARADE", "has_tags", "BD-R" ], [ "THE LOVE PARADE", "in_language", "FRENCH" ], [ "THE LOVED ONE", "has_tags", "BD-R" ], [ "THE LOVED ONE", "release_year", "1965" ], [ "THE MAN IN THE IRON MASK", "has_genre", "ADVENTURE" ], [ "THE MAN IN THE IRON MASK", "has_tags", "ADVENTURE" ], [ "THE MAN IN THE IRON MASK", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "in_language", "FRENCH" ], [ "THE MARK OF ZORRO", "has_genre", "ADVENTURE" ], [ "THE MARK OF ZORRO", "has_tags", "BD-R" ], [ "THE MASK OF FU MANCHU", "has_genre", "ADVENTURE" ], [ "THE MASK OF FU MANCHU", "has_tags", "BD-R" ], [ "THE MASTER OF BALLANTRAE", "has_genre", "ADVENTURE" ], [ "THE MASTER OF BALLANTRAE", "has_tags", "BD-R" ], [ "THE MERRY WIDOW", "has_tags", "BD-R" ], [ "THE MERRY WIDOW", "in_language", "FRENCH" ], [ "THE MUMMY", "has_genre", "ADVENTURE" ], [ "THE MUMMY", "has_tags", "ADVENTURE" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE NUTTY PROFESSOR", "directed_by", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "has_tags", "BD-R" ], [ "THE NUTTY PROFESSOR", "has_tags", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "starred_actors", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "written_by", "JERRY LEWIS" ], [ "THE PEOPLE THAT TIME FORGOT", "has_genre", "ADVENTURE" ], [ "THE PEOPLE THAT TIME FORGOT", "has_tags", "BD-R" ], [ "THE PHANTOM TOLLBOOTH", "has_genre", "ADVENTURE" ], [ "THE PHANTOM TOLLBOOTH", "has_tags", "BD-R" ], [ "THE PRINCE AND THE PAUPER", "has_genre", "ADVENTURE" ], [ "THE PRINCE AND THE PAUPER", "has_tags", "BD-R" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_tags", "BD-R" ], [ "THE ROSE TATTOO", "has_tags", "BD-R" ], [ "THE ROSE TATTOO", "in_language", "ENGLISH" ], [ "THE SCARLET PIMPERNEL", "has_genre", "ADVENTURE" ], [ "THE SCARLET PIMPERNEL", "has_tags", "BD-R" ], [ "THE SCARLET PIMPERNEL", "in_language", "ENGLISH" ], [ "THE SCARLET PIMPERNEL", "in_language", "FRENCH" ], [ "THE SEA HAWK", "has_tags", "BD-R" ], [ "THE SEA HAWK", "in_language", "ENGLISH" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_tags", "BD-R" ], [ "THE SECRET LIFE OF WALTER MITTY", "in_language", "ENGLISH" ], [ "THE SHOP ON MAIN STREET", "has_tags", "BD-R" ], [ "THE SHOP ON MAIN STREET", "release_year", "1965" ], [ "THE SILVER CHALICE", "has_tags", "BD-R" ], [ "THE SILVER CHALICE", "in_language", "ENGLISH" ], [ "THE SON OF THE SHEIK", "has_genre", "ADVENTURE" ], [ "THE SON OF THE SHEIK", "has_tags", "BD-R" ], [ "THE SPY WHO CAME IN FROM THE COLD", "has_tags", "BD-R" ], [ "THE SPY WHO CAME IN FROM THE COLD", "in_language", "ENGLISH" ], [ "THE SPY WHO CAME IN FROM THE COLD", "release_year", "1965" ], [ "THE STRANGER", "has_tags", "BD-R" ], [ "THE STRANGER", "written_by", "ALBERT CAMUS" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_tags", "BD-R" ], [ "THE TRAIN", "has_tags", "BD-R" ], [ "THE TRAIN", "starred_actors", "JEANNE MOREAU" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_genre", "ADVENTURE" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_tags", "BD-R" ], [ "THE TREASURE OF THE SIERRA MADRE", "in_language", "ENGLISH" ], [ "THE TRIAL", "has_tags", "BD-R" ], [ "THE TRIAL", "starred_actors", "JEANNE MOREAU" ], [ "THE TRIAL OF JOAN OF ARC", "has_tags", "BD-R" ], [ "THE TRIAL OF JOAN OF ARC", "in_language", "FRENCH" ], [ "THE UMBRELLAS OF CHERBOURG", "has_tags", "BD-R" ], [ "THE UMBRELLAS OF CHERBOURG", "has_tags", "FRENCH" ], [ "THE UMBRELLAS OF CHERBOURG", "in_language", "FRENCH" ], [ "THE VALACHI PAPERS", "has_tags", "BD-R" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE VANISHING", "has_tags", "BD-R" ], [ "THE VANISHING", "in_language", "ENGLISH" ], [ "THE VANISHING", "in_language", "FRENCH" ], [ "THE VIKINGS", "has_genre", "ADVENTURE" ], [ "THE VIKINGS", "has_tags", "BD-R" ], [ "THE WIND AND THE LION", "has_genre", "ADVENTURE" ], [ "THE WIND AND THE LION", "has_tags", "BD-R" ], [ "THIS HAPPY BREED", "has_tags", "BD-R" ], [ "THIS HAPPY BREED", "in_language", "ENGLISH" ], [ "TO HAVE AND HAVE NOT", "has_genre", "ADVENTURE" ], [ "TO HAVE AND HAVE NOT", "has_tags", "BD-R" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_tags", "BD-R" ], [ "TOM SAWYER", "has_genre", "ADVENTURE" ], [ "TOM SAWYER", "has_tags", "BD-R" ], [ "TRIPLE CROSS", "has_tags", "BD-R" ], [ "TRIPLE CROSS", "in_language", "FRENCH" ], [ "VICTIM", "has_tags", "BD-R" ], [ "VICTIM", "in_language", "ENGLISH" ], [ "VILLAGE OF THE GIANTS", "has_tags", "BD-R" ], [ "VILLAGE OF THE GIANTS", "release_year", "1965" ], [ "VIVA MARIA!", "directed_by", "LOUIS MALLE" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_tags", "BD-R" ], [ "VIVA MARIA!", "has_tags", "BRIGITTE BARDOT" ], [ "VIVA MARIA!", "has_tags", "FRENCH" ], [ "VIVA MARIA!", "has_tags", "JEANNE MOREAU" ], [ "VIVA MARIA!", "has_tags", "LOUIS MALLE" ], [ "VIVA MARIA!", "in_language", "ENGLISH" ], [ "VIVA MARIA!", "in_language", "FRENCH" ], [ "VIVA MARIA!", "release_year", "1965" ], [ "VIVA MARIA!", "starred_actors", "BRIGITTE BARDOT" ], [ "VIVA MARIA!", "starred_actors", "JEANNE MOREAU" ], [ "VIVA MARIA!", "written_by", "LOUIS MALLE" ], [ "WENT THE DAY WELL?", "has_tags", "BD-R" ], [ "WENT THE DAY WELL?", "in_language", "ENGLISH" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_tags", "BD-R" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "in_language", "ENGLISH" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ], [ "WITCHFINDER GENERAL", "in_language", "ENGLISH" ], [ "Z", "has_tags", "BD-R" ], [ "Z", "in_language", "FRENCH" ], [ "ZERO FOR CONDUCT", "has_tags", "BD-R" ], [ "ZERO FOR CONDUCT", "has_tags", "FRENCH" ], [ "ZERO FOR CONDUCT", "in_language", "FRENCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 5438, 1931 18132, 1938 35063, 1976 1092, ARROWSMITH 3706, BEULAH BONDI 32354, FOUR MEN AND A PRAYER 7736, JAMES STEWART 13255, JOHN FORD 15311, OF HUMAN HEARTS 31805, SEAS BENEATH 28357, ST. IVES 7352, STREET SCENE 19417, THE CRIMINAL CODE 36235, THE MAN WHO SHOT LIBERTY VALANCE 31357, THE SHOOTIST 32860, THE SHOPWORN ANGEL 30453, THE STAR WITNESS 37207, TWO RODE TOGETHER 13631, VIVACIOUS LADY 27356, WALTER HUSTON 8184, YOU CAN'T TAKE IT WITH YOU src, edge_attr, dst 1092, directed_by, 13255 1092, release_year, 5438 32354, directed_by, 13255 32354, release_year, 18132 15311, release_year, 18132 15311, starred_actors, 3706 15311, starred_actors, 7736 15311, starred_actors, 27356 31805, directed_by, 13255 31805, release_year, 5438 28357, release_year, 35063 7352, release_year, 5438 7352, starred_actors, 3706 19417, release_year, 5438 19417, starred_actors, 27356 36235, directed_by, 13255 36235, has_tags, 7736 36235, has_tags, 13255 36235, starred_actors, 7736 31357, release_year, 35063 31357, starred_actors, 7736 32860, release_year, 18132 32860, starred_actors, 7736 30453, release_year, 5438 30453, starred_actors, 27356 37207, directed_by, 13255 37207, starred_actors, 7736 13631, release_year, 18132 13631, starred_actors, 3706 13631, starred_actors, 7736 8184, has_tags, 7736 8184, release_year, 18132 8184, starred_actors, 7736 Question: For what reason are ARROWSMITH, OF HUMAN HEARTS, and ST. IVES associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ARROWSMITH", "OF HUMAN HEARTS", "ST. IVES" ], "valid_edges": [ [ "ARROWSMITH", "directed_by", "JOHN FORD" ], [ "ARROWSMITH", "release_year", "1931" ], [ "FOUR MEN AND A PRAYER", "directed_by", "JOHN FORD" ], [ "FOUR MEN AND A PRAYER", "release_year", "1938" ], [ "OF HUMAN HEARTS", "release_year", "1938" ], [ "OF HUMAN HEARTS", "starred_actors", "BEULAH BONDI" ], [ "OF HUMAN HEARTS", "starred_actors", "JAMES STEWART" ], [ "OF HUMAN HEARTS", "starred_actors", "WALTER HUSTON" ], [ "SEAS BENEATH", "directed_by", "JOHN FORD" ], [ "SEAS BENEATH", "release_year", "1931" ], [ "ST. IVES", "release_year", "1976" ], [ "STREET SCENE", "release_year", "1931" ], [ "STREET SCENE", "starred_actors", "BEULAH BONDI" ], [ "THE CRIMINAL CODE", "release_year", "1931" ], [ "THE CRIMINAL CODE", "starred_actors", "WALTER HUSTON" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE SHOOTIST", "release_year", "1976" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SHOPWORN ANGEL", "release_year", "1938" ], [ "THE SHOPWORN ANGEL", "starred_actors", "JAMES STEWART" ], [ "THE STAR WITNESS", "release_year", "1931" ], [ "THE STAR WITNESS", "starred_actors", "WALTER HUSTON" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "VIVACIOUS LADY", "starred_actors", "BEULAH BONDI" ], [ "VIVACIOUS LADY", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JAMES STEWART" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36173, 1946 30146, A CHRISTMAS CAROL 16150, A CHRISTMAS STORY 19697, ALAIN RESNAIS 9677, ANATOMY OF A MURDER 25570, BEAUTY AND THE BEAST 2313, BEN-HUR 17280, CHRISTMAS 14728, CLASSIC 22958, FAMOUS 1331, IT'S A WONDERFUL LIFE 7736, JAMES STEWART 30057, LAST YEAR AT MARIENBAD 39471, LETTERS TO JULIET 25534, LONG 13672, LOVE ACTUALLY 1994, NOTORIOUS 15644, OLIVER TWIST 37135, REAR WINDOW 38875, ROMANTIC 40066, THE JUNGLE BOOK 28776, THE WIZARD OF OZ 7957, VERTIGO 33318, YOU AIN'T SEEN NOTHIN' YET src, edge_attr, dst 30146, has_imdb_votes, 22958 30146, has_tags, 17280 30146, has_tags, 14728 16150, has_tags, 17280 16150, has_tags, 14728 9677, has_imdb_votes, 22958 9677, has_tags, 7736 9677, starred_actors, 7736 25570, has_imdb_votes, 22958 25570, has_tags, 14728 25570, release_year, 36173 2313, has_imdb_votes, 22958 2313, has_tags, 25534 1331, has_tags, 17280 1331, has_tags, 14728 1331, has_tags, 7736 1331, has_tags, 25534 1331, release_year, 36173 1331, starred_actors, 7736 30057, directed_by, 19697 30057, has_imdb_votes, 22958 30057, has_tags, 19697 39471, has_imdb_votes, 22958 39471, has_tags, 38875 13672, has_tags, 17280 13672, has_tags, 38875 1994, has_imdb_votes, 22958 1994, release_year, 36173 15644, has_imdb_votes, 22958 15644, has_tags, 14728 37135, has_tags, 14728 37135, has_tags, 7736 37135, starred_actors, 7736 40066, has_imdb_votes, 22958 40066, has_tags, 14728 28776, has_imdb_votes, 22958 28776, has_tags, 14728 7957, has_tags, 14728 7957, has_tags, 7736 7957, starred_actors, 7736 33318, directed_by, 19697 33318, has_tags, 19697 33318, written_by, 19697 Question: How are IT'S A WONDERFUL LIFE, LETTERS TO JULIET, and YOU AIN'T SEEN NOTHIN' YET related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "IT'S A WONDERFUL LIFE", "LETTERS TO JULIET", "YOU AIN'T SEEN NOTHIN' YET" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_imdb_votes", "FAMOUS" ], [ "A CHRISTMAS CAROL", "has_tags", "CHRISTMAS" ], [ "A CHRISTMAS CAROL", "has_tags", "CLASSIC" ], [ "A CHRISTMAS STORY", "has_tags", "CHRISTMAS" ], [ "A CHRISTMAS STORY", "has_tags", "CLASSIC" ], [ "ANATOMY OF A MURDER", "has_imdb_votes", "FAMOUS" ], [ "ANATOMY OF A MURDER", "has_tags", "JAMES STEWART" ], [ "ANATOMY OF A MURDER", "starred_actors", "JAMES STEWART" ], [ "BEAUTY AND THE BEAST", "has_imdb_votes", "FAMOUS" ], [ "BEAUTY AND THE BEAST", "has_tags", "CLASSIC" ], [ "BEAUTY AND THE BEAST", "release_year", "1946" ], [ "BEN-HUR", "has_imdb_votes", "FAMOUS" ], [ "BEN-HUR", "has_tags", "LONG" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CHRISTMAS" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CLASSIC" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "LONG" ], [ "IT'S A WONDERFUL LIFE", "release_year", "1946" ], [ "IT'S A WONDERFUL LIFE", "starred_actors", "JAMES STEWART" ], [ "LAST YEAR AT MARIENBAD", "directed_by", "ALAIN RESNAIS" ], [ "LAST YEAR AT MARIENBAD", "has_imdb_votes", "FAMOUS" ], [ "LAST YEAR AT MARIENBAD", "has_tags", "ALAIN RESNAIS" ], [ "LETTERS TO JULIET", "has_imdb_votes", "FAMOUS" ], [ "LETTERS TO JULIET", "has_tags", "ROMANTIC" ], [ "LOVE ACTUALLY", "has_tags", "CHRISTMAS" ], [ "LOVE ACTUALLY", "has_tags", "ROMANTIC" ], [ "NOTORIOUS", "has_imdb_votes", "FAMOUS" ], [ "NOTORIOUS", "release_year", "1946" ], [ "OLIVER TWIST", "has_imdb_votes", "FAMOUS" ], [ "OLIVER TWIST", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "JAMES STEWART" ], [ "REAR WINDOW", "starred_actors", "JAMES STEWART" ], [ "THE JUNGLE BOOK", "has_imdb_votes", "FAMOUS" ], [ "THE JUNGLE BOOK", "has_tags", "CLASSIC" ], [ "THE WIZARD OF OZ", "has_imdb_votes", "FAMOUS" ], [ "THE WIZARD OF OZ", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "JAMES STEWART" ], [ "VERTIGO", "starred_actors", "JAMES STEWART" ], [ "YOU AIN'T SEEN NOTHIN' YET", "directed_by", "ALAIN RESNAIS" ], [ "YOU AIN'T SEEN NOTHIN' YET", "has_tags", "ALAIN RESNAIS" ], [ "YOU AIN'T SEEN NOTHIN' YET", "written_by", "ALAIN RESNAIS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1421, 2013 3560, A FIELD IN ENGLAND 20723, ALAN PARTRIDGE 30870, BEAUTIFUL CREATURES 8381, DETOUR 31783, ENGLISH 37158, ERIC HEISSERER 21573, GIRL ON A BICYCLE 12776, GRAND PIANO 33776, HOURS 847, JACK THE GIANT KILLER 37407, JACK THE GIANT SLAYER 29418, JEREMY IRONS 24015, LORD OF TEARS 31324, NIGHT TRAIN TO LISBON 16883, NORWEGIAN 25824, PARADISE 8352, PARANOIA 39135, REACHING FOR THE MOON 38271, SNOWPIERCER 18443, SONDRE KROGTOFT LARSEN 30357, STOKER 6949, SUNSHINE ON LEITH 38107, THE EAST 24306, THE ENGLISH TEACHER 38918, THE FAMILY 2872, THE GREAT GATSBY 30746, THE SECRET LIFE OF WALTER MITTY 19624, THE THING 30209, YEH JAWAANI HAI DEEWANI 17777, ZULU src, edge_attr, dst 3560, in_language, 31783 3560, release_year, 1421 20723, in_language, 31783 20723, release_year, 1421 30870, release_year, 1421 30870, starred_actors, 29418 8381, in_language, 16883 8381, starred_actors, 18443 21573, in_language, 31783 21573, release_year, 1421 12776, in_language, 31783 12776, release_year, 1421 33776, directed_by, 37158 33776, release_year, 1421 33776, written_by, 37158 847, in_language, 31783 847, release_year, 1421 37407, in_language, 31783 37407, release_year, 1421 24015, in_language, 31783 24015, release_year, 1421 31324, has_tags, 29418 31324, in_language, 31783 31324, release_year, 1421 31324, starred_actors, 29418 25824, in_language, 31783 25824, release_year, 1421 8352, release_year, 1421 39135, in_language, 31783 39135, release_year, 1421 38271, in_language, 31783 38271, release_year, 1421 30357, in_language, 31783 30357, release_year, 1421 6949, in_language, 31783 6949, release_year, 1421 38107, in_language, 31783 38107, release_year, 1421 24306, has_tags, 31783 24306, in_language, 31783 24306, release_year, 1421 38918, in_language, 31783 38918, release_year, 1421 2872, in_language, 31783 2872, release_year, 1421 30746, in_language, 31783 30746, release_year, 1421 19624, has_tags, 16883 19624, has_tags, 8352 19624, in_language, 16883 19624, written_by, 37158 30209, in_language, 31783 30209, release_year, 1421 17777, in_language, 31783 17777, release_year, 1421 Question: In what context are ERIC HEISSERER, NIGHT TRAIN TO LISBON, and SONDRE KROGTOFT LARSEN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ERIC HEISSERER", "NIGHT TRAIN TO LISBON", "SONDRE KROGTOFT LARSEN" ], "valid_edges": [ [ "A FIELD IN ENGLAND", "in_language", "ENGLISH" ], [ "A FIELD IN ENGLAND", "release_year", "2013" ], [ "ALAN PARTRIDGE", "in_language", "ENGLISH" ], [ "ALAN PARTRIDGE", "release_year", "2013" ], [ "BEAUTIFUL CREATURES", "release_year", "2013" ], [ "BEAUTIFUL CREATURES", "starred_actors", "JEREMY IRONS" ], [ "DETOUR", "in_language", "NORWEGIAN" ], [ "DETOUR", "starred_actors", "SONDRE KROGTOFT LARSEN" ], [ "GIRL ON A BICYCLE", "in_language", "ENGLISH" ], [ "GIRL ON A BICYCLE", "release_year", "2013" ], [ "GRAND PIANO", "in_language", "ENGLISH" ], [ "GRAND PIANO", "release_year", "2013" ], [ "HOURS", "directed_by", "ERIC HEISSERER" ], [ "HOURS", "release_year", "2013" ], [ "HOURS", "written_by", "ERIC HEISSERER" ], [ "JACK THE GIANT KILLER", "in_language", "ENGLISH" ], [ "JACK THE GIANT KILLER", "release_year", "2013" ], [ "JACK THE GIANT SLAYER", "in_language", "ENGLISH" ], [ "JACK THE GIANT SLAYER", "release_year", "2013" ], [ "LORD OF TEARS", "in_language", "ENGLISH" ], [ "LORD OF TEARS", "release_year", "2013" ], [ "NIGHT TRAIN TO LISBON", "has_tags", "JEREMY IRONS" ], [ "NIGHT TRAIN TO LISBON", "in_language", "ENGLISH" ], [ "NIGHT TRAIN TO LISBON", "release_year", "2013" ], [ "NIGHT TRAIN TO LISBON", "starred_actors", "JEREMY IRONS" ], [ "PARADISE", "in_language", "ENGLISH" ], [ "PARADISE", "release_year", "2013" ], [ "PARANOIA", "release_year", "2013" ], [ "REACHING FOR THE MOON", "in_language", "ENGLISH" ], [ "REACHING FOR THE MOON", "release_year", "2013" ], [ "SNOWPIERCER", "in_language", "ENGLISH" ], [ "SNOWPIERCER", "release_year", "2013" ], [ "STOKER", "in_language", "ENGLISH" ], [ "STOKER", "release_year", "2013" ], [ "SUNSHINE ON LEITH", "in_language", "ENGLISH" ], [ "SUNSHINE ON LEITH", "release_year", "2013" ], [ "THE EAST", "in_language", "ENGLISH" ], [ "THE EAST", "release_year", "2013" ], [ "THE ENGLISH TEACHER", "has_tags", "ENGLISH" ], [ "THE ENGLISH TEACHER", "in_language", "ENGLISH" ], [ "THE ENGLISH TEACHER", "release_year", "2013" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FAMILY", "release_year", "2013" ], [ "THE GREAT GATSBY", "in_language", "ENGLISH" ], [ "THE GREAT GATSBY", "release_year", "2013" ], [ "THE SECRET LIFE OF WALTER MITTY", "in_language", "ENGLISH" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "2013" ], [ "THE THING", "has_tags", "NORWEGIAN" ], [ "THE THING", "has_tags", "PARANOIA" ], [ "THE THING", "in_language", "NORWEGIAN" ], [ "THE THING", "written_by", "ERIC HEISSERER" ], [ "YEH JAWAANI HAI DEEWANI", "in_language", "ENGLISH" ], [ "YEH JAWAANI HAI DEEWANI", "release_year", "2013" ], [ "ZULU", "in_language", "ENGLISH" ], [ "ZULU", "release_year", "2013" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36279, 10 YEARS 29424, 2011 23250, 50/50 5158, A BAG OF HAMMERS 10158, A PRINCESS FOR CHRISTMAS 37154, ALAN JACOBS 26599, AMERICAN GUN 29881, AMERICANO 188, ANOTHER HAPPY DAY 23286, CARNAGE 28503, CLOUDBURST 23452, DARK HORSE 6375, DELICACY 14132, DESI BOYZ 36212, DRAMA 17854, GOING DOWN IN LA-LA LAND 13198, HOLY FLYING CIRCUS 21922, JANE EYRE 37830, JEFF, WHO LIVES AT HOME 15175, LE HAVRE 3800, LOSERS' CLUB 19802, LOVE 4234, MADEA'S BIG HAPPY FAMILY 35399, MICHAEL BRANDT 33300, NATURAL SELECTION 20537, NEWLYWEDS 10021, OUR IDIOT BROTHER 35664, RESTLESS 12301, SALMON FISHING IN THE YEMEN 23708, SUICIDE ROOM 18005, TAKE THIS WALTZ 26586, THAT'S WHAT I AM 39795, THE ARTIST 5838, THE CLOWN 11393, THE DESCENDANTS 32295, THE DILEMMA 3680, THE DOUBLE 6289, THE INTOUCHABLES 7816, THE THREE MUSKETEERS 13003, THE WELL-DIGGER'S DAUGHTER 5529, THIN ICE 8957, WE BOUGHT A ZOO 35511, WE HAVE A POPE 33483, WEEKEND 36565, WIN WIN 11924, YOUNG ADULT 16822, YOUR SISTER'S SISTER 28489, ZINDAGI NA MILEGI DOBARA src, edge_attr, dst 36279, has_genre, 36212 36279, release_year, 29424 23250, has_genre, 36212 23250, release_year, 29424 5158, has_genre, 36212 5158, release_year, 29424 10158, has_genre, 36212 10158, release_year, 29424 26599, directed_by, 37154 26599, has_genre, 36212 26599, written_by, 37154 29881, has_genre, 36212 29881, release_year, 29424 188, has_genre, 36212 188, release_year, 29424 23286, has_genre, 36212 23286, release_year, 29424 28503, has_genre, 36212 28503, release_year, 29424 23452, has_genre, 36212 23452, release_year, 29424 6375, has_genre, 36212 6375, release_year, 29424 14132, has_genre, 36212 14132, release_year, 29424 17854, has_genre, 36212 17854, release_year, 29424 13198, has_genre, 36212 13198, release_year, 29424 21922, has_genre, 36212 21922, release_year, 29424 37830, has_genre, 36212 37830, release_year, 29424 15175, has_genre, 36212 15175, release_year, 29424 3800, has_genre, 36212 3800, release_year, 29424 19802, has_genre, 36212 19802, release_year, 29424 4234, has_genre, 36212 4234, release_year, 29424 33300, has_genre, 36212 33300, release_year, 29424 20537, has_genre, 36212 20537, release_year, 29424 10021, has_genre, 36212 10021, release_year, 29424 35664, has_genre, 36212 35664, release_year, 29424 12301, has_genre, 36212 12301, release_year, 29424 23708, has_genre, 36212 23708, release_year, 29424 18005, has_genre, 36212 18005, release_year, 29424 26586, has_genre, 36212 26586, release_year, 29424 39795, has_genre, 36212 39795, has_tags, 36212 39795, release_year, 29424 5838, has_genre, 36212 5838, release_year, 29424 11393, has_genre, 36212 11393, has_tags, 36212 11393, release_year, 29424 32295, has_genre, 36212 32295, release_year, 29424 3680, directed_by, 35399 3680, release_year, 29424 3680, written_by, 35399 6289, has_genre, 36212 6289, release_year, 29424 7816, has_genre, 36212 7816, release_year, 29424 13003, has_genre, 36212 13003, release_year, 29424 5529, has_genre, 36212 5529, release_year, 29424 8957, has_genre, 36212 8957, release_year, 29424 35511, has_genre, 36212 35511, release_year, 29424 33483, has_genre, 36212 33483, release_year, 29424 36565, has_genre, 36212 36565, release_year, 29424 11924, has_genre, 36212 11924, has_tags, 36212 11924, release_year, 29424 16822, has_genre, 36212 16822, release_year, 29424 28489, has_genre, 36212 28489, release_year, 29424 Question: How are ALAN JACOBS, MICHAEL BRANDT, and SUICIDE ROOM related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALAN JACOBS", "MICHAEL BRANDT", "SUICIDE ROOM" ], "valid_edges": [ [ "10 YEARS", "has_genre", "DRAMA" ], [ "10 YEARS", "release_year", "2011" ], [ "50/50", "has_genre", "DRAMA" ], [ "50/50", "release_year", "2011" ], [ "A BAG OF HAMMERS", "has_genre", "DRAMA" ], [ "A BAG OF HAMMERS", "release_year", "2011" ], [ "A PRINCESS FOR CHRISTMAS", "has_genre", "DRAMA" ], [ "A PRINCESS FOR CHRISTMAS", "release_year", "2011" ], [ "AMERICAN GUN", "directed_by", "ALAN JACOBS" ], [ "AMERICAN GUN", "has_genre", "DRAMA" ], [ "AMERICAN GUN", "written_by", "ALAN JACOBS" ], [ "AMERICANO", "has_genre", "DRAMA" ], [ "AMERICANO", "release_year", "2011" ], [ "ANOTHER HAPPY DAY", "has_genre", "DRAMA" ], [ "ANOTHER HAPPY DAY", "release_year", "2011" ], [ "CARNAGE", "has_genre", "DRAMA" ], [ "CARNAGE", "release_year", "2011" ], [ "CLOUDBURST", "has_genre", "DRAMA" ], [ "CLOUDBURST", "release_year", "2011" ], [ "DARK HORSE", "has_genre", "DRAMA" ], [ "DARK HORSE", "release_year", "2011" ], [ "DELICACY", "has_genre", "DRAMA" ], [ "DELICACY", "release_year", "2011" ], [ "DESI BOYZ", "has_genre", "DRAMA" ], [ "DESI BOYZ", "release_year", "2011" ], [ "GOING DOWN IN LA-LA LAND", "has_genre", "DRAMA" ], [ "GOING DOWN IN LA-LA LAND", "release_year", "2011" ], [ "HOLY FLYING CIRCUS", "has_genre", "DRAMA" ], [ "HOLY FLYING CIRCUS", "release_year", "2011" ], [ "JANE EYRE", "has_genre", "DRAMA" ], [ "JANE EYRE", "release_year", "2011" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "DRAMA" ], [ "JEFF, WHO LIVES AT HOME", "release_year", "2011" ], [ "LE HAVRE", "has_genre", "DRAMA" ], [ "LE HAVRE", "release_year", "2011" ], [ "LOSERS' CLUB", "has_genre", "DRAMA" ], [ "LOSERS' CLUB", "release_year", "2011" ], [ "LOVE", "has_genre", "DRAMA" ], [ "LOVE", "release_year", "2011" ], [ "MADEA'S BIG HAPPY FAMILY", "has_genre", "DRAMA" ], [ "MADEA'S BIG HAPPY FAMILY", "release_year", "2011" ], [ "NATURAL SELECTION", "has_genre", "DRAMA" ], [ "NATURAL SELECTION", "release_year", "2011" ], [ "NEWLYWEDS", "has_genre", "DRAMA" ], [ "NEWLYWEDS", "release_year", "2011" ], [ "OUR IDIOT BROTHER", "has_genre", "DRAMA" ], [ "OUR IDIOT BROTHER", "release_year", "2011" ], [ "RESTLESS", "has_genre", "DRAMA" ], [ "RESTLESS", "release_year", "2011" ], [ "SALMON FISHING IN THE YEMEN", "has_genre", "DRAMA" ], [ "SALMON FISHING IN THE YEMEN", "release_year", "2011" ], [ "SUICIDE ROOM", "has_genre", "DRAMA" ], [ "SUICIDE ROOM", "release_year", "2011" ], [ "TAKE THIS WALTZ", "has_genre", "DRAMA" ], [ "TAKE THIS WALTZ", "release_year", "2011" ], [ "THAT'S WHAT I AM", "has_genre", "DRAMA" ], [ "THAT'S WHAT I AM", "release_year", "2011" ], [ "THE ARTIST", "has_genre", "DRAMA" ], [ "THE ARTIST", "has_tags", "DRAMA" ], [ "THE ARTIST", "release_year", "2011" ], [ "THE CLOWN", "has_genre", "DRAMA" ], [ "THE CLOWN", "release_year", "2011" ], [ "THE DESCENDANTS", "has_genre", "DRAMA" ], [ "THE DESCENDANTS", "has_tags", "DRAMA" ], [ "THE DESCENDANTS", "release_year", "2011" ], [ "THE DILEMMA", "has_genre", "DRAMA" ], [ "THE DILEMMA", "release_year", "2011" ], [ "THE DOUBLE", "directed_by", "MICHAEL BRANDT" ], [ "THE DOUBLE", "release_year", "2011" ], [ "THE DOUBLE", "written_by", "MICHAEL BRANDT" ], [ "THE INTOUCHABLES", "has_genre", "DRAMA" ], [ "THE INTOUCHABLES", "release_year", "2011" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE THREE MUSKETEERS", "release_year", "2011" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "DRAMA" ], [ "THE WELL-DIGGER'S DAUGHTER", "release_year", "2011" ], [ "THIN ICE", "has_genre", "DRAMA" ], [ "THIN ICE", "release_year", "2011" ], [ "WE BOUGHT A ZOO", "has_genre", "DRAMA" ], [ "WE BOUGHT A ZOO", "release_year", "2011" ], [ "WE HAVE A POPE", "has_genre", "DRAMA" ], [ "WE HAVE A POPE", "release_year", "2011" ], [ "WEEKEND", "has_genre", "DRAMA" ], [ "WEEKEND", "release_year", "2011" ], [ "WIN WIN", "has_genre", "DRAMA" ], [ "WIN WIN", "release_year", "2011" ], [ "YOUNG ADULT", "has_genre", "DRAMA" ], [ "YOUNG ADULT", "has_tags", "DRAMA" ], [ "YOUNG ADULT", "release_year", "2011" ], [ "YOUR SISTER'S SISTER", "has_genre", "DRAMA" ], [ "YOUR SISTER'S SISTER", "release_year", "2011" ], [ "ZINDAGI NA MILEGI DOBARA", "has_genre", "DRAMA" ], [ "ZINDAGI NA MILEGI DOBARA", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 4763, ADVENTURE 524, CHARLIE'S ANGELS 36066, FANTASY 36940, LABYRINTH 18795, MARY CROSBY 21057, QUEST 19740, RYAN ROWE 25296, THE ICE PIRATES 24404, THE NEVERENDING STORY src, edge_attr, dst 524, has_genre, 4763 524, written_by, 19740 36940, has_genre, 4763 36940, has_genre, 36066 36940, has_tags, 4763 36940, has_tags, 36066 36940, has_tags, 21057 25296, release_year, 24525 25296, starred_actors, 18795 24404, has_tags, 36066 24404, has_tags, 21057 24404, release_year, 24525 Question: In what context are MARY CROSBY, QUEST, and RYAN ROWE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MARY CROSBY", "QUEST", "RYAN ROWE" ], "valid_edges": [ [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "written_by", "RYAN ROWE" ], [ "LABYRINTH", "has_genre", "ADVENTURE" ], [ "LABYRINTH", "has_genre", "FANTASY" ], [ "LABYRINTH", "has_tags", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "FANTASY" ], [ "LABYRINTH", "has_tags", "QUEST" ], [ "THE ICE PIRATES", "release_year", "1984" ], [ "THE ICE PIRATES", "starred_actors", "MARY CROSBY" ], [ "THE NEVERENDING STORY", "has_tags", "FANTASY" ], [ "THE NEVERENDING STORY", "has_tags", "QUEST" ], [ "THE NEVERENDING STORY", "release_year", "1984" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2493, 13 35798, 2010 24480, A NIGHTMARE ON ELM STREET 2201, ANTICHRIST 26267, CINEMATOGRAPHY 27843, CLASH OF THE TITANS 37059, DEATH AT A FUNERAL 13272, DON'T BE AFRAID OF THE DARK 15439, I SPIT ON YOUR GRAVE 29987, LET ME IN 37521, OWEN DAVIS 23228, PUTTY HILL 28729, REMAKE 25463, THE CRAZIES 2599, THE EXPERIMENT 2872, THE GREAT GATSBY 13329, THE KARATE KID 1208, THE NEXT THREE DAYS 17910, THE OMEN src, edge_attr, dst 2493, has_tags, 28729 2493, release_year, 35798 24480, has_tags, 28729 24480, release_year, 35798 2201, has_tags, 26267 27843, has_tags, 28729 27843, release_year, 35798 37059, has_tags, 28729 37059, release_year, 35798 13272, has_tags, 28729 13272, release_year, 35798 15439, has_tags, 28729 15439, release_year, 35798 29987, has_tags, 28729 29987, release_year, 35798 23228, release_year, 35798 25463, has_tags, 28729 25463, release_year, 35798 2599, has_tags, 28729 2599, release_year, 35798 2872, has_tags, 26267 2872, written_by, 37521 13329, has_tags, 28729 13329, release_year, 35798 1208, has_tags, 28729 1208, release_year, 35798 17910, has_tags, 2201 17910, has_tags, 28729 Question: In what context are OWEN DAVIS, PUTTY HILL, and THE OMEN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "OWEN DAVIS", "PUTTY HILL", "THE OMEN" ], "valid_edges": [ [ "13", "has_tags", "REMAKE" ], [ "13", "release_year", "2010" ], [ "A NIGHTMARE ON ELM STREET", "has_tags", "REMAKE" ], [ "A NIGHTMARE ON ELM STREET", "release_year", "2010" ], [ "ANTICHRIST", "has_tags", "CINEMATOGRAPHY" ], [ "CLASH OF THE TITANS", "has_tags", "REMAKE" ], [ "CLASH OF THE TITANS", "release_year", "2010" ], [ "DEATH AT A FUNERAL", "has_tags", "REMAKE" ], [ "DEATH AT A FUNERAL", "release_year", "2010" ], [ "DON'T BE AFRAID OF THE DARK", "has_tags", "REMAKE" ], [ "DON'T BE AFRAID OF THE DARK", "release_year", "2010" ], [ "I SPIT ON YOUR GRAVE", "has_tags", "REMAKE" ], [ "I SPIT ON YOUR GRAVE", "release_year", "2010" ], [ "LET ME IN", "has_tags", "REMAKE" ], [ "LET ME IN", "release_year", "2010" ], [ "PUTTY HILL", "release_year", "2010" ], [ "THE CRAZIES", "has_tags", "REMAKE" ], [ "THE CRAZIES", "release_year", "2010" ], [ "THE EXPERIMENT", "has_tags", "REMAKE" ], [ "THE EXPERIMENT", "release_year", "2010" ], [ "THE GREAT GATSBY", "has_tags", "CINEMATOGRAPHY" ], [ "THE GREAT GATSBY", "written_by", "OWEN DAVIS" ], [ "THE KARATE KID", "has_tags", "REMAKE" ], [ "THE KARATE KID", "release_year", "2010" ], [ "THE NEXT THREE DAYS", "has_tags", "REMAKE" ], [ "THE NEXT THREE DAYS", "release_year", "2010" ], [ "THE OMEN", "has_tags", "ANTICHRIST" ], [ "THE OMEN", "has_tags", "REMAKE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 30665, 7 DAYS IN HAVANA 21289, ENTITY 6221, FRIENDS WITH BENEFITS 11565, GOOD 5722, HUMAN RESOURCES 2722, INSIDE LLEWYN DAVIS 17585, JOHN GOODMAN 14768, JUSTIN TIMBERLAKE 8795, LAURENT CANTET 17451, TROUBLE WITH THE CURVE 16982, WOODY HARRELSON src, edge_attr, dst 658, has_tags, 16982 30665, directed_by, 8795 30665, release_year, 658 30665, written_by, 8795 21289, release_year, 658 6221, has_tags, 14768 6221, has_tags, 16982 6221, starred_actors, 14768 5722, directed_by, 8795 5722, has_tags, 8795 5722, written_by, 8795 2722, has_imdb_rating, 11565 2722, has_tags, 17585 2722, has_tags, 14768 2722, starred_actors, 14768 17451, has_imdb_rating, 11565 17451, has_tags, 17585 17451, has_tags, 14768 17451, release_year, 658 Question: How are ENTITY, HUMAN RESOURCES, and JUSTIN TIMBERLAKE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ENTITY", "HUMAN RESOURCES", "JUSTIN TIMBERLAKE" ], "valid_edges": [ [ "2012", "has_tags", "WOODY HARRELSON" ], [ "7 DAYS IN HAVANA", "directed_by", "LAURENT CANTET" ], [ "7 DAYS IN HAVANA", "release_year", "2012" ], [ "7 DAYS IN HAVANA", "written_by", "LAURENT CANTET" ], [ "ENTITY", "release_year", "2012" ], [ "FRIENDS WITH BENEFITS", "has_tags", "JUSTIN TIMBERLAKE" ], [ "FRIENDS WITH BENEFITS", "has_tags", "WOODY HARRELSON" ], [ "FRIENDS WITH BENEFITS", "starred_actors", "JUSTIN TIMBERLAKE" ], [ "HUMAN RESOURCES", "directed_by", "LAURENT CANTET" ], [ "HUMAN RESOURCES", "has_tags", "LAURENT CANTET" ], [ "HUMAN RESOURCES", "written_by", "LAURENT CANTET" ], [ "INSIDE LLEWYN DAVIS", "has_imdb_rating", "GOOD" ], [ "INSIDE LLEWYN DAVIS", "has_tags", "JOHN GOODMAN" ], [ "INSIDE LLEWYN DAVIS", "has_tags", "JUSTIN TIMBERLAKE" ], [ "INSIDE LLEWYN DAVIS", "starred_actors", "JUSTIN TIMBERLAKE" ], [ "TROUBLE WITH THE CURVE", "has_imdb_rating", "GOOD" ], [ "TROUBLE WITH THE CURVE", "has_tags", "JOHN GOODMAN" ], [ "TROUBLE WITH THE CURVE", "has_tags", "JUSTIN TIMBERLAKE" ], [ "TROUBLE WITH THE CURVE", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8779, 1945 35798, 2010 29638, ALICE IN WONDERLAND 32479, BEWITCHED 13225, BLITHE SPIRIT 39570, BUNRAKU 27843, CLASH OF THE TITANS 13272, DON'T BE AFRAID OF THE DARK 36066, FANTASY 12817, FRANK BORZAGE 5387, HEREAFTER 13549, HOW TO TRAIN YOUR DRAGON 26991, JONAH HEX 32481, MANNEQUIN 36999, MAUREEN O'HARA 32823, MIRACLE ON 34TH STREET 6952, MY JOY 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 38073, THE LAST AIRBENDER 8168, THE SPANISH MAIN 15218, THE SWORD AND THE SORCERER 26036, THE TEMPEST 37516, THE WARRIOR'S WAY 14716, TROLLHUNTER 15472, YOLANDA AND THE THIEF src, edge_attr, dst 29638, has_genre, 36066 29638, has_tags, 36066 29638, release_year, 35798 32479, has_genre, 36066 32479, release_year, 8779 13225, has_genre, 36066 13225, release_year, 8779 39570, has_tags, 36066 39570, release_year, 35798 27843, has_genre, 36066 27843, has_tags, 36066 27843, release_year, 35798 13272, has_genre, 36066 13272, release_year, 35798 5387, has_genre, 36066 5387, release_year, 35798 13549, has_tags, 36066 13549, release_year, 35798 26991, has_genre, 36066 26991, release_year, 35798 32481, directed_by, 12817 32481, has_genre, 36066 32823, has_genre, 36066 32823, has_tags, 36999 32823, starred_actors, 36999 6952, release_year, 35798 10344, has_genre, 36066 10344, release_year, 35798 38073, has_tags, 36066 38073, release_year, 35798 8168, directed_by, 12817 8168, release_year, 8779 8168, starred_actors, 36999 15218, has_genre, 36066 26036, has_genre, 36066 26036, release_year, 35798 37516, has_genre, 36066 37516, release_year, 35798 14716, has_genre, 36066 14716, has_tags, 36066 14716, release_year, 35798 15472, has_genre, 36066 15472, release_year, 8779 Question: For what reason are MY JOY, THE SPANISH MAIN, and THE SWORD AND THE SORCERER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "MY JOY", "THE SPANISH MAIN", "THE SWORD AND THE SORCERER" ], "valid_edges": [ [ "ALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "ALICE IN WONDERLAND", "has_tags", "FANTASY" ], [ "ALICE IN WONDERLAND", "release_year", "2010" ], [ "BEWITCHED", "has_genre", "FANTASY" ], [ "BEWITCHED", "release_year", "1945" ], [ "BLITHE SPIRIT", "has_genre", "FANTASY" ], [ "BLITHE SPIRIT", "release_year", "1945" ], [ "BUNRAKU", "has_tags", "FANTASY" ], [ "BUNRAKU", "release_year", "2010" ], [ "CLASH OF THE TITANS", "has_genre", "FANTASY" ], [ "CLASH OF THE TITANS", "has_tags", "FANTASY" ], [ "CLASH OF THE TITANS", "release_year", "2010" ], [ "DON'T BE AFRAID OF THE DARK", "has_genre", "FANTASY" ], [ "DON'T BE AFRAID OF THE DARK", "release_year", "2010" ], [ "HEREAFTER", "has_genre", "FANTASY" ], [ "HEREAFTER", "release_year", "2010" ], [ "HOW TO TRAIN YOUR DRAGON", "has_tags", "FANTASY" ], [ "HOW TO TRAIN YOUR DRAGON", "release_year", "2010" ], [ "JONAH HEX", "has_genre", "FANTASY" ], [ "JONAH HEX", "release_year", "2010" ], [ "MANNEQUIN", "directed_by", "FRANK BORZAGE" ], [ "MANNEQUIN", "has_genre", "FANTASY" ], [ "MIRACLE ON 34TH STREET", "has_genre", "FANTASY" ], [ "MIRACLE ON 34TH STREET", "has_tags", "MAUREEN O'HARA" ], [ "MIRACLE ON 34TH STREET", "starred_actors", "MAUREEN O'HARA" ], [ "MY JOY", "release_year", "2010" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "FANTASY" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "release_year", "2010" ], [ "THE LAST AIRBENDER", "has_tags", "FANTASY" ], [ "THE LAST AIRBENDER", "release_year", "2010" ], [ "THE SPANISH MAIN", "directed_by", "FRANK BORZAGE" ], [ "THE SPANISH MAIN", "release_year", "1945" ], [ "THE SPANISH MAIN", "starred_actors", "MAUREEN O'HARA" ], [ "THE SWORD AND THE SORCERER", "has_genre", "FANTASY" ], [ "THE TEMPEST", "has_genre", "FANTASY" ], [ "THE TEMPEST", "release_year", "2010" ], [ "THE WARRIOR'S WAY", "has_genre", "FANTASY" ], [ "THE WARRIOR'S WAY", "release_year", "2010" ], [ "TROLLHUNTER", "has_genre", "FANTASY" ], [ "TROLLHUNTER", "has_tags", "FANTASY" ], [ "TROLLHUNTER", "release_year", "2010" ], [ "YOLANDA AND THE THIEF", "has_genre", "FANTASY" ], [ "YOLANDA AND THE THIEF", "release_year", "1945" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 29424, 2011 37908, AFRICAN CATS 39613, BEAUTY DAY 26510, BORN TO BE WILD 29342, BULLY 17035, DEBTOCRACY 12841, DOCUMENTARY 1519, DREAMS OF A LIFE 39366, HAPPY 28468, MAGIC TRIP 7839, MISS REPRESENTATION 23408, OF TIME AND THE CITY 29488, ONE DAY 35524, ONE LIFE 2108, PEARL JAM TWENTY 29086, PINA 10984, REVENGE OF THE ELECTRIC CAR 12599, SURVIVING PROGRESS 2588, THE AMBASSADOR 11259, THE BLACK POWER MIXTAPE 1967-1975 20837, THE CAPTAINS 20969, THE FLAT 30700, THE INTERRUPTERS 38461, THE LAST LIONS 27444, THE LAST MOUNTAIN 39587, THE OTHER F WORD 30593, THE VIOLENT YEARS 29052, THESE AMAZING SHADOWS 36765, THIS IS NOT A FILM 8476, TOUTE LA MÉMOIRE DU MONDE 16214, UNLAWFUL KILLING 4896, WHORES' GLORY 9056, YOU'VE BEEN TRUMPED src, edge_attr, dst 37908, has_genre, 12841 37908, release_year, 29424 39613, has_genre, 12841 39613, release_year, 29424 26510, has_genre, 12841 26510, release_year, 29424 29342, has_genre, 12841 29342, release_year, 29424 17035, has_genre, 12841 17035, release_year, 29424 1519, has_genre, 12841 1519, release_year, 29424 39366, has_genre, 12841 39366, has_tags, 12841 39366, release_year, 29424 28468, has_genre, 12841 28468, release_year, 29424 7839, has_genre, 12841 7839, release_year, 29424 23408, has_genre, 12841 29488, release_year, 29424 35524, has_genre, 12841 35524, release_year, 29424 2108, has_genre, 12841 2108, release_year, 29424 29086, has_genre, 12841 29086, has_tags, 12841 29086, release_year, 29424 10984, has_genre, 12841 10984, release_year, 29424 12599, has_genre, 12841 12599, has_tags, 12841 12599, release_year, 29424 2588, has_genre, 12841 2588, release_year, 29424 11259, has_genre, 12841 11259, release_year, 29424 20837, has_genre, 12841 20837, release_year, 29424 20969, has_genre, 12841 20969, release_year, 29424 30700, has_genre, 12841 30700, release_year, 29424 38461, has_genre, 12841 38461, release_year, 29424 27444, has_genre, 12841 27444, release_year, 29424 39587, has_genre, 12841 39587, release_year, 29424 30593, release_year, 9177 29052, has_genre, 12841 29052, release_year, 29424 36765, has_genre, 12841 36765, release_year, 29424 8476, has_genre, 12841 8476, release_year, 9177 16214, has_genre, 12841 16214, release_year, 29424 4896, has_genre, 12841 4896, has_tags, 12841 4896, release_year, 29424 9056, has_genre, 12841 9056, release_year, 29424 Question: For what reason are OF TIME AND THE CITY, ONE DAY, and THE VIOLENT YEARS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "OF TIME AND THE CITY", "ONE DAY", "THE VIOLENT YEARS" ], "valid_edges": [ [ "AFRICAN CATS", "has_genre", "DOCUMENTARY" ], [ "AFRICAN CATS", "release_year", "2011" ], [ "BEAUTY DAY", "has_genre", "DOCUMENTARY" ], [ "BEAUTY DAY", "release_year", "2011" ], [ "BORN TO BE WILD", "has_genre", "DOCUMENTARY" ], [ "BORN TO BE WILD", "release_year", "2011" ], [ "BULLY", "has_genre", "DOCUMENTARY" ], [ "BULLY", "release_year", "2011" ], [ "DEBTOCRACY", "has_genre", "DOCUMENTARY" ], [ "DEBTOCRACY", "release_year", "2011" ], [ "DREAMS OF A LIFE", "has_genre", "DOCUMENTARY" ], [ "DREAMS OF A LIFE", "release_year", "2011" ], [ "HAPPY", "has_genre", "DOCUMENTARY" ], [ "HAPPY", "has_tags", "DOCUMENTARY" ], [ "HAPPY", "release_year", "2011" ], [ "MAGIC TRIP", "has_genre", "DOCUMENTARY" ], [ "MAGIC TRIP", "release_year", "2011" ], [ "MISS REPRESENTATION", "has_genre", "DOCUMENTARY" ], [ "MISS REPRESENTATION", "release_year", "2011" ], [ "OF TIME AND THE CITY", "has_genre", "DOCUMENTARY" ], [ "ONE DAY", "release_year", "2011" ], [ "ONE LIFE", "has_genre", "DOCUMENTARY" ], [ "ONE LIFE", "release_year", "2011" ], [ "PEARL JAM TWENTY", "has_genre", "DOCUMENTARY" ], [ "PEARL JAM TWENTY", "release_year", "2011" ], [ "PINA", "has_genre", "DOCUMENTARY" ], [ "PINA", "has_tags", "DOCUMENTARY" ], [ "PINA", "release_year", "2011" ], [ "REVENGE OF THE ELECTRIC CAR", "has_genre", "DOCUMENTARY" ], [ "REVENGE OF THE ELECTRIC CAR", "release_year", "2011" ], [ "SURVIVING PROGRESS", "has_genre", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "has_tags", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "release_year", "2011" ], [ "THE AMBASSADOR", "has_genre", "DOCUMENTARY" ], [ "THE AMBASSADOR", "release_year", "2011" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "has_genre", "DOCUMENTARY" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "release_year", "2011" ], [ "THE CAPTAINS", "has_genre", "DOCUMENTARY" ], [ "THE CAPTAINS", "release_year", "2011" ], [ "THE FLAT", "has_genre", "DOCUMENTARY" ], [ "THE FLAT", "release_year", "2011" ], [ "THE INTERRUPTERS", "has_genre", "DOCUMENTARY" ], [ "THE INTERRUPTERS", "release_year", "2011" ], [ "THE LAST LIONS", "has_genre", "DOCUMENTARY" ], [ "THE LAST LIONS", "release_year", "2011" ], [ "THE LAST MOUNTAIN", "has_genre", "DOCUMENTARY" ], [ "THE LAST MOUNTAIN", "release_year", "2011" ], [ "THE OTHER F WORD", "has_genre", "DOCUMENTARY" ], [ "THE OTHER F WORD", "release_year", "2011" ], [ "THE VIOLENT YEARS", "release_year", "1956" ], [ "THESE AMAZING SHADOWS", "has_genre", "DOCUMENTARY" ], [ "THESE AMAZING SHADOWS", "release_year", "2011" ], [ "THIS IS NOT A FILM", "has_genre", "DOCUMENTARY" ], [ "THIS IS NOT A FILM", "release_year", "2011" ], [ "TOUTE LA MÉMOIRE DU MONDE", "has_genre", "DOCUMENTARY" ], [ "TOUTE LA MÉMOIRE DU MONDE", "release_year", "1956" ], [ "UNLAWFUL KILLING", "has_genre", "DOCUMENTARY" ], [ "UNLAWFUL KILLING", "release_year", "2011" ], [ "WHORES' GLORY", "has_genre", "DOCUMENTARY" ], [ "WHORES' GLORY", "has_tags", "DOCUMENTARY" ], [ "WHORES' GLORY", "release_year", "2011" ], [ "YOU'VE BEEN TRUMPED", "has_genre", "DOCUMENTARY" ], [ "YOU'VE BEEN TRUMPED", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 36647, 8 WOMEN 11957, 9 DEAD GAY GUYS 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 17111, ALI G INDAHOUSE 22569, ALL ABOUT THE BENJAMINS 16113, ANALYZE THAT 35314, AUSTIN POWERS IN GOLDMEMBER 29535, AVENGING ANGELO 23899, BAD COMPANY 36819, BARBERSHOP 19159, BEER FOR MY HORSES 15433, BEND IT LIKE BECKHAM 39619, BIG FAT LIAR 8732, BIG TROUBLE 27128, BOAT TRIP 9565, BOYS AND GIRLS 32620, BUBBA HO-TEP 14572, BUYING THE COW 27929, CABIN FEVER 23286, CARNAGE 20073, CHERISH 10349, CHICAGO 32644, CHINESE ODYSSEY 2002 30463, COMEDY 21391, CRACKERJACK 30019, CROSSROADS 21730, DAY OF THE WACKO 14292, DEAD IN THE WATER 19179, DEATH TO SMOOCHY 21079, DIRTY DEEDS 25651, DUMMY 26815, EIGHT CRAZY NIGHTS 38543, EIGHT LEGGED FREAKS 27539, FRANK MCKLUSKY, C.I. 29241, FRIDAY AFTER NEXT 10990, HEARTLANDS 3829, HERO 15629, HOME ALONE 4 22069, I SPY 27919, I'M WITH LUCY 16371, ICE AGE 17197, IGBY GOES DOWN 33001, JUST A KISS 2204, JUWANNA MANN 32010, KISS THE BRIDE 12137, LIFE OR SOMETHING LIKE IT 28832, LIFE WITHOUT DICK 16155, LOVE LIZA 9812, MAID IN MANHATTAN 4270, MEN WITH BROOMS 39368, MICHAEL SALOMON 36083, MIRANDA 20803, MR. DEEDS 22064, MY BIG FAT GREEK WEDDING 4887, MY LEFT EYE SEES GHOSTS 35262, MY MOTHER LIKES WOMEN 35794, NOVO 1493, NOW YOU KNOW 2721, OCCIDENT 4582, ONCE UPON A TIME IN THE MIDLANDS 37178, ORANGE COUNTY 27117, PASSIONADA 9976, PIPE DREAM 3688, PUMPKIN 34602, PUNCH-DRUNK LOVE 21890, R.S.V.P. 25769, ROGER DODGER 12987, SCOOBY-DOO 19244, SERVING SARA 6603, SEX IS COMEDY 26261, SHOWTIME 15043, SLACKERS 25151, SNOW DOGS 24961, SORORITY BOYS 35843, SPUN 5170, STEALING HARVARD 15100, SUPER SUCKER 9276, SWEET HOME ALABAMA 26790, SWEPT AWAY 36316, THE ADVENTURES OF PLUTO NASH 2316, THE ANARCHIST COOKBOOK 304, THE BANGER SISTERS 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 914, THE GOOD GIRL 26531, THE GURU 24302, THE HOT CHICK 13534, THE IMPORTANCE OF BEING EARNEST 2147, THE MAN WITHOUT A PAST 6908, THE MASTER OF DISGUISE 295, THE NEW GUY 1192, THE ONE AND ONLY 31401, THE RULES OF ATTRACTION 7052, THE SWEETEST THING 34172, THE TUXEDO 10720, TRIGGERMEN 9612, TWO WEEKS NOTICE 13214, UNCONDITIONAL LOVE 16991, UNDERCOVER BROTHER 21576, WAKING UP IN RENO 37568, WELCOME TO COLLINWOOD 39802, WHEN IN ROME src, edge_attr, dst 4310, has_genre, 30463 4310, release_year, 35935 9408, has_genre, 30463 9408, has_tags, 30463 9408, release_year, 35935 36647, has_genre, 30463 36647, release_year, 35935 11957, has_genre, 30463 11957, release_year, 35935 6008, has_genre, 30463 6008, has_tags, 30463 6008, release_year, 35935 37599, has_genre, 30463 37599, has_tags, 30463 37599, release_year, 35935 17111, has_genre, 30463 17111, release_year, 35935 22569, has_genre, 30463 22569, has_tags, 30463 22569, release_year, 35935 16113, has_genre, 30463 16113, has_tags, 30463 16113, release_year, 35935 35314, has_genre, 30463 35314, has_tags, 30463 35314, release_year, 35935 29535, has_genre, 30463 29535, release_year, 35935 23899, has_genre, 30463 23899, release_year, 35935 36819, has_genre, 30463 36819, release_year, 35935 19159, directed_by, 39368 19159, has_genre, 30463 15433, has_genre, 30463 15433, release_year, 35935 39619, has_genre, 30463 39619, release_year, 35935 8732, has_genre, 30463 8732, release_year, 35935 27128, has_genre, 30463 27128, release_year, 35935 9565, has_genre, 30463 32620, has_genre, 30463 32620, has_tags, 30463 32620, release_year, 35935 14572, has_genre, 30463 14572, release_year, 35935 27929, has_genre, 30463 27929, release_year, 35935 23286, has_genre, 30463 23286, release_year, 35935 20073, has_genre, 30463 20073, release_year, 35935 10349, has_genre, 30463 10349, release_year, 35935 32644, has_genre, 30463 32644, release_year, 35935 21391, has_genre, 30463 21391, release_year, 35935 30019, has_genre, 30463 30019, release_year, 35935 21730, has_genre, 30463 21730, release_year, 35935 14292, release_year, 35935 19179, has_genre, 30463 19179, release_year, 35935 21079, has_genre, 30463 21079, has_tags, 30463 21079, release_year, 35935 25651, has_genre, 30463 25651, release_year, 35935 26815, has_genre, 30463 26815, release_year, 35935 38543, has_genre, 30463 38543, release_year, 35935 27539, has_genre, 30463 27539, release_year, 35935 29241, has_genre, 30463 29241, release_year, 35935 10990, has_genre, 30463 10990, release_year, 35935 3829, has_genre, 30463 3829, release_year, 35935 15629, has_genre, 30463 15629, release_year, 35935 22069, has_genre, 30463 22069, has_tags, 30463 22069, release_year, 35935 27919, has_genre, 30463 27919, release_year, 35935 16371, has_genre, 30463 16371, has_tags, 30463 16371, release_year, 35935 17197, has_genre, 30463 17197, release_year, 35935 33001, has_genre, 30463 33001, release_year, 35935 2204, has_genre, 30463 2204, release_year, 35935 32010, has_genre, 30463 32010, release_year, 35935 12137, has_genre, 30463 12137, release_year, 35935 28832, has_genre, 30463 28832, release_year, 35935 16155, has_genre, 30463 16155, release_year, 35935 9812, has_genre, 30463 9812, release_year, 35935 4270, has_genre, 30463 4270, release_year, 35935 36083, has_genre, 30463 36083, release_year, 35935 20803, has_genre, 30463 20803, release_year, 35935 22064, has_genre, 30463 22064, has_tags, 30463 22064, release_year, 35935 4887, has_genre, 30463 4887, release_year, 35935 35262, has_genre, 30463 35262, release_year, 35935 35794, has_genre, 30463 35794, release_year, 35935 1493, has_genre, 30463 1493, release_year, 35935 2721, has_genre, 30463 2721, release_year, 35935 4582, has_genre, 30463 4582, release_year, 35935 37178, has_genre, 30463 37178, release_year, 35935 27117, has_genre, 30463 27117, release_year, 35935 9976, has_genre, 30463 9976, release_year, 35935 3688, has_genre, 30463 3688, release_year, 35935 34602, has_genre, 30463 34602, has_tags, 30463 34602, release_year, 35935 21890, has_genre, 30463 21890, release_year, 35935 25769, has_genre, 30463 25769, release_year, 35935 12987, has_genre, 30463 12987, release_year, 35935 19244, has_genre, 30463 19244, release_year, 35935 6603, has_genre, 30463 6603, release_year, 35935 26261, has_genre, 30463 26261, release_year, 35935 15043, has_genre, 30463 15043, release_year, 35935 25151, has_genre, 30463 25151, release_year, 35935 24961, has_genre, 30463 24961, release_year, 35935 35843, has_genre, 30463 35843, release_year, 35935 5170, has_genre, 30463 5170, release_year, 35935 15100, has_genre, 30463 15100, release_year, 35935 9276, has_genre, 30463 9276, release_year, 35935 26790, has_genre, 30463 26790, release_year, 35935 36316, has_genre, 30463 36316, release_year, 35935 2316, has_genre, 30463 2316, release_year, 35935 304, has_genre, 30463 304, release_year, 35935 11696, has_genre, 30463 11696, release_year, 35935 3324, has_genre, 30463 3324, release_year, 35935 914, has_genre, 30463 914, release_year, 35935 26531, has_genre, 30463 26531, release_year, 35935 24302, has_genre, 30463 24302, has_tags, 30463 24302, release_year, 35935 13534, has_genre, 30463 13534, release_year, 35935 2147, has_genre, 30463 2147, release_year, 35935 6908, has_genre, 30463 6908, release_year, 35935 295, has_genre, 30463 295, release_year, 35935 1192, has_genre, 30463 1192, release_year, 35935 31401, has_genre, 30463 31401, release_year, 35935 7052, has_genre, 30463 7052, has_tags, 30463 7052, release_year, 35935 34172, has_genre, 30463 34172, has_tags, 30463 34172, release_year, 35935 10720, has_genre, 30463 10720, release_year, 35935 9612, has_genre, 30463 9612, release_year, 35935 13214, has_genre, 30463 13214, release_year, 35935 16991, has_genre, 30463 16991, release_year, 35935 21576, has_genre, 30463 21576, release_year, 35935 37568, has_genre, 30463 37568, has_tags, 30463 37568, release_year, 35935 39802, has_genre, 30463 39802, release_year, 35935 Question: How are BOYS AND GIRLS, DEAD IN THE WATER, and MICHAEL SALOMON related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BOYS AND GIRLS", "DEAD IN THE WATER", "MICHAEL SALOMON" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_genre", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "release_year", "2002" ], [ "9 DEAD GAY GUYS", "has_genre", "COMEDY" ], [ "9 DEAD GAY GUYS", "release_year", "2002" ], [ "ABOUT A BOY", "has_genre", "COMEDY" ], [ "ABOUT A BOY", "has_tags", "COMEDY" ], [ "ABOUT A BOY", "release_year", "2002" ], [ "ABOUT SCHMIDT", "has_genre", "COMEDY" ], [ "ABOUT SCHMIDT", "has_tags", "COMEDY" ], [ "ABOUT SCHMIDT", "release_year", "2002" ], [ "ALI G INDAHOUSE", "has_genre", "COMEDY" ], [ "ALI G INDAHOUSE", "release_year", "2002" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "release_year", "2002" ], [ "ANALYZE THAT", "has_genre", "COMEDY" ], [ "ANALYZE THAT", "has_tags", "COMEDY" ], [ "ANALYZE THAT", "release_year", "2002" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_genre", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_tags", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "release_year", "2002" ], [ "AVENGING ANGELO", "has_genre", "COMEDY" ], [ "AVENGING ANGELO", "release_year", "2002" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "release_year", "2002" ], [ "BARBERSHOP", "has_genre", "COMEDY" ], [ "BARBERSHOP", "release_year", "2002" ], [ "BEER FOR MY HORSES", "directed_by", "MICHAEL SALOMON" ], [ "BEER FOR MY HORSES", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "release_year", "2002" ], [ "BIG FAT LIAR", "has_genre", "COMEDY" ], [ "BIG FAT LIAR", "release_year", "2002" ], [ "BIG TROUBLE", "has_genre", "COMEDY" ], [ "BIG TROUBLE", "release_year", "2002" ], [ "BOAT TRIP", "has_genre", "COMEDY" ], [ "BOAT TRIP", "release_year", "2002" ], [ "BOYS AND GIRLS", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_tags", "COMEDY" ], [ "BUBBA HO-TEP", "release_year", "2002" ], [ "BUYING THE COW", "has_genre", "COMEDY" ], [ "BUYING THE COW", "release_year", "2002" ], [ "CABIN FEVER", "has_genre", "COMEDY" ], [ "CABIN FEVER", "release_year", "2002" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "release_year", "2002" ], [ "CHERISH", "has_genre", "COMEDY" ], [ "CHERISH", "release_year", "2002" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "release_year", "2002" ], [ "CHINESE ODYSSEY 2002", "has_genre", "COMEDY" ], [ "CHINESE ODYSSEY 2002", "release_year", "2002" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "2002" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "release_year", "2002" ], [ "DAY OF THE WACKO", "has_genre", "COMEDY" ], [ "DAY OF THE WACKO", "release_year", "2002" ], [ "DEAD IN THE WATER", "release_year", "2002" ], [ "DEATH TO SMOOCHY", "has_genre", "COMEDY" ], [ "DEATH TO SMOOCHY", "release_year", "2002" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIRTY DEEDS", "release_year", "2002" ], [ "DUMMY", "has_genre", "COMEDY" ], [ "DUMMY", "release_year", "2002" ], [ "EIGHT CRAZY NIGHTS", "has_genre", "COMEDY" ], [ "EIGHT CRAZY NIGHTS", "release_year", "2002" ], [ "EIGHT LEGGED FREAKS", "has_genre", "COMEDY" ], [ "EIGHT LEGGED FREAKS", "release_year", "2002" ], [ "FRANK MCKLUSKY, C.I.", "has_genre", "COMEDY" ], [ "FRANK MCKLUSKY, C.I.", "release_year", "2002" ], [ "FRIDAY AFTER NEXT", "has_genre", "COMEDY" ], [ "FRIDAY AFTER NEXT", "release_year", "2002" ], [ "HEARTLANDS", "has_genre", "COMEDY" ], [ "HEARTLANDS", "release_year", "2002" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "release_year", "2002" ], [ "HOME ALONE 4", "has_genre", "COMEDY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "I SPY", "has_genre", "COMEDY" ], [ "I SPY", "has_tags", "COMEDY" ], [ "I SPY", "release_year", "2002" ], [ "I'M WITH LUCY", "has_genre", "COMEDY" ], [ "I'M WITH LUCY", "release_year", "2002" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "release_year", "2002" ], [ "IGBY GOES DOWN", "has_genre", "COMEDY" ], [ "IGBY GOES DOWN", "release_year", "2002" ], [ "JUST A KISS", "has_genre", "COMEDY" ], [ "JUST A KISS", "release_year", "2002" ], [ "JUWANNA MANN", "has_genre", "COMEDY" ], [ "JUWANNA MANN", "release_year", "2002" ], [ "KISS THE BRIDE", "has_genre", "COMEDY" ], [ "KISS THE BRIDE", "release_year", "2002" ], [ "LIFE OR SOMETHING LIKE IT", "has_genre", "COMEDY" ], [ "LIFE OR SOMETHING LIKE IT", "release_year", "2002" ], [ "LIFE WITHOUT DICK", "has_genre", "COMEDY" ], [ "LIFE WITHOUT DICK", "release_year", "2002" ], [ "LOVE LIZA", "has_genre", "COMEDY" ], [ "LOVE LIZA", "release_year", "2002" ], [ "MAID IN MANHATTAN", "has_genre", "COMEDY" ], [ "MAID IN MANHATTAN", "release_year", "2002" ], [ "MEN WITH BROOMS", "has_genre", "COMEDY" ], [ "MEN WITH BROOMS", "release_year", "2002" ], [ "MIRANDA", "has_genre", "COMEDY" ], [ "MIRANDA", "release_year", "2002" ], [ "MR. DEEDS", "has_genre", "COMEDY" ], [ "MR. DEEDS", "release_year", "2002" ], [ "MY BIG FAT GREEK WEDDING", "has_genre", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "has_tags", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "release_year", "2002" ], [ "MY LEFT EYE SEES GHOSTS", "has_genre", "COMEDY" ], [ "MY LEFT EYE SEES GHOSTS", "release_year", "2002" ], [ "MY MOTHER LIKES WOMEN", "has_genre", "COMEDY" ], [ "MY MOTHER LIKES WOMEN", "release_year", "2002" ], [ "NOVO", "has_genre", "COMEDY" ], [ "NOVO", "release_year", "2002" ], [ "NOW YOU KNOW", "has_genre", "COMEDY" ], [ "NOW YOU KNOW", "release_year", "2002" ], [ "OCCIDENT", "has_genre", "COMEDY" ], [ "OCCIDENT", "release_year", "2002" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "has_genre", "COMEDY" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "release_year", "2002" ], [ "ORANGE COUNTY", "has_genre", "COMEDY" ], [ "ORANGE COUNTY", "release_year", "2002" ], [ "PASSIONADA", "has_genre", "COMEDY" ], [ "PASSIONADA", "release_year", "2002" ], [ "PIPE DREAM", "has_genre", "COMEDY" ], [ "PIPE DREAM", "release_year", "2002" ], [ "PUMPKIN", "has_genre", "COMEDY" ], [ "PUMPKIN", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "R.S.V.P.", "has_genre", "COMEDY" ], [ "R.S.V.P.", "release_year", "2002" ], [ "ROGER DODGER", "has_genre", "COMEDY" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SCOOBY-DOO", "has_genre", "COMEDY" ], [ "SCOOBY-DOO", "release_year", "2002" ], [ "SERVING SARA", "has_genre", "COMEDY" ], [ "SERVING SARA", "release_year", "2002" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "SHOWTIME", "has_genre", "COMEDY" ], [ "SHOWTIME", "release_year", "2002" ], [ "SLACKERS", "has_genre", "COMEDY" ], [ "SLACKERS", "release_year", "2002" ], [ "SNOW DOGS", "has_genre", "COMEDY" ], [ "SNOW DOGS", "release_year", "2002" ], [ "SORORITY BOYS", "has_genre", "COMEDY" ], [ "SORORITY BOYS", "release_year", "2002" ], [ "SPUN", "has_genre", "COMEDY" ], [ "SPUN", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SUPER SUCKER", "has_genre", "COMEDY" ], [ "SUPER SUCKER", "release_year", "2002" ], [ "SWEET HOME ALABAMA", "has_genre", "COMEDY" ], [ "SWEET HOME ALABAMA", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "THE ADVENTURES OF PLUTO NASH", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PLUTO NASH", "release_year", "2002" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "COMEDY" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BANGER SISTERS", "has_genre", "COMEDY" ], [ "THE BANGER SISTERS", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "COMEDY" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "COMEDY" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "release_year", "2002" ], [ "THE GURU", "has_genre", "COMEDY" ], [ "THE GURU", "release_year", "2002" ], [ "THE HOT CHICK", "has_genre", "COMEDY" ], [ "THE HOT CHICK", "has_tags", "COMEDY" ], [ "THE HOT CHICK", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "COMEDY" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE MAN WITHOUT A PAST", "has_genre", "COMEDY" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE MASTER OF DISGUISE", "has_genre", "COMEDY" ], [ "THE MASTER OF DISGUISE", "release_year", "2002" ], [ "THE NEW GUY", "has_genre", "COMEDY" ], [ "THE NEW GUY", "release_year", "2002" ], [ "THE ONE AND ONLY", "has_genre", "COMEDY" ], [ "THE ONE AND ONLY", "release_year", "2002" ], [ "THE RULES OF ATTRACTION", "has_genre", "COMEDY" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SWEETEST THING", "has_genre", "COMEDY" ], [ "THE SWEETEST THING", "has_tags", "COMEDY" ], [ "THE SWEETEST THING", "release_year", "2002" ], [ "THE TUXEDO", "has_genre", "COMEDY" ], [ "THE TUXEDO", "has_tags", "COMEDY" ], [ "THE TUXEDO", "release_year", "2002" ], [ "TRIGGERMEN", "has_genre", "COMEDY" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "TWO WEEKS NOTICE", "has_genre", "COMEDY" ], [ "TWO WEEKS NOTICE", "release_year", "2002" ], [ "UNCONDITIONAL LOVE", "has_genre", "COMEDY" ], [ "UNCONDITIONAL LOVE", "release_year", "2002" ], [ "UNDERCOVER BROTHER", "has_genre", "COMEDY" ], [ "UNDERCOVER BROTHER", "release_year", "2002" ], [ "WAKING UP IN RENO", "has_genre", "COMEDY" ], [ "WAKING UP IN RENO", "release_year", "2002" ], [ "WELCOME TO COLLINWOOD", "has_genre", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "has_tags", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "release_year", "2002" ], [ "WHEN IN ROME", "has_genre", "COMEDY" ], [ "WHEN IN ROME", "release_year", "2002" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15374, 2005 4763, ADVENTURE 5155, DANNY DYER 7498, FLIGHTPLAN 37073, MRS. PALFREY AT THE CLAREMONT 24949, NICK LOVE 24746, NOAH RINGER 13539, OUTLAW 21756, RUPERT FRIEND 11043, SEAN BEAN 29129, THE ADVENTURES OF ROBIN HOOD 35282, THE BUSINESS 32465, THE FOOTBALL FACTORY 38073, THE LAST AIRBENDER 4786, THE WILLOW TREE src, edge_attr, dst 7498, release_year, 15374 7498, starred_actors, 11043 37073, release_year, 15374 37073, starred_actors, 21756 13539, directed_by, 24949 13539, starred_actors, 5155 13539, starred_actors, 21756 13539, starred_actors, 11043 13539, written_by, 24949 29129, has_genre, 4763 29129, has_tags, 13539 35282, directed_by, 24949 35282, release_year, 15374 35282, starred_actors, 5155 35282, written_by, 24949 32465, directed_by, 24949 32465, starred_actors, 5155 32465, written_by, 24949 38073, has_genre, 4763 38073, starred_actors, 24746 4786, release_year, 15374 Question: In what context are NOAH RINGER, OUTLAW, and THE WILLOW TREE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "NOAH RINGER", "OUTLAW", "THE WILLOW TREE" ], "valid_edges": [ [ "FLIGHTPLAN", "release_year", "2005" ], [ "FLIGHTPLAN", "starred_actors", "SEAN BEAN" ], [ "MRS. PALFREY AT THE CLAREMONT", "release_year", "2005" ], [ "MRS. PALFREY AT THE CLAREMONT", "starred_actors", "RUPERT FRIEND" ], [ "OUTLAW", "directed_by", "NICK LOVE" ], [ "OUTLAW", "starred_actors", "DANNY DYER" ], [ "OUTLAW", "starred_actors", "RUPERT FRIEND" ], [ "OUTLAW", "starred_actors", "SEAN BEAN" ], [ "OUTLAW", "written_by", "NICK LOVE" ], [ "THE ADVENTURES OF ROBIN HOOD", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF ROBIN HOOD", "has_tags", "OUTLAW" ], [ "THE BUSINESS", "directed_by", "NICK LOVE" ], [ "THE BUSINESS", "release_year", "2005" ], [ "THE BUSINESS", "starred_actors", "DANNY DYER" ], [ "THE BUSINESS", "written_by", "NICK LOVE" ], [ "THE FOOTBALL FACTORY", "directed_by", "NICK LOVE" ], [ "THE FOOTBALL FACTORY", "starred_actors", "DANNY DYER" ], [ "THE FOOTBALL FACTORY", "written_by", "NICK LOVE" ], [ "THE LAST AIRBENDER", "has_genre", "ADVENTURE" ], [ "THE LAST AIRBENDER", "starred_actors", "NOAH RINGER" ], [ "THE WILLOW TREE", "release_year", "2005" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 9377, 2014 5906, ANDREW WIGHT 31095, BRIDESMAIDS 33773, BÉBÉ'S KIDS 13812, CALVARY 33403, CHRIS O'DOWD 30463, COMEDY 36212, DRAMA 26412, FRIENDS WITH KIDS 17037, HOUSE PARTY 22972, MAYA RUDOLPH 29527, MELISSA MCCARTHY 22173, REGINALD HUDLIN 29173, ROBIN HARRIS 7209, SANCTUM 19715, ST. VINCENT src, edge_attr, dst 31095, has_genre, 30463 31095, has_tags, 33403 31095, has_tags, 30463 31095, has_tags, 22972 31095, has_tags, 29527 31095, release_year, 29424 31095, starred_actors, 22972 33773, has_genre, 30463 33773, starred_actors, 29173 33773, written_by, 22173 33773, written_by, 29173 13812, has_genre, 36212 13812, has_tags, 33403 13812, release_year, 9377 13812, starred_actors, 33403 26412, has_genre, 30463 26412, has_tags, 33403 26412, has_tags, 22972 26412, release_year, 29424 26412, starred_actors, 33403 26412, starred_actors, 22972 17037, directed_by, 22173 17037, has_genre, 30463 17037, has_tags, 22173 17037, starred_actors, 29173 17037, written_by, 22173 7209, has_genre, 36212 7209, release_year, 29424 7209, written_by, 5906 19715, has_genre, 30463 19715, has_genre, 36212 19715, has_tags, 33403 19715, has_tags, 29527 19715, release_year, 9377 19715, starred_actors, 33403 19715, starred_actors, 29527 Question: In what context are ANDREW WIGHT, CHRIS O'DOWD, and ROBIN HARRIS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANDREW WIGHT", "CHRIS O'DOWD", "ROBIN HARRIS" ], "valid_edges": [ [ "BRIDESMAIDS", "has_genre", "COMEDY" ], [ "BRIDESMAIDS", "has_tags", "CHRIS O'DOWD" ], [ "BRIDESMAIDS", "has_tags", "COMEDY" ], [ "BRIDESMAIDS", "has_tags", "MAYA RUDOLPH" ], [ "BRIDESMAIDS", "has_tags", "MELISSA MCCARTHY" ], [ "BRIDESMAIDS", "release_year", "2011" ], [ "BRIDESMAIDS", "starred_actors", "MAYA RUDOLPH" ], [ "BÉBÉ'S KIDS", "has_genre", "COMEDY" ], [ "BÉBÉ'S KIDS", "starred_actors", "ROBIN HARRIS" ], [ "BÉBÉ'S KIDS", "written_by", "REGINALD HUDLIN" ], [ "BÉBÉ'S KIDS", "written_by", "ROBIN HARRIS" ], [ "CALVARY", "has_genre", "DRAMA" ], [ "CALVARY", "has_tags", "CHRIS O'DOWD" ], [ "CALVARY", "release_year", "2014" ], [ "CALVARY", "starred_actors", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "has_genre", "COMEDY" ], [ "FRIENDS WITH KIDS", "has_tags", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "has_tags", "MAYA RUDOLPH" ], [ "FRIENDS WITH KIDS", "release_year", "2011" ], [ "FRIENDS WITH KIDS", "starred_actors", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "starred_actors", "MAYA RUDOLPH" ], [ "HOUSE PARTY", "directed_by", "REGINALD HUDLIN" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "has_tags", "REGINALD HUDLIN" ], [ "HOUSE PARTY", "starred_actors", "ROBIN HARRIS" ], [ "HOUSE PARTY", "written_by", "REGINALD HUDLIN" ], [ "SANCTUM", "has_genre", "DRAMA" ], [ "SANCTUM", "release_year", "2011" ], [ "SANCTUM", "written_by", "ANDREW WIGHT" ], [ "ST. VINCENT", "has_genre", "COMEDY" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "has_tags", "CHRIS O'DOWD" ], [ "ST. VINCENT", "has_tags", "MELISSA MCCARTHY" ], [ "ST. VINCENT", "release_year", "2014" ], [ "ST. VINCENT", "starred_actors", "CHRIS O'DOWD" ], [ "ST. VINCENT", "starred_actors", "MELISSA MCCARTHY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26002, 10 TO MIDNIGHT 25221, 1981 15206, ANTHOLOGY 35575, CHARLES BRONSON 2979, DEATH HUNT 32864, GHOST STORY 27238, HAPPY BIRTHDAY TO ME 25412, HOOD OF HORROR 19805, J. LEE THOMPSON 4418, KWAIDAN 30157, LOLA 10823, MESSENGER OF DEATH 156, MURPHY'S LAW 28357, ST. IVES 2878, THE EVIL THAT MEN DO src, edge_attr, dst 26002, directed_by, 19805 26002, starred_actors, 35575 2979, release_year, 25221 2979, starred_actors, 35575 32864, release_year, 25221 27238, directed_by, 19805 27238, release_year, 25221 25412, has_tags, 15206 4418, has_tags, 15206 4418, has_tags, 32864 30157, release_year, 25221 30157, starred_actors, 35575 10823, directed_by, 19805 10823, starred_actors, 35575 156, directed_by, 19805 156, starred_actors, 35575 28357, directed_by, 19805 28357, starred_actors, 35575 2878, directed_by, 19805 2878, starred_actors, 35575 Question: In what context are GHOST STORY, HOOD OF HORROR, and MURPHY'S LAW connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GHOST STORY", "HOOD OF HORROR", "MURPHY'S LAW" ], "valid_edges": [ [ "10 TO MIDNIGHT", "directed_by", "J. LEE THOMPSON" ], [ "10 TO MIDNIGHT", "starred_actors", "CHARLES BRONSON" ], [ "DEATH HUNT", "release_year", "1981" ], [ "DEATH HUNT", "starred_actors", "CHARLES BRONSON" ], [ "GHOST STORY", "release_year", "1981" ], [ "HAPPY BIRTHDAY TO ME", "directed_by", "J. LEE THOMPSON" ], [ "HAPPY BIRTHDAY TO ME", "release_year", "1981" ], [ "HOOD OF HORROR", "has_tags", "ANTHOLOGY" ], [ "KWAIDAN", "has_tags", "ANTHOLOGY" ], [ "KWAIDAN", "has_tags", "GHOST STORY" ], [ "LOLA", "release_year", "1981" ], [ "LOLA", "starred_actors", "CHARLES BRONSON" ], [ "MESSENGER OF DEATH", "directed_by", "J. LEE THOMPSON" ], [ "MESSENGER OF DEATH", "starred_actors", "CHARLES BRONSON" ], [ "MURPHY'S LAW", "directed_by", "J. LEE THOMPSON" ], [ "MURPHY'S LAW", "starred_actors", "CHARLES BRONSON" ], [ "ST. IVES", "directed_by", "J. LEE THOMPSON" ], [ "ST. IVES", "starred_actors", "CHARLES BRONSON" ], [ "THE EVIL THAT MEN DO", "directed_by", "J. LEE THOMPSON" ], [ "THE EVIL THAT MEN DO", "starred_actors", "CHARLES BRONSON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26513, EDMOND O'BRIEN 31783, ENGLISH 819, FIST OF THE NORTH STAR 15667, HUMPHREY BOGART 8239, KID GALAHAD 13889, MICHAEL CURTIZ 32167, SETON I. MILLER 7554, THE BAREFOOT CONTESSA 11265, THE SEA HAWK 11351, TONY RANDEL src, edge_attr, dst 819, directed_by, 11351 819, in_language, 31783 819, written_by, 11351 8239, directed_by, 13889 8239, has_tags, 13889 8239, starred_actors, 15667 8239, written_by, 32167 7554, starred_actors, 26513 7554, starred_actors, 15667 11265, directed_by, 13889 11265, has_tags, 13889 11265, in_language, 31783 11265, written_by, 32167 Question: In what context are EDMOND O'BRIEN, SETON I. MILLER, and TONY RANDEL connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EDMOND O'BRIEN", "SETON I. MILLER", "TONY RANDEL" ], "valid_edges": [ [ "FIST OF THE NORTH STAR", "directed_by", "TONY RANDEL" ], [ "FIST OF THE NORTH STAR", "in_language", "ENGLISH" ], [ "FIST OF THE NORTH STAR", "written_by", "TONY RANDEL" ], [ "KID GALAHAD", "directed_by", "MICHAEL CURTIZ" ], [ "KID GALAHAD", "has_tags", "MICHAEL CURTIZ" ], [ "KID GALAHAD", "starred_actors", "HUMPHREY BOGART" ], [ "KID GALAHAD", "written_by", "SETON I. MILLER" ], [ "THE BAREFOOT CONTESSA", "starred_actors", "EDMOND O'BRIEN" ], [ "THE BAREFOOT CONTESSA", "starred_actors", "HUMPHREY BOGART" ], [ "THE SEA HAWK", "directed_by", "MICHAEL CURTIZ" ], [ "THE SEA HAWK", "has_tags", "MICHAEL CURTIZ" ], [ "THE SEA HAWK", "in_language", "ENGLISH" ], [ "THE SEA HAWK", "written_by", "SETON I. MILLER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32082, 11-11-11 18132, 1938 658, 2012 30146, A CHRISTMAS CAROL 25735, ALAN MOWBRAY 6793, AND THEN THERE WERE NONE 10045, BD-R 38850, BILLIE BURKE 235, BRINGING UP BABY 38693, CHILD BRIDE 32610, CONSTANCE BENNETT 12161, DARREN LYNN BOUSMAN 24481, FRANCHISE 7289, HOLIDAY 5870, HORROR 14156, KING SOLOMON'S MINES 628, LEIGH WHANNELL 10284, LOVE FINDS ANDY HARDY 21045, MAX SCHRECK 3092, MERRILY WE LIVE 24593, MUSICAL 32891, NOSFERATU 33032, PORT OF SHADOWS 30416, REPO! THE GENETIC OPERA 27857, ROLAND YOUNG 6201, ROOM SERVICE 2561, SAW II 5812, SAW III 22536, SAW IV 13197, SHAWNEE SMITH 22336, TERRANCE ZDUNICH 8220, THAT HAMILTON WOMAN 3223, THE BARKLEYS OF BROADWAY 25250, THE BARRENS 7153, THE DEVIL'S CARNIVAL 4091, THE LADY VANISHES 5128, THERE GOES MY HEART 12105, TOBIN BELL 9800, TOPPER TAKES A TRIP 9050, WHAT PRICE HOLLYWOOD? src, edge_attr, dst 32082, directed_by, 12161 32082, has_genre, 5870 32082, written_by, 12161 30146, has_tags, 10045 30146, release_year, 18132 6793, has_tags, 10045 6793, starred_actors, 27857 235, has_tags, 10045 235, release_year, 18132 38693, has_tags, 10045 38693, release_year, 18132 7289, has_tags, 10045 7289, release_year, 18132 14156, has_tags, 10045 14156, starred_actors, 27857 10284, has_tags, 10045 10284, release_year, 18132 3092, has_tags, 10045 3092, release_year, 18132 3092, starred_actors, 25735 3092, starred_actors, 38850 3092, starred_actors, 32610 32891, has_genre, 5870 32891, has_tags, 10045 32891, starred_actors, 21045 33032, has_tags, 10045 33032, release_year, 18132 30416, directed_by, 12161 30416, has_genre, 5870 30416, has_genre, 24593 30416, has_tags, 24593 30416, written_by, 22336 6201, has_tags, 10045 6201, release_year, 18132 2561, directed_by, 12161 2561, has_genre, 5870 2561, has_tags, 12161 2561, has_tags, 24481 2561, has_tags, 5870 2561, starred_actors, 13197 2561, starred_actors, 12105 2561, written_by, 12161 2561, written_by, 628 5812, directed_by, 12161 5812, has_genre, 5870 5812, has_tags, 12161 5812, has_tags, 24481 5812, starred_actors, 13197 5812, starred_actors, 12105 5812, written_by, 628 22536, directed_by, 12161 22536, has_genre, 5870 22536, has_tags, 12161 22536, has_tags, 24481 22536, starred_actors, 12105 8220, has_tags, 10045 8220, starred_actors, 25735 3223, has_tags, 10045 3223, starred_actors, 38850 25250, directed_by, 12161 25250, has_genre, 5870 25250, release_year, 658 25250, written_by, 12161 7153, directed_by, 12161 7153, has_genre, 5870 7153, has_genre, 24593 7153, release_year, 658 7153, starred_actors, 22336 7153, written_by, 22336 4091, has_tags, 10045 4091, release_year, 18132 5128, has_tags, 10045 5128, release_year, 18132 9800, has_tags, 10045 9800, release_year, 18132 9800, starred_actors, 25735 9800, starred_actors, 38850 9800, starred_actors, 32610 9800, starred_actors, 27857 9050, has_tags, 10045 9050, starred_actors, 32610 Question: For what reason are DARREN LYNN BOUSMAN, MAX SCHRECK, and TOPPER TAKES A TRIP associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DARREN LYNN BOUSMAN", "MAX SCHRECK", "TOPPER TAKES A TRIP" ], "valid_edges": [ [ "11-11-11", "directed_by", "DARREN LYNN BOUSMAN" ], [ "11-11-11", "has_genre", "HORROR" ], [ "11-11-11", "written_by", "DARREN LYNN BOUSMAN" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "release_year", "1938" ], [ "AND THEN THERE WERE NONE", "has_tags", "BD-R" ], [ "AND THEN THERE WERE NONE", "starred_actors", "ROLAND YOUNG" ], [ "BRINGING UP BABY", "has_tags", "BD-R" ], [ "BRINGING UP BABY", "release_year", "1938" ], [ "CHILD BRIDE", "has_tags", "BD-R" ], [ "CHILD BRIDE", "release_year", "1938" ], [ "HOLIDAY", "has_tags", "BD-R" ], [ "HOLIDAY", "release_year", "1938" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KING SOLOMON'S MINES", "starred_actors", "ROLAND YOUNG" ], [ "LOVE FINDS ANDY HARDY", "has_tags", "BD-R" ], [ "LOVE FINDS ANDY HARDY", "release_year", "1938" ], [ "MERRILY WE LIVE", "has_tags", "BD-R" ], [ "MERRILY WE LIVE", "release_year", "1938" ], [ "MERRILY WE LIVE", "starred_actors", "ALAN MOWBRAY" ], [ "MERRILY WE LIVE", "starred_actors", "BILLIE BURKE" ], [ "MERRILY WE LIVE", "starred_actors", "CONSTANCE BENNETT" ], [ "NOSFERATU", "has_genre", "HORROR" ], [ "NOSFERATU", "has_tags", "BD-R" ], [ "NOSFERATU", "starred_actors", "MAX SCHRECK" ], [ "PORT OF SHADOWS", "has_tags", "BD-R" ], [ "PORT OF SHADOWS", "release_year", "1938" ], [ "REPO! THE GENETIC OPERA", "directed_by", "DARREN LYNN BOUSMAN" ], [ "REPO! THE GENETIC OPERA", "has_genre", "HORROR" ], [ "REPO! THE GENETIC OPERA", "has_genre", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "has_tags", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "written_by", "TERRANCE ZDUNICH" ], [ "ROOM SERVICE", "has_tags", "BD-R" ], [ "ROOM SERVICE", "release_year", "1938" ], [ "SAW II", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW II", "has_genre", "HORROR" ], [ "SAW II", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW II", "has_tags", "FRANCHISE" ], [ "SAW II", "has_tags", "HORROR" ], [ "SAW II", "starred_actors", "SHAWNEE SMITH" ], [ "SAW II", "starred_actors", "TOBIN BELL" ], [ "SAW II", "written_by", "DARREN LYNN BOUSMAN" ], [ "SAW II", "written_by", "LEIGH WHANNELL" ], [ "SAW III", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW III", "has_genre", "HORROR" ], [ "SAW III", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW III", "has_tags", "FRANCHISE" ], [ "SAW III", "starred_actors", "SHAWNEE SMITH" ], [ "SAW III", "starred_actors", "TOBIN BELL" ], [ "SAW III", "written_by", "LEIGH WHANNELL" ], [ "SAW IV", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW IV", "has_genre", "HORROR" ], [ "SAW IV", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW IV", "has_tags", "FRANCHISE" ], [ "SAW IV", "starred_actors", "TOBIN BELL" ], [ "THAT HAMILTON WOMAN", "has_tags", "BD-R" ], [ "THAT HAMILTON WOMAN", "starred_actors", "ALAN MOWBRAY" ], [ "THE BARKLEYS OF BROADWAY", "has_tags", "BD-R" ], [ "THE BARKLEYS OF BROADWAY", "starred_actors", "BILLIE BURKE" ], [ "THE BARRENS", "directed_by", "DARREN LYNN BOUSMAN" ], [ "THE BARRENS", "has_genre", "HORROR" ], [ "THE BARRENS", "release_year", "2012" ], [ "THE BARRENS", "written_by", "DARREN LYNN BOUSMAN" ], [ "THE DEVIL'S CARNIVAL", "directed_by", "DARREN LYNN BOUSMAN" ], [ "THE DEVIL'S CARNIVAL", "has_genre", "HORROR" ], [ "THE DEVIL'S CARNIVAL", "has_genre", "MUSICAL" ], [ "THE DEVIL'S CARNIVAL", "release_year", "2012" ], [ "THE DEVIL'S CARNIVAL", "starred_actors", "TERRANCE ZDUNICH" ], [ "THE DEVIL'S CARNIVAL", "written_by", "TERRANCE ZDUNICH" ], [ "THE LADY VANISHES", "has_tags", "BD-R" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "THERE GOES MY HEART", "has_tags", "BD-R" ], [ "THERE GOES MY HEART", "release_year", "1938" ], [ "TOPPER TAKES A TRIP", "has_tags", "BD-R" ], [ "TOPPER TAKES A TRIP", "release_year", "1938" ], [ "TOPPER TAKES A TRIP", "starred_actors", "ALAN MOWBRAY" ], [ "TOPPER TAKES A TRIP", "starred_actors", "BILLIE BURKE" ], [ "TOPPER TAKES A TRIP", "starred_actors", "CONSTANCE BENNETT" ], [ "TOPPER TAKES A TRIP", "starred_actors", "ROLAND YOUNG" ], [ "WHAT PRICE HOLLYWOOD?", "has_tags", "BD-R" ], [ "WHAT PRICE HOLLYWOOD?", "starred_actors", "CONSTANCE BENNETT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38707, ASYLUM 36212, DRAMA 12367, HASSINA BURGAN 5870, HORROR 10128, JACOB'S LADDER 37353, NOEL 3100, PSYCHOLOGICAL HORROR 6696, SESSION 9 1195, THE PATIENCE STONE 22214, WAR src, edge_attr, dst 38707, has_genre, 36212 10128, has_genre, 5870 10128, has_tags, 3100 10128, has_tags, 22214 37353, has_genre, 36212 37353, has_tags, 36212 6696, has_genre, 5870 6696, has_tags, 38707 6696, has_tags, 5870 6696, has_tags, 3100 1195, has_genre, 36212 1195, has_genre, 22214 1195, starred_actors, 12367 Question: In what context are HASSINA BURGAN, NOEL, and PSYCHOLOGICAL HORROR connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HASSINA BURGAN", "NOEL", "PSYCHOLOGICAL HORROR" ], "valid_edges": [ [ "ASYLUM", "has_genre", "DRAMA" ], [ "JACOB'S LADDER", "has_genre", "HORROR" ], [ "JACOB'S LADDER", "has_tags", "PSYCHOLOGICAL HORROR" ], [ "JACOB'S LADDER", "has_tags", "WAR" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "SESSION 9", "has_genre", "HORROR" ], [ "SESSION 9", "has_tags", "ASYLUM" ], [ "SESSION 9", "has_tags", "HORROR" ], [ "SESSION 9", "has_tags", "PSYCHOLOGICAL HORROR" ], [ "THE PATIENCE STONE", "has_genre", "DRAMA" ], [ "THE PATIENCE STONE", "has_genre", "WAR" ], [ "THE PATIENCE STONE", "starred_actors", "HASSINA BURGAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 39137, AS GOOD AS IT GETS 9340, BABY MAMA 10445, COLD PREY 2 24116, COLLEGE 2159, GHOST TOWN 31060, GIGANTIC 11565, GOOD 6608, GOOD DICK 28501, GOODBYE SOLO 18734, GREG KINNEAR 33476, PAUL LYNCH 24736, PROM NIGHT 19341, RACE 24467, SPEED RACER 13613, THE LAZARUS PROJECT 26588, THE SECRETS OF JONATHAN SPERRY 5465, WHAT DOESN'T KILL YOU src, edge_attr, dst 39137, has_imdb_rating, 11565 39137, has_tags, 18734 39137, starred_actors, 18734 9340, has_tags, 18734 9340, release_year, 26762 9340, starred_actors, 18734 10445, has_imdb_rating, 11565 10445, release_year, 26762 24116, has_imdb_rating, 11565 24116, release_year, 26762 2159, has_tags, 18734 2159, release_year, 26762 2159, starred_actors, 18734 31060, has_imdb_rating, 11565 31060, release_year, 26762 11565, has_imdb_rating, 11565 11565, release_year, 26762 6608, has_imdb_rating, 11565 6608, release_year, 26762 28501, has_imdb_rating, 11565 28501, release_year, 26762 24736, directed_by, 33476 24736, release_year, 26762 19341, has_imdb_rating, 11565 19341, release_year, 26762 24467, has_imdb_rating, 11565 24467, release_year, 26762 13613, has_imdb_rating, 11565 13613, release_year, 26762 26588, release_year, 26762 5465, has_imdb_rating, 11565 5465, release_year, 26762 Question: For what reason are AS GOOD AS IT GETS, PAUL LYNCH, and THE SECRETS OF JONATHAN SPERRY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AS GOOD AS IT GETS", "PAUL LYNCH", "THE SECRETS OF JONATHAN SPERRY" ], "valid_edges": [ [ "AS GOOD AS IT GETS", "has_imdb_rating", "GOOD" ], [ "AS GOOD AS IT GETS", "has_tags", "GREG KINNEAR" ], [ "AS GOOD AS IT GETS", "starred_actors", "GREG KINNEAR" ], [ "BABY MAMA", "has_tags", "GREG KINNEAR" ], [ "BABY MAMA", "release_year", "2008" ], [ "BABY MAMA", "starred_actors", "GREG KINNEAR" ], [ "COLD PREY 2", "has_imdb_rating", "GOOD" ], [ "COLD PREY 2", "release_year", "2008" ], [ "COLLEGE", "has_imdb_rating", "GOOD" ], [ "COLLEGE", "release_year", "2008" ], [ "GHOST TOWN", "has_tags", "GREG KINNEAR" ], [ "GHOST TOWN", "release_year", "2008" ], [ "GHOST TOWN", "starred_actors", "GREG KINNEAR" ], [ "GIGANTIC", "has_imdb_rating", "GOOD" ], [ "GIGANTIC", "release_year", "2008" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD", "release_year", "2008" ], [ "GOOD DICK", "has_imdb_rating", "GOOD" ], [ "GOOD DICK", "release_year", "2008" ], [ "GOODBYE SOLO", "has_imdb_rating", "GOOD" ], [ "GOODBYE SOLO", "release_year", "2008" ], [ "PROM NIGHT", "directed_by", "PAUL LYNCH" ], [ "PROM NIGHT", "release_year", "2008" ], [ "RACE", "has_imdb_rating", "GOOD" ], [ "RACE", "release_year", "2008" ], [ "SPEED RACER", "has_imdb_rating", "GOOD" ], [ "SPEED RACER", "release_year", "2008" ], [ "THE LAZARUS PROJECT", "has_imdb_rating", "GOOD" ], [ "THE LAZARUS PROJECT", "release_year", "2008" ], [ "THE SECRETS OF JONATHAN SPERRY", "release_year", "2008" ], [ "WHAT DOESN'T KILL YOU", "has_imdb_rating", "GOOD" ], [ "WHAT DOESN'T KILL YOU", "release_year", "2008" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 25005, A MURDER OF CROWS 9719, AFTER LIFE 6395, BLUES HARP 36016, COUSIN BETTE 6943, FALLEN 21204, GEORGE CLOONEY 3553, GODZILLA 11565, GOOD 36874, JAPANESE 14797, O BROTHER, WHERE ART THOU? 31950, OCEAN WAVES 4235, OUT OF SIGHT 3297, PATCH ADAMS 27361, RIDING ALONE FOR THOUSANDS OF MILES 28, RING 32418, THE AMERICAN 38882, THE BIRD PEOPLE IN CHINA 4662, THE GOOD GERMAN 29181, THE MONUMENTS MEN 16029, THE TATTOOED WIDOW 30136, THE THIN RED LINE 9811, VEXILLE 38318, WHAT DREAMS MAY COME 19845, WITHOUT LIMITS 15808, YOU'VE GOT MAIL src, edge_attr, dst 25005, has_imdb_rating, 11565 25005, release_year, 2133 9719, in_language, 36874 9719, release_year, 2133 6395, in_language, 36874 6395, release_year, 2133 36016, has_imdb_rating, 11565 36016, release_year, 2133 6943, has_imdb_rating, 11565 6943, release_year, 2133 3553, in_language, 36874 3553, release_year, 2133 11565, has_imdb_rating, 11565 14797, has_imdb_rating, 11565 14797, has_tags, 21204 14797, starred_actors, 21204 31950, has_imdb_rating, 11565 31950, in_language, 36874 4235, has_tags, 21204 4235, release_year, 2133 4235, starred_actors, 21204 3297, has_imdb_rating, 11565 3297, release_year, 2133 27361, has_imdb_rating, 11565 27361, in_language, 36874 28, in_language, 36874 28, release_year, 2133 32418, has_tags, 21204 32418, starred_actors, 21204 38882, in_language, 36874 38882, release_year, 2133 4662, has_imdb_rating, 11565 4662, has_tags, 21204 4662, starred_actors, 21204 29181, directed_by, 21204 29181, has_imdb_rating, 11565 29181, has_tags, 21204 29181, starred_actors, 21204 29181, written_by, 21204 16029, has_imdb_rating, 11565 16029, release_year, 2133 30136, has_tags, 21204 30136, release_year, 2133 9811, in_language, 36874 38318, has_imdb_rating, 11565 38318, release_year, 2133 19845, has_imdb_rating, 11565 19845, release_year, 2133 15808, has_imdb_rating, 11565 15808, release_year, 2133 Question: For what reason are A MURDER OF CROWS, THE AMERICAN, and VEXILLE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A MURDER OF CROWS", "THE AMERICAN", "VEXILLE" ], "valid_edges": [ [ "A MURDER OF CROWS", "has_imdb_rating", "GOOD" ], [ "A MURDER OF CROWS", "release_year", "1998" ], [ "AFTER LIFE", "in_language", "JAPANESE" ], [ "AFTER LIFE", "release_year", "1998" ], [ "BLUES HARP", "in_language", "JAPANESE" ], [ "BLUES HARP", "release_year", "1998" ], [ "COUSIN BETTE", "has_imdb_rating", "GOOD" ], [ "COUSIN BETTE", "release_year", "1998" ], [ "FALLEN", "has_imdb_rating", "GOOD" ], [ "FALLEN", "release_year", "1998" ], [ "GODZILLA", "in_language", "JAPANESE" ], [ "GODZILLA", "release_year", "1998" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "GEORGE CLOONEY" ], [ "O BROTHER, WHERE ART THOU?", "starred_actors", "GEORGE CLOONEY" ], [ "OCEAN WAVES", "has_imdb_rating", "GOOD" ], [ "OCEAN WAVES", "in_language", "JAPANESE" ], [ "OUT OF SIGHT", "has_tags", "GEORGE CLOONEY" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "OUT OF SIGHT", "starred_actors", "GEORGE CLOONEY" ], [ "PATCH ADAMS", "has_imdb_rating", "GOOD" ], [ "PATCH ADAMS", "release_year", "1998" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "has_imdb_rating", "GOOD" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "in_language", "JAPANESE" ], [ "RING", "in_language", "JAPANESE" ], [ "RING", "release_year", "1998" ], [ "THE AMERICAN", "has_tags", "GEORGE CLOONEY" ], [ "THE AMERICAN", "starred_actors", "GEORGE CLOONEY" ], [ "THE BIRD PEOPLE IN CHINA", "in_language", "JAPANESE" ], [ "THE BIRD PEOPLE IN CHINA", "release_year", "1998" ], [ "THE GOOD GERMAN", "has_imdb_rating", "GOOD" ], [ "THE GOOD GERMAN", "has_tags", "GEORGE CLOONEY" ], [ "THE GOOD GERMAN", "starred_actors", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "directed_by", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "has_imdb_rating", "GOOD" ], [ "THE MONUMENTS MEN", "has_tags", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "starred_actors", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "written_by", "GEORGE CLOONEY" ], [ "THE TATTOOED WIDOW", "has_imdb_rating", "GOOD" ], [ "THE TATTOOED WIDOW", "release_year", "1998" ], [ "THE THIN RED LINE", "has_tags", "GEORGE CLOONEY" ], [ "THE THIN RED LINE", "release_year", "1998" ], [ "VEXILLE", "in_language", "JAPANESE" ], [ "WHAT DREAMS MAY COME", "has_imdb_rating", "GOOD" ], [ "WHAT DREAMS MAY COME", "release_year", "1998" ], [ "WITHOUT LIMITS", "has_imdb_rating", "GOOD" ], [ "WITHOUT LIMITS", "release_year", "1998" ], [ "YOU'VE GOT MAIL", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "release_year", "1998" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15416, BOYFRIENDS AND GIRLFRIENDS 30463, COMEDY 20990, HOLY MATRIMONY 39920, OFFICE SPACE 5947, SOPHIE RENOIR src, edge_attr, dst 15416, has_genre, 30463 15416, starred_actors, 5947 20990, has_genre, 30463 39920, has_genre, 30463 39920, has_tags, 30463 Question: For what reason are HOLY MATRIMONY, OFFICE SPACE, and SOPHIE RENOIR associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HOLY MATRIMONY", "OFFICE SPACE", "SOPHIE RENOIR" ], "valid_edges": [ [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "starred_actors", "SOPHIE RENOIR" ], [ "HOLY MATRIMONY", "has_genre", "COMEDY" ], [ "OFFICE SPACE", "has_genre", "COMEDY" ], [ "OFFICE SPACE", "has_tags", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 28210, ALAN ORMSBY 36853, ALTERED STATES 36593, BLACK CHRISTMAS 27791, BOB CLARK 37912, CAT PEOPLE 15226, CHILDREN SHOULDN'T PLAY WITH DEAD THINGS 25738, CHRISTMAS EVIL 13888, CITY OF THE LIVING DEAD 16813, CONTAMINATION 14128, D.J. COTRONA 9248, DEATH SHIP 22215, FRIDAY THE 13TH 1408, HE KNOWS YOU'RE ALONE 2600, HELL OF THE LIVING DEAD 5870, HORROR 24167, INFERNO 24437, MANIAC 30047, MOTEL HELL 19825, MOTHER'S DAY 8138, POPCORN 4604, PRIVATE BENJAMIN 24736, PROM NIGHT 5864, THE AWAKENING 34039, THE CHANGELING 27423, THE FOG 5592, THE HEARSE 19018, THE SHINING 14962, THE WATCHER IN THE WOODS 27274, VENOM 21887, WITHOUT WARNING src, edge_attr, dst 36853, has_genre, 5870 36853, release_year, 36268 36593, directed_by, 27791 36593, has_genre, 5870 36593, has_tags, 27791 36593, has_tags, 5870 37912, has_genre, 5870 37912, written_by, 28210 15226, directed_by, 27791 15226, has_genre, 5870 15226, starred_actors, 28210 15226, written_by, 28210 15226, written_by, 27791 25738, has_genre, 5870 25738, release_year, 36268 13888, has_genre, 5870 13888, has_tags, 5870 13888, release_year, 36268 16813, has_genre, 5870 16813, release_year, 36268 9248, has_genre, 5870 9248, release_year, 36268 22215, has_genre, 5870 22215, release_year, 36268 1408, has_genre, 5870 1408, release_year, 36268 2600, has_genre, 5870 2600, release_year, 36268 24167, has_genre, 5870 24167, release_year, 36268 24437, has_genre, 5870 24437, release_year, 36268 30047, has_genre, 5870 30047, release_year, 36268 19825, has_genre, 5870 19825, release_year, 36268 8138, directed_by, 28210 8138, has_genre, 5870 8138, written_by, 28210 4604, release_year, 36268 24736, has_genre, 5870 24736, release_year, 36268 5864, has_genre, 5870 5864, has_tags, 5870 5864, release_year, 36268 34039, has_genre, 5870 34039, release_year, 36268 27423, has_genre, 5870 27423, has_tags, 5870 27423, release_year, 36268 5592, has_genre, 5870 5592, release_year, 36268 19018, has_genre, 5870 19018, has_tags, 5870 19018, release_year, 36268 14962, has_genre, 5870 14962, release_year, 36268 27274, has_genre, 5870 27274, starred_actors, 14128 21887, has_genre, 5870 21887, release_year, 36268 Question: How are CHILDREN SHOULDN'T PLAY WITH DEAD THINGS, D.J. COTRONA, and PRIVATE BENJAMIN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "D.J. COTRONA", "PRIVATE BENJAMIN" ], "valid_edges": [ [ "ALTERED STATES", "has_genre", "HORROR" ], [ "ALTERED STATES", "release_year", "1980" ], [ "BLACK CHRISTMAS", "directed_by", "BOB CLARK" ], [ "BLACK CHRISTMAS", "has_genre", "HORROR" ], [ "BLACK CHRISTMAS", "has_tags", "BOB CLARK" ], [ "BLACK CHRISTMAS", "has_tags", "HORROR" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "written_by", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "directed_by", "BOB CLARK" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "has_genre", "HORROR" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "starred_actors", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "written_by", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "written_by", "BOB CLARK" ], [ "CHRISTMAS EVIL", "has_genre", "HORROR" ], [ "CHRISTMAS EVIL", "release_year", "1980" ], [ "CITY OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CONTAMINATION", "has_genre", "HORROR" ], [ "CONTAMINATION", "release_year", "1980" ], [ "DEATH SHIP", "has_genre", "HORROR" ], [ "DEATH SHIP", "release_year", "1980" ], [ "FRIDAY THE 13TH", "has_genre", "HORROR" ], [ "FRIDAY THE 13TH", "release_year", "1980" ], [ "HE KNOWS YOU'RE ALONE", "has_genre", "HORROR" ], [ "HE KNOWS YOU'RE ALONE", "release_year", "1980" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "INFERNO", "has_genre", "HORROR" ], [ "INFERNO", "release_year", "1980" ], [ "MANIAC", "has_genre", "HORROR" ], [ "MANIAC", "release_year", "1980" ], [ "MOTEL HELL", "has_genre", "HORROR" ], [ "MOTEL HELL", "release_year", "1980" ], [ "MOTHER'S DAY", "has_genre", "HORROR" ], [ "MOTHER'S DAY", "release_year", "1980" ], [ "POPCORN", "directed_by", "ALAN ORMSBY" ], [ "POPCORN", "has_genre", "HORROR" ], [ "POPCORN", "written_by", "ALAN ORMSBY" ], [ "PRIVATE BENJAMIN", "release_year", "1980" ], [ "PROM NIGHT", "has_genre", "HORROR" ], [ "PROM NIGHT", "release_year", "1980" ], [ "THE AWAKENING", "has_genre", "HORROR" ], [ "THE AWAKENING", "has_tags", "HORROR" ], [ "THE AWAKENING", "release_year", "1980" ], [ "THE CHANGELING", "has_genre", "HORROR" ], [ "THE CHANGELING", "release_year", "1980" ], [ "THE FOG", "has_genre", "HORROR" ], [ "THE FOG", "has_tags", "HORROR" ], [ "THE FOG", "release_year", "1980" ], [ "THE HEARSE", "has_genre", "HORROR" ], [ "THE HEARSE", "release_year", "1980" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "release_year", "1980" ], [ "THE WATCHER IN THE WOODS", "has_genre", "HORROR" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "VENOM", "has_genre", "HORROR" ], [ "VENOM", "starred_actors", "D.J. COTRONA" ], [ "WITHOUT WARNING", "has_genre", "HORROR" ], [ "WITHOUT WARNING", "release_year", "1980" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6721, 1972 17315, 2007 37655, AL PACINO 2973, ALL THE COLORS OF THE DARK 9942, ANTHONY SHAFFER 15278, AVANTI! 13211, CALIBER 9 26346, DADDY'S LITTLE GIRLS 24214, DON'T TORTURE A DUCKLING 2848, FRENZY 31307, GODZILLA VS. GIGAN 33673, HEAT 11233, HIDEO YAMAMOTO 4215, ICHI THE KILLER 16200, ITALIAN 36874, JAPANESE 23374, LAST OF THE RED HOT LOVERS 31211, LUDWIG 1153, MICHAEL CAINE 15145, MYSTERY 37159, NEIL SIMON 37810, PULP 13081, R 28729, REMAKE 6119, SLEUTH 15568, THE CANTERBURY TALES 6524, THE GETAWAY 35551, THE GODFATHER 19595, THE HEARTBREAK KID 15202, THE LAST HOUSE ON THE LEFT 36168, THE MATTEI AFFAIR 8839, THE MECHANIC 34254, THEY ONLY KILL THEIR MASTERS 34730, TYLER PERRY 4117, UNDER THE FLAG OF THE RISING SUN 28211, WHAT HAVE YOU DONE TO SOLANGE? 6287, WHY DID I GET MARRIED? src, edge_attr, dst 2973, in_language, 16200 2973, release_year, 6721 15278, in_language, 16200 15278, release_year, 6721 13211, in_language, 16200 13211, release_year, 6721 26346, directed_by, 34730 26346, release_year, 17315 26346, written_by, 34730 24214, in_language, 16200 24214, release_year, 6721 2848, release_year, 6721 2848, written_by, 9942 31307, in_language, 36874 31307, release_year, 6721 33673, has_tags, 37655 33673, has_tags, 13081 33673, release_year, 6721 33673, starred_actors, 37655 4215, in_language, 36874 4215, written_by, 11233 23374, release_year, 6721 23374, written_by, 37159 31211, in_language, 16200 31211, release_year, 6721 37810, release_year, 6721 37810, starred_actors, 1153 6119, has_genre, 15145 6119, has_tags, 1153 6119, has_tags, 15145 6119, has_tags, 13081 6119, in_language, 16200 6119, release_year, 6721 6119, release_year, 17315 6119, starred_actors, 1153 6119, written_by, 9942 15568, in_language, 16200 15568, release_year, 6721 6524, has_tags, 28729 6524, release_year, 6721 35551, has_tags, 37655 35551, has_tags, 16200 35551, has_tags, 13081 35551, in_language, 16200 35551, release_year, 6721 35551, starred_actors, 37655 19595, has_tags, 37159 19595, has_tags, 13081 19595, has_tags, 28729 19595, release_year, 6721 19595, release_year, 17315 19595, written_by, 37159 15202, has_tags, 28729 15202, release_year, 6721 36168, in_language, 16200 36168, release_year, 6721 8839, has_tags, 28729 8839, release_year, 6721 34254, has_genre, 15145 34254, release_year, 6721 4117, in_language, 36874 4117, release_year, 6721 28211, has_genre, 15145 28211, in_language, 16200 28211, release_year, 6721 6287, directed_by, 34730 6287, has_tags, 34730 6287, release_year, 17315 6287, starred_actors, 34730 6287, written_by, 34730 Question: How are 1972, HIDEO YAMAMOTO, and WHY DID I GET MARRIED? related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1972", "HIDEO YAMAMOTO", "WHY DID I GET MARRIED?" ], "valid_edges": [ [ "ALL THE COLORS OF THE DARK", "in_language", "ITALIAN" ], [ "ALL THE COLORS OF THE DARK", "release_year", "1972" ], [ "AVANTI!", "in_language", "ITALIAN" ], [ "AVANTI!", "release_year", "1972" ], [ "CALIBER 9", "in_language", "ITALIAN" ], [ "CALIBER 9", "release_year", "1972" ], [ "DADDY'S LITTLE GIRLS", "directed_by", "TYLER PERRY" ], [ "DADDY'S LITTLE GIRLS", "release_year", "2007" ], [ "DADDY'S LITTLE GIRLS", "written_by", "TYLER PERRY" ], [ "DON'T TORTURE A DUCKLING", "in_language", "ITALIAN" ], [ "DON'T TORTURE A DUCKLING", "release_year", "1972" ], [ "FRENZY", "release_year", "1972" ], [ "FRENZY", "written_by", "ANTHONY SHAFFER" ], [ "GODZILLA VS. GIGAN", "in_language", "JAPANESE" ], [ "GODZILLA VS. GIGAN", "release_year", "1972" ], [ "HEAT", "has_tags", "AL PACINO" ], [ "HEAT", "has_tags", "R" ], [ "HEAT", "release_year", "1972" ], [ "HEAT", "starred_actors", "AL PACINO" ], [ "ICHI THE KILLER", "in_language", "JAPANESE" ], [ "ICHI THE KILLER", "written_by", "HIDEO YAMAMOTO" ], [ "LAST OF THE RED HOT LOVERS", "release_year", "1972" ], [ "LAST OF THE RED HOT LOVERS", "written_by", "NEIL SIMON" ], [ "LUDWIG", "in_language", "ITALIAN" ], [ "LUDWIG", "release_year", "1972" ], [ "PULP", "release_year", "1972" ], [ "PULP", "starred_actors", "MICHAEL CAINE" ], [ "SLEUTH", "has_genre", "MYSTERY" ], [ "SLEUTH", "has_tags", "MICHAEL CAINE" ], [ "SLEUTH", "has_tags", "MYSTERY" ], [ "SLEUTH", "has_tags", "R" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "SLEUTH", "release_year", "1972" ], [ "SLEUTH", "release_year", "2007" ], [ "SLEUTH", "starred_actors", "MICHAEL CAINE" ], [ "SLEUTH", "written_by", "ANTHONY SHAFFER" ], [ "THE CANTERBURY TALES", "in_language", "ITALIAN" ], [ "THE CANTERBURY TALES", "release_year", "1972" ], [ "THE GETAWAY", "has_tags", "REMAKE" ], [ "THE GETAWAY", "release_year", "1972" ], [ "THE GODFATHER", "has_tags", "AL PACINO" ], [ "THE GODFATHER", "has_tags", "ITALIAN" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "in_language", "ITALIAN" ], [ "THE GODFATHER", "release_year", "1972" ], [ "THE GODFATHER", "starred_actors", "AL PACINO" ], [ "THE HEARTBREAK KID", "has_tags", "NEIL SIMON" ], [ "THE HEARTBREAK KID", "has_tags", "R" ], [ "THE HEARTBREAK KID", "has_tags", "REMAKE" ], [ "THE HEARTBREAK KID", "release_year", "1972" ], [ "THE HEARTBREAK KID", "release_year", "2007" ], [ "THE HEARTBREAK KID", "written_by", "NEIL SIMON" ], [ "THE LAST HOUSE ON THE LEFT", "has_tags", "REMAKE" ], [ "THE LAST HOUSE ON THE LEFT", "release_year", "1972" ], [ "THE MATTEI AFFAIR", "in_language", "ITALIAN" ], [ "THE MATTEI AFFAIR", "release_year", "1972" ], [ "THE MECHANIC", "has_tags", "REMAKE" ], [ "THE MECHANIC", "release_year", "1972" ], [ "THEY ONLY KILL THEIR MASTERS", "has_genre", "MYSTERY" ], [ "THEY ONLY KILL THEIR MASTERS", "release_year", "1972" ], [ "UNDER THE FLAG OF THE RISING SUN", "in_language", "JAPANESE" ], [ "UNDER THE FLAG OF THE RISING SUN", "release_year", "1972" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "has_genre", "MYSTERY" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "in_language", "ITALIAN" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "release_year", "1972" ], [ "WHY DID I GET MARRIED?", "directed_by", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "has_tags", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "release_year", "2007" ], [ "WHY DID I GET MARRIED?", "starred_actors", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "written_by", "TYLER PERRY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29561, 1943 29424, 2011 37908, AFRICAN CATS 37994, ANGEL DOG 39613, BEAUTY DAY 21372, BEVERLY HILLS CHIHUAHUA 2 26510, BORN TO BE WILD 29342, BULLY 17035, DEBTOCRACY 12841, DOCUMENTARY 3032, DOLPHIN TALE 1519, DREAMS OF A LIFE 10509, FAMILY 39366, HAPPY 20013, HAPPY FEET TWO 17345, HERE WITHOUT ME 23442, HOODWINKED TOO! HOOD VS. EVIL 21922, JANE EYRE 24247, LEONOR WATLING 19802, LOVE 28468, MAGIC TRIP 7839, MISS REPRESENTATION 12706, MR. POPPER'S PENGUINS 35524, ONE LIFE 2108, PEARL JAM TWENTY 29086, PINA 38002, RED DOG 10984, REVENGE OF THE ELECTRIC CAR 12599, SURVIVING PROGRESS 9972, TALK TO HER 2588, THE AMBASSADOR 24264, THE BATTLE OF RUSSIA 11259, THE BLACK POWER MIXTAPE 1967-1975 20837, THE CAPTAINS 20969, THE FLAT 39978, THE HUMAN COMEDY 30700, THE INTERRUPTERS 38461, THE LAST LIONS 27444, THE LAST MOUNTAIN 39587, THE OTHER F WORD 29052, THESE AMAZING SHADOWS 36765, THIS IS NOT A FILM 16214, UNLAWFUL KILLING 8957, WE BOUGHT A ZOO 4896, WHORES' GLORY 9056, YOU'VE BEEN TRUMPED src, edge_attr, dst 37908, has_genre, 12841 37908, release_year, 29424 37994, has_genre, 10509 37994, release_year, 29424 39613, has_genre, 12841 39613, release_year, 29424 21372, has_genre, 10509 21372, release_year, 29424 26510, has_genre, 12841 26510, release_year, 29424 29342, has_genre, 12841 29342, release_year, 29424 17035, has_genre, 12841 17035, release_year, 29424 3032, has_genre, 10509 3032, has_tags, 10509 3032, release_year, 29424 1519, has_genre, 12841 1519, release_year, 29424 39366, has_genre, 12841 39366, has_genre, 10509 39366, has_tags, 12841 39366, release_year, 29424 20013, has_genre, 10509 20013, release_year, 29424 17345, has_genre, 10509 17345, release_year, 29424 23442, has_genre, 10509 23442, release_year, 29424 21922, release_year, 29561 21922, release_year, 29424 19802, release_year, 29424 28468, has_genre, 12841 28468, release_year, 29424 7839, has_genre, 12841 7839, release_year, 29424 12706, has_genre, 10509 12706, release_year, 29424 35524, has_genre, 12841 35524, release_year, 29424 2108, has_genre, 12841 2108, release_year, 29424 29086, has_genre, 12841 29086, has_tags, 12841 29086, release_year, 29424 38002, has_genre, 10509 38002, release_year, 29424 10984, has_genre, 12841 10984, release_year, 29424 12599, has_genre, 12841 12599, has_tags, 12841 12599, release_year, 29424 9972, has_tags, 24247 9972, has_tags, 19802 9972, starred_actors, 24247 2588, has_genre, 12841 2588, release_year, 29424 24264, has_genre, 12841 24264, release_year, 29561 11259, has_genre, 12841 11259, release_year, 29424 20837, has_genre, 12841 20837, release_year, 29424 20969, has_genre, 12841 20969, release_year, 29424 39978, has_genre, 10509 39978, release_year, 29561 30700, has_genre, 12841 30700, release_year, 29424 38461, has_genre, 12841 38461, release_year, 29424 27444, has_genre, 12841 27444, release_year, 29424 39587, has_genre, 12841 39587, release_year, 29424 29052, has_genre, 12841 29052, release_year, 29424 36765, has_genre, 12841 36765, release_year, 29424 16214, has_genre, 12841 16214, release_year, 29424 8957, has_genre, 10509 8957, has_tags, 10509 8957, release_year, 29424 4896, has_genre, 12841 4896, has_tags, 12841 4896, release_year, 29424 9056, has_genre, 12841 9056, release_year, 29424 Question: How are DREAMS OF A LIFE, LEONOR WATLING, and THE HUMAN COMEDY related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DREAMS OF A LIFE", "LEONOR WATLING", "THE HUMAN COMEDY" ], "valid_edges": [ [ "AFRICAN CATS", "has_genre", "DOCUMENTARY" ], [ "AFRICAN CATS", "release_year", "2011" ], [ "ANGEL DOG", "has_genre", "FAMILY" ], [ "ANGEL DOG", "release_year", "2011" ], [ "BEAUTY DAY", "has_genre", "DOCUMENTARY" ], [ "BEAUTY DAY", "release_year", "2011" ], [ "BEVERLY HILLS CHIHUAHUA 2", "has_genre", "FAMILY" ], [ "BEVERLY HILLS CHIHUAHUA 2", "release_year", "2011" ], [ "BORN TO BE WILD", "has_genre", "DOCUMENTARY" ], [ "BORN TO BE WILD", "release_year", "2011" ], [ "BULLY", "has_genre", "DOCUMENTARY" ], [ "BULLY", "release_year", "2011" ], [ "DEBTOCRACY", "has_genre", "DOCUMENTARY" ], [ "DEBTOCRACY", "release_year", "2011" ], [ "DOLPHIN TALE", "has_genre", "FAMILY" ], [ "DOLPHIN TALE", "has_tags", "FAMILY" ], [ "DOLPHIN TALE", "release_year", "2011" ], [ "DREAMS OF A LIFE", "has_genre", "DOCUMENTARY" ], [ "DREAMS OF A LIFE", "release_year", "2011" ], [ "HAPPY", "has_genre", "DOCUMENTARY" ], [ "HAPPY", "has_genre", "FAMILY" ], [ "HAPPY", "has_tags", "DOCUMENTARY" ], [ "HAPPY", "release_year", "2011" ], [ "HAPPY FEET TWO", "has_genre", "FAMILY" ], [ "HAPPY FEET TWO", "release_year", "2011" ], [ "HERE WITHOUT ME", "has_genre", "FAMILY" ], [ "HERE WITHOUT ME", "release_year", "2011" ], [ "HOODWINKED TOO! HOOD VS. EVIL", "has_genre", "FAMILY" ], [ "HOODWINKED TOO! HOOD VS. EVIL", "release_year", "2011" ], [ "JANE EYRE", "release_year", "1943" ], [ "JANE EYRE", "release_year", "2011" ], [ "LOVE", "release_year", "2011" ], [ "MAGIC TRIP", "has_genre", "DOCUMENTARY" ], [ "MAGIC TRIP", "release_year", "2011" ], [ "MISS REPRESENTATION", "has_genre", "DOCUMENTARY" ], [ "MISS REPRESENTATION", "release_year", "2011" ], [ "MR. POPPER'S PENGUINS", "has_genre", "FAMILY" ], [ "MR. POPPER'S PENGUINS", "release_year", "2011" ], [ "ONE LIFE", "has_genre", "DOCUMENTARY" ], [ "ONE LIFE", "release_year", "2011" ], [ "PEARL JAM TWENTY", "has_genre", "DOCUMENTARY" ], [ "PEARL JAM TWENTY", "release_year", "2011" ], [ "PINA", "has_genre", "DOCUMENTARY" ], [ "PINA", "has_tags", "DOCUMENTARY" ], [ "PINA", "release_year", "2011" ], [ "RED DOG", "has_genre", "FAMILY" ], [ "RED DOG", "release_year", "2011" ], [ "REVENGE OF THE ELECTRIC CAR", "has_genre", "DOCUMENTARY" ], [ "REVENGE OF THE ELECTRIC CAR", "release_year", "2011" ], [ "SURVIVING PROGRESS", "has_genre", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "has_tags", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "release_year", "2011" ], [ "TALK TO HER", "has_tags", "LEONOR WATLING" ], [ "TALK TO HER", "has_tags", "LOVE" ], [ "TALK TO HER", "starred_actors", "LEONOR WATLING" ], [ "THE AMBASSADOR", "has_genre", "DOCUMENTARY" ], [ "THE AMBASSADOR", "release_year", "2011" ], [ "THE BATTLE OF RUSSIA", "has_genre", "DOCUMENTARY" ], [ "THE BATTLE OF RUSSIA", "release_year", "1943" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "has_genre", "DOCUMENTARY" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "release_year", "2011" ], [ "THE CAPTAINS", "has_genre", "DOCUMENTARY" ], [ "THE CAPTAINS", "release_year", "2011" ], [ "THE FLAT", "has_genre", "DOCUMENTARY" ], [ "THE FLAT", "release_year", "2011" ], [ "THE HUMAN COMEDY", "has_genre", "FAMILY" ], [ "THE HUMAN COMEDY", "release_year", "1943" ], [ "THE INTERRUPTERS", "has_genre", "DOCUMENTARY" ], [ "THE INTERRUPTERS", "release_year", "2011" ], [ "THE LAST LIONS", "has_genre", "DOCUMENTARY" ], [ "THE LAST LIONS", "release_year", "2011" ], [ "THE LAST MOUNTAIN", "has_genre", "DOCUMENTARY" ], [ "THE LAST MOUNTAIN", "release_year", "2011" ], [ "THE OTHER F WORD", "has_genre", "DOCUMENTARY" ], [ "THE OTHER F WORD", "release_year", "2011" ], [ "THESE AMAZING SHADOWS", "has_genre", "DOCUMENTARY" ], [ "THESE AMAZING SHADOWS", "release_year", "2011" ], [ "THIS IS NOT A FILM", "has_genre", "DOCUMENTARY" ], [ "THIS IS NOT A FILM", "release_year", "2011" ], [ "UNLAWFUL KILLING", "has_genre", "DOCUMENTARY" ], [ "UNLAWFUL KILLING", "release_year", "2011" ], [ "WE BOUGHT A ZOO", "has_genre", "FAMILY" ], [ "WE BOUGHT A ZOO", "has_tags", "FAMILY" ], [ "WE BOUGHT A ZOO", "release_year", "2011" ], [ "WHORES' GLORY", "has_genre", "DOCUMENTARY" ], [ "WHORES' GLORY", "has_tags", "DOCUMENTARY" ], [ "WHORES' GLORY", "release_year", "2011" ], [ "YOU'VE BEEN TRUMPED", "has_genre", "DOCUMENTARY" ], [ "YOU'VE BEEN TRUMPED", "release_year", "2011" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35749, BRECKIN MEYER 1148, CONFESSIONS 8872, DANCER, TEXAS POP. 81 36212, DRAMA 4108, KANAE MINATO 12106, MATTHEW RHYS 27064, THE SCAPEGOAT src, edge_attr, dst 1148, has_genre, 36212 1148, written_by, 4108 8872, has_genre, 36212 8872, starred_actors, 35749 27064, has_genre, 36212 27064, starred_actors, 12106 Question: In what context are BRECKIN MEYER, KANAE MINATO, and MATTHEW RHYS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRECKIN MEYER", "KANAE MINATO", "MATTHEW RHYS" ], "valid_edges": [ [ "CONFESSIONS", "has_genre", "DRAMA" ], [ "CONFESSIONS", "written_by", "KANAE MINATO" ], [ "DANCER, TEXAS POP. 81", "has_genre", "DRAMA" ], [ "DANCER, TEXAS POP. 81", "starred_actors", "BRECKIN MEYER" ], [ "THE SCAPEGOAT", "has_genre", "DRAMA" ], [ "THE SCAPEGOAT", "starred_actors", "MATTHEW RHYS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13805, BRET ROBERTS 30463, COMEDY 5870, HORROR 13963, JOHNNY VEGAS 35018, KING COBRA 19020, NATIONAL LAMPOON PRESENTS DORM DAZE 34937, PATRICK CASEY 2327, SCOTT HILLENBRAND 39218, SEX LIVES OF THE POTATO MEN 8494, THE VIOLENT KIND 14057, TRANSYLMANIA src, edge_attr, dst 35018, directed_by, 2327 35018, has_genre, 5870 35018, starred_actors, 2327 35018, written_by, 2327 19020, directed_by, 2327 19020, has_genre, 30463 19020, written_by, 34937 39218, has_genre, 30463 39218, starred_actors, 13963 8494, has_genre, 5870 8494, starred_actors, 13805 14057, directed_by, 2327 14057, has_genre, 30463 14057, has_genre, 5870 14057, starred_actors, 34937 14057, written_by, 34937 Question: In what context are BRET ROBERTS, JOHNNY VEGAS, and SCOTT HILLENBRAND connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BRET ROBERTS", "JOHNNY VEGAS", "SCOTT HILLENBRAND" ], "valid_edges": [ [ "KING COBRA", "directed_by", "SCOTT HILLENBRAND" ], [ "KING COBRA", "has_genre", "HORROR" ], [ "KING COBRA", "starred_actors", "SCOTT HILLENBRAND" ], [ "KING COBRA", "written_by", "SCOTT HILLENBRAND" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "directed_by", "SCOTT HILLENBRAND" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "has_genre", "COMEDY" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "written_by", "PATRICK CASEY" ], [ "SEX LIVES OF THE POTATO MEN", "has_genre", "COMEDY" ], [ "SEX LIVES OF THE POTATO MEN", "starred_actors", "JOHNNY VEGAS" ], [ "THE VIOLENT KIND", "has_genre", "HORROR" ], [ "THE VIOLENT KIND", "starred_actors", "BRET ROBERTS" ], [ "TRANSYLMANIA", "directed_by", "SCOTT HILLENBRAND" ], [ "TRANSYLMANIA", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "has_genre", "HORROR" ], [ "TRANSYLMANIA", "starred_actors", "PATRICK CASEY" ], [ "TRANSYLMANIA", "written_by", "PATRICK CASEY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 20981, A WOMAN OF AFFAIRS 10340, ADRIFT 37608, AUSTRALIA 24556, DOWNSTAIRS 36212, DRAMA 29560, HE WHO GETS SLAPPED 5667, JOHN GILBERT 16469, LINH DAN PHAM 9235, MR. NOBODY 23155, WALKABOUT src, edge_attr, dst 20981, has_genre, 36212 20981, starred_actors, 5667 10340, has_genre, 36212 10340, release_year, 27261 10340, starred_actors, 16469 37608, has_genre, 36212 37608, has_tags, 37608 24556, has_genre, 36212 24556, starred_actors, 5667 24556, written_by, 5667 29560, has_genre, 36212 29560, starred_actors, 5667 9235, has_genre, 36212 9235, release_year, 27261 9235, starred_actors, 16469 23155, has_tags, 37608 Question: For what reason are JOHN GILBERT, LINH DAN PHAM, and WALKABOUT associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOHN GILBERT", "LINH DAN PHAM", "WALKABOUT" ], "valid_edges": [ [ "A WOMAN OF AFFAIRS", "has_genre", "DRAMA" ], [ "A WOMAN OF AFFAIRS", "starred_actors", "JOHN GILBERT" ], [ "ADRIFT", "has_genre", "DRAMA" ], [ "ADRIFT", "release_year", "2009" ], [ "ADRIFT", "starred_actors", "LINH DAN PHAM" ], [ "AUSTRALIA", "has_genre", "DRAMA" ], [ "AUSTRALIA", "has_tags", "AUSTRALIA" ], [ "DOWNSTAIRS", "has_genre", "DRAMA" ], [ "DOWNSTAIRS", "starred_actors", "JOHN GILBERT" ], [ "DOWNSTAIRS", "written_by", "JOHN GILBERT" ], [ "HE WHO GETS SLAPPED", "has_genre", "DRAMA" ], [ "HE WHO GETS SLAPPED", "starred_actors", "JOHN GILBERT" ], [ "MR. NOBODY", "has_genre", "DRAMA" ], [ "MR. NOBODY", "release_year", "2009" ], [ "MR. NOBODY", "starred_actors", "LINH DAN PHAM" ], [ "WALKABOUT", "has_tags", "AUSTRALIA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 12569, ACTS OF WORSHIP 29180, CHU CHIN CHOW 30463, COMEDY 14627, GEORGE ROBEY 30384, JUMP TOMORROW 28958, MICHAEL HYATT 19692, TUNDE ADEBIMPE src, edge_attr, dst 12569, release_year, 13408 12569, starred_actors, 28958 29180, has_genre, 30463 29180, starred_actors, 14627 30384, has_genre, 30463 30384, release_year, 13408 30384, starred_actors, 19692 Question: In what context are GEORGE ROBEY, MICHAEL HYATT, and TUNDE ADEBIMPE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GEORGE ROBEY", "MICHAEL HYATT", "TUNDE ADEBIMPE" ], "valid_edges": [ [ "ACTS OF WORSHIP", "release_year", "2001" ], [ "ACTS OF WORSHIP", "starred_actors", "MICHAEL HYATT" ], [ "CHU CHIN CHOW", "has_genre", "COMEDY" ], [ "CHU CHIN CHOW", "starred_actors", "GEORGE ROBEY" ], [ "JUMP TOMORROW", "has_genre", "COMEDY" ], [ "JUMP TOMORROW", "release_year", "2001" ], [ "JUMP TOMORROW", "starred_actors", "TUNDE ADEBIMPE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 27261, 2009 39750, ALIENS 4652, ANGELA SHELTON 23390, ARCADE 34587, BAD TASTE 23100, BODY BAGS 25126, BODY SNATCHERS 2747, CARNOSAUR 30463, COMEDY 29377, CRONOS 6692, DISTRICT 9 36212, DRAMA 5372, FORGOTTEN SILVER 28939, FRAN WALSH 17870, GHOST IN THE MACHINE 20214, HEAVENLY CREATURES 5870, HORROR 19098, KING KONG 32278, LEPRECHAUN 39670, MAN'S BEST FRIEND 9131, MEET THE FEEBLES 21188, MR. JONES 8519, MY BOYFRIEND'S BACK 25168, NEW ZEALAND 15793, NIGHT TERRORS 14075, PETER JACKSON 29013, PUPPET MASTER 4 23898, SUPERNATURAL 25979, THE DARK HALF 21684, THE FRIGHTENERS 26894, THE LOVELY BONES 13101, TUMBLEWEEDS src, edge_attr, dst 39750, has_tags, 5870 23390, has_genre, 5870 23390, release_year, 24438 34587, directed_by, 14075 34587, has_genre, 30463 34587, has_genre, 5870 34587, has_tags, 39750 34587, has_tags, 25168 34587, has_tags, 14075 34587, written_by, 14075 23100, has_genre, 5870 23100, release_year, 24438 25126, has_genre, 5870 25126, release_year, 24438 2747, has_genre, 5870 2747, release_year, 24438 29377, has_genre, 5870 29377, release_year, 24438 6692, has_tags, 14075 6692, release_year, 27261 5372, directed_by, 14075 5372, has_tags, 25168 5372, has_tags, 14075 5372, starred_actors, 14075 5372, written_by, 14075 17870, has_genre, 5870 17870, release_year, 24438 20214, directed_by, 14075 20214, has_genre, 36212 20214, has_tags, 25168 20214, has_tags, 14075 20214, written_by, 28939 20214, written_by, 14075 19098, directed_by, 14075 19098, has_tags, 19098 19098, has_tags, 14075 19098, written_by, 14075 32278, has_genre, 5870 32278, has_tags, 5870 32278, release_year, 24438 39670, has_genre, 5870 39670, release_year, 24438 9131, directed_by, 14075 9131, has_genre, 30463 9131, has_tags, 25168 9131, has_tags, 14075 9131, written_by, 28939 9131, written_by, 14075 21188, has_genre, 5870 21188, release_year, 24438 8519, has_genre, 5870 8519, release_year, 24438 15793, has_genre, 5870 15793, release_year, 24438 29013, has_genre, 5870 29013, release_year, 24438 25979, has_genre, 5870 25979, release_year, 24438 21684, directed_by, 14075 21684, has_genre, 30463 21684, has_genre, 5870 21684, has_tags, 14075 21684, has_tags, 23898 21684, written_by, 28939 21684, written_by, 14075 26894, directed_by, 14075 26894, has_genre, 36212 26894, has_tags, 14075 26894, has_tags, 23898 26894, release_year, 27261 26894, written_by, 14075 13101, has_genre, 30463 13101, has_genre, 36212 13101, written_by, 4652 Question: For what reason are ANGELA SHELTON, PETER JACKSON, and PUPPET MASTER 4 associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANGELA SHELTON", "PETER JACKSON", "PUPPET MASTER 4" ], "valid_edges": [ [ "ALIENS", "has_tags", "HORROR" ], [ "ARCADE", "has_genre", "HORROR" ], [ "ARCADE", "release_year", "1993" ], [ "BAD TASTE", "directed_by", "PETER JACKSON" ], [ "BAD TASTE", "has_genre", "COMEDY" ], [ "BAD TASTE", "has_genre", "HORROR" ], [ "BAD TASTE", "has_tags", "ALIENS" ], [ "BAD TASTE", "has_tags", "NEW ZEALAND" ], [ "BAD TASTE", "has_tags", "PETER JACKSON" ], [ "BAD TASTE", "written_by", "PETER JACKSON" ], [ "BODY BAGS", "has_genre", "HORROR" ], [ "BODY BAGS", "release_year", "1993" ], [ "BODY SNATCHERS", "has_genre", "HORROR" ], [ "BODY SNATCHERS", "release_year", "1993" ], [ "CARNOSAUR", "has_genre", "HORROR" ], [ "CARNOSAUR", "release_year", "1993" ], [ "CRONOS", "has_genre", "HORROR" ], [ "CRONOS", "release_year", "1993" ], [ "DISTRICT 9", "has_tags", "PETER JACKSON" ], [ "DISTRICT 9", "release_year", "2009" ], [ "FORGOTTEN SILVER", "directed_by", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "has_tags", "NEW ZEALAND" ], [ "FORGOTTEN SILVER", "has_tags", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "starred_actors", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "written_by", "PETER JACKSON" ], [ "GHOST IN THE MACHINE", "has_genre", "HORROR" ], [ "GHOST IN THE MACHINE", "release_year", "1993" ], [ "HEAVENLY CREATURES", "directed_by", "PETER JACKSON" ], [ "HEAVENLY CREATURES", "has_genre", "DRAMA" ], [ "HEAVENLY CREATURES", "has_tags", "NEW ZEALAND" ], [ "HEAVENLY CREATURES", "has_tags", "PETER JACKSON" ], [ "HEAVENLY CREATURES", "written_by", "FRAN WALSH" ], [ "HEAVENLY CREATURES", "written_by", "PETER JACKSON" ], [ "KING KONG", "directed_by", "PETER JACKSON" ], [ "KING KONG", "has_tags", "KING KONG" ], [ "KING KONG", "has_tags", "PETER JACKSON" ], [ "KING KONG", "written_by", "PETER JACKSON" ], [ "LEPRECHAUN", "has_genre", "HORROR" ], [ "LEPRECHAUN", "has_tags", "HORROR" ], [ "LEPRECHAUN", "release_year", "1993" ], [ "MAN'S BEST FRIEND", "has_genre", "HORROR" ], [ "MAN'S BEST FRIEND", "release_year", "1993" ], [ "MEET THE FEEBLES", "directed_by", "PETER JACKSON" ], [ "MEET THE FEEBLES", "has_genre", "COMEDY" ], [ "MEET THE FEEBLES", "has_tags", "NEW ZEALAND" ], [ "MEET THE FEEBLES", "has_tags", "PETER JACKSON" ], [ "MEET THE FEEBLES", "written_by", "FRAN WALSH" ], [ "MEET THE FEEBLES", "written_by", "PETER JACKSON" ], [ "MR. JONES", "has_genre", "HORROR" ], [ "MR. JONES", "release_year", "1993" ], [ "MY BOYFRIEND'S BACK", "has_genre", "HORROR" ], [ "MY BOYFRIEND'S BACK", "release_year", "1993" ], [ "NIGHT TERRORS", "has_genre", "HORROR" ], [ "NIGHT TERRORS", "release_year", "1993" ], [ "PUPPET MASTER 4", "has_genre", "HORROR" ], [ "PUPPET MASTER 4", "release_year", "1993" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "release_year", "1993" ], [ "THE FRIGHTENERS", "directed_by", "PETER JACKSON" ], [ "THE FRIGHTENERS", "has_genre", "COMEDY" ], [ "THE FRIGHTENERS", "has_genre", "HORROR" ], [ "THE FRIGHTENERS", "has_tags", "PETER JACKSON" ], [ "THE FRIGHTENERS", "has_tags", "SUPERNATURAL" ], [ "THE FRIGHTENERS", "written_by", "FRAN WALSH" ], [ "THE FRIGHTENERS", "written_by", "PETER JACKSON" ], [ "THE LOVELY BONES", "directed_by", "PETER JACKSON" ], [ "THE LOVELY BONES", "has_genre", "DRAMA" ], [ "THE LOVELY BONES", "has_tags", "PETER JACKSON" ], [ "THE LOVELY BONES", "has_tags", "SUPERNATURAL" ], [ "THE LOVELY BONES", "release_year", "2009" ], [ "THE LOVELY BONES", "written_by", "PETER JACKSON" ], [ "TUMBLEWEEDS", "has_genre", "COMEDY" ], [ "TUMBLEWEEDS", "has_genre", "DRAMA" ], [ "TUMBLEWEEDS", "written_by", "ANGELA SHELTON" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 35845, 2006 18243, A SCANNER DARKLY 23754, AFTER THE WEDDING 6938, ALPHA DOG 8229, APOCALYPTO 24301, ART SCHOOL CONFIDENTIAL 18820, ASK THE DUST 24366, BABEL 36593, BLACK CHRISTMAS 16664, BLOOD DIAMOND 10531, BOBBY 867, BREAKING AND ENTERING 12724, BROKEN SKY 17899, BUG 33360, CANDY 22435, CHILDREN OF MEN 21625, CLERKS II 37750, CRANK 15115, CURSE OF THE GOLDEN FLOWER 3567, DAYS OF GLORY 24699, ELEGY 8262, FAMILY LAW 13766, FAST FOOD NATION 13893, FIDO 18217, FIND ME GUILTY 10315, FLAGS OF OUR FATHERS 39988, FRIENDS WITH MONEY 7879, HALF NELSON 26170, HOLLYWOODLAND 17120, INFAMOUS 19637, INLAND EMPIRE 7264, INSIDE MAN 18934, LETTERS FROM IWO JIMA 11277, LITTLE CHILDREN 24376, LITTLE MISS SUNSHINE 39673, LOS OLVIDADOS 33950, LUCKY NUMBER SLEVIN 38677, MIAMI VICE 3519, MY NAME IS JUANI 39852, PAN'S LABYRINTH 3451, PAPRIKA 24369, QUINCEAÑERA 13081, R 18480, RENAISSANCE 5766, RUNNING WITH SCISSORS 17383, SHERRYBABY 26930, SLITHER 12333, SMOKIN' ACES 7556, SPANISH 37498, TENACIOUS D IN THE PICK OF DESTINY 24057, THE BACKWOODS 11948, THE BLACK DAHLIA 31353, THE CONTRACT 1059, THE DA VINCI CODE 18997, THE DEPARTED 1723, THE FALL 4662, THE GOOD GERMAN 15862, THE GOOD SHEPHERD 32459, THE HAMMER 31309, THE HOAX 2467, THE LAST KING OF SCOTLAND 14315, THE LIVES OF OTHERS 22880, THE MACHINIST 17393, THE NIGHT LISTENER 1846, THE ONE PERCENT 956, THE ORPHANAGE 11383, THE SCIENCE OF SLEEP 37148, THE SECRET IN THEIR EYES 8334, TRANSSIBERIAN 25806, UNITED 93 23568, VANILLA SKY 36753, VENUS 35728, VOLVER src, edge_attr, dst 29145, has_tags, 13081 29145, release_year, 35845 18243, has_tags, 13081 18243, release_year, 35845 23754, has_tags, 13081 23754, release_year, 35845 6938, has_tags, 13081 6938, release_year, 35845 8229, has_tags, 13081 8229, release_year, 35845 24301, has_tags, 13081 24301, release_year, 35845 18820, has_tags, 13081 18820, release_year, 35845 24366, has_tags, 13081 24366, release_year, 35845 36593, has_tags, 13081 36593, release_year, 35845 16664, has_tags, 13081 16664, release_year, 35845 10531, has_tags, 13081 10531, release_year, 35845 867, has_tags, 13081 867, release_year, 35845 12724, in_language, 7556 12724, release_year, 35845 17899, has_tags, 13081 17899, release_year, 35845 33360, has_tags, 13081 33360, release_year, 35845 22435, has_tags, 13081 22435, release_year, 35845 21625, has_tags, 13081 21625, release_year, 35845 37750, has_tags, 13081 37750, release_year, 35845 15115, has_tags, 13081 15115, release_year, 35845 3567, has_tags, 13081 3567, release_year, 35845 24699, has_tags, 13081 24699, in_language, 7556 8262, in_language, 7556 8262, release_year, 35845 13766, has_tags, 13081 13766, release_year, 35845 13893, has_tags, 13081 13893, release_year, 35845 18217, has_tags, 13081 18217, release_year, 35845 10315, has_tags, 13081 10315, release_year, 35845 39988, has_tags, 13081 39988, release_year, 35845 7879, has_tags, 13081 7879, release_year, 35845 26170, has_tags, 13081 26170, release_year, 35845 17120, has_tags, 13081 17120, release_year, 35845 19637, has_tags, 13081 19637, release_year, 35845 7264, has_tags, 13081 7264, release_year, 35845 18934, has_tags, 13081 18934, release_year, 35845 11277, has_tags, 13081 11277, release_year, 35845 24376, has_tags, 13081 24376, release_year, 35845 39673, in_language, 7556 33950, has_tags, 13081 33950, release_year, 35845 38677, has_tags, 13081 38677, release_year, 35845 3519, in_language, 7556 3519, release_year, 35845 39852, has_tags, 13081 39852, has_tags, 7556 39852, in_language, 7556 39852, release_year, 35845 3451, has_tags, 13081 3451, release_year, 35845 24369, in_language, 7556 24369, release_year, 35845 18480, has_tags, 13081 18480, release_year, 35845 5766, has_tags, 13081 5766, release_year, 35845 17383, has_tags, 13081 17383, release_year, 35845 26930, has_tags, 13081 26930, release_year, 35845 12333, has_tags, 13081 12333, release_year, 35845 37498, has_tags, 13081 37498, release_year, 35845 24057, in_language, 7556 24057, release_year, 35845 11948, has_tags, 13081 11948, release_year, 35845 31353, has_tags, 13081 31353, release_year, 35845 1059, has_tags, 13081 1059, release_year, 35845 18997, has_tags, 13081 18997, release_year, 35845 1723, has_tags, 13081 1723, release_year, 35845 4662, has_tags, 13081 4662, release_year, 35845 15862, has_tags, 13081 15862, release_year, 35845 32459, has_tags, 13081 31309, has_tags, 13081 31309, release_year, 35845 2467, has_tags, 13081 2467, release_year, 35845 14315, has_tags, 13081 14315, release_year, 35845 22880, has_tags, 13081 22880, in_language, 7556 17393, has_tags, 13081 17393, release_year, 35845 1846, release_year, 35845 956, has_tags, 13081 956, has_tags, 7556 956, in_language, 7556 11383, has_tags, 13081 11383, release_year, 35845 37148, has_tags, 13081 37148, has_tags, 7556 37148, in_language, 7556 8334, has_tags, 13081 8334, in_language, 7556 25806, has_tags, 13081 25806, release_year, 35845 23568, has_tags, 13081 23568, in_language, 7556 36753, has_tags, 13081 36753, release_year, 35845 35728, has_tags, 13081 35728, has_tags, 7556 35728, in_language, 7556 35728, release_year, 35845 Question: How are LOS OLVIDADOS, THE HAMMER, and THE ONE PERCENT related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LOS OLVIDADOS", "THE HAMMER", "THE ONE PERCENT" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_tags", "R" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "A SCANNER DARKLY", "has_tags", "R" ], [ "A SCANNER DARKLY", "release_year", "2006" ], [ "AFTER THE WEDDING", "has_tags", "R" ], [ "AFTER THE WEDDING", "release_year", "2006" ], [ "ALPHA DOG", "has_tags", "R" ], [ "ALPHA DOG", "release_year", "2006" ], [ "APOCALYPTO", "has_tags", "R" ], [ "APOCALYPTO", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_tags", "R" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "ASK THE DUST", "has_tags", "R" ], [ "ASK THE DUST", "release_year", "2006" ], [ "BABEL", "has_tags", "R" ], [ "BABEL", "release_year", "2006" ], [ "BLACK CHRISTMAS", "has_tags", "R" ], [ "BLACK CHRISTMAS", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "R" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "BOBBY", "has_tags", "R" ], [ "BOBBY", "release_year", "2006" ], [ "BREAKING AND ENTERING", "has_tags", "R" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "BROKEN SKY", "in_language", "SPANISH" ], [ "BROKEN SKY", "release_year", "2006" ], [ "BUG", "has_tags", "R" ], [ "BUG", "release_year", "2006" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "R" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "CLERKS II", "has_tags", "R" ], [ "CLERKS II", "release_year", "2006" ], [ "CRANK", "has_tags", "R" ], [ "CRANK", "release_year", "2006" ], [ "CURSE OF THE GOLDEN FLOWER", "has_tags", "R" ], [ "CURSE OF THE GOLDEN FLOWER", "release_year", "2006" ], [ "DAYS OF GLORY", "has_tags", "R" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "ELEGY", "has_tags", "R" ], [ "ELEGY", "in_language", "SPANISH" ], [ "FAMILY LAW", "in_language", "SPANISH" ], [ "FAMILY LAW", "release_year", "2006" ], [ "FAST FOOD NATION", "has_tags", "R" ], [ "FAST FOOD NATION", "release_year", "2006" ], [ "FIDO", "has_tags", "R" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_tags", "R" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FRIENDS WITH MONEY", "has_tags", "R" ], [ "FRIENDS WITH MONEY", "release_year", "2006" ], [ "HALF NELSON", "has_tags", "R" ], [ "HALF NELSON", "release_year", "2006" ], [ "HOLLYWOODLAND", "has_tags", "R" ], [ "HOLLYWOODLAND", "release_year", "2006" ], [ "INFAMOUS", "has_tags", "R" ], [ "INFAMOUS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "R" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "INSIDE MAN", "has_tags", "R" ], [ "INSIDE MAN", "release_year", "2006" ], [ "LETTERS FROM IWO JIMA", "has_tags", "R" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "LITTLE CHILDREN", "has_tags", "R" ], [ "LITTLE CHILDREN", "release_year", "2006" ], [ "LITTLE MISS SUNSHINE", "has_tags", "R" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LOS OLVIDADOS", "in_language", "SPANISH" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "release_year", "2006" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MIAMI VICE", "release_year", "2006" ], [ "MY NAME IS JUANI", "in_language", "SPANISH" ], [ "MY NAME IS JUANI", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_tags", "R" ], [ "PAN'S LABYRINTH", "has_tags", "SPANISH" ], [ "PAN'S LABYRINTH", "in_language", "SPANISH" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PAPRIKA", "has_tags", "R" ], [ "PAPRIKA", "release_year", "2006" ], [ "QUINCEAÑERA", "in_language", "SPANISH" ], [ "QUINCEAÑERA", "release_year", "2006" ], [ "RENAISSANCE", "has_tags", "R" ], [ "RENAISSANCE", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_tags", "R" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "SHERRYBABY", "has_tags", "R" ], [ "SHERRYBABY", "release_year", "2006" ], [ "SLITHER", "has_tags", "R" ], [ "SLITHER", "release_year", "2006" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "R" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE BACKWOODS", "in_language", "SPANISH" ], [ "THE BACKWOODS", "release_year", "2006" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE BLACK DAHLIA", "release_year", "2006" ], [ "THE CONTRACT", "has_tags", "R" ], [ "THE CONTRACT", "release_year", "2006" ], [ "THE DA VINCI CODE", "has_tags", "R" ], [ "THE DA VINCI CODE", "release_year", "2006" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "release_year", "2006" ], [ "THE FALL", "has_tags", "R" ], [ "THE FALL", "release_year", "2006" ], [ "THE GOOD GERMAN", "has_tags", "R" ], [ "THE GOOD GERMAN", "release_year", "2006" ], [ "THE GOOD SHEPHERD", "has_tags", "R" ], [ "THE GOOD SHEPHERD", "release_year", "2006" ], [ "THE HAMMER", "has_tags", "R" ], [ "THE HOAX", "has_tags", "R" ], [ "THE HOAX", "release_year", "2006" ], [ "THE LAST KING OF SCOTLAND", "has_tags", "R" ], [ "THE LAST KING OF SCOTLAND", "release_year", "2006" ], [ "THE LIVES OF OTHERS", "has_tags", "R" ], [ "THE LIVES OF OTHERS", "release_year", "2006" ], [ "THE MACHINIST", "has_tags", "R" ], [ "THE MACHINIST", "in_language", "SPANISH" ], [ "THE NIGHT LISTENER", "has_tags", "R" ], [ "THE NIGHT LISTENER", "release_year", "2006" ], [ "THE ONE PERCENT", "release_year", "2006" ], [ "THE ORPHANAGE", "has_tags", "R" ], [ "THE ORPHANAGE", "has_tags", "SPANISH" ], [ "THE ORPHANAGE", "in_language", "SPANISH" ], [ "THE SCIENCE OF SLEEP", "has_tags", "R" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE SECRET IN THEIR EYES", "has_tags", "SPANISH" ], [ "THE SECRET IN THEIR EYES", "in_language", "SPANISH" ], [ "TRANSSIBERIAN", "has_tags", "R" ], [ "TRANSSIBERIAN", "in_language", "SPANISH" ], [ "UNITED 93", "has_tags", "R" ], [ "UNITED 93", "release_year", "2006" ], [ "VANILLA SKY", "has_tags", "R" ], [ "VANILLA SKY", "in_language", "SPANISH" ], [ "VENUS", "has_tags", "R" ], [ "VENUS", "release_year", "2006" ], [ "VOLVER", "has_tags", "R" ], [ "VOLVER", "has_tags", "SPANISH" ], [ "VOLVER", "in_language", "SPANISH" ], [ "VOLVER", "release_year", "2006" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37224, 1990 19905, A TALE OF SPRINGTIME 28725, ANNE TEYSSÈDRE 1856, EUROPA EUROPA 22011, NIGHTBREED 10981, SERIAL KILLER src, edge_attr, dst 19905, release_year, 37224 19905, starred_actors, 28725 1856, release_year, 37224 22011, has_tags, 10981 22011, release_year, 37224 Question: For what reason are ANNE TEYSSÈDRE, EUROPA EUROPA, and SERIAL KILLER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANNE TEYSSÈDRE", "EUROPA EUROPA", "SERIAL KILLER" ], "valid_edges": [ [ "A TALE OF SPRINGTIME", "release_year", "1990" ], [ "A TALE OF SPRINGTIME", "starred_actors", "ANNE TEYSSÈDRE" ], [ "EUROPA EUROPA", "release_year", "1990" ], [ "NIGHTBREED", "has_tags", "SERIAL KILLER" ], [ "NIGHTBREED", "release_year", "1990" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 33645, BILL OBERST JR. 31778, BLACK SHEEP 29691, CHRIS FARLEY 5870, HORROR 9520, JODY LAMBERT 31312, PEOPLE LIKE US 24992, SCARY OR DIE src, edge_attr, dst 31778, has_genre, 5870 31778, has_tags, 29691 31778, starred_actors, 29691 31312, release_year, 658 31312, written_by, 9520 24992, has_genre, 5870 24992, release_year, 658 24992, starred_actors, 33645 Question: For what reason are BILL OBERST JR., CHRIS FARLEY, and JODY LAMBERT associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BILL OBERST JR.", "CHRIS FARLEY", "JODY LAMBERT" ], "valid_edges": [ [ "BLACK SHEEP", "has_genre", "HORROR" ], [ "BLACK SHEEP", "has_tags", "CHRIS FARLEY" ], [ "BLACK SHEEP", "starred_actors", "CHRIS FARLEY" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "PEOPLE LIKE US", "written_by", "JODY LAMBERT" ], [ "SCARY OR DIE", "has_genre", "HORROR" ], [ "SCARY OR DIE", "release_year", "2012" ], [ "SCARY OR DIE", "starred_actors", "BILL OBERST JR." ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39641, ALONG CAME JONES 24276, CASANOVA BROWN 30463, COMEDY 29757, GARY COOPER 12557, HOW TO MARRY A MILLIONAIRE 34414, KARYN BOSNAK 35230, MICHAEL DUDIKOFF 11190, NUNNALLY JOHNSON 32766, RADIOACTIVE DREAMS 11290, TAKE HER, SHE'S MINE 29742, WHAT'S YOUR NUMBER? src, edge_attr, dst 39641, has_genre, 30463 39641, starred_actors, 29757 39641, written_by, 11190 24276, has_genre, 30463 24276, starred_actors, 29757 24276, written_by, 11190 12557, has_genre, 30463 12557, written_by, 11190 32766, has_genre, 30463 32766, starred_actors, 35230 11290, has_genre, 30463 11290, written_by, 11190 29742, has_genre, 30463 29742, written_by, 34414 Question: In what context are KARYN BOSNAK, MICHAEL DUDIKOFF, and NUNNALLY JOHNSON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KARYN BOSNAK", "MICHAEL DUDIKOFF", "NUNNALLY JOHNSON" ], "valid_edges": [ [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "starred_actors", "GARY COOPER" ], [ "ALONG CAME JONES", "written_by", "NUNNALLY JOHNSON" ], [ "CASANOVA BROWN", "has_genre", "COMEDY" ], [ "CASANOVA BROWN", "starred_actors", "GARY COOPER" ], [ "CASANOVA BROWN", "written_by", "NUNNALLY JOHNSON" ], [ "HOW TO MARRY A MILLIONAIRE", "has_genre", "COMEDY" ], [ "HOW TO MARRY A MILLIONAIRE", "written_by", "NUNNALLY JOHNSON" ], [ "RADIOACTIVE DREAMS", "has_genre", "COMEDY" ], [ "RADIOACTIVE DREAMS", "starred_actors", "MICHAEL DUDIKOFF" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "written_by", "NUNNALLY JOHNSON" ], [ "WHAT'S YOUR NUMBER?", "has_genre", "COMEDY" ], [ "WHAT'S YOUR NUMBER?", "written_by", "KARYN BOSNAK" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 22088, A BRIDGE TOO FAR 25987, A GUY NAMED JOE 23445, A MIDNIGHT CLEAR 27553, ACT OF VALOR 7663, ACTION IN THE NORTH ATLANTIC 22726, ANNE FRANK REMEMBERED 36876, ATTACK 32014, BALLAD OF A SOLDIER 34734, BATTLE OF THE BULGE 12185, BATTLEGROUND 6817, BENNO VIGNY 1912, BEYOND ALL BOUNDARIES 40074, BLACK BOOK 25285, COME AND SEE 10293, CONSPIRACY 4615, DARK BLUE WORLD 18972, DAS BOOT 11363, DEFIANCE 16353, EDGES OF THE LORD 26918, EMPEROR 22028, EMPIRE OF THE SUN 16930, ENEMY AT THE GATES 21289, ENTITY 27958, FIRES ON THE PLAIN 10315, FLAGS OF OUR FATHERS 13834, FLYING TIGERS 39145, FURY 30162, GUADALCANAL DIARY 15765, HAMSUN 33545, HART'S WAR 15343, IN DARKNESS 35518, IN HARM'S WAY 28700, INTO THE WHITE 38574, IT HAPPENED HERE 22012, IVAN'S CHILDHOOD 22167, KING RAT 9595, MEMPHIS BELLE 1422, MOROCCO 5127, MOTHER NIGHT 38294, MRS. MINIVER 20581, OPERATION PACIFIC 16806, PATTON 27373, RED DAWN 17742, RED TAILS 7978, RUROUNI KENSHIN 35586, SAHARA 23006, SANDS OF IWO JIMA 24365, SAVING PRIVATE RYAN 21196, STALAG 17 11124, STALINGRAD 37855, TEA WITH MUSSOLINI 38627, TEN TALL MEN 16103, THE AVENGERS 27210, THE BEST YEARS OF OUR LIVES 7710, THE BIG RED ONE 29788, THE BRIDGE AT REMAGEN 14436, THE BURMESE HARP 36692, THE CAINE MUTINY 828, THE ENEMY BELOW 30507, THE FIGHTING SEABEES 6424, THE GREAT ESCAPE 31393, THE GREAT RAID 405, THE HIDING PLACE 20299, THE HILL 27237, THE LONGEST DAY 30294, THE NIGHT OF THE GENERALS 1195, THE PATIENCE STONE 12614, THE PIANIST 32618, THE RAPE OF EUROPA 2739, THE SAPPHIRES 4962, THE SORROW AND THE PITY 21548, THE SUN 30136, THE THIN RED LINE 35911, THE TUSKEGEE AIRMEN 3123, THEY WERE EXPENDABLE 38352, TWELVE O'CLOCK HIGH 38730, TWO MEN WENT TO WAR 37253, U-571 39558, UNDERGROUND 33011, VALKYRIE 2175, VON RYAN'S EXPRESS 22214, WAR 9159, WAR COMES TO AMERICA 30056, WAR WITCH 5949, WHEN TRUMPETS FADE 23537, WHERE EAGLES DARE 24155, WORLD WAR II 15904, YANKS 16849, ZERO DARK THIRTY src, edge_attr, dst 22088, has_genre, 22214 22088, has_tags, 22214 22088, has_tags, 24155 25987, has_genre, 22214 25987, has_tags, 24155 23445, has_genre, 22214 23445, has_tags, 22214 23445, has_tags, 24155 27553, has_genre, 22214 27553, release_year, 658 7663, has_genre, 22214 7663, has_tags, 24155 22726, has_genre, 22214 22726, has_tags, 24155 36876, has_genre, 22214 36876, has_tags, 24155 32014, has_genre, 22214 32014, has_tags, 24155 34734, has_genre, 22214 34734, has_tags, 24155 12185, has_genre, 22214 12185, has_tags, 22214 12185, has_tags, 24155 1912, has_genre, 22214 1912, has_tags, 24155 40074, has_genre, 22214 40074, has_tags, 24155 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 4615, has_genre, 22214 4615, has_tags, 24155 18972, has_genre, 22214 18972, has_tags, 22214 18972, has_tags, 24155 11363, has_tags, 22214 11363, has_tags, 24155 16353, has_genre, 22214 16353, has_tags, 24155 26918, has_tags, 22214 26918, release_year, 658 22028, has_genre, 22214 22028, has_tags, 22214 22028, has_tags, 24155 16930, has_tags, 22214 16930, has_tags, 24155 21289, release_year, 658 27958, has_genre, 22214 27958, has_tags, 24155 10315, has_genre, 22214 10315, has_tags, 22214 10315, has_tags, 24155 13834, has_genre, 22214 13834, has_tags, 24155 39145, has_genre, 22214 39145, has_tags, 22214 39145, has_tags, 24155 30162, has_genre, 22214 30162, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 33545, has_genre, 22214 33545, has_tags, 24155 15343, has_genre, 22214 15343, has_tags, 22214 15343, has_tags, 24155 35518, has_genre, 22214 35518, has_tags, 24155 28700, has_genre, 22214 28700, release_year, 658 38574, has_genre, 22214 38574, has_tags, 24155 22012, has_genre, 22214 22012, has_tags, 22214 22012, has_tags, 24155 22167, has_genre, 22214 22167, has_tags, 24155 9595, has_genre, 22214 9595, has_tags, 24155 1422, written_by, 6817 5127, has_genre, 22214 5127, has_tags, 24155 38294, has_genre, 22214 38294, has_tags, 24155 20581, has_genre, 22214 20581, has_tags, 24155 16806, has_genre, 22214 16806, has_tags, 22214 16806, has_tags, 24155 27373, has_genre, 22214 27373, has_tags, 22214 27373, release_year, 658 17742, has_tags, 24155 17742, release_year, 658 7978, has_tags, 22214 7978, release_year, 658 35586, has_genre, 22214 35586, has_tags, 24155 23006, has_genre, 22214 23006, has_tags, 24155 24365, has_genre, 22214 24365, has_tags, 22214 24365, has_tags, 24155 21196, has_genre, 22214 21196, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 37855, has_genre, 22214 37855, has_tags, 24155 38627, has_genre, 22214 38627, has_tags, 1422 16103, has_tags, 22214 16103, release_year, 658 27210, has_genre, 22214 27210, has_tags, 24155 7710, has_genre, 22214 7710, has_tags, 24155 29788, has_genre, 22214 29788, has_tags, 24155 14436, has_genre, 22214 14436, has_tags, 24155 36692, has_genre, 22214 36692, has_tags, 24155 828, has_tags, 22214 828, has_tags, 24155 30507, has_genre, 22214 30507, has_tags, 24155 6424, has_tags, 22214 6424, has_tags, 24155 31393, has_genre, 22214 31393, has_tags, 24155 405, has_genre, 22214 405, has_tags, 24155 20299, has_genre, 22214 20299, has_tags, 24155 27237, has_tags, 22214 27237, has_tags, 24155 30294, has_tags, 22214 30294, has_tags, 24155 1195, has_genre, 22214 1195, release_year, 658 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 32618, has_genre, 22214 32618, has_tags, 24155 2739, has_tags, 22214 2739, release_year, 658 4962, has_genre, 22214 4962, has_tags, 24155 21548, has_tags, 22214 21548, has_tags, 24155 30136, has_genre, 22214 30136, has_tags, 22214 30136, has_tags, 24155 35911, has_genre, 22214 35911, has_tags, 24155 3123, has_genre, 22214 3123, has_tags, 24155 38352, has_genre, 22214 38352, has_tags, 24155 38730, has_genre, 22214 38730, has_tags, 24155 37253, has_genre, 22214 37253, has_tags, 22214 37253, has_tags, 24155 39558, has_genre, 22214 39558, has_tags, 24155 33011, has_genre, 22214 33011, has_tags, 24155 2175, has_genre, 22214 2175, has_tags, 24155 9159, has_genre, 22214 9159, has_tags, 24155 30056, has_genre, 22214 30056, release_year, 658 5949, has_genre, 22214 5949, has_tags, 24155 23537, has_genre, 22214 23537, has_tags, 24155 15904, has_genre, 22214 15904, has_tags, 24155 16849, has_tags, 22214 16849, release_year, 658 Question: In what context are BENNO VIGNY, ENTITY, and KING RAT connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BENNO VIGNY", "ENTITY", "KING RAT" ], "valid_edges": [ [ "A BRIDGE TOO FAR", "has_genre", "WAR" ], [ "A BRIDGE TOO FAR", "has_tags", "WAR" ], [ "A BRIDGE TOO FAR", "has_tags", "WORLD WAR II" ], [ "A GUY NAMED JOE", "has_genre", "WAR" ], [ "A GUY NAMED JOE", "has_tags", "WORLD WAR II" ], [ "A MIDNIGHT CLEAR", "has_genre", "WAR" ], [ "A MIDNIGHT CLEAR", "has_tags", "WAR" ], [ "A MIDNIGHT CLEAR", "has_tags", "WORLD WAR II" ], [ "ACT OF VALOR", "has_genre", "WAR" ], [ "ACT OF VALOR", "release_year", "2012" ], [ "ACTION IN THE NORTH ATLANTIC", "has_genre", "WAR" ], [ "ACTION IN THE NORTH ATLANTIC", "has_tags", "WORLD WAR II" ], [ "ANNE FRANK REMEMBERED", "has_genre", "WAR" ], [ "ANNE FRANK REMEMBERED", "has_tags", "WORLD WAR II" ], [ "ATTACK", "has_genre", "WAR" ], [ "ATTACK", "has_tags", "WORLD WAR II" ], [ "BALLAD OF A SOLDIER", "has_genre", "WAR" ], [ "BALLAD OF A SOLDIER", "has_tags", "WORLD WAR II" ], [ "BATTLE OF THE BULGE", "has_genre", "WAR" ], [ "BATTLE OF THE BULGE", "has_tags", "WORLD WAR II" ], [ "BATTLEGROUND", "has_genre", "WAR" ], [ "BATTLEGROUND", "has_tags", "WAR" ], [ "BATTLEGROUND", "has_tags", "WORLD WAR II" ], [ "BEYOND ALL BOUNDARIES", "has_genre", "WAR" ], [ "BEYOND ALL BOUNDARIES", "has_tags", "WORLD WAR II" ], [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "has_tags", "WORLD WAR II" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "DARK BLUE WORLD", "has_genre", "WAR" ], [ "DARK BLUE WORLD", "has_tags", "WORLD WAR II" ], [ "DAS BOOT", "has_genre", "WAR" ], [ "DAS BOOT", "has_tags", "WAR" ], [ "DAS BOOT", "has_tags", "WORLD WAR II" ], [ "DEFIANCE", "has_tags", "WAR" ], [ "DEFIANCE", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "has_genre", "WAR" ], [ "EDGES OF THE LORD", "has_tags", "WORLD WAR II" ], [ "EMPEROR", "has_tags", "WAR" ], [ "EMPEROR", "release_year", "2012" ], [ "EMPIRE OF THE SUN", "has_genre", "WAR" ], [ "EMPIRE OF THE SUN", "has_tags", "WAR" ], [ "EMPIRE OF THE SUN", "has_tags", "WORLD WAR II" ], [ "ENEMY AT THE GATES", "has_tags", "WAR" ], [ "ENEMY AT THE GATES", "has_tags", "WORLD WAR II" ], [ "ENTITY", "release_year", "2012" ], [ "FIRES ON THE PLAIN", "has_genre", "WAR" ], [ "FIRES ON THE PLAIN", "has_tags", "WORLD WAR II" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WORLD WAR II" ], [ "FLYING TIGERS", "has_genre", "WAR" ], [ "FLYING TIGERS", "has_tags", "WORLD WAR II" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "has_tags", "WORLD WAR II" ], [ "GUADALCANAL DIARY", "has_genre", "WAR" ], [ "GUADALCANAL DIARY", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HART'S WAR", "has_genre", "WAR" ], [ "HART'S WAR", "has_tags", "WORLD WAR II" ], [ "IN DARKNESS", "has_genre", "WAR" ], [ "IN DARKNESS", "has_tags", "WAR" ], [ "IN DARKNESS", "has_tags", "WORLD WAR II" ], [ "IN HARM'S WAY", "has_genre", "WAR" ], [ "IN HARM'S WAY", "has_tags", "WORLD WAR II" ], [ "INTO THE WHITE", "has_genre", "WAR" ], [ "INTO THE WHITE", "release_year", "2012" ], [ "IT HAPPENED HERE", "has_genre", "WAR" ], [ "IT HAPPENED HERE", "has_tags", "WORLD WAR II" ], [ "IVAN'S CHILDHOOD", "has_genre", "WAR" ], [ "IVAN'S CHILDHOOD", "has_tags", "WAR" ], [ "IVAN'S CHILDHOOD", "has_tags", "WORLD WAR II" ], [ "KING RAT", "has_genre", "WAR" ], [ "KING RAT", "has_tags", "WORLD WAR II" ], [ "MEMPHIS BELLE", "has_genre", "WAR" ], [ "MEMPHIS BELLE", "has_tags", "WORLD WAR II" ], [ "MOROCCO", "written_by", "BENNO VIGNY" ], [ "MOTHER NIGHT", "has_genre", "WAR" ], [ "MOTHER NIGHT", "has_tags", "WORLD WAR II" ], [ "MRS. MINIVER", "has_genre", "WAR" ], [ "MRS. MINIVER", "has_tags", "WORLD WAR II" ], [ "OPERATION PACIFIC", "has_genre", "WAR" ], [ "OPERATION PACIFIC", "has_tags", "WORLD WAR II" ], [ "PATTON", "has_genre", "WAR" ], [ "PATTON", "has_tags", "WAR" ], [ "PATTON", "has_tags", "WORLD WAR II" ], [ "RED DAWN", "has_genre", "WAR" ], [ "RED DAWN", "has_tags", "WAR" ], [ "RED DAWN", "release_year", "2012" ], [ "RED TAILS", "has_tags", "WORLD WAR II" ], [ "RED TAILS", "release_year", "2012" ], [ "RUROUNI KENSHIN", "has_tags", "WAR" ], [ "RUROUNI KENSHIN", "release_year", "2012" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "SANDS OF IWO JIMA", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "has_tags", "WORLD WAR II" ], [ "SAVING PRIVATE RYAN", "has_genre", "WAR" ], [ "SAVING PRIVATE RYAN", "has_tags", "WAR" ], [ "SAVING PRIVATE RYAN", "has_tags", "WORLD WAR II" ], [ "STALAG 17", "has_genre", "WAR" ], [ "STALAG 17", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "TEA WITH MUSSOLINI", "has_genre", "WAR" ], [ "TEA WITH MUSSOLINI", "has_tags", "WORLD WAR II" ], [ "TEN TALL MEN", "has_genre", "WAR" ], [ "TEN TALL MEN", "has_tags", "MOROCCO" ], [ "THE AVENGERS", "has_tags", "WAR" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE BEST YEARS OF OUR LIVES", "has_genre", "WAR" ], [ "THE BEST YEARS OF OUR LIVES", "has_tags", "WORLD WAR II" ], [ "THE BIG RED ONE", "has_genre", "WAR" ], [ "THE BIG RED ONE", "has_tags", "WORLD WAR II" ], [ "THE BRIDGE AT REMAGEN", "has_genre", "WAR" ], [ "THE BRIDGE AT REMAGEN", "has_tags", "WORLD WAR II" ], [ "THE BURMESE HARP", "has_genre", "WAR" ], [ "THE BURMESE HARP", "has_tags", "WORLD WAR II" ], [ "THE CAINE MUTINY", "has_genre", "WAR" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE ENEMY BELOW", "has_tags", "WAR" ], [ "THE ENEMY BELOW", "has_tags", "WORLD WAR II" ], [ "THE FIGHTING SEABEES", "has_genre", "WAR" ], [ "THE FIGHTING SEABEES", "has_tags", "WORLD WAR II" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "has_tags", "WORLD WAR II" ], [ "THE GREAT RAID", "has_genre", "WAR" ], [ "THE GREAT RAID", "has_tags", "WORLD WAR II" ], [ "THE HIDING PLACE", "has_genre", "WAR" ], [ "THE HIDING PLACE", "has_tags", "WORLD WAR II" ], [ "THE HILL", "has_genre", "WAR" ], [ "THE HILL", "has_tags", "WORLD WAR II" ], [ "THE LONGEST DAY", "has_tags", "WAR" ], [ "THE LONGEST DAY", "has_tags", "WORLD WAR II" ], [ "THE NIGHT OF THE GENERALS", "has_tags", "WAR" ], [ "THE NIGHT OF THE GENERALS", "has_tags", "WORLD WAR II" ], [ "THE PATIENCE STONE", "has_genre", "WAR" ], [ "THE PATIENCE STONE", "release_year", "2012" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "THE RAPE OF EUROPA", "has_genre", "WAR" ], [ "THE RAPE OF EUROPA", "has_tags", "WORLD WAR II" ], [ "THE SAPPHIRES", "has_tags", "WAR" ], [ "THE SAPPHIRES", "release_year", "2012" ], [ "THE SORROW AND THE PITY", "has_genre", "WAR" ], [ "THE SORROW AND THE PITY", "has_tags", "WORLD WAR II" ], [ "THE SUN", "has_tags", "WAR" ], [ "THE SUN", "has_tags", "WORLD WAR II" ], [ "THE THIN RED LINE", "has_genre", "WAR" ], [ "THE THIN RED LINE", "has_tags", "WAR" ], [ "THE THIN RED LINE", "has_tags", "WORLD WAR II" ], [ "THE TUSKEGEE AIRMEN", "has_genre", "WAR" ], [ "THE TUSKEGEE AIRMEN", "has_tags", "WORLD WAR II" ], [ "THEY WERE EXPENDABLE", "has_genre", "WAR" ], [ "THEY WERE EXPENDABLE", "has_tags", "WORLD WAR II" ], [ "TWELVE O'CLOCK HIGH", "has_genre", "WAR" ], [ "TWELVE O'CLOCK HIGH", "has_tags", "WORLD WAR II" ], [ "TWO MEN WENT TO WAR", "has_genre", "WAR" ], [ "TWO MEN WENT TO WAR", "has_tags", "WORLD WAR II" ], [ "U-571", "has_genre", "WAR" ], [ "U-571", "has_tags", "WAR" ], [ "U-571", "has_tags", "WORLD WAR II" ], [ "UNDERGROUND", "has_genre", "WAR" ], [ "UNDERGROUND", "has_tags", "WORLD WAR II" ], [ "VALKYRIE", "has_genre", "WAR" ], [ "VALKYRIE", "has_tags", "WORLD WAR II" ], [ "VON RYAN'S EXPRESS", "has_genre", "WAR" ], [ "VON RYAN'S EXPRESS", "has_tags", "WORLD WAR II" ], [ "WAR COMES TO AMERICA", "has_genre", "WAR" ], [ "WAR COMES TO AMERICA", "has_tags", "WORLD WAR II" ], [ "WAR WITCH", "has_genre", "WAR" ], [ "WAR WITCH", "release_year", "2012" ], [ "WHEN TRUMPETS FADE", "has_genre", "WAR" ], [ "WHEN TRUMPETS FADE", "has_tags", "WORLD WAR II" ], [ "WHERE EAGLES DARE", "has_genre", "WAR" ], [ "WHERE EAGLES DARE", "has_tags", "WORLD WAR II" ], [ "YANKS", "has_genre", "WAR" ], [ "YANKS", "has_tags", "WORLD WAR II" ], [ "ZERO DARK THIRTY", "has_tags", "WAR" ], [ "ZERO DARK THIRTY", "release_year", "2012" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 33511, DRACULA UNTOLD 26691, FREEZER 4336, GARY SHORE 11593, JUSTIN LADER 11121, MIKAEL SALOMON 22108, THE ONE I LOVE src, edge_attr, dst 33511, directed_by, 4336 33511, release_year, 9377 26691, directed_by, 11121 26691, release_year, 9377 22108, release_year, 9377 22108, written_by, 11593 Question: In what context are GARY SHORE, JUSTIN LADER, and MIKAEL SALOMON connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GARY SHORE", "JUSTIN LADER", "MIKAEL SALOMON" ], "valid_edges": [ [ "DRACULA UNTOLD", "directed_by", "GARY SHORE" ], [ "DRACULA UNTOLD", "release_year", "2014" ], [ "FREEZER", "directed_by", "MIKAEL SALOMON" ], [ "FREEZER", "release_year", "2014" ], [ "THE ONE I LOVE", "release_year", "2014" ], [ "THE ONE I LOVE", "written_by", "JUSTIN LADER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 16785, HENRY KING 21518, HONEY, I SHRUNK THE KIDS 34716, JOAN CHEN 21580, KIDS 33783, KRISTINE SUTHERLAND 30583, THE GUNFIGHTER 3579, THE HUNTED 37284, THE SUN ALSO RISES src, edge_attr, dst 21518, has_tags, 21580 21518, starred_actors, 33783 21580, release_year, 3702 30583, directed_by, 16785 30583, has_tags, 16785 3579, release_year, 3702 3579, starred_actors, 34716 37284, directed_by, 16785 37284, starred_actors, 34716 Question: How are KRISTINE SUTHERLAND, THE GUNFIGHTER, and THE HUNTED related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "KRISTINE SUTHERLAND", "THE GUNFIGHTER", "THE HUNTED" ], "valid_edges": [ [ "HONEY, I SHRUNK THE KIDS", "has_tags", "KIDS" ], [ "HONEY, I SHRUNK THE KIDS", "starred_actors", "KRISTINE SUTHERLAND" ], [ "KIDS", "release_year", "1995" ], [ "THE GUNFIGHTER", "directed_by", "HENRY KING" ], [ "THE GUNFIGHTER", "has_tags", "HENRY KING" ], [ "THE HUNTED", "release_year", "1995" ], [ "THE HUNTED", "starred_actors", "JOAN CHEN" ], [ "THE SUN ALSO RISES", "directed_by", "HENRY KING" ], [ "THE SUN ALSO RISES", "starred_actors", "JOAN CHEN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 135, 1926 25395, AMERICAN GRAFFITI 10768, BACK TO THE FUTURE 9097, BLADE RUNNER 16240, HARRISON FORD 26458, LON CHANEY 12574, LONDON AFTER MIDNIGHT 36980, MARCELINE DAY 37497, NATIONAL FILM REGISTRY 29299, RAIDERS OF THE LOST ARK 32090, ROBERT ZEMECKIS 4689, SABRINA 34215, TELL IT TO THE MARINES 21989, THE BLACKBIRD 31204, THE CAMERAMAN 28677, THE CONVERSATION 31647, THE SON OF THE SHEIK 28744, THE UNHOLY THREE 19823, THE UNKNOWN 28747, TOD BROWNING 24209, WEST OF ZANZIBAR 1524, WHAT LIES BENEATH 9246, WHERE EAST IS EAST src, edge_attr, dst 25395, has_tags, 16240 25395, has_tags, 37497 10768, directed_by, 32090 10768, has_tags, 37497 10768, has_tags, 32090 10768, written_by, 32090 9097, has_tags, 16240 9097, has_tags, 37497 9097, starred_actors, 16240 12574, starred_actors, 26458 12574, starred_actors, 36980 12574, written_by, 28747 29299, has_tags, 16240 29299, has_tags, 37497 29299, starred_actors, 16240 4689, has_tags, 16240 4689, has_tags, 37497 4689, starred_actors, 16240 34215, release_year, 135 34215, starred_actors, 26458 21989, directed_by, 28747 21989, release_year, 135 21989, starred_actors, 26458 21989, written_by, 28747 31204, has_tags, 37497 31204, starred_actors, 36980 28677, has_tags, 16240 28677, has_tags, 37497 31647, has_tags, 37497 31647, release_year, 135 28744, directed_by, 28747 28744, starred_actors, 26458 19823, directed_by, 28747 19823, has_tags, 26458 19823, has_tags, 28747 19823, starred_actors, 26458 19823, written_by, 28747 24209, directed_by, 28747 24209, starred_actors, 26458 1524, directed_by, 32090 1524, has_tags, 16240 1524, has_tags, 32090 9246, directed_by, 28747 9246, starred_actors, 26458 9246, written_by, 28747 Question: How are LONDON AFTER MIDNIGHT, THE SON OF THE SHEIK, and WHAT LIES BENEATH related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LONDON AFTER MIDNIGHT", "THE SON OF THE SHEIK", "WHAT LIES BENEATH" ], "valid_edges": [ [ "AMERICAN GRAFFITI", "has_tags", "HARRISON FORD" ], [ "AMERICAN GRAFFITI", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BACK TO THE FUTURE", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BACK TO THE FUTURE", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE", "written_by", "ROBERT ZEMECKIS" ], [ "BLADE RUNNER", "has_tags", "HARRISON FORD" ], [ "BLADE RUNNER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BLADE RUNNER", "starred_actors", "HARRISON FORD" ], [ "LONDON AFTER MIDNIGHT", "starred_actors", "LON CHANEY" ], [ "LONDON AFTER MIDNIGHT", "starred_actors", "MARCELINE DAY" ], [ "LONDON AFTER MIDNIGHT", "written_by", "TOD BROWNING" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "NATIONAL FILM REGISTRY" ], [ "RAIDERS OF THE LOST ARK", "starred_actors", "HARRISON FORD" ], [ "SABRINA", "has_tags", "HARRISON FORD" ], [ "SABRINA", "has_tags", "NATIONAL FILM REGISTRY" ], [ "SABRINA", "starred_actors", "HARRISON FORD" ], [ "TELL IT TO THE MARINES", "release_year", "1926" ], [ "TELL IT TO THE MARINES", "starred_actors", "LON CHANEY" ], [ "THE BLACKBIRD", "directed_by", "TOD BROWNING" ], [ "THE BLACKBIRD", "release_year", "1926" ], [ "THE BLACKBIRD", "starred_actors", "LON CHANEY" ], [ "THE BLACKBIRD", "written_by", "TOD BROWNING" ], [ "THE CAMERAMAN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE CAMERAMAN", "starred_actors", "MARCELINE DAY" ], [ "THE CONVERSATION", "has_tags", "HARRISON FORD" ], [ "THE CONVERSATION", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SON OF THE SHEIK", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SON OF THE SHEIK", "release_year", "1926" ], [ "THE UNHOLY THREE", "directed_by", "TOD BROWNING" ], [ "THE UNHOLY THREE", "starred_actors", "LON CHANEY" ], [ "THE UNKNOWN", "directed_by", "TOD BROWNING" ], [ "THE UNKNOWN", "has_tags", "LON CHANEY" ], [ "THE UNKNOWN", "has_tags", "TOD BROWNING" ], [ "THE UNKNOWN", "starred_actors", "LON CHANEY" ], [ "THE UNKNOWN", "written_by", "TOD BROWNING" ], [ "WEST OF ZANZIBAR", "directed_by", "TOD BROWNING" ], [ "WEST OF ZANZIBAR", "starred_actors", "LON CHANEY" ], [ "WHAT LIES BENEATH", "directed_by", "ROBERT ZEMECKIS" ], [ "WHAT LIES BENEATH", "has_tags", "HARRISON FORD" ], [ "WHAT LIES BENEATH", "has_tags", "ROBERT ZEMECKIS" ], [ "WHERE EAST IS EAST", "directed_by", "TOD BROWNING" ], [ "WHERE EAST IS EAST", "starred_actors", "LON CHANEY" ], [ "WHERE EAST IS EAST", "written_by", "TOD BROWNING" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4058, 16 YEARS OF ALCOHOL 1097, 2003 31345, 21 GRAMS 30643, ACROSS THE UNIVERSE 26501, ALILA 39500, ALL THE REAL GIRLS 16391, AMERICAN SPLENDOR 30281, ANA AND THE OTHERS 12144, BAD BOYS 33140, BAGHBAN 2419, BEYOND BORDERS 18822, BIG FISH 39878, BRIGHT FUTURE 22639, BRIGHT YOUNG THINGS 29448, CARANDIRU 19510, CLEOPATRA 4890, COLD MOUNTAIN 35932, DANA FUCHS 28659, DEAD END 28862, DOGVILLE 23182, DOPAMINE 36212, DRAMA 34486, EILA 14257, ELEPHANT 9048, EVIL 7866, FLYWHEEL 39946, GACY 3674, GAMES OF LOVE AND CHANCE 7599, GIRL WITH A PEARL EARRING 39494, HOLES 35319, HOPE SPRINGS 20309, HOUSE OF SAND AND FOG 19839, I ACCUSE 6684, I'LL SLEEP WHEN I'M DEAD 21437, IN THE CITY 31900, INCANTATO 39987, IT RUNS IN THE FAMILY 6425, IT'S ALL ABOUT LOVE 21614, JAPANESE STORY 8844, JONNY VANG 31245, KAL HO NAA HO 26853, LATTER DAYS 13296, LEVITY 15814, LOST IN TRANSLATION 35948, LOVE COMES SOFTLY 2088, MAIN PREM KI DIWANI HOON 11334, MASKED AND ANONYMOUS 18198, MATCHSTICK MEN 25936, MONA LISA SMILE 27827, MONSTER 12944, MY LIFE WITHOUT ME 9343, MYSTIC RIVER 37329, NATHALIE... 34705, NORMAL 21446, OFF THE MAP 10789, OPEN WATER 34120, OSAMA 23553, OUR TOWN 24769, OUT OF THE ASHES 23801, PARTY MONSTER 26350, PIECES OF APRIL 29357, RECONSTRUCTION 16708, ROADS TO KOKTEBEL 16356, ROBOT STORIES 5145, SAINTS AND SOLDIERS 3416, SARABAND 39821, SECONDHAND LIONS 4027, SHARA 38114, SHATTERED GLASS 5710, SOLDIER'S GIRL 19971, SPIN 6323, STRAYED 16954, SYLVIA 7985, SYMMETRY 11605, TAKE MY EYES 38965, THE BARBARIAN INVASIONS 38410, THE BATTLE OF SHAKER HEIGHTS 5144, THE BIG EMPTY 25461, THE COOLER 9758, THE CRAIGSLIST KILLER 21345, THE DREAMERS 12047, THE EVENT 20929, THE FIGHTING TEMPTATIONS 12447, THE HUMAN STAIN 32030, THE LOST PRINCE 24434, THE MUDGE BOY 28919, THE RETURN 30906, THE ROOM 38858, THE SHAPE OF THINGS 12883, THE SLEEPING DICTIONARY 2259, THE STATEMENT 38108, THE STATION AGENT 39036, THE STORY OF MARIE AND JULIEN 39883, THE STORY OF THE WEEPING CAMEL 22820, THE UNITED STATES OF LELAND 1411, THIRTEEN 10628, TIME OF THE WOLF 35264, TWO DAYS 11544, UNDER THE TUSCAN SUN 14956, VOICES OF A DISTANT STAR 39171, WHO KILLED BAMBI? 31862, WONDERLAND 27708, WUTHERING HEIGHTS 39834, YOUNG ADAM src, edge_attr, dst 4058, has_genre, 36212 4058, release_year, 1097 31345, has_genre, 36212 31345, has_tags, 36212 31345, release_year, 1097 30643, has_genre, 36212 30643, starred_actors, 35932 26501, has_genre, 36212 26501, release_year, 1097 39500, has_genre, 36212 39500, release_year, 1097 16391, has_genre, 36212 16391, release_year, 1097 30281, has_genre, 36212 30281, release_year, 1097 12144, has_genre, 36212 12144, release_year, 1097 33140, has_genre, 36212 33140, release_year, 1097 2419, has_genre, 36212 2419, release_year, 1097 18822, has_genre, 36212 18822, release_year, 1097 39878, has_genre, 36212 39878, release_year, 1097 22639, has_genre, 36212 22639, release_year, 1097 29448, has_genre, 36212 29448, release_year, 1097 19510, has_genre, 36212 19510, release_year, 1097 4890, has_genre, 36212 4890, has_tags, 36212 4890, release_year, 1097 28659, has_genre, 36212 28659, release_year, 1097 28862, has_genre, 36212 28862, has_tags, 36212 28862, release_year, 1097 23182, has_genre, 36212 23182, release_year, 1097 34486, has_genre, 36212 34486, release_year, 1097 14257, has_genre, 36212 14257, release_year, 1097 9048, has_genre, 36212 9048, release_year, 1097 7866, has_genre, 36212 7866, release_year, 1097 39946, has_genre, 36212 39946, release_year, 1097 3674, has_genre, 36212 3674, release_year, 1097 7599, has_genre, 36212 7599, has_tags, 36212 7599, release_year, 1097 39494, has_genre, 36212 39494, release_year, 1097 35319, has_genre, 36212 35319, release_year, 1097 20309, has_genre, 36212 20309, release_year, 1097 19839, has_genre, 36212 19839, release_year, 1097 6684, has_genre, 36212 6684, release_year, 1097 21437, has_genre, 36212 21437, release_year, 1097 31900, has_genre, 36212 31900, release_year, 1097 39987, has_genre, 36212 39987, release_year, 1097 6425, has_genre, 36212 6425, release_year, 1097 21614, has_genre, 36212 21614, release_year, 1097 8844, has_genre, 36212 8844, release_year, 1097 31245, has_genre, 36212 31245, release_year, 1097 26853, has_genre, 36212 26853, release_year, 1097 13296, has_genre, 36212 13296, release_year, 1097 15814, has_genre, 36212 15814, release_year, 1097 35948, has_genre, 36212 35948, release_year, 1097 2088, has_genre, 36212 2088, release_year, 1097 11334, has_genre, 36212 11334, release_year, 1097 18198, has_genre, 36212 18198, has_tags, 36212 18198, release_year, 1097 25936, has_genre, 36212 25936, release_year, 1097 27827, has_genre, 36212 27827, has_tags, 36212 27827, release_year, 1097 12944, has_genre, 36212 12944, release_year, 1097 9343, has_genre, 36212 9343, has_tags, 36212 9343, release_year, 1097 37329, has_genre, 36212 37329, release_year, 1097 34705, has_genre, 36212 34705, release_year, 1097 21446, has_genre, 36212 21446, has_tags, 36212 21446, release_year, 1097 10789, has_genre, 36212 10789, release_year, 1097 34120, has_genre, 36212 34120, release_year, 1097 23553, has_genre, 36212 23553, release_year, 1097 24769, has_genre, 36212 24769, release_year, 1097 23801, has_genre, 36212 23801, release_year, 1097 26350, has_genre, 36212 26350, release_year, 1097 29357, has_genre, 36212 29357, release_year, 1097 16708, has_genre, 36212 16708, release_year, 1097 16356, has_genre, 36212 16356, release_year, 1097 5145, has_genre, 36212 5145, release_year, 1097 3416, has_genre, 36212 3416, has_tags, 36212 3416, release_year, 1097 39821, has_genre, 36212 39821, release_year, 1097 4027, has_genre, 36212 4027, release_year, 1097 38114, has_genre, 36212 38114, release_year, 1097 5710, has_genre, 36212 5710, release_year, 1097 19971, has_genre, 36212 19971, release_year, 1097 6323, has_genre, 36212 6323, release_year, 1097 16954, has_genre, 36212 16954, release_year, 1097 7985, has_genre, 36212 7985, release_year, 1097 11605, has_genre, 36212 11605, release_year, 1097 38965, has_genre, 36212 38965, release_year, 1097 38410, has_genre, 36212 38410, release_year, 1097 5144, has_genre, 36212 5144, release_year, 1097 25461, has_genre, 36212 25461, release_year, 1097 9758, has_genre, 36212 21345, has_genre, 36212 21345, release_year, 1097 12047, has_genre, 36212 12047, release_year, 1097 20929, has_genre, 36212 20929, release_year, 1097 12447, has_genre, 36212 12447, release_year, 1097 32030, has_genre, 36212 32030, release_year, 1097 24434, has_genre, 36212 24434, release_year, 1097 28919, has_genre, 36212 28919, release_year, 1097 30906, has_genre, 36212 30906, release_year, 1097 38858, has_genre, 36212 38858, release_year, 1097 12883, has_genre, 36212 12883, release_year, 1097 2259, has_genre, 36212 2259, release_year, 1097 38108, has_genre, 36212 38108, release_year, 1097 39036, has_genre, 36212 39036, release_year, 1097 39883, has_genre, 36212 39883, release_year, 1097 22820, has_genre, 36212 22820, release_year, 1097 1411, has_genre, 36212 1411, has_tags, 36212 1411, release_year, 1097 10628, has_genre, 36212 10628, release_year, 1097 35264, has_genre, 36212 35264, release_year, 1097 11544, has_genre, 36212 11544, release_year, 1097 14956, has_genre, 36212 14956, release_year, 1097 39171, release_year, 1097 31862, has_genre, 36212 31862, release_year, 1097 27708, has_genre, 36212 27708, release_year, 1097 39834, has_genre, 36212 39834, release_year, 1097 Question: In what context are DANA FUCHS, THE CRAIGSLIST KILLER, and WHO KILLED BAMBI? connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DANA FUCHS", "THE CRAIGSLIST KILLER", "WHO KILLED BAMBI?" ], "valid_edges": [ [ "16 YEARS OF ALCOHOL", "has_genre", "DRAMA" ], [ "16 YEARS OF ALCOHOL", "release_year", "2003" ], [ "21 GRAMS", "has_genre", "DRAMA" ], [ "21 GRAMS", "has_tags", "DRAMA" ], [ "21 GRAMS", "release_year", "2003" ], [ "ACROSS THE UNIVERSE", "has_genre", "DRAMA" ], [ "ACROSS THE UNIVERSE", "starred_actors", "DANA FUCHS" ], [ "ALILA", "has_genre", "DRAMA" ], [ "ALILA", "release_year", "2003" ], [ "ALL THE REAL GIRLS", "has_genre", "DRAMA" ], [ "ALL THE REAL GIRLS", "release_year", "2003" ], [ "AMERICAN SPLENDOR", "has_genre", "DRAMA" ], [ "AMERICAN SPLENDOR", "release_year", "2003" ], [ "ANA AND THE OTHERS", "has_genre", "DRAMA" ], [ "ANA AND THE OTHERS", "release_year", "2003" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "release_year", "2003" ], [ "BAGHBAN", "has_genre", "DRAMA" ], [ "BAGHBAN", "release_year", "2003" ], [ "BEYOND BORDERS", "has_genre", "DRAMA" ], [ "BEYOND BORDERS", "release_year", "2003" ], [ "BIG FISH", "has_genre", "DRAMA" ], [ "BIG FISH", "release_year", "2003" ], [ "BRIGHT FUTURE", "has_genre", "DRAMA" ], [ "BRIGHT FUTURE", "release_year", "2003" ], [ "BRIGHT YOUNG THINGS", "has_genre", "DRAMA" ], [ "BRIGHT YOUNG THINGS", "release_year", "2003" ], [ "CARANDIRU", "has_genre", "DRAMA" ], [ "CARANDIRU", "release_year", "2003" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "2003" ], [ "COLD MOUNTAIN", "has_genre", "DRAMA" ], [ "COLD MOUNTAIN", "has_tags", "DRAMA" ], [ "COLD MOUNTAIN", "release_year", "2003" ], [ "DEAD END", "has_genre", "DRAMA" ], [ "DEAD END", "release_year", "2003" ], [ "DOGVILLE", "has_genre", "DRAMA" ], [ "DOGVILLE", "has_tags", "DRAMA" ], [ "DOGVILLE", "release_year", "2003" ], [ "DOPAMINE", "has_genre", "DRAMA" ], [ "DOPAMINE", "release_year", "2003" ], [ "EILA", "has_genre", "DRAMA" ], [ "EILA", "release_year", "2003" ], [ "ELEPHANT", "has_genre", "DRAMA" ], [ "ELEPHANT", "release_year", "2003" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "release_year", "2003" ], [ "FLYWHEEL", "has_genre", "DRAMA" ], [ "FLYWHEEL", "release_year", "2003" ], [ "GACY", "has_genre", "DRAMA" ], [ "GACY", "release_year", "2003" ], [ "GAMES OF LOVE AND CHANCE", "has_genre", "DRAMA" ], [ "GAMES OF LOVE AND CHANCE", "release_year", "2003" ], [ "GIRL WITH A PEARL EARRING", "has_genre", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "has_tags", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "release_year", "2003" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HOLES", "release_year", "2003" ], [ "HOPE SPRINGS", "has_genre", "DRAMA" ], [ "HOPE SPRINGS", "release_year", "2003" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "release_year", "2003" ], [ "I ACCUSE", "has_genre", "DRAMA" ], [ "I ACCUSE", "release_year", "2003" ], [ "I'LL SLEEP WHEN I'M DEAD", "has_genre", "DRAMA" ], [ "I'LL SLEEP WHEN I'M DEAD", "release_year", "2003" ], [ "IN THE CITY", "has_genre", "DRAMA" ], [ "IN THE CITY", "release_year", "2003" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "release_year", "2003" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "IT RUNS IN THE FAMILY", "release_year", "2003" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "release_year", "2003" ], [ "JAPANESE STORY", "has_genre", "DRAMA" ], [ "JAPANESE STORY", "release_year", "2003" ], [ "JONNY VANG", "has_genre", "DRAMA" ], [ "JONNY VANG", "release_year", "2003" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KAL HO NAA HO", "release_year", "2003" ], [ "LATTER DAYS", "has_genre", "DRAMA" ], [ "LATTER DAYS", "release_year", "2003" ], [ "LEVITY", "has_genre", "DRAMA" ], [ "LEVITY", "release_year", "2003" ], [ "LOST IN TRANSLATION", "has_genre", "DRAMA" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "release_year", "2003" ], [ "MAIN PREM KI DIWANI HOON", "has_genre", "DRAMA" ], [ "MAIN PREM KI DIWANI HOON", "release_year", "2003" ], [ "MASKED AND ANONYMOUS", "has_genre", "DRAMA" ], [ "MASKED AND ANONYMOUS", "release_year", "2003" ], [ "MATCHSTICK MEN", "has_genre", "DRAMA" ], [ "MATCHSTICK MEN", "has_tags", "DRAMA" ], [ "MATCHSTICK MEN", "release_year", "2003" ], [ "MONA LISA SMILE", "has_genre", "DRAMA" ], [ "MONA LISA SMILE", "release_year", "2003" ], [ "MONSTER", "has_genre", "DRAMA" ], [ "MONSTER", "has_tags", "DRAMA" ], [ "MONSTER", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "MYSTIC RIVER", "has_genre", "DRAMA" ], [ "MYSTIC RIVER", "has_tags", "DRAMA" ], [ "MYSTIC RIVER", "release_year", "2003" ], [ "NATHALIE...", "has_genre", "DRAMA" ], [ "NATHALIE...", "release_year", "2003" ], [ "NORMAL", "has_genre", "DRAMA" ], [ "NORMAL", "release_year", "2003" ], [ "OFF THE MAP", "has_genre", "DRAMA" ], [ "OFF THE MAP", "has_tags", "DRAMA" ], [ "OFF THE MAP", "release_year", "2003" ], [ "OPEN WATER", "has_genre", "DRAMA" ], [ "OPEN WATER", "release_year", "2003" ], [ "OSAMA", "has_genre", "DRAMA" ], [ "OSAMA", "release_year", "2003" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "release_year", "2003" ], [ "OUT OF THE ASHES", "has_genre", "DRAMA" ], [ "OUT OF THE ASHES", "release_year", "2003" ], [ "PARTY MONSTER", "has_genre", "DRAMA" ], [ "PARTY MONSTER", "release_year", "2003" ], [ "PIECES OF APRIL", "has_genre", "DRAMA" ], [ "PIECES OF APRIL", "release_year", "2003" ], [ "RECONSTRUCTION", "has_genre", "DRAMA" ], [ "RECONSTRUCTION", "release_year", "2003" ], [ "ROADS TO KOKTEBEL", "has_genre", "DRAMA" ], [ "ROADS TO KOKTEBEL", "release_year", "2003" ], [ "ROBOT STORIES", "has_genre", "DRAMA" ], [ "ROBOT STORIES", "release_year", "2003" ], [ "SAINTS AND SOLDIERS", "has_genre", "DRAMA" ], [ "SAINTS AND SOLDIERS", "release_year", "2003" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "release_year", "2003" ], [ "SECONDHAND LIONS", "has_genre", "DRAMA" ], [ "SECONDHAND LIONS", "release_year", "2003" ], [ "SHARA", "has_genre", "DRAMA" ], [ "SHARA", "release_year", "2003" ], [ "SHATTERED GLASS", "has_genre", "DRAMA" ], [ "SHATTERED GLASS", "release_year", "2003" ], [ "SOLDIER'S GIRL", "has_genre", "DRAMA" ], [ "SOLDIER'S GIRL", "release_year", "2003" ], [ "SPIN", "has_genre", "DRAMA" ], [ "SPIN", "release_year", "2003" ], [ "STRAYED", "has_genre", "DRAMA" ], [ "STRAYED", "release_year", "2003" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "release_year", "2003" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "release_year", "2003" ], [ "TAKE MY EYES", "has_genre", "DRAMA" ], [ "TAKE MY EYES", "release_year", "2003" ], [ "THE BARBARIAN INVASIONS", "has_genre", "DRAMA" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BATTLE OF SHAKER HEIGHTS", "has_genre", "DRAMA" ], [ "THE BATTLE OF SHAKER HEIGHTS", "release_year", "2003" ], [ "THE BIG EMPTY", "has_genre", "DRAMA" ], [ "THE BIG EMPTY", "release_year", "2003" ], [ "THE COOLER", "has_genre", "DRAMA" ], [ "THE COOLER", "release_year", "2003" ], [ "THE CRAIGSLIST KILLER", "has_genre", "DRAMA" ], [ "THE DREAMERS", "has_genre", "DRAMA" ], [ "THE DREAMERS", "release_year", "2003" ], [ "THE EVENT", "has_genre", "DRAMA" ], [ "THE EVENT", "release_year", "2003" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "DRAMA" ], [ "THE FIGHTING TEMPTATIONS", "release_year", "2003" ], [ "THE HUMAN STAIN", "has_genre", "DRAMA" ], [ "THE HUMAN STAIN", "release_year", "2003" ], [ "THE LOST PRINCE", "has_genre", "DRAMA" ], [ "THE LOST PRINCE", "release_year", "2003" ], [ "THE MUDGE BOY", "has_genre", "DRAMA" ], [ "THE MUDGE BOY", "release_year", "2003" ], [ "THE RETURN", "has_genre", "DRAMA" ], [ "THE RETURN", "release_year", "2003" ], [ "THE ROOM", "has_genre", "DRAMA" ], [ "THE ROOM", "release_year", "2003" ], [ "THE SHAPE OF THINGS", "has_genre", "DRAMA" ], [ "THE SHAPE OF THINGS", "release_year", "2003" ], [ "THE SLEEPING DICTIONARY", "has_genre", "DRAMA" ], [ "THE SLEEPING DICTIONARY", "release_year", "2003" ], [ "THE STATEMENT", "has_genre", "DRAMA" ], [ "THE STATEMENT", "release_year", "2003" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE STORY OF MARIE AND JULIEN", "has_genre", "DRAMA" ], [ "THE STORY OF MARIE AND JULIEN", "release_year", "2003" ], [ "THE STORY OF THE WEEPING CAMEL", "has_genre", "DRAMA" ], [ "THE STORY OF THE WEEPING CAMEL", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_genre", "DRAMA" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THIRTEEN", "has_genre", "DRAMA" ], [ "THIRTEEN", "has_tags", "DRAMA" ], [ "THIRTEEN", "release_year", "2003" ], [ "TIME OF THE WOLF", "has_genre", "DRAMA" ], [ "TIME OF THE WOLF", "release_year", "2003" ], [ "TWO DAYS", "has_genre", "DRAMA" ], [ "TWO DAYS", "release_year", "2003" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "release_year", "2003" ], [ "VOICES OF A DISTANT STAR", "has_genre", "DRAMA" ], [ "VOICES OF A DISTANT STAR", "release_year", "2003" ], [ "WHO KILLED BAMBI?", "release_year", "2003" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "2003" ], [ "WUTHERING HEIGHTS", "has_genre", "DRAMA" ], [ "WUTHERING HEIGHTS", "release_year", "2003" ], [ "YOUNG ADAM", "has_genre", "DRAMA" ], [ "YOUNG ADAM", "release_year", "2003" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 35046, FRANKLIN J. SCHAFFNER 28620, HIPPIES 13825, INSOMNIA 27037, NIKOLAJ FROBENIUS 27643, PLANET OF THE APES 26868, PSYCH-OUT 28729, REMAKE src, edge_attr, dst 13825, has_tags, 13825 13825, has_tags, 28729 13825, written_by, 27037 27643, directed_by, 35046 27643, has_tags, 35046 27643, has_tags, 28729 27643, release_year, 27810 26868, has_tags, 28620 26868, release_year, 27810 Question: For what reason are FRANKLIN J. SCHAFFNER, HIPPIES, and NIKOLAJ FROBENIUS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FRANKLIN J. SCHAFFNER", "HIPPIES", "NIKOLAJ FROBENIUS" ], "valid_edges": [ [ "INSOMNIA", "has_tags", "INSOMNIA" ], [ "INSOMNIA", "has_tags", "REMAKE" ], [ "INSOMNIA", "written_by", "NIKOLAJ FROBENIUS" ], [ "PLANET OF THE APES", "directed_by", "FRANKLIN J. SCHAFFNER" ], [ "PLANET OF THE APES", "has_tags", "FRANKLIN J. SCHAFFNER" ], [ "PLANET OF THE APES", "has_tags", "REMAKE" ], [ "PLANET OF THE APES", "release_year", "1968" ], [ "PSYCH-OUT", "has_tags", "HIPPIES" ], [ "PSYCH-OUT", "release_year", "1968" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 39964, 247°F 38344, A STREETCAR NAMED DESIRE 12981, ALL-STAR SUPERMAN 15253, COMIC BOOK 39571, DC COMICS 20538, DIANE LANE 24481, FRANCHISE 22361, JERRY SIEGEL 26324, JOHN ERMAN 9033, MAN OF STEEL 21474, MARLON BRANDO 2980, SUPERHERO 20948, SUPERMAN src, edge_attr, dst 39964, release_year, 29424 38344, directed_by, 26324 38344, has_tags, 21474 38344, starred_actors, 20538 38344, starred_actors, 21474 12981, has_tags, 20948 12981, release_year, 29424 9033, has_tags, 15253 9033, has_tags, 39571 9033, has_tags, 24481 9033, has_tags, 2980 9033, has_tags, 20948 9033, starred_actors, 20538 9033, written_by, 22361 20948, has_tags, 15253 20948, has_tags, 39571 20948, has_tags, 24481 20948, has_tags, 21474 20948, has_tags, 2980 20948, has_tags, 20948 20948, starred_actors, 21474 20948, written_by, 22361 Question: In what context are 247°F, JERRY SIEGEL, and JOHN ERMAN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "247°F", "JERRY SIEGEL", "JOHN ERMAN" ], "valid_edges": [ [ "247°F", "release_year", "2011" ], [ "A STREETCAR NAMED DESIRE", "directed_by", "JOHN ERMAN" ], [ "A STREETCAR NAMED DESIRE", "has_tags", "MARLON BRANDO" ], [ "A STREETCAR NAMED DESIRE", "starred_actors", "DIANE LANE" ], [ "A STREETCAR NAMED DESIRE", "starred_actors", "MARLON BRANDO" ], [ "ALL-STAR SUPERMAN", "has_tags", "SUPERMAN" ], [ "ALL-STAR SUPERMAN", "release_year", "2011" ], [ "MAN OF STEEL", "has_tags", "COMIC BOOK" ], [ "MAN OF STEEL", "has_tags", "DC COMICS" ], [ "MAN OF STEEL", "has_tags", "FRANCHISE" ], [ "MAN OF STEEL", "has_tags", "SUPERHERO" ], [ "MAN OF STEEL", "has_tags", "SUPERMAN" ], [ "MAN OF STEEL", "starred_actors", "DIANE LANE" ], [ "MAN OF STEEL", "written_by", "JERRY SIEGEL" ], [ "SUPERMAN", "has_tags", "COMIC BOOK" ], [ "SUPERMAN", "has_tags", "DC COMICS" ], [ "SUPERMAN", "has_tags", "FRANCHISE" ], [ "SUPERMAN", "has_tags", "MARLON BRANDO" ], [ "SUPERMAN", "has_tags", "SUPERHERO" ], [ "SUPERMAN", "has_tags", "SUPERMAN" ], [ "SUPERMAN", "starred_actors", "MARLON BRANDO" ], [ "SUPERMAN", "written_by", "JERRY SIEGEL" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1006, 1996 13408, 2001 39289, ACTION 32427, ALL THE QUEEN'S MEN 32015, BEHIND ENEMY LINES 28544, BLACK HAWK DOWN 23820, CARLA'S SONG 25285, COME AND SEE 10293, CONSPIRACY 4615, DARK BLUE WORLD 11363, DEFIANCE 16353, EDGES OF THE LORD 26690, ELLING 16930, ENEMY AT THE GATES 19194, ENIGMA 10315, FLAGS OF OUR FATHERS 15765, HAMSUN 33545, HART'S WAR 8842, INDEPENDENCE DAY 625, K-9 32792, LIBERTARIAS 5127, MOTHER NIGHT 16883, NORWEGIAN 17600, OFF LIMITS 234, PEARL HARBOR 34732, PLATOON 33042, PRISONER OF THE MOUNTAINS 17691, ROD DANIEL 35586, SAHARA 11124, STALINGRAD 10522, TAKING SIDES 13491, THE DEVIL'S BACKBONE 36390, THE ENGLISH PATIENT 27237, THE LONGEST DAY 23300, THE LOST BATTALION 16845, THE MAN WHO CAPTURED EICHMANN 3651, THE OTHER SIDE OF SUNDAY 12614, THE PIANIST 34479, TO END ALL WARS 3432, TRUE BLUE 6655, UPRISING 22214, WAR 23537, WHERE EAGLES DARE 11850, WILLEM DAFOE 24155, WORLD WAR II src, edge_attr, dst 32427, has_genre, 22214 32427, release_year, 13408 32015, has_genre, 22214 32015, has_tags, 22214 32015, release_year, 13408 28544, has_tags, 22214 28544, release_year, 13408 23820, has_genre, 22214 23820, release_year, 1006 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 10293, release_year, 13408 4615, has_genre, 22214 4615, has_tags, 24155 4615, release_year, 13408 11363, has_tags, 22214 11363, has_tags, 24155 16353, has_genre, 22214 16353, has_tags, 24155 16353, release_year, 13408 16353, starred_actors, 11850 26690, in_language, 16883 26690, release_year, 13408 16930, has_tags, 22214 16930, has_tags, 24155 16930, release_year, 13408 19194, has_tags, 24155 19194, release_year, 13408 10315, has_genre, 22214 10315, has_tags, 22214 10315, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 15765, in_language, 16883 15765, release_year, 1006 33545, has_genre, 22214 33545, has_tags, 24155 8842, has_tags, 22214 8842, release_year, 1006 625, directed_by, 17691 625, has_genre, 39289 625, has_tags, 17691 32792, has_genre, 22214 32792, release_year, 1006 5127, has_genre, 22214 5127, has_tags, 24155 5127, release_year, 1006 17600, has_genre, 22214 17600, starred_actors, 11850 234, has_tags, 22214 234, release_year, 13408 34732, has_genre, 22214 34732, has_tags, 22214 34732, has_tags, 11850 34732, starred_actors, 11850 33042, has_genre, 22214 33042, release_year, 1006 35586, has_genre, 22214 35586, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 10522, has_genre, 22214 10522, release_year, 13408 13491, has_tags, 22214 13491, release_year, 13408 36390, has_genre, 22214 36390, has_tags, 22214 36390, release_year, 1006 27237, has_tags, 22214 27237, has_tags, 24155 23300, has_genre, 22214 23300, release_year, 13408 16845, has_genre, 22214 16845, release_year, 1006 3651, in_language, 16883 3651, release_year, 1006 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 34479, has_genre, 22214 34479, has_tags, 22214 34479, release_year, 13408 3432, release_year, 1006 3432, release_year, 13408 6655, has_genre, 22214 6655, release_year, 13408 22214, has_genre, 39289 23537, has_genre, 22214 23537, has_tags, 24155 Question: For what reason are EDGES OF THE LORD, ROD DANIEL, and THE OTHER SIDE OF SUNDAY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EDGES OF THE LORD", "ROD DANIEL", "THE OTHER SIDE OF SUNDAY" ], "valid_edges": [ [ "ALL THE QUEEN'S MEN", "has_genre", "WAR" ], [ "ALL THE QUEEN'S MEN", "release_year", "2001" ], [ "BEHIND ENEMY LINES", "has_genre", "WAR" ], [ "BEHIND ENEMY LINES", "has_tags", "WAR" ], [ "BEHIND ENEMY LINES", "release_year", "2001" ], [ "BLACK HAWK DOWN", "has_tags", "WAR" ], [ "BLACK HAWK DOWN", "release_year", "2001" ], [ "CARLA'S SONG", "has_genre", "WAR" ], [ "CARLA'S SONG", "release_year", "1996" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "release_year", "2001" ], [ "DARK BLUE WORLD", "has_genre", "WAR" ], [ "DARK BLUE WORLD", "has_tags", "WORLD WAR II" ], [ "DARK BLUE WORLD", "release_year", "2001" ], [ "DEFIANCE", "has_tags", "WAR" ], [ "DEFIANCE", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "has_genre", "WAR" ], [ "EDGES OF THE LORD", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "release_year", "2001" ], [ "EDGES OF THE LORD", "starred_actors", "WILLEM DAFOE" ], [ "ELLING", "in_language", "NORWEGIAN" ], [ "ELLING", "release_year", "2001" ], [ "ENEMY AT THE GATES", "has_tags", "WAR" ], [ "ENEMY AT THE GATES", "has_tags", "WORLD WAR II" ], [ "ENEMY AT THE GATES", "release_year", "2001" ], [ "ENIGMA", "has_tags", "WORLD WAR II" ], [ "ENIGMA", "release_year", "2001" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "in_language", "NORWEGIAN" ], [ "HAMSUN", "release_year", "1996" ], [ "HART'S WAR", "has_genre", "WAR" ], [ "HART'S WAR", "has_tags", "WORLD WAR II" ], [ "INDEPENDENCE DAY", "has_tags", "WAR" ], [ "INDEPENDENCE DAY", "release_year", "1996" ], [ "K-9", "directed_by", "ROD DANIEL" ], [ "K-9", "has_genre", "ACTION" ], [ "K-9", "has_tags", "ROD DANIEL" ], [ "LIBERTARIAS", "has_genre", "WAR" ], [ "LIBERTARIAS", "release_year", "1996" ], [ "MOTHER NIGHT", "has_genre", "WAR" ], [ "MOTHER NIGHT", "has_tags", "WORLD WAR II" ], [ "MOTHER NIGHT", "release_year", "1996" ], [ "OFF LIMITS", "has_genre", "WAR" ], [ "OFF LIMITS", "starred_actors", "WILLEM DAFOE" ], [ "PEARL HARBOR", "has_tags", "WAR" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PLATOON", "has_genre", "WAR" ], [ "PLATOON", "has_tags", "WAR" ], [ "PLATOON", "has_tags", "WILLEM DAFOE" ], [ "PLATOON", "starred_actors", "WILLEM DAFOE" ], [ "PRISONER OF THE MOUNTAINS", "has_genre", "WAR" ], [ "PRISONER OF THE MOUNTAINS", "release_year", "1996" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "TAKING SIDES", "has_genre", "WAR" ], [ "TAKING SIDES", "release_year", "2001" ], [ "THE DEVIL'S BACKBONE", "has_tags", "WAR" ], [ "THE DEVIL'S BACKBONE", "release_year", "2001" ], [ "THE ENGLISH PATIENT", "has_genre", "WAR" ], [ "THE ENGLISH PATIENT", "has_tags", "WAR" ], [ "THE ENGLISH PATIENT", "release_year", "1996" ], [ "THE LONGEST DAY", "has_tags", "WAR" ], [ "THE LONGEST DAY", "has_tags", "WORLD WAR II" ], [ "THE LOST BATTALION", "has_genre", "WAR" ], [ "THE LOST BATTALION", "release_year", "2001" ], [ "THE MAN WHO CAPTURED EICHMANN", "has_genre", "WAR" ], [ "THE MAN WHO CAPTURED EICHMANN", "release_year", "1996" ], [ "THE OTHER SIDE OF SUNDAY", "in_language", "NORWEGIAN" ], [ "THE OTHER SIDE OF SUNDAY", "release_year", "1996" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "TO END ALL WARS", "has_genre", "WAR" ], [ "TO END ALL WARS", "has_tags", "WAR" ], [ "TO END ALL WARS", "release_year", "2001" ], [ "TRUE BLUE", "release_year", "1996" ], [ "TRUE BLUE", "release_year", "2001" ], [ "UPRISING", "has_genre", "WAR" ], [ "UPRISING", "release_year", "2001" ], [ "WAR", "has_genre", "ACTION" ], [ "WHERE EAGLES DARE", "has_genre", "WAR" ], [ "WHERE EAGLES DARE", "has_tags", "WORLD WAR II" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 32287, CARNIVAL OF SOULS 34298, CHARLES GEORGE HILDEBRANDT 28333, DAVID PROWSE 19365, FRANKENSTEIN AND THE MONSTER FROM HELL 5870, HORROR 9515, RING OF TERROR 26202, TALES OF TERROR 17361, THE BRAIN THAT WOULDN'T DIE 5773, THE DEADLY SPAWN 17058, THE HORRIBLE DR. HICHCOCK src, edge_attr, dst 32287, has_genre, 5870 32287, release_year, 3863 19365, has_genre, 5870 19365, starred_actors, 28333 9515, has_genre, 5870 9515, release_year, 3863 26202, has_genre, 5870 26202, release_year, 3863 17361, has_genre, 5870 17361, release_year, 3863 5773, has_genre, 5870 5773, starred_actors, 34298 17058, has_genre, 5870 17058, release_year, 3863 Question: How are 1962, CHARLES GEORGE HILDEBRANDT, and DAVID PROWSE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "1962", "CHARLES GEORGE HILDEBRANDT", "DAVID PROWSE" ], "valid_edges": [ [ "CARNIVAL OF SOULS", "has_genre", "HORROR" ], [ "CARNIVAL OF SOULS", "release_year", "1962" ], [ "FRANKENSTEIN AND THE MONSTER FROM HELL", "has_genre", "HORROR" ], [ "FRANKENSTEIN AND THE MONSTER FROM HELL", "starred_actors", "DAVID PROWSE" ], [ "RING OF TERROR", "has_genre", "HORROR" ], [ "RING OF TERROR", "release_year", "1962" ], [ "TALES OF TERROR", "has_genre", "HORROR" ], [ "TALES OF TERROR", "release_year", "1962" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "release_year", "1962" ], [ "THE DEADLY SPAWN", "has_genre", "HORROR" ], [ "THE DEADLY SPAWN", "starred_actors", "CHARLES GEORGE HILDEBRANDT" ], [ "THE HORRIBLE DR. HICHCOCK", "has_genre", "HORROR" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 26277, A FEW GOOD MEN 15184, AARON SORKIN 25843, ALEX ZAMM 37558, ALICE MUNRO 21372, BEVERLY HILLS CHIHUAHUA 2 30463, COMEDY 4725, COURT 9192, COURTROOM 36212, DRAMA 26714, EDGE OF MADNESS 11565, GOOD 30221, LAW 33307, LAWYER 23580, LAWYERS 17559, LEGALLY BLONDE 28476, MURDER 21919, MY COUSIN VINNY 15607, THE LITTLE RASCALS SAVE THE DAY 5106, THE SOCIAL NETWORK src, edge_attr, dst 26277, has_genre, 36212 26277, has_imdb_rating, 11565 26277, has_tags, 15184 26277, has_tags, 4725 26277, has_tags, 9192 26277, has_tags, 36212 26277, has_tags, 30221 26277, has_tags, 33307 26277, has_tags, 23580 26277, has_tags, 28476 26277, release_year, 24818 26277, written_by, 15184 21372, directed_by, 25843 21372, has_genre, 30463 26714, has_genre, 36212 26714, written_by, 37558 17559, has_genre, 30463 17559, has_imdb_rating, 11565 17559, has_tags, 30463 17559, has_tags, 30221 17559, has_tags, 28476 21919, has_genre, 30463 21919, has_tags, 30463 21919, has_tags, 4725 21919, has_tags, 9192 21919, has_tags, 30221 21919, has_tags, 33307 21919, has_tags, 23580 21919, has_tags, 28476 21919, release_year, 24818 15607, directed_by, 25843 15607, has_genre, 30463 15607, written_by, 25843 5106, has_genre, 36212 5106, has_tags, 15184 5106, has_tags, 30221 5106, written_by, 15184 Question: In what context are ALEX ZAMM, ALICE MUNRO, and LAW connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ALEX ZAMM", "ALICE MUNRO", "LAW" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_imdb_rating", "GOOD" ], [ "A FEW GOOD MEN", "has_tags", "AARON SORKIN" ], [ "A FEW GOOD MEN", "has_tags", "COURT" ], [ "A FEW GOOD MEN", "has_tags", "COURTROOM" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "LAW" ], [ "A FEW GOOD MEN", "has_tags", "LAWYER" ], [ "A FEW GOOD MEN", "has_tags", "LAWYERS" ], [ "A FEW GOOD MEN", "has_tags", "MURDER" ], [ "A FEW GOOD MEN", "release_year", "1992" ], [ "A FEW GOOD MEN", "written_by", "AARON SORKIN" ], [ "BEVERLY HILLS CHIHUAHUA 2", "directed_by", "ALEX ZAMM" ], [ "BEVERLY HILLS CHIHUAHUA 2", "has_genre", "COMEDY" ], [ "EDGE OF MADNESS", "has_genre", "DRAMA" ], [ "EDGE OF MADNESS", "written_by", "ALICE MUNRO" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEGALLY BLONDE", "has_tags", "LAW" ], [ "LEGALLY BLONDE", "has_tags", "MURDER" ], [ "MY COUSIN VINNY", "has_genre", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COURT" ], [ "MY COUSIN VINNY", "has_tags", "COURTROOM" ], [ "MY COUSIN VINNY", "has_tags", "LAW" ], [ "MY COUSIN VINNY", "has_tags", "LAWYER" ], [ "MY COUSIN VINNY", "has_tags", "LAWYERS" ], [ "MY COUSIN VINNY", "has_tags", "MURDER" ], [ "MY COUSIN VINNY", "release_year", "1992" ], [ "THE LITTLE RASCALS SAVE THE DAY", "directed_by", "ALEX ZAMM" ], [ "THE LITTLE RASCALS SAVE THE DAY", "has_genre", "COMEDY" ], [ "THE LITTLE RASCALS SAVE THE DAY", "written_by", "ALEX ZAMM" ], [ "THE SOCIAL NETWORK", "has_genre", "DRAMA" ], [ "THE SOCIAL NETWORK", "has_tags", "AARON SORKIN" ], [ "THE SOCIAL NETWORK", "has_tags", "LAW" ], [ "THE SOCIAL NETWORK", "written_by", "AARON SORKIN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 11079, BORDERTOWN 8432, CONCUSSION 36212, DRAMA 18716, JULIA DEVILLERS 13401, READ IT AND WEEP 34632, STACIE PASSON 15289, WALLACE SMITH src, edge_attr, dst 11079, has_genre, 36212 11079, release_year, 35845 11079, written_by, 15289 8432, directed_by, 34632 8432, has_genre, 36212 8432, written_by, 34632 13401, release_year, 35845 13401, written_by, 18716 Question: In what context are JULIA DEVILLERS, STACIE PASSON, and WALLACE SMITH connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JULIA DEVILLERS", "STACIE PASSON", "WALLACE SMITH" ], "valid_edges": [ [ "BORDERTOWN", "has_genre", "DRAMA" ], [ "BORDERTOWN", "release_year", "2006" ], [ "BORDERTOWN", "written_by", "WALLACE SMITH" ], [ "CONCUSSION", "directed_by", "STACIE PASSON" ], [ "CONCUSSION", "has_genre", "DRAMA" ], [ "CONCUSSION", "written_by", "STACIE PASSON" ], [ "READ IT AND WEEP", "release_year", "2006" ], [ "READ IT AND WEEP", "written_by", "JULIA DEVILLERS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 9538, DON SIEGEL 30217, HELL IS FOR HEROES 35995, MAXIMILIAN SCHELL 18454, MY GEISHA 33101, SHIRLEY MACLAINE 18670, THE CHOSEN 17058, THE HORRIBLE DR. HICHCOCK 13523, THE RELUCTANT SAINT 7843, TWO FOR THE SEESAW 37550, TWO MULES FOR SISTER SARA src, edge_attr, dst 30217, directed_by, 9538 30217, has_tags, 9538 30217, release_year, 3863 18454, release_year, 3863 18454, starred_actors, 33101 18670, starred_actors, 35995 17058, release_year, 3863 13523, has_tags, 35995 13523, release_year, 3863 13523, starred_actors, 35995 7843, has_tags, 33101 7843, release_year, 3863 7843, starred_actors, 33101 37550, directed_by, 9538 37550, has_tags, 9538 37550, starred_actors, 33101 Question: For what reason are THE CHOSEN, THE HORRIBLE DR. HICHCOCK, and TWO MULES FOR SISTER SARA associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "THE CHOSEN", "THE HORRIBLE DR. HICHCOCK", "TWO MULES FOR SISTER SARA" ], "valid_edges": [ [ "HELL IS FOR HEROES", "directed_by", "DON SIEGEL" ], [ "HELL IS FOR HEROES", "has_tags", "DON SIEGEL" ], [ "HELL IS FOR HEROES", "release_year", "1962" ], [ "MY GEISHA", "release_year", "1962" ], [ "MY GEISHA", "starred_actors", "SHIRLEY MACLAINE" ], [ "THE CHOSEN", "starred_actors", "MAXIMILIAN SCHELL" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ], [ "THE RELUCTANT SAINT", "has_tags", "MAXIMILIAN SCHELL" ], [ "THE RELUCTANT SAINT", "release_year", "1962" ], [ "THE RELUCTANT SAINT", "starred_actors", "MAXIMILIAN SCHELL" ], [ "TWO FOR THE SEESAW", "has_tags", "SHIRLEY MACLAINE" ], [ "TWO FOR THE SEESAW", "release_year", "1962" ], [ "TWO FOR THE SEESAW", "starred_actors", "SHIRLEY MACLAINE" ], [ "TWO MULES FOR SISTER SARA", "directed_by", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "has_tags", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "starred_actors", "SHIRLEY MACLAINE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35798, 2010 30463, COMEDY 36212, DRAMA 4838, EAT PRAY LOVE 4090, LOUIS C.K 35134, MERCEDES MCNAB 5766, RUNNING WITH SCISSORS 31492, RYAN MURPHY 35470, THE NORMAL HEART 33138, THIRST 8012, TOMORROW NIGHT src, edge_attr, dst 4838, directed_by, 31492 4838, has_genre, 36212 4838, release_year, 35798 4838, written_by, 31492 5766, directed_by, 31492 5766, has_genre, 30463 5766, has_genre, 36212 5766, written_by, 31492 35470, directed_by, 31492 35470, has_genre, 36212 33138, has_genre, 36212 33138, release_year, 35798 33138, starred_actors, 35134 8012, has_genre, 30463 8012, has_tags, 30463 8012, has_tags, 4090 Question: For what reason are LOUIS C.K, MERCEDES MCNAB, and RYAN MURPHY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LOUIS C.K", "MERCEDES MCNAB", "RYAN MURPHY" ], "valid_edges": [ [ "EAT PRAY LOVE", "directed_by", "RYAN MURPHY" ], [ "EAT PRAY LOVE", "has_genre", "DRAMA" ], [ "EAT PRAY LOVE", "release_year", "2010" ], [ "EAT PRAY LOVE", "written_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "directed_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "has_genre", "COMEDY" ], [ "RUNNING WITH SCISSORS", "has_genre", "DRAMA" ], [ "RUNNING WITH SCISSORS", "written_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "directed_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "has_genre", "DRAMA" ], [ "THIRST", "has_genre", "DRAMA" ], [ "THIRST", "release_year", "2010" ], [ "THIRST", "starred_actors", "MERCEDES MCNAB" ], [ "TOMORROW NIGHT", "has_genre", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "LOUIS C.K" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 23439, +1 1421, 2013 35522, A COMMON MAN 18644, A RESURRECTION 20629, A SINGLE SHOT 36431, ASSAULT ON WALL STREET 21421, BIG BAD WOLVES 16664, BLOOD DIAMOND 7483, BLOOD TIES 11338, BLUE RUIN 39346, BORGMAN 38211, BROKEN CITY 39398, CAPTAIN PHILLIPS 25216, COHERENCE 25131, COLD COMES THE NIGHT 38680, COMPULSION 40079, CONTRACTED 22349, CRAWLSPACE 9647, D-DAY 33372, DARK SKIES 9641, DIRTY PRETTY THINGS 8823, DRISHYAM 3047, ENEMY 8491, ESCAPE PLAN 2577, EVIDENCE 40134, FELONY 5287, FROZEN 22832, GETAWAY 35657, GLORIA 12776, GRAND PIANO 31326, GRAVITY 14366, HAUNTER 33891, HORNS 33776, HOURS 13177, HOUSE HUNTING 571, IN SECRET 32370, JOY BRYANT 378, JOY RIDE 17358, LAST PASSENGER 17319, LONDON 26190, MAGIC MAGIC 33165, MISCHIEF NIGHT 11517, MISSIONARY 21188, MR. JONES 25264, NOTES ON A SCANDAL 26943, NOW YOU SEE ME 12443, ODD THOMAS 32954, OLDBOY 536, OUT OF THE FURNACE 8352, PARANOIA 32279, PARKER 38966, PAUL WALKER 29074, PENTHOUSE NORTH 4066, PIONEER 13471, PRISONERS 10085, R. LANCE HILL 22512, RUNNER RUNNER 6745, SCENIC ROUTE 38583, SHIFTY 2404, SIDE EFFECTS 27160, SOLO 33956, SOUTH AFRICA 2485, SPARKS 26621, STAY 30357, STOKER 16450, STRANGER BY THE LAKE 34509, SWEETWATER 28652, TABLE NO. 21 16900, THE CALL 29799, THE CANYONS 31128, THE COUNSELOR 38107, THE EAST 2878, THE EVIL THAT MEN DO 35937, THE FIFTH ESTATE 36893, THE GIRL ON THE TRAIN 13613, THE LAZARUS PROJECT 8137, THE MACHINE 31276, THE NUMBERS STATION 27098, THE PRESTIGE 6427, THE PURGE 13106, THE SACRAMENT 32390, THE SKULLS 24811, THRILLER 38582, TOM AT THE FARM 27476, TORMENT 15230, TRANCE 5603, VEHICLE 19 26489, WELCOME TO THE PUNCH 32403, WHITE HOUSE DOWN src, edge_attr, dst 23439, has_genre, 24811 23439, release_year, 1421 35522, has_genre, 24811 35522, release_year, 1421 18644, has_genre, 24811 18644, release_year, 1421 20629, has_genre, 24811 20629, release_year, 1421 36431, has_genre, 24811 36431, release_year, 1421 21421, has_genre, 24811 21421, release_year, 1421 16664, has_genre, 24811 16664, has_tags, 33956 7483, has_genre, 24811 7483, release_year, 1421 11338, has_genre, 24811 11338, release_year, 1421 39346, has_genre, 24811 39346, release_year, 1421 38211, has_genre, 24811 38211, release_year, 1421 39398, has_genre, 24811 39398, release_year, 1421 25216, has_genre, 24811 25216, release_year, 1421 25131, has_genre, 24811 25131, release_year, 1421 38680, has_genre, 24811 38680, release_year, 1421 40079, has_genre, 24811 40079, release_year, 1421 22349, has_genre, 24811 22349, release_year, 1421 9647, has_genre, 24811 9647, release_year, 1421 33372, has_genre, 24811 33372, release_year, 1421 9641, has_genre, 24811 9641, has_tags, 17319 8823, has_genre, 24811 8823, release_year, 1421 3047, has_genre, 24811 3047, release_year, 1421 8491, has_genre, 24811 8491, release_year, 1421 2577, has_genre, 24811 2577, release_year, 1421 40134, has_genre, 24811 40134, release_year, 1421 5287, has_genre, 24811 5287, release_year, 1421 22832, has_genre, 24811 22832, release_year, 1421 35657, has_genre, 24811 35657, release_year, 1421 12776, has_genre, 24811 12776, release_year, 1421 31326, has_genre, 24811 31326, release_year, 1421 14366, has_genre, 24811 14366, release_year, 1421 33891, has_genre, 24811 33891, release_year, 1421 33776, has_genre, 24811 33776, release_year, 1421 33776, starred_actors, 38966 13177, has_genre, 24811 13177, release_year, 1421 571, has_genre, 24811 571, release_year, 1421 378, has_genre, 24811 378, has_tags, 38966 378, starred_actors, 38966 17358, has_genre, 24811 17358, release_year, 1421 17319, starred_actors, 32370 26190, has_genre, 24811 26190, release_year, 1421 33165, has_genre, 24811 33165, release_year, 1421 11517, has_genre, 24811 11517, release_year, 1421 21188, has_genre, 24811 21188, release_year, 1421 25264, has_genre, 24811 25264, has_tags, 17319 26943, has_genre, 24811 26943, release_year, 1421 12443, has_genre, 24811 12443, release_year, 1421 32954, has_genre, 24811 32954, release_year, 1421 536, has_genre, 24811 536, release_year, 1421 8352, has_genre, 24811 8352, release_year, 1421 32279, has_genre, 24811 32279, release_year, 1421 29074, has_genre, 24811 29074, release_year, 1421 4066, has_genre, 24811 4066, release_year, 1421 13471, has_tags, 24811 13471, release_year, 1421 22512, has_genre, 24811 22512, has_tags, 24811 22512, release_year, 1421 6745, has_genre, 24811 6745, release_year, 1421 38583, has_genre, 24811 38583, has_tags, 17319 2404, has_genre, 24811 2404, release_year, 1421 27160, has_genre, 24811 27160, release_year, 1421 2485, has_genre, 24811 2485, release_year, 1421 26621, has_genre, 24811 26621, release_year, 1421 30357, has_genre, 24811 30357, has_tags, 24811 30357, release_year, 1421 16450, has_genre, 24811 16450, release_year, 1421 34509, has_genre, 24811 34509, release_year, 1421 28652, has_genre, 24811 28652, release_year, 1421 16900, has_genre, 24811 16900, release_year, 1421 29799, has_genre, 24811 29799, release_year, 1421 31128, has_genre, 24811 31128, release_year, 1421 38107, has_genre, 24811 38107, release_year, 1421 2878, has_genre, 24811 2878, written_by, 10085 35937, has_genre, 24811 35937, release_year, 1421 36893, has_genre, 24811 36893, release_year, 1421 13613, has_genre, 24811 13613, starred_actors, 38966 8137, has_genre, 24811 8137, release_year, 1421 31276, has_genre, 24811 31276, release_year, 1421 27098, has_genre, 24811 27098, has_tags, 17319 27098, has_tags, 24811 6427, has_genre, 24811 6427, release_year, 1421 13106, has_genre, 24811 13106, release_year, 1421 32390, has_genre, 24811 32390, starred_actors, 38966 38582, has_genre, 24811 38582, release_year, 1421 27476, has_genre, 24811 27476, release_year, 1421 15230, has_tags, 24811 15230, release_year, 1421 5603, has_genre, 24811 5603, has_tags, 33956 5603, release_year, 1421 5603, starred_actors, 38966 26489, has_genre, 24811 26489, release_year, 1421 32403, has_genre, 24811 32403, has_tags, 24811 32403, release_year, 1421 Question: How are JOY BRYANT, R. LANCE HILL, and VEHICLE 19 related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOY BRYANT", "R. LANCE HILL", "VEHICLE 19" ], "valid_edges": [ [ "+1", "has_genre", "THRILLER" ], [ "+1", "release_year", "2013" ], [ "A COMMON MAN", "has_genre", "THRILLER" ], [ "A COMMON MAN", "release_year", "2013" ], [ "A RESURRECTION", "has_genre", "THRILLER" ], [ "A RESURRECTION", "release_year", "2013" ], [ "A SINGLE SHOT", "has_genre", "THRILLER" ], [ "A SINGLE SHOT", "release_year", "2013" ], [ "ASSAULT ON WALL STREET", "has_genre", "THRILLER" ], [ "ASSAULT ON WALL STREET", "release_year", "2013" ], [ "BIG BAD WOLVES", "has_genre", "THRILLER" ], [ "BIG BAD WOLVES", "release_year", "2013" ], [ "BLOOD DIAMOND", "has_genre", "THRILLER" ], [ "BLOOD DIAMOND", "has_tags", "SOUTH AFRICA" ], [ "BLOOD TIES", "has_genre", "THRILLER" ], [ "BLOOD TIES", "release_year", "2013" ], [ "BLUE RUIN", "has_genre", "THRILLER" ], [ "BLUE RUIN", "release_year", "2013" ], [ "BORGMAN", "has_genre", "THRILLER" ], [ "BORGMAN", "release_year", "2013" ], [ "BROKEN CITY", "has_genre", "THRILLER" ], [ "BROKEN CITY", "release_year", "2013" ], [ "CAPTAIN PHILLIPS", "has_genre", "THRILLER" ], [ "CAPTAIN PHILLIPS", "release_year", "2013" ], [ "COHERENCE", "has_genre", "THRILLER" ], [ "COHERENCE", "release_year", "2013" ], [ "COLD COMES THE NIGHT", "has_genre", "THRILLER" ], [ "COLD COMES THE NIGHT", "release_year", "2013" ], [ "COMPULSION", "has_genre", "THRILLER" ], [ "COMPULSION", "release_year", "2013" ], [ "CONTRACTED", "has_genre", "THRILLER" ], [ "CONTRACTED", "release_year", "2013" ], [ "CRAWLSPACE", "has_genre", "THRILLER" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "D-DAY", "has_genre", "THRILLER" ], [ "D-DAY", "release_year", "2013" ], [ "DARK SKIES", "has_genre", "THRILLER" ], [ "DARK SKIES", "release_year", "2013" ], [ "DIRTY PRETTY THINGS", "has_genre", "THRILLER" ], [ "DIRTY PRETTY THINGS", "has_tags", "LONDON" ], [ "DRISHYAM", "has_genre", "THRILLER" ], [ "DRISHYAM", "release_year", "2013" ], [ "ENEMY", "has_genre", "THRILLER" ], [ "ENEMY", "release_year", "2013" ], [ "ESCAPE PLAN", "has_genre", "THRILLER" ], [ "ESCAPE PLAN", "release_year", "2013" ], [ "EVIDENCE", "has_genre", "THRILLER" ], [ "EVIDENCE", "release_year", "2013" ], [ "FELONY", "has_genre", "THRILLER" ], [ "FELONY", "release_year", "2013" ], [ "FROZEN", "has_genre", "THRILLER" ], [ "FROZEN", "release_year", "2013" ], [ "GETAWAY", "has_genre", "THRILLER" ], [ "GETAWAY", "release_year", "2013" ], [ "GLORIA", "has_genre", "THRILLER" ], [ "GLORIA", "release_year", "2013" ], [ "GRAND PIANO", "has_genre", "THRILLER" ], [ "GRAND PIANO", "release_year", "2013" ], [ "GRAVITY", "has_genre", "THRILLER" ], [ "GRAVITY", "release_year", "2013" ], [ "HAUNTER", "has_genre", "THRILLER" ], [ "HAUNTER", "release_year", "2013" ], [ "HORNS", "has_genre", "THRILLER" ], [ "HORNS", "release_year", "2013" ], [ "HOURS", "has_genre", "THRILLER" ], [ "HOURS", "release_year", "2013" ], [ "HOURS", "starred_actors", "PAUL WALKER" ], [ "HOUSE HUNTING", "has_genre", "THRILLER" ], [ "HOUSE HUNTING", "release_year", "2013" ], [ "IN SECRET", "has_genre", "THRILLER" ], [ "IN SECRET", "release_year", "2013" ], [ "JOY RIDE", "has_genre", "THRILLER" ], [ "JOY RIDE", "has_tags", "PAUL WALKER" ], [ "JOY RIDE", "starred_actors", "PAUL WALKER" ], [ "LAST PASSENGER", "has_genre", "THRILLER" ], [ "LAST PASSENGER", "release_year", "2013" ], [ "LONDON", "starred_actors", "JOY BRYANT" ], [ "MAGIC MAGIC", "has_genre", "THRILLER" ], [ "MAGIC MAGIC", "release_year", "2013" ], [ "MISCHIEF NIGHT", "has_genre", "THRILLER" ], [ "MISCHIEF NIGHT", "release_year", "2013" ], [ "MISSIONARY", "has_genre", "THRILLER" ], [ "MISSIONARY", "release_year", "2013" ], [ "MR. JONES", "has_genre", "THRILLER" ], [ "MR. JONES", "release_year", "2013" ], [ "NOTES ON A SCANDAL", "has_genre", "THRILLER" ], [ "NOTES ON A SCANDAL", "has_tags", "LONDON" ], [ "NOW YOU SEE ME", "has_genre", "THRILLER" ], [ "NOW YOU SEE ME", "release_year", "2013" ], [ "ODD THOMAS", "has_genre", "THRILLER" ], [ "ODD THOMAS", "release_year", "2013" ], [ "OLDBOY", "has_genre", "THRILLER" ], [ "OLDBOY", "release_year", "2013" ], [ "OUT OF THE FURNACE", "has_genre", "THRILLER" ], [ "OUT OF THE FURNACE", "release_year", "2013" ], [ "PARANOIA", "has_genre", "THRILLER" ], [ "PARANOIA", "release_year", "2013" ], [ "PARKER", "has_genre", "THRILLER" ], [ "PARKER", "release_year", "2013" ], [ "PENTHOUSE NORTH", "has_genre", "THRILLER" ], [ "PENTHOUSE NORTH", "release_year", "2013" ], [ "PIONEER", "has_genre", "THRILLER" ], [ "PIONEER", "release_year", "2013" ], [ "PRISONERS", "has_tags", "THRILLER" ], [ "PRISONERS", "release_year", "2013" ], [ "RUNNER RUNNER", "has_genre", "THRILLER" ], [ "RUNNER RUNNER", "has_tags", "THRILLER" ], [ "RUNNER RUNNER", "release_year", "2013" ], [ "SCENIC ROUTE", "has_genre", "THRILLER" ], [ "SCENIC ROUTE", "release_year", "2013" ], [ "SHIFTY", "has_genre", "THRILLER" ], [ "SHIFTY", "has_tags", "LONDON" ], [ "SIDE EFFECTS", "has_genre", "THRILLER" ], [ "SIDE EFFECTS", "release_year", "2013" ], [ "SOLO", "has_genre", "THRILLER" ], [ "SOLO", "release_year", "2013" ], [ "SPARKS", "has_genre", "THRILLER" ], [ "SPARKS", "release_year", "2013" ], [ "STAY", "has_genre", "THRILLER" ], [ "STAY", "release_year", "2013" ], [ "STOKER", "has_genre", "THRILLER" ], [ "STOKER", "has_tags", "THRILLER" ], [ "STOKER", "release_year", "2013" ], [ "STRANGER BY THE LAKE", "has_genre", "THRILLER" ], [ "STRANGER BY THE LAKE", "release_year", "2013" ], [ "SWEETWATER", "has_genre", "THRILLER" ], [ "SWEETWATER", "release_year", "2013" ], [ "TABLE NO. 21", "has_genre", "THRILLER" ], [ "TABLE NO. 21", "release_year", "2013" ], [ "THE CALL", "has_genre", "THRILLER" ], [ "THE CALL", "release_year", "2013" ], [ "THE CANYONS", "has_genre", "THRILLER" ], [ "THE CANYONS", "release_year", "2013" ], [ "THE COUNSELOR", "has_genre", "THRILLER" ], [ "THE COUNSELOR", "release_year", "2013" ], [ "THE EAST", "has_genre", "THRILLER" ], [ "THE EAST", "release_year", "2013" ], [ "THE EVIL THAT MEN DO", "has_genre", "THRILLER" ], [ "THE EVIL THAT MEN DO", "written_by", "R. LANCE HILL" ], [ "THE FIFTH ESTATE", "has_genre", "THRILLER" ], [ "THE FIFTH ESTATE", "release_year", "2013" ], [ "THE GIRL ON THE TRAIN", "has_genre", "THRILLER" ], [ "THE GIRL ON THE TRAIN", "release_year", "2013" ], [ "THE LAZARUS PROJECT", "has_genre", "THRILLER" ], [ "THE LAZARUS PROJECT", "starred_actors", "PAUL WALKER" ], [ "THE MACHINE", "has_genre", "THRILLER" ], [ "THE MACHINE", "release_year", "2013" ], [ "THE NUMBERS STATION", "has_genre", "THRILLER" ], [ "THE NUMBERS STATION", "release_year", "2013" ], [ "THE PRESTIGE", "has_genre", "THRILLER" ], [ "THE PRESTIGE", "has_tags", "LONDON" ], [ "THE PRESTIGE", "has_tags", "THRILLER" ], [ "THE PURGE", "has_genre", "THRILLER" ], [ "THE PURGE", "release_year", "2013" ], [ "THE SACRAMENT", "has_genre", "THRILLER" ], [ "THE SACRAMENT", "release_year", "2013" ], [ "THE SKULLS", "has_genre", "THRILLER" ], [ "THE SKULLS", "starred_actors", "PAUL WALKER" ], [ "TOM AT THE FARM", "has_genre", "THRILLER" ], [ "TOM AT THE FARM", "release_year", "2013" ], [ "TORMENT", "has_genre", "THRILLER" ], [ "TORMENT", "release_year", "2013" ], [ "TRANCE", "has_tags", "THRILLER" ], [ "TRANCE", "release_year", "2013" ], [ "VEHICLE 19", "has_genre", "THRILLER" ], [ "VEHICLE 19", "has_tags", "SOUTH AFRICA" ], [ "VEHICLE 19", "release_year", "2013" ], [ "VEHICLE 19", "starred_actors", "PAUL WALKER" ], [ "WELCOME TO THE PUNCH", "has_genre", "THRILLER" ], [ "WELCOME TO THE PUNCH", "release_year", "2013" ], [ "WHITE HOUSE DOWN", "has_genre", "THRILLER" ], [ "WHITE HOUSE DOWN", "has_tags", "THRILLER" ], [ "WHITE HOUSE DOWN", "release_year", "2013" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 33387, CITY OF GOD 32183, DOUGLAS SILVA 15436, EPIC 11565, GOOD 26124, GOOD NEIGHBOR SAM 12502, GOODBYE CHARLIE 37848, MURDER MOST FOUL 23364, RENÉ PETER 34860, THIS IS THE NIGHT src, edge_attr, dst 33387, has_tags, 15436 33387, starred_actors, 32183 15436, has_imdb_rating, 11565 11565, has_imdb_rating, 11565 26124, has_imdb_rating, 11565 26124, release_year, 30172 12502, has_imdb_rating, 11565 12502, release_year, 30172 37848, has_imdb_rating, 11565 37848, release_year, 30172 34860, has_imdb_rating, 11565 34860, written_by, 23364 Question: For what reason are DOUGLAS SILVA, GOODBYE CHARLIE, and RENÉ PETER associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DOUGLAS SILVA", "GOODBYE CHARLIE", "RENÉ PETER" ], "valid_edges": [ [ "CITY OF GOD", "has_tags", "EPIC" ], [ "CITY OF GOD", "starred_actors", "DOUGLAS SILVA" ], [ "EPIC", "has_imdb_rating", "GOOD" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "release_year", "1964" ], [ "GOODBYE CHARLIE", "has_imdb_rating", "GOOD" ], [ "GOODBYE CHARLIE", "release_year", "1964" ], [ "MURDER MOST FOUL", "has_imdb_rating", "GOOD" ], [ "MURDER MOST FOUL", "release_year", "1964" ], [ "THIS IS THE NIGHT", "has_imdb_rating", "GOOD" ], [ "THIS IS THE NIGHT", "written_by", "RENÉ PETER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32539, BREAKFAST WITH SCOT 30463, COMEDY 36690, COMRADE X 9353, LAURIE LYND 3459, LONESOME JIM src, edge_attr, dst 32539, directed_by, 9353 32539, has_genre, 30463 36690, has_genre, 30463 3459, has_genre, 30463 Question: How are COMRADE X, LAURIE LYND, and LONESOME JIM related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "COMRADE X", "LAURIE LYND", "LONESOME JIM" ], "valid_edges": [ [ "BREAKFAST WITH SCOT", "directed_by", "LAURIE LYND" ], [ "BREAKFAST WITH SCOT", "has_genre", "COMEDY" ], [ "COMRADE X", "has_genre", "COMEDY" ], [ "LONESOME JIM", "has_genre", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39397, AIMEE MOLLOY 20757, CLOUDS OF SILS MARIA 36212, DRAMA 7480, EDEN 6480, GERMAN 15765, HAMSUN 16788, INBETWEEN WORLDS 39284, POSSESSION 30919, PRISON 3126, ROSEWATER 3416, SARABAND 23194, STATIONS OF THE CROSS 2227, THE GIRL IN THE PARK 9406, THE IMITATION GAME 14874, THE SCARLET LETTER src, edge_attr, dst 20757, has_genre, 36212 20757, in_language, 6480 7480, has_genre, 36212 7480, in_language, 6480 15765, has_genre, 36212 15765, in_language, 6480 16788, has_genre, 36212 16788, in_language, 6480 39284, has_genre, 36212 39284, in_language, 6480 30919, has_genre, 36212 3126, has_genre, 36212 3126, has_tags, 30919 3126, written_by, 39397 3416, has_genre, 36212 3416, has_tags, 36212 3416, in_language, 6480 23194, has_genre, 36212 23194, in_language, 6480 2227, has_genre, 36212 9406, has_genre, 36212 9406, in_language, 6480 14874, has_genre, 36212 14874, in_language, 6480 Question: In what context are AIMEE MOLLOY, THE GIRL IN THE PARK, and THE SCARLET LETTER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "AIMEE MOLLOY", "THE GIRL IN THE PARK", "THE SCARLET LETTER" ], "valid_edges": [ [ "CLOUDS OF SILS MARIA", "has_genre", "DRAMA" ], [ "CLOUDS OF SILS MARIA", "in_language", "GERMAN" ], [ "EDEN", "has_genre", "DRAMA" ], [ "EDEN", "in_language", "GERMAN" ], [ "HAMSUN", "has_genre", "DRAMA" ], [ "HAMSUN", "in_language", "GERMAN" ], [ "INBETWEEN WORLDS", "has_genre", "DRAMA" ], [ "INBETWEEN WORLDS", "in_language", "GERMAN" ], [ "POSSESSION", "has_genre", "DRAMA" ], [ "POSSESSION", "in_language", "GERMAN" ], [ "PRISON", "has_genre", "DRAMA" ], [ "ROSEWATER", "has_genre", "DRAMA" ], [ "ROSEWATER", "has_tags", "PRISON" ], [ "ROSEWATER", "written_by", "AIMEE MOLLOY" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "in_language", "GERMAN" ], [ "STATIONS OF THE CROSS", "has_genre", "DRAMA" ], [ "STATIONS OF THE CROSS", "in_language", "GERMAN" ], [ "THE GIRL IN THE PARK", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "in_language", "GERMAN" ], [ "THE SCARLET LETTER", "has_genre", "DRAMA" ], [ "THE SCARLET LETTER", "in_language", "GERMAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 22229, CLAIRE OF THE MOON 30463, COMEDY 2890, DESERT HEARTS 36212, DRAMA 35150, FRIED GREEN TOMATOES 35421, GO FISH 8635, LESBIAN 7221, LOVE SICK 10378, MAURY YESTON 17860, NINE 8280, PARIAH 22661, RAISE THE RED LANTERN 24853, SPIDER LILIES 27200, SU TONG 20210, THE WOMEN src, edge_attr, dst 22229, has_genre, 36212 22229, has_tags, 8635 2890, has_genre, 36212 2890, has_tags, 8635 35150, has_genre, 30463 35150, has_genre, 36212 35150, has_tags, 36212 35150, has_tags, 8635 35150, release_year, 10702 35421, has_genre, 36212 35421, has_tags, 8635 7221, has_genre, 36212 7221, has_tags, 8635 17860, has_genre, 36212 17860, written_by, 10378 8280, has_genre, 36212 8280, has_tags, 8635 22661, release_year, 10702 22661, written_by, 27200 24853, has_genre, 36212 24853, has_tags, 36212 24853, has_tags, 8635 20210, has_genre, 30463 20210, has_genre, 36212 20210, has_tags, 8635 Question: In what context are LESBIAN, MAURY YESTON, and SU TONG connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "LESBIAN", "MAURY YESTON", "SU TONG" ], "valid_edges": [ [ "CLAIRE OF THE MOON", "has_genre", "DRAMA" ], [ "CLAIRE OF THE MOON", "has_tags", "LESBIAN" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "has_tags", "LESBIAN" ], [ "FRIED GREEN TOMATOES", "has_genre", "COMEDY" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "LESBIAN" ], [ "FRIED GREEN TOMATOES", "release_year", "1991" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "LESBIAN" ], [ "LOVE SICK", "has_genre", "DRAMA" ], [ "LOVE SICK", "has_tags", "LESBIAN" ], [ "NINE", "has_genre", "DRAMA" ], [ "NINE", "written_by", "MAURY YESTON" ], [ "PARIAH", "has_genre", "DRAMA" ], [ "PARIAH", "has_tags", "LESBIAN" ], [ "RAISE THE RED LANTERN", "release_year", "1991" ], [ "RAISE THE RED LANTERN", "written_by", "SU TONG" ], [ "SPIDER LILIES", "has_genre", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "LESBIAN" ], [ "THE WOMEN", "has_genre", "COMEDY" ], [ "THE WOMEN", "has_genre", "DRAMA" ], [ "THE WOMEN", "has_tags", "LESBIAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 10597, BECOMING JANE 30501, BEOWULF 21275, BROKEN ENGLISH 1424, CALIFORNIA DREAMIN' 3928, CHEENI KUM 30463, COMEDY 928, CONTROL 31783, ENGLISH 9003, FUNNY GAMES 26968, HOT FUZZ 12821, JAB WE MET 29792, JOY DIVISION 14878, KABHI HAAN KABHI NAA 33888, LOVE IN THE TIME OF CHOLERA 28622, MY BLUEBERRY NIGHTS 20348, PATHFINDER 12825, PERSUASION 1643, RISE OF THE FOOTSOLDIER 17447, SON OF RAMBOW 28002, SUKIYAKI WESTERN DJANGO 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 30090, THE AIR UP THERE 8201, THE BAND'S VISIT 25509, THE DEBT 1589, THE FLOCK 32459, THE HAMMER 10331, THE KITE RUNNER 8712, THE LORD OF THE RINGS 21696, THE MAN FROM LONDON 11046, UNDER THE SAME MOON 9265, YOLANDA VAZQUEZ src, edge_attr, dst 10597, in_language, 31783 10597, release_year, 17315 30501, in_language, 31783 30501, release_year, 17315 21275, in_language, 31783 21275, release_year, 17315 1424, in_language, 31783 1424, release_year, 17315 3928, in_language, 31783 3928, release_year, 17315 928, in_language, 31783 928, release_year, 17315 9003, in_language, 31783 9003, release_year, 17315 26968, has_genre, 30463 26968, has_tags, 30463 26968, in_language, 31783 26968, release_year, 17315 12821, has_genre, 30463 12821, in_language, 31783 12821, release_year, 17315 29792, in_language, 31783 29792, release_year, 17315 14878, has_genre, 30463 14878, in_language, 31783 33888, in_language, 31783 33888, release_year, 17315 28622, in_language, 31783 28622, release_year, 17315 20348, in_language, 31783 20348, release_year, 17315 12825, in_language, 31783 12825, release_year, 17315 1643, in_language, 31783 1643, release_year, 17315 17447, has_genre, 30463 17447, in_language, 31783 17447, release_year, 17315 28002, in_language, 31783 28002, release_year, 17315 25270, has_genre, 30463 25270, in_language, 31783 30090, has_genre, 30463 30090, has_tags, 30463 30090, starred_actors, 9265 8201, in_language, 31783 8201, release_year, 17315 25509, in_language, 31783 25509, release_year, 17315 1589, in_language, 31783 1589, release_year, 17315 32459, has_genre, 30463 32459, release_year, 17315 10331, in_language, 31783 10331, release_year, 17315 8712, in_language, 31783 21696, in_language, 31783 21696, release_year, 17315 11046, in_language, 31783 11046, release_year, 17315 Question: For what reason are THE HAMMER, THE LORD OF THE RINGS, and YOLANDA VAZQUEZ associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "THE HAMMER", "THE LORD OF THE RINGS", "YOLANDA VAZQUEZ" ], "valid_edges": [ [ "BECOMING JANE", "in_language", "ENGLISH" ], [ "BECOMING JANE", "release_year", "2007" ], [ "BEOWULF", "in_language", "ENGLISH" ], [ "BEOWULF", "release_year", "2007" ], [ "BROKEN ENGLISH", "in_language", "ENGLISH" ], [ "BROKEN ENGLISH", "release_year", "2007" ], [ "CALIFORNIA DREAMIN'", "in_language", "ENGLISH" ], [ "CALIFORNIA DREAMIN'", "release_year", "2007" ], [ "CHEENI KUM", "in_language", "ENGLISH" ], [ "CHEENI KUM", "release_year", "2007" ], [ "CONTROL", "in_language", "ENGLISH" ], [ "CONTROL", "release_year", "2007" ], [ "FUNNY GAMES", "in_language", "ENGLISH" ], [ "FUNNY GAMES", "release_year", "2007" ], [ "HOT FUZZ", "has_genre", "COMEDY" ], [ "HOT FUZZ", "has_tags", "COMEDY" ], [ "HOT FUZZ", "in_language", "ENGLISH" ], [ "HOT FUZZ", "release_year", "2007" ], [ "JAB WE MET", "has_genre", "COMEDY" ], [ "JAB WE MET", "in_language", "ENGLISH" ], [ "JAB WE MET", "release_year", "2007" ], [ "JOY DIVISION", "in_language", "ENGLISH" ], [ "JOY DIVISION", "release_year", "2007" ], [ "KABHI HAAN KABHI NAA", "has_genre", "COMEDY" ], [ "KABHI HAAN KABHI NAA", "in_language", "ENGLISH" ], [ "LOVE IN THE TIME OF CHOLERA", "in_language", "ENGLISH" ], [ "LOVE IN THE TIME OF CHOLERA", "release_year", "2007" ], [ "MY BLUEBERRY NIGHTS", "in_language", "ENGLISH" ], [ "MY BLUEBERRY NIGHTS", "release_year", "2007" ], [ "PATHFINDER", "in_language", "ENGLISH" ], [ "PATHFINDER", "release_year", "2007" ], [ "PERSUASION", "in_language", "ENGLISH" ], [ "PERSUASION", "release_year", "2007" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "RISE OF THE FOOTSOLDIER", "release_year", "2007" ], [ "SON OF RAMBOW", "has_genre", "COMEDY" ], [ "SON OF RAMBOW", "in_language", "ENGLISH" ], [ "SON OF RAMBOW", "release_year", "2007" ], [ "SUKIYAKI WESTERN DJANGO", "in_language", "ENGLISH" ], [ "SUKIYAKI WESTERN DJANGO", "release_year", "2007" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "in_language", "ENGLISH" ], [ "THE AIR UP THERE", "has_genre", "COMEDY" ], [ "THE AIR UP THERE", "has_tags", "COMEDY" ], [ "THE AIR UP THERE", "starred_actors", "YOLANDA VAZQUEZ" ], [ "THE BAND'S VISIT", "in_language", "ENGLISH" ], [ "THE BAND'S VISIT", "release_year", "2007" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2007" ], [ "THE FLOCK", "in_language", "ENGLISH" ], [ "THE FLOCK", "release_year", "2007" ], [ "THE HAMMER", "has_genre", "COMEDY" ], [ "THE HAMMER", "release_year", "2007" ], [ "THE KITE RUNNER", "in_language", "ENGLISH" ], [ "THE KITE RUNNER", "release_year", "2007" ], [ "THE LORD OF THE RINGS", "in_language", "ENGLISH" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MAN FROM LONDON", "release_year", "2007" ], [ "UNDER THE SAME MOON", "in_language", "ENGLISH" ], [ "UNDER THE SAME MOON", "release_year", "2007" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 6216, 1952 15374, 2005 38588, 5 FINGERS 33955, EMPIRE OF THE WOLVES 7498, FLIGHTPLAN 6480, GERMAN 34073, HELL 6047, HÔTEL DES INVALIDES 38312, MOUTH TO MOUTH 36899, SHORT 3008, SUMMER IN BERLIN 12267, THE BLUE LIGHT 3354, THE BROTHERS GRIMM 10661, THE MUSIC BOX 6575, THE WAVE 38370, VAMPYR 39544, WE FEED THE WORLD src, edge_attr, dst 38588, in_language, 6480 38588, release_year, 6216 33955, release_year, 15374 7498, in_language, 6480 7498, release_year, 15374 34073, in_language, 6480 34073, release_year, 15374 6047, has_genre, 36899 6047, release_year, 6216 38312, in_language, 6480 38312, release_year, 15374 3008, in_language, 6480 3008, release_year, 15374 12267, in_language, 6480 12267, release_year, 1892 3354, in_language, 6480 3354, release_year, 15374 10661, has_genre, 36899 10661, has_tags, 36899 10661, release_year, 1892 6575, has_genre, 36899 6575, in_language, 6480 38370, in_language, 6480 38370, release_year, 1892 39544, in_language, 6480 39544, release_year, 15374 Question: For what reason are EMPIRE OF THE WOLVES, HÔTEL DES INVALIDES, and VAMPYR associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EMPIRE OF THE WOLVES", "HÔTEL DES INVALIDES", "VAMPYR" ], "valid_edges": [ [ "5 FINGERS", "in_language", "GERMAN" ], [ "5 FINGERS", "release_year", "1952" ], [ "EMPIRE OF THE WOLVES", "release_year", "2005" ], [ "FLIGHTPLAN", "in_language", "GERMAN" ], [ "FLIGHTPLAN", "release_year", "2005" ], [ "HELL", "in_language", "GERMAN" ], [ "HELL", "release_year", "2005" ], [ "HÔTEL DES INVALIDES", "has_genre", "SHORT" ], [ "HÔTEL DES INVALIDES", "release_year", "1952" ], [ "MOUTH TO MOUTH", "in_language", "GERMAN" ], [ "MOUTH TO MOUTH", "release_year", "2005" ], [ "SUMMER IN BERLIN", "in_language", "GERMAN" ], [ "SUMMER IN BERLIN", "release_year", "2005" ], [ "THE BLUE LIGHT", "in_language", "GERMAN" ], [ "THE BLUE LIGHT", "release_year", "1932" ], [ "THE BROTHERS GRIMM", "in_language", "GERMAN" ], [ "THE BROTHERS GRIMM", "release_year", "2005" ], [ "THE MUSIC BOX", "has_genre", "SHORT" ], [ "THE MUSIC BOX", "has_tags", "SHORT" ], [ "THE MUSIC BOX", "release_year", "1932" ], [ "THE WAVE", "has_genre", "SHORT" ], [ "THE WAVE", "in_language", "GERMAN" ], [ "VAMPYR", "in_language", "GERMAN" ], [ "VAMPYR", "release_year", "1932" ], [ "WE FEED THE WORLD", "in_language", "GERMAN" ], [ "WE FEED THE WORLD", "release_year", "2005" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4763, ADVENTURE 27192, DON PAUL 36212, DRAMA 36153, LAWRENCE B. MARCUS 15525, PETULIA 1400, RICHARD BRIERS 23530, THE ROAD TO EL DORADO 25311, WATERSHIP DOWN src, edge_attr, dst 15525, has_genre, 36212 15525, written_by, 36153 23530, directed_by, 27192 23530, has_genre, 4763 25311, has_genre, 4763 25311, has_genre, 36212 25311, starred_actors, 1400 Question: For what reason are DON PAUL, LAWRENCE B. MARCUS, and RICHARD BRIERS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DON PAUL", "LAWRENCE B. MARCUS", "RICHARD BRIERS" ], "valid_edges": [ [ "PETULIA", "has_genre", "DRAMA" ], [ "PETULIA", "written_by", "LAWRENCE B. MARCUS" ], [ "THE ROAD TO EL DORADO", "directed_by", "DON PAUL" ], [ "THE ROAD TO EL DORADO", "has_genre", "ADVENTURE" ], [ "WATERSHIP DOWN", "has_genre", "ADVENTURE" ], [ "WATERSHIP DOWN", "has_genre", "DRAMA" ], [ "WATERSHIP DOWN", "starred_actors", "RICHARD BRIERS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1006, 1996 36448, DEADLY VOYAGE 9445, JANET GUNN 63, MICHAEL JORDAN 3288, SPACE JAM 12863, THE QUEST src, edge_attr, dst 36448, release_year, 1006 3288, release_year, 1006 3288, starred_actors, 63 12863, release_year, 1006 12863, starred_actors, 9445 Question: For what reason are DEADLY VOYAGE, JANET GUNN, and MICHAEL JORDAN associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DEADLY VOYAGE", "JANET GUNN", "MICHAEL JORDAN" ], "valid_edges": [ [ "DEADLY VOYAGE", "release_year", "1996" ], [ "SPACE JAM", "release_year", "1996" ], [ "SPACE JAM", "starred_actors", "MICHAEL JORDAN" ], [ "THE QUEST", "release_year", "1996" ], [ "THE QUEST", "starred_actors", "JANET GUNN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7158, 1958 25221, 1981 33215, A NIGHT TO REMEMBER 21806, AUNTIE MAME 19992, BIG DEAL ON MADONNA STREET 30463, COMEDY 27772, GIANTS AND TOYS 5527, GIGI 14193, HOUSEBOAT 9712, INDISCREET 22253, JUDIT POGÁNY 9198, MALIBU'S MOST WANTED 8610, ME AND THE COLONEL 31657, MON ONCLE 24842, NO TIME FOR SERGEANTS 15070, ONIONHEAD 15988, PARTY GIRL 12895, TEACHER'S PET 7973, THE HIDDEN FORTRESS 22174, THE LITTLE FOX 6857, THE MATCHMAKER 36072, THE RELUCTANT DEBUTANTE 15546, THE TUNNEL OF LOVE src, edge_attr, dst 25221, has_genre, 30463 33215, has_genre, 30463 33215, release_year, 7158 21806, has_genre, 30463 21806, release_year, 7158 19992, has_genre, 30463 19992, release_year, 7158 27772, has_genre, 30463 27772, release_year, 7158 5527, has_genre, 30463 5527, release_year, 7158 14193, has_genre, 30463 14193, release_year, 7158 9712, has_genre, 30463 9712, release_year, 7158 9198, has_genre, 30463 8610, has_genre, 30463 8610, release_year, 7158 31657, has_genre, 30463 31657, release_year, 7158 24842, has_genre, 30463 24842, release_year, 7158 15070, has_genre, 30463 15070, release_year, 7158 15988, has_genre, 30463 15988, release_year, 7158 12895, has_genre, 30463 12895, release_year, 7158 7973, release_year, 7158 22174, release_year, 25221 22174, starred_actors, 22253 6857, has_genre, 30463 6857, release_year, 7158 36072, has_genre, 30463 36072, release_year, 7158 15546, has_genre, 30463 15546, release_year, 7158 Question: In what context are JUDIT POGÁNY, MALIBU'S MOST WANTED, and THE HIDDEN FORTRESS connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JUDIT POGÁNY", "MALIBU'S MOST WANTED", "THE HIDDEN FORTRESS" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "A NIGHT TO REMEMBER", "has_genre", "COMEDY" ], [ "A NIGHT TO REMEMBER", "release_year", "1958" ], [ "AUNTIE MAME", "has_genre", "COMEDY" ], [ "AUNTIE MAME", "release_year", "1958" ], [ "BIG DEAL ON MADONNA STREET", "has_genre", "COMEDY" ], [ "BIG DEAL ON MADONNA STREET", "release_year", "1958" ], [ "GIANTS AND TOYS", "has_genre", "COMEDY" ], [ "GIANTS AND TOYS", "release_year", "1958" ], [ "GIGI", "has_genre", "COMEDY" ], [ "GIGI", "release_year", "1958" ], [ "HOUSEBOAT", "has_genre", "COMEDY" ], [ "HOUSEBOAT", "release_year", "1958" ], [ "INDISCREET", "has_genre", "COMEDY" ], [ "INDISCREET", "release_year", "1958" ], [ "MALIBU'S MOST WANTED", "has_genre", "COMEDY" ], [ "ME AND THE COLONEL", "has_genre", "COMEDY" ], [ "ME AND THE COLONEL", "release_year", "1958" ], [ "MON ONCLE", "has_genre", "COMEDY" ], [ "MON ONCLE", "release_year", "1958" ], [ "NO TIME FOR SERGEANTS", "has_genre", "COMEDY" ], [ "NO TIME FOR SERGEANTS", "release_year", "1958" ], [ "ONIONHEAD", "has_genre", "COMEDY" ], [ "ONIONHEAD", "release_year", "1958" ], [ "PARTY GIRL", "has_genre", "COMEDY" ], [ "PARTY GIRL", "release_year", "1958" ], [ "TEACHER'S PET", "has_genre", "COMEDY" ], [ "TEACHER'S PET", "release_year", "1958" ], [ "THE HIDDEN FORTRESS", "release_year", "1958" ], [ "THE LITTLE FOX", "release_year", "1981" ], [ "THE LITTLE FOX", "starred_actors", "JUDIT POGÁNY" ], [ "THE MATCHMAKER", "has_genre", "COMEDY" ], [ "THE MATCHMAKER", "release_year", "1958" ], [ "THE RELUCTANT DEBUTANTE", "has_genre", "COMEDY" ], [ "THE RELUCTANT DEBUTANTE", "release_year", "1958" ], [ "THE TUNNEL OF LOVE", "has_genre", "COMEDY" ], [ "THE TUNNEL OF LOVE", "release_year", "1958" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17978, AMERICAN VIOLET 13792, DON JON 36212, DRAMA 7585, TEXAS 2555, THE RARE BREED 11614, TIM DISNEY 25313, TONY DANZA 36026, WESTERN src, edge_attr, dst 17978, directed_by, 11614 17978, has_genre, 36212 17978, has_tags, 7585 13792, has_genre, 36212 13792, starred_actors, 25313 7585, has_genre, 36026 2555, has_genre, 36026 Question: For what reason are THE RARE BREED, TIM DISNEY, and TONY DANZA associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "THE RARE BREED", "TIM DISNEY", "TONY DANZA" ], "valid_edges": [ [ "AMERICAN VIOLET", "directed_by", "TIM DISNEY" ], [ "AMERICAN VIOLET", "has_genre", "DRAMA" ], [ "AMERICAN VIOLET", "has_tags", "TEXAS" ], [ "DON JON", "has_genre", "DRAMA" ], [ "DON JON", "starred_actors", "TONY DANZA" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26048, AMERICAN HUSTLE 11079, BORDERTOWN 29517, CARROLL GRAHAM 6871, COP LAND 14724, CRIME 36212, DRAMA 21640, GARDEN STATE 4246, JERSEY BOYS 22845, MUSIC 25511, NEW JERSEY 10275, ROBERT VERNAY 19351, THE COUNT OF MONTE CRISTO src, edge_attr, dst 26048, has_genre, 14724 26048, has_genre, 36212 26048, has_tags, 25511 11079, has_genre, 36212 11079, written_by, 29517 6871, has_genre, 14724 6871, has_genre, 36212 6871, has_tags, 14724 6871, has_tags, 36212 6871, has_tags, 25511 21640, has_genre, 36212 21640, has_tags, 22845 21640, has_tags, 25511 4246, has_genre, 36212 4246, has_genre, 22845 4246, has_tags, 22845 4246, has_tags, 25511 19351, directed_by, 10275 19351, has_genre, 36212 19351, written_by, 10275 Question: In what context are CARROLL GRAHAM, NEW JERSEY, and ROBERT VERNAY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CARROLL GRAHAM", "NEW JERSEY", "ROBERT VERNAY" ], "valid_edges": [ [ "AMERICAN HUSTLE", "has_genre", "CRIME" ], [ "AMERICAN HUSTLE", "has_genre", "DRAMA" ], [ "AMERICAN HUSTLE", "has_tags", "NEW JERSEY" ], [ "BORDERTOWN", "has_genre", "DRAMA" ], [ "BORDERTOWN", "written_by", "CARROLL GRAHAM" ], [ "COP LAND", "has_genre", "CRIME" ], [ "COP LAND", "has_genre", "DRAMA" ], [ "COP LAND", "has_tags", "CRIME" ], [ "COP LAND", "has_tags", "DRAMA" ], [ "COP LAND", "has_tags", "NEW JERSEY" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "has_tags", "MUSIC" ], [ "GARDEN STATE", "has_tags", "NEW JERSEY" ], [ "JERSEY BOYS", "has_genre", "DRAMA" ], [ "JERSEY BOYS", "has_genre", "MUSIC" ], [ "JERSEY BOYS", "has_tags", "MUSIC" ], [ "JERSEY BOYS", "has_tags", "NEW JERSEY" ], [ "THE COUNT OF MONTE CRISTO", "directed_by", "ROBERT VERNAY" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "written_by", "ROBERT VERNAY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25717, 1953 1567, 1954 2355, 3 RING CIRCUS 35934, A LADY TAKES A CHANCE 18914, A LESSON IN LOVE 9152, A STAR IS BORN 21802, ABBOTT AND COSTELLO GO TO MARS 15922, ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE 22569, ALL ABOUT THE BENJAMINS 39641, ALONG CAME JONES 33952, ATHENA 38657, BEAT THE DEVIL 4698, BETTY GRABLE 10218, BLACK WIDOW 29294, BREAD, LOVE AND DREAMS 26642, BUS STOP 8430, CALL ME MADAM 24276, CASANOVA BROWN 16795, CASANOVA'S BIG NIGHT 30463, COMEDY 5865, DAVID WAYNE 27558, DESIGNING WOMAN 36492, DIAMONDS 1480, DREAM WIFE 36249, GENEVIEVE 38125, HIS PRIVATE SECRETARY 20400, HOBSON'S CHOICE 12557, HOW TO MARRY A MILLIONAIRE 17344, I VITELLONI 14341, IT COULD HAPPEN TO YOU 30470, IT SHOULD HAPPEN TO YOU 12435, JOHN WAYNE 6956, KNOCK ON WOOD 31519, LAUREN BACALL 10267, LET'S MAKE LOVE 432, LOTTERY 27297, MAGIC TOWN 21143, MARILYN MONROE 7495, MCLINTOCK! 13717, MONKEY BUSINESS 18524, MY BLUE HEAVEN 1436, NIGHT PEOPLE 30968, NOTHING SACRED 11190, NUNNALLY JOHNSON 39193, PHFFFT 13096, ROMAN HOLIDAY 20954, ROXIE HART 4689, SABRINA 7941, SEX AND THE SINGLE GIRL 26840, SOME LIKE IT HOT 39543, SUSAN SLEPT HERE 11290, TAKE HER, SHE'S MINE 22407, THE ACTRESS 32851, THE BAND WAGON 18855, THE CADDY 18055, THE CAPTAIN'S PARADISE 23631, THE HIGH AND THE MIGHTY 17527, THE MIRROR HAS TWO FACES 12672, THE MOON IS BLUE 16199, THE QUIET MAN 11310, THE REFORMER AND THE REDHEAD 3848, THE RETURN OF DON CAMILLO 25574, THE SEVEN YEAR ITCH 31357, THE SHOOTIST 10991, THE SUN SHINES BRIGHT 23294, THE TENDER TRAP 8289, THE TITFIELD THUNDERBOLT 15263, THE TWONKY 17209, THERE'S NO BUSINESS LIKE SHOW BUSINESS 27872, TRACK OF THE CAT 31364, WE'RE NOT MARRIED! 36409, WELCOME MR. MARSHALL! 24706, WILLIAM A. WELLMAN src, edge_attr, dst 2355, has_genre, 30463 2355, release_year, 1567 35934, has_genre, 30463 35934, starred_actors, 12435 18914, has_genre, 30463 18914, release_year, 1567 9152, directed_by, 24706 9152, has_tags, 24706 9152, release_year, 1567 9152, written_by, 24706 21802, has_genre, 30463 21802, release_year, 25717 15922, has_genre, 30463 15922, release_year, 25717 22569, has_genre, 30463 22569, has_tags, 30463 22569, has_tags, 432 39641, has_genre, 30463 39641, written_by, 11190 33952, has_genre, 30463 33952, release_year, 1567 38657, has_genre, 30463 38657, release_year, 25717 10218, directed_by, 11190 10218, release_year, 1567 10218, written_by, 11190 29294, has_genre, 30463 29294, release_year, 25717 26642, has_genre, 30463 26642, has_tags, 21143 26642, starred_actors, 21143 8430, has_genre, 30463 8430, release_year, 25717 24276, has_genre, 30463 24276, written_by, 11190 16795, has_genre, 30463 16795, release_year, 1567 27558, has_genre, 30463 27558, starred_actors, 31519 36492, has_genre, 30463 36492, starred_actors, 31519 1480, has_genre, 30463 1480, release_year, 25717 36249, has_genre, 30463 36249, release_year, 25717 38125, has_genre, 30463 38125, starred_actors, 12435 20400, has_genre, 30463 20400, release_year, 1567 12557, has_genre, 30463 12557, has_tags, 31519 12557, has_tags, 21143 12557, release_year, 25717 12557, starred_actors, 4698 12557, starred_actors, 5865 12557, starred_actors, 31519 12557, starred_actors, 21143 12557, written_by, 11190 17344, has_genre, 30463 17344, release_year, 25717 14341, has_genre, 30463 14341, has_tags, 30463 14341, has_tags, 432 30470, has_genre, 30463 30470, release_year, 1567 6956, has_genre, 30463 6956, release_year, 1567 10267, has_genre, 30463 10267, starred_actors, 21143 27297, directed_by, 24706 27297, has_genre, 30463 7495, has_genre, 30463 7495, has_tags, 12435 7495, starred_actors, 12435 13717, has_genre, 30463 13717, has_tags, 30463 13717, starred_actors, 21143 18524, has_genre, 30463 18524, starred_actors, 4698 1436, directed_by, 11190 1436, release_year, 1567 1436, written_by, 11190 30968, directed_by, 24706 30968, has_genre, 30463 30968, has_tags, 24706 39193, has_genre, 30463 39193, release_year, 1567 13096, has_genre, 30463 13096, has_tags, 30463 13096, release_year, 25717 20954, directed_by, 24706 20954, has_genre, 30463 20954, has_tags, 24706 4689, has_genre, 30463 4689, release_year, 1567 7941, has_genre, 30463 7941, starred_actors, 31519 26840, has_genre, 30463 26840, has_tags, 30463 26840, has_tags, 21143 26840, starred_actors, 21143 39543, has_genre, 30463 39543, release_year, 1567 11290, has_genre, 30463 11290, written_by, 11190 22407, has_genre, 30463 22407, release_year, 25717 32851, has_genre, 30463 32851, release_year, 25717 18855, has_genre, 30463 18855, release_year, 25717 18055, has_genre, 30463 18055, release_year, 25717 23631, directed_by, 24706 23631, has_tags, 24706 23631, release_year, 1567 23631, starred_actors, 12435 17527, has_genre, 30463 17527, starred_actors, 31519 12672, has_genre, 30463 12672, release_year, 25717 16199, has_genre, 30463 16199, has_tags, 12435 16199, starred_actors, 12435 11310, has_genre, 30463 11310, starred_actors, 5865 3848, has_genre, 30463 3848, release_year, 25717 25574, has_genre, 30463 25574, has_tags, 21143 25574, starred_actors, 21143 31357, has_tags, 12435 31357, starred_actors, 12435 31357, starred_actors, 31519 10991, has_genre, 30463 10991, release_year, 25717 23294, has_genre, 30463 23294, starred_actors, 5865 8289, has_genre, 30463 8289, release_year, 25717 15263, has_genre, 30463 15263, release_year, 25717 17209, has_genre, 30463 17209, release_year, 1567 17209, starred_actors, 21143 27872, directed_by, 24706 27872, release_year, 1567 31364, has_genre, 30463 31364, starred_actors, 21143 36409, has_genre, 30463 36409, release_year, 25717 Question: In what context are HOW TO MARRY A MILLIONAIRE, LOTTERY, and THE HIGH AND THE MIGHTY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HOW TO MARRY A MILLIONAIRE", "LOTTERY", "THE HIGH AND THE MIGHTY" ], "valid_edges": [ [ "3 RING CIRCUS", "has_genre", "COMEDY" ], [ "3 RING CIRCUS", "release_year", "1954" ], [ "A LADY TAKES A CHANCE", "has_genre", "COMEDY" ], [ "A LADY TAKES A CHANCE", "starred_actors", "JOHN WAYNE" ], [ "A LESSON IN LOVE", "has_genre", "COMEDY" ], [ "A LESSON IN LOVE", "release_year", "1954" ], [ "A STAR IS BORN", "directed_by", "WILLIAM A. WELLMAN" ], [ "A STAR IS BORN", "has_tags", "WILLIAM A. WELLMAN" ], [ "A STAR IS BORN", "release_year", "1954" ], [ "A STAR IS BORN", "written_by", "WILLIAM A. WELLMAN" ], [ "ABBOTT AND COSTELLO GO TO MARS", "has_genre", "COMEDY" ], [ "ABBOTT AND COSTELLO GO TO MARS", "release_year", "1953" ], [ "ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE", "has_genre", "COMEDY" ], [ "ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE", "release_year", "1953" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "LOTTERY" ], [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "written_by", "NUNNALLY JOHNSON" ], [ "ATHENA", "has_genre", "COMEDY" ], [ "ATHENA", "release_year", "1954" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "release_year", "1953" ], [ "BLACK WIDOW", "directed_by", "NUNNALLY JOHNSON" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BLACK WIDOW", "written_by", "NUNNALLY JOHNSON" ], [ "BREAD, LOVE AND DREAMS", "has_genre", "COMEDY" ], [ "BREAD, LOVE AND DREAMS", "release_year", "1953" ], [ "BUS STOP", "has_genre", "COMEDY" ], [ "BUS STOP", "has_tags", "MARILYN MONROE" ], [ "BUS STOP", "starred_actors", "MARILYN MONROE" ], [ "CALL ME MADAM", "has_genre", "COMEDY" ], [ "CALL ME MADAM", "release_year", "1953" ], [ "CASANOVA BROWN", "has_genre", "COMEDY" ], [ "CASANOVA BROWN", "written_by", "NUNNALLY JOHNSON" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "release_year", "1954" ], [ "DESIGNING WOMAN", "has_genre", "COMEDY" ], [ "DESIGNING WOMAN", "starred_actors", "LAUREN BACALL" ], [ "DIAMONDS", "has_genre", "COMEDY" ], [ "DIAMONDS", "starred_actors", "LAUREN BACALL" ], [ "DREAM WIFE", "has_genre", "COMEDY" ], [ "DREAM WIFE", "release_year", "1953" ], [ "GENEVIEVE", "has_genre", "COMEDY" ], [ "GENEVIEVE", "release_year", "1953" ], [ "HIS PRIVATE SECRETARY", "has_genre", "COMEDY" ], [ "HIS PRIVATE SECRETARY", "starred_actors", "JOHN WAYNE" ], [ "HOBSON'S CHOICE", "has_genre", "COMEDY" ], [ "HOBSON'S CHOICE", "release_year", "1954" ], [ "HOW TO MARRY A MILLIONAIRE", "has_genre", "COMEDY" ], [ "HOW TO MARRY A MILLIONAIRE", "has_tags", "LAUREN BACALL" ], [ "HOW TO MARRY A MILLIONAIRE", "has_tags", "MARILYN MONROE" ], [ "HOW TO MARRY A MILLIONAIRE", "release_year", "1953" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "BETTY GRABLE" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "DAVID WAYNE" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "LAUREN BACALL" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "MARILYN MONROE" ], [ "HOW TO MARRY A MILLIONAIRE", "written_by", "NUNNALLY JOHNSON" ], [ "I VITELLONI", "has_genre", "COMEDY" ], [ "I VITELLONI", "release_year", "1953" ], [ "IT COULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "LOTTERY" ], [ "IT SHOULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT SHOULD HAPPEN TO YOU", "release_year", "1954" ], [ "KNOCK ON WOOD", "has_genre", "COMEDY" ], [ "KNOCK ON WOOD", "release_year", "1954" ], [ "LET'S MAKE LOVE", "has_genre", "COMEDY" ], [ "LET'S MAKE LOVE", "starred_actors", "MARILYN MONROE" ], [ "MAGIC TOWN", "directed_by", "WILLIAM A. WELLMAN" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_tags", "JOHN WAYNE" ], [ "MCLINTOCK!", "starred_actors", "JOHN WAYNE" ], [ "MONKEY BUSINESS", "has_genre", "COMEDY" ], [ "MONKEY BUSINESS", "has_tags", "COMEDY" ], [ "MONKEY BUSINESS", "starred_actors", "MARILYN MONROE" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "starred_actors", "BETTY GRABLE" ], [ "NIGHT PEOPLE", "directed_by", "NUNNALLY JOHNSON" ], [ "NIGHT PEOPLE", "release_year", "1954" ], [ "NIGHT PEOPLE", "written_by", "NUNNALLY JOHNSON" ], [ "NOTHING SACRED", "directed_by", "WILLIAM A. WELLMAN" ], [ "NOTHING SACRED", "has_genre", "COMEDY" ], [ "NOTHING SACRED", "has_tags", "WILLIAM A. WELLMAN" ], [ "PHFFFT", "has_genre", "COMEDY" ], [ "PHFFFT", "release_year", "1954" ], [ "ROMAN HOLIDAY", "has_genre", "COMEDY" ], [ "ROMAN HOLIDAY", "has_tags", "COMEDY" ], [ "ROMAN HOLIDAY", "release_year", "1953" ], [ "ROXIE HART", "directed_by", "WILLIAM A. WELLMAN" ], [ "ROXIE HART", "has_genre", "COMEDY" ], [ "ROXIE HART", "has_tags", "WILLIAM A. WELLMAN" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "release_year", "1954" ], [ "SEX AND THE SINGLE GIRL", "has_genre", "COMEDY" ], [ "SEX AND THE SINGLE GIRL", "starred_actors", "LAUREN BACALL" ], [ "SOME LIKE IT HOT", "has_genre", "COMEDY" ], [ "SOME LIKE IT HOT", "has_tags", "COMEDY" ], [ "SOME LIKE IT HOT", "has_tags", "MARILYN MONROE" ], [ "SOME LIKE IT HOT", "starred_actors", "MARILYN MONROE" ], [ "SUSAN SLEPT HERE", "has_genre", "COMEDY" ], [ "SUSAN SLEPT HERE", "release_year", "1954" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "written_by", "NUNNALLY JOHNSON" ], [ "THE ACTRESS", "has_genre", "COMEDY" ], [ "THE ACTRESS", "release_year", "1953" ], [ "THE BAND WAGON", "has_genre", "COMEDY" ], [ "THE BAND WAGON", "release_year", "1953" ], [ "THE CADDY", "has_genre", "COMEDY" ], [ "THE CADDY", "release_year", "1953" ], [ "THE CAPTAIN'S PARADISE", "has_genre", "COMEDY" ], [ "THE CAPTAIN'S PARADISE", "release_year", "1953" ], [ "THE HIGH AND THE MIGHTY", "directed_by", "WILLIAM A. WELLMAN" ], [ "THE HIGH AND THE MIGHTY", "has_tags", "WILLIAM A. WELLMAN" ], [ "THE HIGH AND THE MIGHTY", "release_year", "1954" ], [ "THE HIGH AND THE MIGHTY", "starred_actors", "JOHN WAYNE" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "COMEDY" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "LAUREN BACALL" ], [ "THE MOON IS BLUE", "has_genre", "COMEDY" ], [ "THE MOON IS BLUE", "release_year", "1953" ], [ "THE QUIET MAN", "has_genre", "COMEDY" ], [ "THE QUIET MAN", "has_tags", "JOHN WAYNE" ], [ "THE QUIET MAN", "starred_actors", "JOHN WAYNE" ], [ "THE REFORMER AND THE REDHEAD", "has_genre", "COMEDY" ], [ "THE REFORMER AND THE REDHEAD", "starred_actors", "DAVID WAYNE" ], [ "THE RETURN OF DON CAMILLO", "has_genre", "COMEDY" ], [ "THE RETURN OF DON CAMILLO", "release_year", "1953" ], [ "THE SEVEN YEAR ITCH", "has_genre", "COMEDY" ], [ "THE SEVEN YEAR ITCH", "has_tags", "MARILYN MONROE" ], [ "THE SEVEN YEAR ITCH", "starred_actors", "MARILYN MONROE" ], [ "THE SHOOTIST", "has_tags", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "LAUREN BACALL" ], [ "THE SUN SHINES BRIGHT", "has_genre", "COMEDY" ], [ "THE SUN SHINES BRIGHT", "release_year", "1953" ], [ "THE TENDER TRAP", "has_genre", "COMEDY" ], [ "THE TENDER TRAP", "starred_actors", "DAVID WAYNE" ], [ "THE TITFIELD THUNDERBOLT", "has_genre", "COMEDY" ], [ "THE TITFIELD THUNDERBOLT", "release_year", "1953" ], [ "THE TWONKY", "has_genre", "COMEDY" ], [ "THE TWONKY", "release_year", "1953" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "COMEDY" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "release_year", "1954" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "starred_actors", "MARILYN MONROE" ], [ "TRACK OF THE CAT", "directed_by", "WILLIAM A. WELLMAN" ], [ "TRACK OF THE CAT", "release_year", "1954" ], [ "WE'RE NOT MARRIED!", "has_genre", "COMEDY" ], [ "WE'RE NOT MARRIED!", "starred_actors", "MARILYN MONROE" ], [ "WELCOME MR. MARSHALL!", "has_genre", "COMEDY" ], [ "WELCOME MR. MARSHALL!", "release_year", "1953" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10045, BD-R 235, BRINGING UP BABY 30463, COMEDY 23299, GET CARTER 22984, HAGAR WILDE 13163, I LOVE TROUBLE 8097, S. SYLVAN SIMON 4088, STEPHEN KAY src, edge_attr, dst 235, has_genre, 30463 235, has_tags, 10045 235, has_tags, 30463 235, written_by, 22984 23299, directed_by, 4088 23299, has_tags, 10045 13163, directed_by, 8097 13163, has_genre, 30463 Question: In what context are HAGAR WILDE, S. SYLVAN SIMON, and STEPHEN KAY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HAGAR WILDE", "S. SYLVAN SIMON", "STEPHEN KAY" ], "valid_edges": [ [ "BRINGING UP BABY", "has_genre", "COMEDY" ], [ "BRINGING UP BABY", "has_tags", "BD-R" ], [ "BRINGING UP BABY", "has_tags", "COMEDY" ], [ "BRINGING UP BABY", "written_by", "HAGAR WILDE" ], [ "GET CARTER", "directed_by", "STEPHEN KAY" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "I LOVE TROUBLE", "directed_by", "S. SYLVAN SIMON" ], [ "I LOVE TROUBLE", "has_genre", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 23257, AN UNFORGETTABLE SUMMER 2537, ANDRE DUBUS III 36212, DRAMA 18266, ERICSON CORE 20309, HOUSE OF SAND AND FOG 23380, INVINCIBLE 22155, LUCIAN PINTILIE 27464, ROMANIAN 25792, THE OAK src, edge_attr, dst 23257, directed_by, 22155 23257, has_genre, 36212 23257, in_language, 27464 23257, written_by, 22155 20309, has_genre, 36212 20309, written_by, 2537 23380, directed_by, 18266 23380, has_genre, 36212 25792, directed_by, 22155 25792, has_genre, 36212 25792, in_language, 27464 25792, written_by, 22155 Question: For what reason are ANDRE DUBUS III, ERICSON CORE, and LUCIAN PINTILIE associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANDRE DUBUS III", "ERICSON CORE", "LUCIAN PINTILIE" ], "valid_edges": [ [ "AN UNFORGETTABLE SUMMER", "directed_by", "LUCIAN PINTILIE" ], [ "AN UNFORGETTABLE SUMMER", "has_genre", "DRAMA" ], [ "AN UNFORGETTABLE SUMMER", "in_language", "ROMANIAN" ], [ "AN UNFORGETTABLE SUMMER", "written_by", "LUCIAN PINTILIE" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "written_by", "ANDRE DUBUS III" ], [ "INVINCIBLE", "directed_by", "ERICSON CORE" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "THE OAK", "directed_by", "LUCIAN PINTILIE" ], [ "THE OAK", "has_genre", "DRAMA" ], [ "THE OAK", "in_language", "ROMANIAN" ], [ "THE OAK", "written_by", "LUCIAN PINTILIE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 1543, 61* 30721, A BEAUTIFUL MIND 30146, A CHRISTMAS CAROL 19865, A.I. ARTIFICIAL INTELLIGENCE 1538, ALIAS BETTY 4141, AN AMERICAN RHAPSODY 22873, ANGEL EYES 462, AUTUMN SPRING 1156, AVALON 5593, BABY BOY 6309, BABY TAKE A BOW 23952, BANDITS 13418, BARTLEBY 28835, BIG BULLY 11298, BOLIVIA 20912, BRIDE OF THE WIND 7461, BROTHERHOOD OF THE WOLF 17892, CAMOUFLAGE 29794, CHARLOTTE GRAY 18016, CLICK 30463, COMEDY 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 10293, CONSPIRACY 23979, CRAZY/BEAUTIFUL 656, CRUSH 6935, DIANE BAKER 1915, DIL CHAHTA HAI 7281, DON'S PLUM 22255, DONNIE DARKO 36212, DRAMA 27747, DRIVEN 10941, DRIVING MISS DAISY 17266, DUST 19194, ENIGMA 24686, FATE 6915, FOCUS 12664, GHOST WORLD 38300, GLITTER 15389, GYPSY 83 1937, HANNAH AND HER SISTERS 29107, HARLEM NIGHTS 21060, HARVARD MAN 19139, HEARTS IN ATLANTIS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 35625, HUMAN NATURE 10714, I AM SAM 20430, IN THE BEDROOM 23380, INVINCIBLE 39987, IT RUNS IN THE FAMILY 23526, JACKPOT 12610, JOE SOMEBODY 31226, JULIE JOHNSON 6206, KABHI KHUSHI KABHIE GHAM... 7699, KINGDOM COME 7888, L.I.E. 19121, LAST ORDERS 39962, LIFE AS A HOUSE 29734, LITTLE SECRETS 22386, LOST AND DELIRIOUS 17728, MAD LOVE 30062, MANIC 33714, MEAN MACHINE 14565, MONSTER'S BALL 24616, MOSTLY MARTHA 10824, O 32514, ONE 2 KA 4 32186, ONE MAN UP 5023, PARENTHOOD 28044, PAULINE AND PAULETTE 234, PEARL HARBOR 29748, PISTOL OPERA 28106, PROZAC NATION 8367, RAIN 28182, RARE BIRDS 38381, ROCK STAR 29441, SEX AND LUCIA 2407, SON OF THE BRIDE 7175, STOLEN KISSES 7949, STORYTELLING 27762, SWEET NOVEMBER 15887, TAPE 13270, TEXAS RANGERS 2582, THE AFFAIR OF THE NECKLACE 15795, THE ANNIVERSARY PARTY 33436, THE BANK 267, THE BELIEVER 25674, THE BROTHERS 4789, THE BROTHERS MCMULLEN 30854, THE CAT'S MEOW 4946, THE CAVEMAN'S VALENTINE 28948, THE FAMILY STONE 27328, THE HORSE IN THE GRAY FLANNEL SUIT 39978, THE HUMAN COMEDY 14993, THE INVISIBLE CIRCUS 23268, THE JIMMY SHOW 4143, THE LAST CASTLE 28107, THE LAST KISS 12566, THE MAJESTIC 23940, THE MAN FROM ELYSIAN FIELDS 22538, THE OTHER SIDE OF HEAVEN 27573, THE OTHERS 39469, THE PORNOGRAPHER 18649, THE RIVER 20728, THE ROYAL TENENBAUMS 23798, THE SHIPPING NEWS 27910, THE UNSAID 2839, THE WIZARD OF BAGHDAD 38275, THIRTEEN CONVERSATIONS ABOUT ONE THING 25783, TIME OUT 27854, TO THE LEFT OF THE FATHER 35988, TORTILLA SOUP 8974, TREED MURRAY 17093, UNFAIR COMPETITION 6655, UPRISING 35443, VIZONTELE 18892, WAKING LIFE 8957, WE BOUGHT A ZOO 19679, WIDE AWAKE 19926, WORLD TRAVELER 25391, Y TU MAMÁ TAMBIÉN src, edge_attr, dst 13747, has_genre, 30463 13747, has_genre, 36212 13747, release_year, 13408 1543, has_genre, 36212 1543, release_year, 13408 30721, has_genre, 36212 30721, has_tags, 36212 30721, release_year, 13408 30146, has_genre, 30463 30146, has_genre, 36212 19865, has_genre, 36212 19865, release_year, 13408 1538, has_genre, 36212 1538, release_year, 13408 4141, has_genre, 36212 4141, release_year, 13408 22873, has_genre, 36212 22873, release_year, 13408 462, has_genre, 36212 462, release_year, 13408 1156, has_genre, 36212 1156, release_year, 13408 5593, has_genre, 30463 5593, has_genre, 36212 5593, release_year, 13408 6309, has_genre, 30463 6309, has_genre, 36212 23952, has_genre, 30463 23952, has_genre, 36212 23952, release_year, 13408 13418, has_genre, 30463 13418, has_genre, 36212 13418, release_year, 13408 28835, has_genre, 30463 28835, has_genre, 36212 11298, has_genre, 36212 11298, release_year, 13408 20912, has_genre, 36212 20912, release_year, 13408 7461, has_genre, 36212 7461, release_year, 13408 17892, has_genre, 30463 17892, has_genre, 36212 17892, release_year, 13408 29794, has_genre, 36212 29794, release_year, 13408 18016, has_genre, 30463 18016, has_genre, 36212 18016, has_tags, 30463 10272, has_genre, 30463 10272, has_tags, 30463 10272, has_tags, 36212 10293, has_genre, 36212 10293, release_year, 13408 23979, has_genre, 36212 23979, release_year, 13408 656, has_genre, 36212 656, release_year, 13408 1915, has_genre, 30463 1915, has_genre, 36212 1915, has_tags, 30463 1915, release_year, 13408 7281, has_genre, 36212 7281, release_year, 13408 22255, has_genre, 36212 22255, release_year, 13408 27747, has_genre, 36212 27747, release_year, 13408 10941, has_genre, 30463 10941, has_genre, 36212 10941, has_tags, 36212 17266, has_genre, 36212 17266, release_year, 13408 19194, has_genre, 36212 19194, release_year, 13408 24686, has_genre, 36212 24686, release_year, 13408 6915, has_genre, 30463 6915, has_genre, 36212 6915, release_year, 13408 12664, has_genre, 30463 12664, has_genre, 36212 12664, release_year, 13408 38300, has_genre, 36212 38300, release_year, 13408 15389, has_genre, 36212 15389, release_year, 13408 1937, has_genre, 30463 1937, has_genre, 36212 1937, has_tags, 30463 29107, has_genre, 30463 29107, has_genre, 36212 21060, has_genre, 30463 21060, has_genre, 36212 21060, release_year, 13408 19139, has_genre, 36212 19139, release_year, 13408 1292, has_genre, 30463 1292, has_genre, 36212 1292, release_year, 13408 38901, has_genre, 30463 38901, has_genre, 36212 38901, release_year, 13408 35625, has_genre, 30463 35625, has_genre, 36212 35625, release_year, 13408 10714, has_genre, 36212 10714, release_year, 13408 20430, has_genre, 36212 20430, has_tags, 36212 20430, release_year, 13408 23380, has_genre, 36212 23380, release_year, 13408 39987, has_genre, 30463 39987, has_genre, 36212 23526, has_genre, 30463 23526, has_genre, 36212 23526, release_year, 13408 12610, has_genre, 30463 12610, has_genre, 36212 12610, release_year, 13408 31226, has_genre, 36212 31226, release_year, 13408 6206, has_genre, 36212 6206, release_year, 13408 7699, has_genre, 30463 7699, has_genre, 36212 7699, release_year, 13408 7888, has_genre, 36212 7888, release_year, 13408 19121, has_genre, 36212 19121, release_year, 13408 39962, has_genre, 36212 39962, release_year, 13408 29734, has_genre, 30463 29734, has_genre, 36212 29734, release_year, 13408 22386, has_genre, 36212 22386, release_year, 13408 17728, has_genre, 36212 17728, release_year, 13408 30062, has_genre, 36212 30062, release_year, 13408 33714, has_genre, 30463 33714, has_genre, 36212 33714, release_year, 13408 14565, has_genre, 36212 14565, release_year, 13408 24616, has_genre, 30463 24616, has_genre, 36212 24616, release_year, 13408 10824, has_genre, 36212 10824, release_year, 13408 32514, has_genre, 36212 32514, release_year, 13408 32186, has_genre, 30463 32186, has_genre, 36212 32186, release_year, 13408 5023, has_genre, 30463 5023, has_genre, 36212 5023, has_tags, 30463 28044, has_genre, 30463 28044, has_genre, 36212 28044, release_year, 13408 234, has_genre, 36212 234, has_tags, 36212 234, release_year, 13408 29748, release_year, 13408 28106, has_genre, 36212 28106, release_year, 13408 8367, has_genre, 36212 8367, release_year, 13408 28182, has_genre, 30463 28182, has_genre, 36212 28182, release_year, 13408 38381, has_genre, 30463 38381, has_genre, 36212 38381, release_year, 13408 29441, has_genre, 36212 29441, release_year, 13408 2407, has_genre, 30463 2407, has_genre, 36212 2407, release_year, 13408 7175, has_genre, 30463 7175, has_genre, 36212 7949, has_genre, 30463 7949, has_genre, 36212 7949, release_year, 13408 27762, has_genre, 30463 27762, has_genre, 36212 27762, release_year, 13408 15887, has_genre, 36212 15887, release_year, 13408 13270, has_genre, 36212 13270, release_year, 13408 2582, has_genre, 36212 2582, release_year, 13408 15795, has_genre, 30463 15795, has_genre, 36212 15795, release_year, 13408 33436, has_genre, 36212 33436, release_year, 13408 267, has_genre, 36212 267, release_year, 13408 25674, has_genre, 30463 25674, has_genre, 36212 25674, release_year, 13408 4789, has_genre, 30463 4789, has_genre, 36212 30854, has_genre, 36212 30854, release_year, 13408 4946, has_genre, 36212 4946, release_year, 13408 28948, has_genre, 30463 28948, has_genre, 36212 28948, has_tags, 30463 28948, has_tags, 36212 27328, has_genre, 30463 27328, starred_actors, 6935 39978, has_genre, 30463 39978, has_genre, 36212 14993, has_genre, 36212 14993, release_year, 13408 23268, has_genre, 36212 23268, release_year, 13408 4143, has_genre, 36212 4143, release_year, 13408 28107, has_genre, 30463 28107, has_genre, 36212 28107, release_year, 13408 12566, has_genre, 36212 12566, release_year, 13408 23940, has_genre, 36212 23940, release_year, 13408 22538, has_genre, 36212 22538, release_year, 13408 27573, has_tags, 36212 27573, release_year, 13408 39469, has_genre, 36212 39469, release_year, 13408 18649, has_genre, 36212 18649, release_year, 13408 20728, has_genre, 30463 20728, has_genre, 36212 20728, has_tags, 30463 20728, release_year, 13408 23798, has_genre, 36212 23798, release_year, 13408 27910, has_genre, 36212 27910, release_year, 13408 2839, has_genre, 30463 2839, starred_actors, 6935 38275, has_genre, 36212 38275, release_year, 13408 25783, has_genre, 36212 25783, release_year, 13408 27854, has_genre, 36212 27854, release_year, 13408 35988, has_genre, 30463 35988, has_genre, 36212 35988, release_year, 13408 8974, has_genre, 36212 8974, release_year, 13408 17093, has_genre, 36212 17093, release_year, 13408 6655, has_genre, 36212 6655, release_year, 13408 35443, has_genre, 30463 35443, has_genre, 36212 35443, has_tags, 30463 35443, release_year, 13408 18892, has_genre, 36212 18892, release_year, 13408 8957, has_genre, 30463 8957, has_genre, 36212 19679, has_genre, 30463 19679, has_genre, 36212 19926, has_genre, 36212 19926, release_year, 13408 25391, has_genre, 36212 25391, has_tags, 36212 25391, release_year, 13408 Question: In what context are DIANE BAKER, HARLEM NIGHTS, and PISTOL OPERA connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DIANE BAKER", "HARLEM NIGHTS", "PISTOL OPERA" ], "valid_edges": [ [ "25 WATTS", "has_genre", "COMEDY" ], [ "25 WATTS", "has_genre", "DRAMA" ], [ "25 WATTS", "release_year", "2001" ], [ "61", "has_genre", "DRAMA" ], [ "61", "release_year", "2001" ], [ "A BEAUTIFUL MIND", "has_genre", "DRAMA" ], [ "A BEAUTIFUL MIND", "has_tags", "DRAMA" ], [ "A BEAUTIFUL MIND", "release_year", "2001" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "release_year", "2001" ], [ "ALIAS BETTY", "has_genre", "DRAMA" ], [ "ALIAS BETTY", "release_year", "2001" ], [ "AN AMERICAN RHAPSODY", "has_genre", "DRAMA" ], [ "AN AMERICAN RHAPSODY", "release_year", "2001" ], [ "ANGEL EYES", "has_genre", "DRAMA" ], [ "ANGEL EYES", "release_year", "2001" ], [ "AUTUMN SPRING", "has_genre", "DRAMA" ], [ "AUTUMN SPRING", "release_year", "2001" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "release_year", "2001" ], [ "BABY BOY", "has_genre", "COMEDY" ], [ "BABY BOY", "has_genre", "DRAMA" ], [ "BABY BOY", "release_year", "2001" ], [ "BABY TAKE A BOW", "has_genre", "COMEDY" ], [ "BABY TAKE A BOW", "has_genre", "DRAMA" ], [ "BANDITS", "has_genre", "COMEDY" ], [ "BANDITS", "has_genre", "DRAMA" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "COMEDY" ], [ "BARTLEBY", "has_genre", "DRAMA" ], [ "BARTLEBY", "release_year", "2001" ], [ "BIG BULLY", "has_genre", "COMEDY" ], [ "BIG BULLY", "has_genre", "DRAMA" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "release_year", "2001" ], [ "BRIDE OF THE WIND", "has_genre", "DRAMA" ], [ "BRIDE OF THE WIND", "release_year", "2001" ], [ "BROTHERHOOD OF THE WOLF", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "COMEDY" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CHARLOTTE GRAY", "has_genre", "DRAMA" ], [ "CHARLOTTE GRAY", "release_year", "2001" ], [ "CLICK", "has_genre", "COMEDY" ], [ "CLICK", "has_genre", "DRAMA" ], [ "CLICK", "has_tags", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONSPIRACY", "has_genre", "DRAMA" ], [ "CONSPIRACY", "release_year", "2001" ], [ "CRAZY/BEAUTIFUL", "has_genre", "DRAMA" ], [ "CRAZY/BEAUTIFUL", "release_year", "2001" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "COMEDY" ], [ "DIL CHAHTA HAI", "has_genre", "DRAMA" ], [ "DIL CHAHTA HAI", "has_tags", "COMEDY" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'S PLUM", "has_genre", "DRAMA" ], [ "DON'S PLUM", "release_year", "2001" ], [ "DONNIE DARKO", "has_genre", "DRAMA" ], [ "DONNIE DARKO", "release_year", "2001" ], [ "DRIVEN", "has_genre", "DRAMA" ], [ "DRIVEN", "release_year", "2001" ], [ "DRIVING MISS DAISY", "has_genre", "COMEDY" ], [ "DRIVING MISS DAISY", "has_genre", "DRAMA" ], [ "DRIVING MISS DAISY", "has_tags", "DRAMA" ], [ "DUST", "has_genre", "DRAMA" ], [ "DUST", "release_year", "2001" ], [ "ENIGMA", "has_genre", "DRAMA" ], [ "ENIGMA", "release_year", "2001" ], [ "FATE", "has_genre", "DRAMA" ], [ "FATE", "release_year", "2001" ], [ "FOCUS", "has_genre", "COMEDY" ], [ "FOCUS", "has_genre", "DRAMA" ], [ "FOCUS", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "COMEDY" ], [ "GHOST WORLD", "has_genre", "DRAMA" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GLITTER", "has_genre", "DRAMA" ], [ "GLITTER", "release_year", "2001" ], [ "GYPSY 83", "has_genre", "DRAMA" ], [ "GYPSY 83", "release_year", "2001" ], [ "HANNAH AND HER SISTERS", "has_genre", "COMEDY" ], [ "HANNAH AND HER SISTERS", "has_genre", "DRAMA" ], [ "HANNAH AND HER SISTERS", "has_tags", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "DRAMA" ], [ "HARVARD MAN", "has_genre", "COMEDY" ], [ "HARVARD MAN", "has_genre", "DRAMA" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HEARTS IN ATLANTIS", "has_genre", "DRAMA" ], [ "HEARTS IN ATLANTIS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "COMEDY" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "DRAMA" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "has_genre", "DRAMA" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "I AM SAM", "has_genre", "DRAMA" ], [ "I AM SAM", "release_year", "2001" ], [ "IN THE BEDROOM", "has_genre", "DRAMA" ], [ "IN THE BEDROOM", "has_tags", "DRAMA" ], [ "IN THE BEDROOM", "release_year", "2001" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "INVINCIBLE", "release_year", "2001" ], [ "IT RUNS IN THE FAMILY", "has_genre", "COMEDY" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "JACKPOT", "has_genre", "COMEDY" ], [ "JACKPOT", "has_genre", "DRAMA" ], [ "JACKPOT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "COMEDY" ], [ "JOE SOMEBODY", "has_genre", "DRAMA" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JULIE JOHNSON", "has_genre", "DRAMA" ], [ "JULIE JOHNSON", "release_year", "2001" ], [ "KABHI KHUSHI KABHIE GHAM...", "has_genre", "DRAMA" ], [ "KABHI KHUSHI KABHIE GHAM...", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "COMEDY" ], [ "KINGDOM COME", "has_genre", "DRAMA" ], [ "KINGDOM COME", "release_year", "2001" ], [ "L.I.E.", "has_genre", "DRAMA" ], [ "L.I.E.", "release_year", "2001" ], [ "LAST ORDERS", "has_genre", "DRAMA" ], [ "LAST ORDERS", "release_year", "2001" ], [ "LIFE AS A HOUSE", "has_genre", "DRAMA" ], [ "LIFE AS A HOUSE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "COMEDY" ], [ "LITTLE SECRETS", "has_genre", "DRAMA" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LOST AND DELIRIOUS", "has_genre", "DRAMA" ], [ "LOST AND DELIRIOUS", "release_year", "2001" ], [ "MAD LOVE", "has_genre", "DRAMA" ], [ "MAD LOVE", "release_year", "2001" ], [ "MANIC", "has_genre", "DRAMA" ], [ "MANIC", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "COMEDY" ], [ "MEAN MACHINE", "has_genre", "DRAMA" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONSTER'S BALL", "has_genre", "DRAMA" ], [ "MONSTER'S BALL", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "COMEDY" ], [ "MOSTLY MARTHA", "has_genre", "DRAMA" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "O", "has_genre", "DRAMA" ], [ "O", "release_year", "2001" ], [ "ONE 2 KA 4", "has_genre", "DRAMA" ], [ "ONE 2 KA 4", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "COMEDY" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "release_year", "2001" ], [ "PARENTHOOD", "has_genre", "COMEDY" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "COMEDY" ], [ "PAULINE AND PAULETTE", "has_genre", "COMEDY" ], [ "PAULINE AND PAULETTE", "has_genre", "DRAMA" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PEARL HARBOR", "has_genre", "DRAMA" ], [ "PEARL HARBOR", "has_tags", "DRAMA" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PISTOL OPERA", "release_year", "2001" ], [ "PROZAC NATION", "has_genre", "DRAMA" ], [ "PROZAC NATION", "release_year", "2001" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "COMEDY" ], [ "RARE BIRDS", "has_genre", "DRAMA" ], [ "RARE BIRDS", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "has_genre", "DRAMA" ], [ "ROCK STAR", "release_year", "2001" ], [ "SEX AND LUCIA", "has_genre", "DRAMA" ], [ "SEX AND LUCIA", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "COMEDY" ], [ "SON OF THE BRIDE", "has_genre", "DRAMA" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "STOLEN KISSES", "has_genre", "COMEDY" ], [ "STOLEN KISSES", "has_genre", "DRAMA" ], [ "STORYTELLING", "has_genre", "COMEDY" ], [ "STORYTELLING", "has_genre", "DRAMA" ], [ "STORYTELLING", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "COMEDY" ], [ "SWEET NOVEMBER", "has_genre", "DRAMA" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TAPE", "has_genre", "DRAMA" ], [ "TAPE", "release_year", "2001" ], [ "TEXAS RANGERS", "has_genre", "DRAMA" ], [ "TEXAS RANGERS", "release_year", "2001" ], [ "THE AFFAIR OF THE NECKLACE", "has_genre", "DRAMA" ], [ "THE AFFAIR OF THE NECKLACE", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "COMEDY" ], [ "THE ANNIVERSARY PARTY", "has_genre", "DRAMA" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BANK", "has_genre", "DRAMA" ], [ "THE BANK", "release_year", "2001" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "COMEDY" ], [ "THE BROTHERS", "has_genre", "DRAMA" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE BROTHERS MCMULLEN", "has_genre", "COMEDY" ], [ "THE BROTHERS MCMULLEN", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "release_year", "2001" ], [ "THE CAVEMAN'S VALENTINE", "has_genre", "DRAMA" ], [ "THE CAVEMAN'S VALENTINE", "release_year", "2001" ], [ "THE FAMILY STONE", "has_genre", "COMEDY" ], [ "THE FAMILY STONE", "has_genre", "DRAMA" ], [ "THE FAMILY STONE", "has_tags", "COMEDY" ], [ "THE FAMILY STONE", "has_tags", "DRAMA" ], [ "THE HORSE IN THE GRAY FLANNEL SUIT", "has_genre", "COMEDY" ], [ "THE HORSE IN THE GRAY FLANNEL SUIT", "starred_actors", "DIANE BAKER" ], [ "THE HUMAN COMEDY", "has_genre", "COMEDY" ], [ "THE HUMAN COMEDY", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "release_year", "2001" ], [ "THE JIMMY SHOW", "has_genre", "DRAMA" ], [ "THE JIMMY SHOW", "release_year", "2001" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAJESTIC", "has_genre", "DRAMA" ], [ "THE MAJESTIC", "release_year", "2001" ], [ "THE MAN FROM ELYSIAN FIELDS", "has_genre", "DRAMA" ], [ "THE MAN FROM ELYSIAN FIELDS", "release_year", "2001" ], [ "THE OTHER SIDE OF HEAVEN", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF HEAVEN", "release_year", "2001" ], [ "THE OTHERS", "has_tags", "DRAMA" ], [ "THE OTHERS", "release_year", "2001" ], [ "THE PORNOGRAPHER", "has_genre", "DRAMA" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "THE RIVER", "has_genre", "DRAMA" ], [ "THE RIVER", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "has_genre", "DRAMA" ], [ "THE ROYAL TENENBAUMS", "has_tags", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHIPPING NEWS", "has_genre", "DRAMA" ], [ "THE SHIPPING NEWS", "release_year", "2001" ], [ "THE UNSAID", "has_genre", "DRAMA" ], [ "THE UNSAID", "release_year", "2001" ], [ "THE WIZARD OF BAGHDAD", "has_genre", "COMEDY" ], [ "THE WIZARD OF BAGHDAD", "starred_actors", "DIANE BAKER" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "has_genre", "DRAMA" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "release_year", "2001" ], [ "TIME OUT", "has_genre", "DRAMA" ], [ "TIME OUT", "release_year", "2001" ], [ "TO THE LEFT OF THE FATHER", "has_genre", "DRAMA" ], [ "TO THE LEFT OF THE FATHER", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "COMEDY" ], [ "TORTILLA SOUP", "has_genre", "DRAMA" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "DRAMA" ], [ "TREED MURRAY", "release_year", "2001" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "release_year", "2001" ], [ "UPRISING", "has_genre", "DRAMA" ], [ "UPRISING", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "COMEDY" ], [ "VIZONTELE", "has_genre", "DRAMA" ], [ "VIZONTELE", "has_tags", "COMEDY" ], [ "VIZONTELE", "release_year", "2001" ], [ "WAKING LIFE", "has_genre", "DRAMA" ], [ "WAKING LIFE", "release_year", "2001" ], [ "WE BOUGHT A ZOO", "has_genre", "COMEDY" ], [ "WE BOUGHT A ZOO", "has_genre", "DRAMA" ], [ "WIDE AWAKE", "has_genre", "COMEDY" ], [ "WIDE AWAKE", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "release_year", "2001" ], [ "Y TU MAMÁ TAMBIÉN", "has_genre", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "has_tags", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "release_year", "2001" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32015, BEHIND ENEMY LINES 30463, COMEDY 21587, HOW I WON THE WAR 15503, JENÉE LAMARQUE 24297, MARK CARLTON 34811, PATRICK RYAN 4335, THE PRETTY ONE 22214, WAR src, edge_attr, dst 32015, has_genre, 22214 32015, has_tags, 22214 32015, starred_actors, 24297 21587, has_genre, 30463 21587, has_genre, 22214 21587, written_by, 34811 4335, directed_by, 15503 4335, has_genre, 30463 4335, written_by, 15503 Question: In what context are JENÉE LAMARQUE, MARK CARLTON, and PATRICK RYAN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JENÉE LAMARQUE", "MARK CARLTON", "PATRICK RYAN" ], "valid_edges": [ [ "BEHIND ENEMY LINES", "has_genre", "WAR" ], [ "BEHIND ENEMY LINES", "has_tags", "WAR" ], [ "BEHIND ENEMY LINES", "starred_actors", "MARK CARLTON" ], [ "HOW I WON THE WAR", "has_genre", "COMEDY" ], [ "HOW I WON THE WAR", "has_genre", "WAR" ], [ "HOW I WON THE WAR", "written_by", "PATRICK RYAN" ], [ "THE PRETTY ONE", "directed_by", "JENÉE LAMARQUE" ], [ "THE PRETTY ONE", "has_genre", "COMEDY" ], [ "THE PRETTY ONE", "written_by", "JENÉE LAMARQUE" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11112, 1939 26633, 1989 33875, A GRAND DAY OUT 24177, ANIMATION 39085, BILLY ELLIOT 16654, BRITISH 32706, FIRST LOVE 17440, GULLIVER'S TRAVELS 17118, HENRY V 24241, LEE HALL 15198, THE HUNCHBACK OF NOTRE DAME 31303, THE LITTLE MERMAID src, edge_attr, dst 33875, has_genre, 24177 33875, has_tags, 16654 33875, release_year, 26633 39085, has_tags, 16654 39085, written_by, 24241 32706, release_year, 11112 17440, has_genre, 24177 17440, release_year, 11112 17118, has_tags, 16654 17118, release_year, 26633 15198, has_genre, 24177 15198, release_year, 11112 31303, has_genre, 24177 31303, has_tags, 24177 31303, release_year, 26633 Question: For what reason are A GRAND DAY OUT, FIRST LOVE, and LEE HALL associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A GRAND DAY OUT", "FIRST LOVE", "LEE HALL" ], "valid_edges": [ [ "A GRAND DAY OUT", "has_genre", "ANIMATION" ], [ "A GRAND DAY OUT", "has_tags", "BRITISH" ], [ "A GRAND DAY OUT", "release_year", "1989" ], [ "BILLY ELLIOT", "has_tags", "BRITISH" ], [ "BILLY ELLIOT", "written_by", "LEE HALL" ], [ "FIRST LOVE", "release_year", "1939" ], [ "GULLIVER'S TRAVELS", "has_genre", "ANIMATION" ], [ "GULLIVER'S TRAVELS", "release_year", "1939" ], [ "HENRY V", "has_tags", "BRITISH" ], [ "HENRY V", "release_year", "1989" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "ANIMATION" ], [ "THE HUNCHBACK OF NOTRE DAME", "release_year", "1939" ], [ "THE LITTLE MERMAID", "has_genre", "ANIMATION" ], [ "THE LITTLE MERMAID", "has_tags", "ANIMATION" ], [ "THE LITTLE MERMAID", "release_year", "1989" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21931, 1941 7841, 1987 10149, A HUNGARIAN FAIRY TALE 36420, A TAXING WOMAN 23612, DOLLS 22028, EMPIRE OF THE SUN 36874, JAPANESE 21030, NANA 7585, TEXAS 735, THE REVISIONARIES 8589, WICKED CITY src, edge_attr, dst 21931, in_language, 36874 10149, release_year, 7841 36420, in_language, 36874 36420, release_year, 7841 23612, in_language, 36874 23612, release_year, 7841 22028, in_language, 36874 22028, release_year, 7841 21030, in_language, 36874 7585, release_year, 21931 735, has_tags, 7585 8589, in_language, 36874 8589, release_year, 7841 Question: For what reason are A HUNGARIAN FAIRY TALE, NANA, and THE REVISIONARIES associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A HUNGARIAN FAIRY TALE", "NANA", "THE REVISIONARIES" ], "valid_edges": [ [ "1941", "in_language", "JAPANESE" ], [ "A HUNGARIAN FAIRY TALE", "release_year", "1987" ], [ "A TAXING WOMAN", "in_language", "JAPANESE" ], [ "A TAXING WOMAN", "release_year", "1987" ], [ "DOLLS", "in_language", "JAPANESE" ], [ "DOLLS", "release_year", "1987" ], [ "EMPIRE OF THE SUN", "in_language", "JAPANESE" ], [ "EMPIRE OF THE SUN", "release_year", "1987" ], [ "NANA", "in_language", "JAPANESE" ], [ "TEXAS", "release_year", "1941" ], [ "THE REVISIONARIES", "has_tags", "TEXAS" ], [ "WICKED CITY", "in_language", "JAPANESE" ], [ "WICKED CITY", "release_year", "1987" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 24525, 1984 38097, 1985 37484, 2004 32087, BARBARA CUPISTI 26883, CEMETERY MAN 9243, CHARLES GRODIN 30463, COMEDY 21942, DAWN OF THE DEAD 6095, DAY OF THE DEAD 18708, DEADHEADS 5963, GEORGE A. ROMERO 2600, HELL OF THE LIVING DEAD 36859, HELLO AGAIN 5870, HORROR 16200, ITALIAN 7548, JUDITH IVEY 25134, LAND OF THE DEAD 2072, MICHELE SOAVI 32988, NIGHT OF THE LIVING DEAD 25714, NIGHTMARE CITY 13081, R 28729, REMAKE 25673, ROMERO 29855, SHAUN OF THE DEAD 10334, THE CHURCH 36990, THE LONELY GUY 16017, THE RETURN OF THE LIVING DEAD 20553, THE WOMAN IN RED 9639, UNDEAD 14902, ZOMBIE 21798, ZOMBIE HOLOCAUST 33616, ZOMBIE LAKE 39354, ZOMBIES src, edge_attr, dst 26883, directed_by, 2072 26883, has_genre, 30463 26883, has_genre, 5870 26883, has_tags, 14902 26883, has_tags, 39354 26883, in_language, 16200 21942, directed_by, 5963 21942, has_genre, 5870 21942, has_tags, 5963 21942, has_tags, 5870 21942, has_tags, 13081 21942, has_tags, 28729 21942, has_tags, 25673 21942, has_tags, 14902 21942, has_tags, 39354 21942, release_year, 37484 21942, written_by, 5963 6095, directed_by, 5963 6095, has_genre, 5870 6095, has_tags, 5963 6095, has_tags, 5870 6095, has_tags, 14902 6095, release_year, 38097 6095, written_by, 5963 18708, has_genre, 30463 18708, has_tags, 30463 18708, has_tags, 14902 2600, has_genre, 5870 2600, has_tags, 14902 2600, has_tags, 39354 2600, in_language, 16200 2600, release_year, 36268 36859, has_genre, 30463 36859, starred_actors, 7548 25134, directed_by, 5963 25134, has_genre, 5870 25134, has_tags, 5963 25134, has_tags, 25673 25134, has_tags, 14902 25134, written_by, 5963 32988, directed_by, 5963 32988, has_genre, 5870 32988, has_tags, 5963 32988, has_tags, 5870 32988, has_tags, 28729 32988, has_tags, 14902 32988, has_tags, 39354 32988, written_by, 5963 25714, has_tags, 14902 25714, has_tags, 39354 25714, in_language, 16200 25714, release_year, 36268 29855, has_genre, 30463 29855, has_tags, 30463 29855, has_tags, 13081 29855, has_tags, 14902 29855, has_tags, 39354 29855, release_year, 37484 10334, directed_by, 2072 10334, has_genre, 5870 10334, in_language, 16200 10334, starred_actors, 32087 10334, written_by, 2072 36990, has_genre, 30463 36990, release_year, 24525 36990, starred_actors, 9243 36990, starred_actors, 7548 16017, has_genre, 30463 16017, has_genre, 5870 16017, has_tags, 14902 16017, has_tags, 39354 16017, release_year, 38097 20553, has_genre, 30463 20553, release_year, 24525 20553, starred_actors, 9243 20553, starred_actors, 7548 9639, has_genre, 30463 9639, has_genre, 5870 9639, has_tags, 14902 21798, has_tags, 14902 21798, in_language, 16200 33616, has_genre, 5870 33616, has_tags, 14902 33616, has_tags, 39354 Question: In what context are BARBARA CUPISTI, JUDITH IVEY, and ZOMBIE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BARBARA CUPISTI", "JUDITH IVEY", "ZOMBIE" ], "valid_edges": [ [ "CEMETERY MAN", "directed_by", "MICHELE SOAVI" ], [ "CEMETERY MAN", "has_genre", "COMEDY" ], [ "CEMETERY MAN", "has_genre", "HORROR" ], [ "CEMETERY MAN", "has_tags", "ZOMBIE" ], [ "CEMETERY MAN", "has_tags", "ZOMBIES" ], [ "CEMETERY MAN", "in_language", "ITALIAN" ], [ "DAWN OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "DAWN OF THE DEAD", "has_genre", "HORROR" ], [ "DAWN OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "DAWN OF THE DEAD", "has_tags", "HORROR" ], [ "DAWN OF THE DEAD", "has_tags", "R" ], [ "DAWN OF THE DEAD", "has_tags", "REMAKE" ], [ "DAWN OF THE DEAD", "has_tags", "ROMERO" ], [ "DAWN OF THE DEAD", "has_tags", "ZOMBIE" ], [ "DAWN OF THE DEAD", "has_tags", "ZOMBIES" ], [ "DAWN OF THE DEAD", "release_year", "2004" ], [ "DAWN OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "has_genre", "HORROR" ], [ "DAY OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "has_tags", "HORROR" ], [ "DAY OF THE DEAD", "has_tags", "ZOMBIE" ], [ "DAY OF THE DEAD", "release_year", "1985" ], [ "DAY OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "DEADHEADS", "has_genre", "COMEDY" ], [ "DEADHEADS", "has_tags", "COMEDY" ], [ "DEADHEADS", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "HELL OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "HELLO AGAIN", "has_genre", "COMEDY" ], [ "HELLO AGAIN", "starred_actors", "JUDITH IVEY" ], [ "LAND OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "LAND OF THE DEAD", "has_genre", "HORROR" ], [ "LAND OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "LAND OF THE DEAD", "has_tags", "ROMERO" ], [ "LAND OF THE DEAD", "has_tags", "ZOMBIE" ], [ "LAND OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "REMAKE" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "NIGHT OF THE LIVING DEAD", "written_by", "GEORGE A. ROMERO" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIE" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIES" ], [ "NIGHTMARE CITY", "in_language", "ITALIAN" ], [ "NIGHTMARE CITY", "release_year", "1980" ], [ "SHAUN OF THE DEAD", "has_genre", "COMEDY" ], [ "SHAUN OF THE DEAD", "has_tags", "COMEDY" ], [ "SHAUN OF THE DEAD", "has_tags", "R" ], [ "SHAUN OF THE DEAD", "has_tags", "ZOMBIE" ], [ "SHAUN OF THE DEAD", "has_tags", "ZOMBIES" ], [ "SHAUN OF THE DEAD", "release_year", "2004" ], [ "THE CHURCH", "directed_by", "MICHELE SOAVI" ], [ "THE CHURCH", "has_genre", "HORROR" ], [ "THE CHURCH", "in_language", "ITALIAN" ], [ "THE CHURCH", "starred_actors", "BARBARA CUPISTI" ], [ "THE CHURCH", "written_by", "MICHELE SOAVI" ], [ "THE LONELY GUY", "has_genre", "COMEDY" ], [ "THE LONELY GUY", "release_year", "1984" ], [ "THE LONELY GUY", "starred_actors", "CHARLES GRODIN" ], [ "THE LONELY GUY", "starred_actors", "JUDITH IVEY" ], [ "THE RETURN OF THE LIVING DEAD", "has_genre", "COMEDY" ], [ "THE RETURN OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "THE RETURN OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "THE RETURN OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "THE RETURN OF THE LIVING DEAD", "release_year", "1985" ], [ "THE WOMAN IN RED", "has_genre", "COMEDY" ], [ "THE WOMAN IN RED", "release_year", "1984" ], [ "THE WOMAN IN RED", "starred_actors", "CHARLES GRODIN" ], [ "THE WOMAN IN RED", "starred_actors", "JUDITH IVEY" ], [ "UNDEAD", "has_genre", "COMEDY" ], [ "UNDEAD", "has_genre", "HORROR" ], [ "UNDEAD", "has_tags", "ZOMBIE" ], [ "ZOMBIE HOLOCAUST", "has_tags", "ZOMBIE" ], [ "ZOMBIE HOLOCAUST", "in_language", "ITALIAN" ], [ "ZOMBIE LAKE", "has_genre", "HORROR" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIE" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIES" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18132, 1938 35798, 2010 10768, BACK TO THE FUTURE 23299, GET CARTER 23544, INCEPTION 978, INFERNAL AFFAIRS 13825, INSOMNIA 29071, MEMENTO 28347, NICK WHITFIELD 32954, OLDBOY 32533, SCIENCE FICTION 11568, SKELETONS 16219, STORY 19102, SUPER 8 34042, THE CITADEL 4091, THE LADY VANISHES 24811, THRILLER 23568, VANILLA SKY src, edge_attr, dst 35798, has_tags, 32533 10768, has_tags, 32533 10768, has_tags, 16219 23299, has_genre, 24811 23299, has_tags, 16219 23544, has_tags, 32533 23544, has_tags, 24811 978, has_genre, 24811 978, has_tags, 16219 978, has_tags, 24811 13825, has_genre, 24811 13825, has_tags, 16219 29071, has_genre, 24811 29071, has_tags, 16219 32954, has_genre, 24811 32954, has_tags, 16219 11568, directed_by, 28347 11568, release_year, 35798 11568, written_by, 28347 19102, has_genre, 24811 19102, has_tags, 32533 19102, has_tags, 16219 34042, release_year, 18132 4091, has_genre, 24811 4091, release_year, 18132 23568, has_tags, 32533 23568, has_tags, 24811 Question: In what context are NICK WHITFIELD, SUPER 8, and THE CITADEL connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "NICK WHITFIELD", "SUPER 8", "THE CITADEL" ], "valid_edges": [ [ "2010", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE", "has_tags", "STORY" ], [ "GET CARTER", "has_genre", "THRILLER" ], [ "GET CARTER", "has_tags", "STORY" ], [ "INCEPTION", "has_tags", "SCIENCE FICTION" ], [ "INCEPTION", "has_tags", "THRILLER" ], [ "INFERNAL AFFAIRS", "has_genre", "THRILLER" ], [ "INFERNAL AFFAIRS", "has_tags", "STORY" ], [ "INFERNAL AFFAIRS", "has_tags", "THRILLER" ], [ "INSOMNIA", "has_genre", "THRILLER" ], [ "INSOMNIA", "has_tags", "STORY" ], [ "MEMENTO", "has_genre", "THRILLER" ], [ "MEMENTO", "has_tags", "STORY" ], [ "OLDBOY", "has_genre", "THRILLER" ], [ "OLDBOY", "has_tags", "STORY" ], [ "SKELETONS", "directed_by", "NICK WHITFIELD" ], [ "SKELETONS", "release_year", "2010" ], [ "SKELETONS", "written_by", "NICK WHITFIELD" ], [ "SUPER 8", "has_genre", "THRILLER" ], [ "SUPER 8", "has_tags", "SCIENCE FICTION" ], [ "SUPER 8", "has_tags", "STORY" ], [ "THE CITADEL", "release_year", "1938" ], [ "THE LADY VANISHES", "has_genre", "THRILLER" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "VANILLA SKY", "has_tags", "SCIENCE FICTION" ], [ "VANILLA SKY", "has_tags", "THRILLER" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 35845, 2006 3209, A NEW WAVE 33360, CANDY 22824, ICELANDIC 31412, JAR CITY 17302, OF HORSES AND MEN 15582, THE SHOES OF THE FISHERMAN src, edge_attr, dst 3209, release_year, 35845 33360, release_year, 27810 33360, release_year, 35845 31412, in_language, 22824 31412, release_year, 35845 17302, in_language, 22824 15582, release_year, 27810 Question: In what context are A NEW WAVE, OF HORSES AND MEN, and THE SHOES OF THE FISHERMAN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A NEW WAVE", "OF HORSES AND MEN", "THE SHOES OF THE FISHERMAN" ], "valid_edges": [ [ "A NEW WAVE", "release_year", "2006" ], [ "CANDY", "release_year", "1968" ], [ "CANDY", "release_year", "2006" ], [ "JAR CITY", "in_language", "ICELANDIC" ], [ "JAR CITY", "release_year", "2006" ], [ "OF HORSES AND MEN", "in_language", "ICELANDIC" ], [ "THE SHOES OF THE FISHERMAN", "release_year", "1968" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 35935, 2002 27059, CATCH ME IF YOU CAN 14724, CRIME 39881, DAVID MCLEAN 17400, GANGS OF NEW YORK 17272, LEONARDO DICAPRIO 23963, MARIKO KAGA 5586, MARTIN SCORSESE 25658, PALE FLOWER 13081, R 18997, THE DEPARTED 29752, THE STRANGLER src, edge_attr, dst 27059, has_genre, 14724 27059, has_tags, 14724 27059, has_tags, 17272 27059, release_year, 35935 27059, starred_actors, 17272 17400, directed_by, 5586 17400, has_genre, 14724 17400, has_tags, 17272 17400, has_tags, 5586 17400, has_tags, 13081 17400, release_year, 35935 17400, starred_actors, 17272 25658, has_genre, 14724 25658, release_year, 30172 25658, starred_actors, 23963 18997, directed_by, 5586 18997, has_genre, 14724 18997, has_tags, 14724 18997, has_tags, 17272 18997, has_tags, 5586 18997, has_tags, 13081 18997, starred_actors, 17272 29752, release_year, 30172 29752, starred_actors, 39881 Question: For what reason are DAVID MCLEAN, LEONARDO DICAPRIO, and MARIKO KAGA associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DAVID MCLEAN", "LEONARDO DICAPRIO", "MARIKO KAGA" ], "valid_edges": [ [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "LEONARDO DICAPRIO" ], [ "CATCH ME IF YOU CAN", "release_year", "2002" ], [ "CATCH ME IF YOU CAN", "starred_actors", "LEONARDO DICAPRIO" ], [ "GANGS OF NEW YORK", "directed_by", "MARTIN SCORSESE" ], [ "GANGS OF NEW YORK", "has_genre", "CRIME" ], [ "GANGS OF NEW YORK", "has_tags", "LEONARDO DICAPRIO" ], [ "GANGS OF NEW YORK", "has_tags", "MARTIN SCORSESE" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "GANGS OF NEW YORK", "starred_actors", "LEONARDO DICAPRIO" ], [ "PALE FLOWER", "has_genre", "CRIME" ], [ "PALE FLOWER", "release_year", "1964" ], [ "PALE FLOWER", "starred_actors", "MARIKO KAGA" ], [ "THE DEPARTED", "directed_by", "MARTIN SCORSESE" ], [ "THE DEPARTED", "has_genre", "CRIME" ], [ "THE DEPARTED", "has_tags", "CRIME" ], [ "THE DEPARTED", "has_tags", "LEONARDO DICAPRIO" ], [ "THE DEPARTED", "has_tags", "MARTIN SCORSESE" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "starred_actors", "LEONARDO DICAPRIO" ], [ "THE STRANGLER", "release_year", "1964" ], [ "THE STRANGLER", "starred_actors", "DAVID MCLEAN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39813, 1971 37484, 2004 20228, A GOOD OLD FASHIONED ORGY 24039, A GOOD YEAR 39801, A NEW LEAF 26525, ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY 1698, ALFIE 21398, AMERICAN PIE 1546, AN AMERICAN WEREWOLF IN LONDON 36172, AND NOW FOR SOMETHING COMPLETELY DIFFERENT 38136, ARACHNOPHOBIA 39137, AS GOOD AS IT GETS 17133, AS YOU LIKE IT 5658, BAD BOY BUBBY 27816, BANANAS 10045, BD-R 26356, BEAUTY IN TROUBLE 36479, BORN TO DANCE 16452, BORN TO WIN 37616, BORN YESTERDAY 34243, BRIGHT EYES 10361, BYE BYE BIRDIE 19950, CHASING LIBERTY 15721, CIAO, PROFESSORE! 34828, COLD TURKEY 24116, COLLEGE 39887, COME BLOW YOUR HORN 30463, COMEDY 36016, COUSIN BETTE 30433, DELUSIONS OF GRANDEUR 20574, DICK VAN DYKE 21079, DIRTY DEEDS 20474, DIVORCE AMERICAN STYLE 33382, DOM HEMINGWAY 22983, DONA FLOR AND HER TWO HUSBANDS 27563, DOUBLE WEDDING 36212, DRAMA 38250, FATHER OF THE BRIDE 31060, GIGANTIC 11565, GOOD 10113, GOOD ADVICE 26282, GOOD HAIR 21763, GOOD MORNING, VIETNAM 26124, GOOD NEIGHBOR SAM 12502, GOODBYE CHARLIE 17652, GOODBYE, COLUMBUS 6388, HAROLD AND MAUDE 11014, HE'S JUST NOT THAT INTO YOU 35856, HEARTS OF THE WEST 10411, HOW TASTY WAS MY LITTLE FRENCHMAN 141, I HEART HUCKABEES 38304, IN GOOD COMPANY 7575, INTIMATE RELATIONS 25290, JERRY MAGUIRE 6099, JOHNNY DANGEROUSLY 1029, JUDE LAW 17397, KISS ME GOODBYE 19232, KOTCH 21091, LADY LIBERTY 22957, LEAP YEAR 17559, LEGALLY BLONDE 35898, LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS 11903, LET IT RIDE 16121, LITTLE MURDERS 3459, LONESOME JIM 32973, LT. ROBIN CRUSOE, U.S.N. 39913, MATINEE 26718, MEET THE PARENTS 27936, MONSTERS UNIVERSITY 12668, MRS. POLLIFAX-SPY 9435, MURDER AT THE GALLOP 112, MUSIC FROM ANOTHER ROOM 18524, MY BLUE HEAVEN 3027, NIGHT AT THE MUSEUM 1271, NO TIME FOR LOVE 15316, NORMAN LEAR 14797, O BROTHER, WHERE ART THOU? 8935, ONE NIGHT AT MCCOOL'S 10734, ORPHANS 36867, PAPER LION 35289, PARANORMAN 3297, PATCH ADAMS 5958, PERCHED ON A TREE 7053, PLATINUM BLONDE 10026, PLAZA SUITE 21040, PRETTY MAIDS ALL IN A ROW 21462, RAISING ARIZONA 32180, RAT RACE 35122, REVENGE OF THE NERDS 10066, ROMANTIC COMEDY 11370, RUSTLERS' RHAPSODY 21512, SHERLOCK HOLMES 6468, SKIN GAME 8456, SPLASH 3350, SUCH GOOD FRIENDS 29113, SUMMER OF '42 23720, TAKING OFF 6667, THE BIG CHILL 5299, THE BIG STORE 39463, THE BOY FRIEND 26573, THE GOLD RUSH 30181, THE GOOD FAIRY 914, THE GOOD GIRL 14807, THE GOODBYE GIRL 26955, THE HOLIDAY 31283, THE HOUND OF THE BASKERVILLES 27062, THE MILLION DOLLAR DUCK 14272, THE NIGHT THEY RAIDED MINSKY'S 15015, THE OPPOSITE SEX 16236, THE SURE THING 29643, THE TAO OF STEVE 33932, THE WHEELER DEALERS 34860, THIS IS THE NIGHT 6839, TOM MURRAY 17536, TRAFIC 832, TRUE STORIES 31620, UUNO TURHAPURO ARMEIJAN LEIVISSÄ 31, WELL KNOWN 26622, WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME? 36996, WHY BE GOOD? 22756, WINDOW TO PARIS 8184, YOU CAN'T TAKE IT WITH YOU 38863, YOU'LL NEVER GET RICH 5178, YOU'RE A GOOD MAN, CHARLIE BROWN 15808, YOU'VE GOT MAIL src, edge_attr, dst 20228, has_genre, 30463 20228, has_imdb_rating, 11565 24039, has_genre, 30463 24039, has_imdb_rating, 11565 39801, has_genre, 30463 39801, release_year, 39813 26525, has_genre, 30463 26525, has_imdb_rating, 11565 1698, has_genre, 30463 1698, has_genre, 36212 1698, has_tags, 10045 1698, has_tags, 1029 1698, release_year, 37484 1698, starred_actors, 1029 21398, has_genre, 30463 21398, has_imdb_rating, 11565 21398, has_tags, 30463 1546, has_genre, 30463 1546, has_imdb_rating, 11565 36172, has_genre, 30463 36172, has_tags, 30463 36172, release_year, 39813 38136, has_genre, 30463 38136, has_imdb_rating, 11565 38136, has_tags, 30463 39137, has_genre, 30463 39137, has_imdb_rating, 11565 39137, has_tags, 30463 17133, has_genre, 30463 17133, has_imdb_rating, 11565 5658, has_genre, 30463 5658, has_imdb_rating, 11565 27816, has_genre, 30463 27816, has_tags, 30463 27816, release_year, 39813 26356, has_genre, 30463 26356, has_imdb_rating, 11565 36479, has_genre, 30463 36479, has_imdb_rating, 11565 16452, has_genre, 30463 16452, release_year, 39813 37616, has_genre, 30463 37616, has_imdb_rating, 11565 34243, has_genre, 30463 34243, has_imdb_rating, 11565 10361, has_genre, 30463 10361, starred_actors, 20574 19950, has_genre, 30463 19950, has_imdb_rating, 11565 15721, has_genre, 30463 15721, has_imdb_rating, 11565 34828, directed_by, 15316 34828, has_genre, 30463 34828, has_imdb_rating, 11565 34828, has_imdb_votes, 31 34828, release_year, 39813 34828, starred_actors, 20574 34828, written_by, 15316 24116, has_genre, 30463 24116, has_imdb_rating, 11565 39887, has_genre, 30463 39887, written_by, 15316 36016, has_genre, 30463 36016, has_imdb_rating, 11565 30433, has_genre, 30463 30433, release_year, 39813 21079, has_genre, 30463 21079, has_imdb_rating, 11565 21079, has_tags, 30463 20474, has_genre, 30463 20474, starred_actors, 20574 20474, written_by, 15316 33382, has_genre, 30463 33382, has_genre, 36212 33382, starred_actors, 1029 22983, has_genre, 30463 22983, has_imdb_rating, 11565 27563, has_genre, 30463 27563, has_imdb_rating, 11565 38250, has_genre, 30463 38250, has_imdb_rating, 11565 38250, has_tags, 30463 31060, has_genre, 30463 31060, has_imdb_rating, 11565 11565, has_imdb_rating, 11565 10113, has_genre, 30463 10113, has_imdb_rating, 11565 26282, has_genre, 30463 26282, has_imdb_rating, 11565 21763, has_genre, 30463 21763, has_imdb_rating, 11565 26124, has_genre, 30463 26124, has_imdb_rating, 11565 12502, has_genre, 30463 12502, has_imdb_rating, 11565 17652, has_genre, 30463 17652, has_imdb_rating, 11565 6388, has_genre, 30463 6388, release_year, 39813 11014, has_genre, 30463 11014, has_imdb_rating, 11565 35856, has_genre, 30463 35856, has_imdb_rating, 11565 10411, has_genre, 30463 10411, release_year, 39813 141, has_genre, 30463 141, has_tags, 30463 141, has_tags, 1029 141, release_year, 37484 38304, has_genre, 30463 38304, has_imdb_rating, 11565 7575, has_genre, 30463 7575, has_imdb_rating, 11565 25290, has_genre, 30463 25290, has_imdb_rating, 11565 25290, has_tags, 30463 6099, has_genre, 30463 6099, has_imdb_rating, 11565 17397, has_genre, 30463 17397, has_imdb_rating, 11565 19232, has_genre, 30463 19232, release_year, 39813 21091, has_genre, 30463 21091, release_year, 39813 22957, has_genre, 30463 22957, has_imdb_rating, 11565 17559, has_genre, 30463 17559, has_imdb_rating, 11565 17559, has_tags, 30463 35898, has_genre, 30463 35898, has_tags, 1029 35898, has_tags, 10734 35898, release_year, 37484 11903, has_genre, 30463 11903, has_imdb_rating, 11565 16121, has_genre, 30463 16121, release_year, 39813 3459, has_genre, 30463 3459, has_imdb_rating, 11565 32973, has_genre, 30463 32973, has_tags, 20574 32973, starred_actors, 20574 39913, has_genre, 30463 39913, has_imdb_rating, 11565 26718, has_genre, 30463 26718, has_imdb_rating, 11565 26718, has_tags, 30463 27936, has_genre, 30463 27936, has_imdb_rating, 11565 27936, has_tags, 30463 12668, has_genre, 30463 12668, release_year, 39813 9435, has_genre, 30463 9435, has_imdb_rating, 11565 112, has_genre, 30463 112, has_genre, 36212 112, has_tags, 1029 112, starred_actors, 1029 18524, has_genre, 30463 18524, has_imdb_rating, 11565 3027, has_genre, 30463 3027, has_tags, 20574 3027, starred_actors, 20574 1271, has_genre, 30463 1271, has_imdb_rating, 11565 14797, has_genre, 30463 14797, has_imdb_rating, 11565 14797, has_tags, 30463 8935, has_genre, 30463 8935, has_imdb_rating, 11565 10734, has_genre, 30463 36867, has_genre, 30463 36867, has_imdb_rating, 11565 35289, has_genre, 30463 35289, has_imdb_rating, 11565 3297, has_genre, 30463 3297, has_imdb_rating, 11565 5958, has_genre, 30463 5958, release_year, 39813 7053, has_genre, 30463 7053, has_imdb_votes, 31 10026, has_genre, 30463 10026, release_year, 39813 21040, has_genre, 30463 21040, release_year, 39813 21462, has_genre, 30463 21462, has_imdb_rating, 11565 21462, has_tags, 30463 32180, has_genre, 30463 32180, has_imdb_rating, 11565 32180, has_tags, 30463 35122, has_genre, 30463 35122, has_imdb_rating, 11565 10066, has_genre, 30463 11370, has_genre, 30463 11370, has_imdb_rating, 11565 21512, has_tags, 30463 21512, has_tags, 1029 21512, has_tags, 21512 21512, starred_actors, 1029 6468, has_genre, 30463 6468, release_year, 39813 8456, has_genre, 30463 8456, has_imdb_rating, 11565 3350, has_genre, 30463 3350, has_imdb_rating, 11565 3350, release_year, 39813 29113, has_genre, 30463 29113, release_year, 39813 23720, has_genre, 30463 23720, release_year, 39813 6667, has_genre, 30463 6667, has_imdb_rating, 11565 5299, has_genre, 30463 5299, has_imdb_rating, 11565 39463, has_genre, 30463 39463, release_year, 39813 26573, has_genre, 30463 26573, has_tags, 30463 26573, starred_actors, 6839 30181, has_genre, 30463 30181, has_imdb_rating, 11565 914, has_genre, 30463 914, has_imdb_rating, 11565 14807, has_genre, 30463 14807, has_imdb_rating, 11565 26955, has_genre, 30463 26955, has_tags, 10045 26955, has_tags, 1029 26955, has_tags, 10066 26955, starred_actors, 1029 31283, has_genre, 30463 31283, has_tags, 21512 27062, has_genre, 30463 27062, release_year, 39813 14272, has_genre, 30463 14272, written_by, 15316 15015, has_genre, 30463 15015, has_imdb_rating, 11565 16236, has_genre, 30463 16236, has_imdb_rating, 11565 29643, has_genre, 30463 29643, has_imdb_rating, 11565 33932, has_genre, 30463 33932, has_imdb_rating, 11565 34860, has_genre, 30463 34860, has_imdb_rating, 11565 17536, has_genre, 30463 17536, has_imdb_rating, 11565 17536, release_year, 39813 832, has_genre, 30463 832, has_imdb_rating, 11565 31620, has_genre, 30463 31620, has_imdb_votes, 31 26622, has_genre, 30463 26622, release_year, 39813 36996, has_genre, 30463 36996, has_imdb_rating, 11565 22756, has_genre, 30463 22756, has_imdb_rating, 11565 8184, has_genre, 30463 8184, has_imdb_rating, 11565 38863, has_genre, 30463 38863, has_imdb_rating, 11565 5178, has_genre, 30463 5178, has_imdb_rating, 11565 15808, has_genre, 30463 15808, has_imdb_rating, 11565 15808, has_tags, 30463 Question: In what context are COLD TURKEY, JUDE LAW, and TOM MURRAY connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "COLD TURKEY", "JUDE LAW", "TOM MURRAY" ], "valid_edges": [ [ "A GOOD OLD FASHIONED ORGY", "has_genre", "COMEDY" ], [ "A GOOD OLD FASHIONED ORGY", "has_imdb_rating", "GOOD" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "has_imdb_rating", "GOOD" ], [ "A NEW LEAF", "has_genre", "COMEDY" ], [ "A NEW LEAF", "release_year", "1971" ], [ "ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY", "has_genre", "COMEDY" ], [ "ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY", "has_imdb_rating", "GOOD" ], [ "ALFIE", "has_genre", "COMEDY" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "has_tags", "BD-R" ], [ "ALFIE", "has_tags", "JUDE LAW" ], [ "ALFIE", "release_year", "2004" ], [ "ALFIE", "starred_actors", "JUDE LAW" ], [ "AMERICAN PIE", "has_genre", "COMEDY" ], [ "AMERICAN PIE", "has_imdb_rating", "GOOD" ], [ "AMERICAN PIE", "has_tags", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_genre", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_imdb_rating", "GOOD" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "has_genre", "COMEDY" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "has_tags", "COMEDY" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "release_year", "1971" ], [ "ARACHNOPHOBIA", "has_genre", "COMEDY" ], [ "ARACHNOPHOBIA", "has_imdb_rating", "GOOD" ], [ "ARACHNOPHOBIA", "has_tags", "COMEDY" ], [ "AS GOOD AS IT GETS", "has_genre", "COMEDY" ], [ "AS GOOD AS IT GETS", "has_imdb_rating", "GOOD" ], [ "AS GOOD AS IT GETS", "has_tags", "COMEDY" ], [ "AS YOU LIKE IT", "has_genre", "COMEDY" ], [ "AS YOU LIKE IT", "has_imdb_rating", "GOOD" ], [ "BAD BOY BUBBY", "has_genre", "COMEDY" ], [ "BAD BOY BUBBY", "has_imdb_rating", "GOOD" ], [ "BANANAS", "has_genre", "COMEDY" ], [ "BANANAS", "has_tags", "COMEDY" ], [ "BANANAS", "release_year", "1971" ], [ "BEAUTY IN TROUBLE", "has_genre", "COMEDY" ], [ "BEAUTY IN TROUBLE", "has_imdb_rating", "GOOD" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BORN TO DANCE", "has_imdb_rating", "GOOD" ], [ "BORN TO WIN", "has_genre", "COMEDY" ], [ "BORN TO WIN", "release_year", "1971" ], [ "BORN YESTERDAY", "has_genre", "COMEDY" ], [ "BORN YESTERDAY", "has_imdb_rating", "GOOD" ], [ "BRIGHT EYES", "has_genre", "COMEDY" ], [ "BRIGHT EYES", "has_imdb_rating", "GOOD" ], [ "BYE BYE BIRDIE", "has_genre", "COMEDY" ], [ "BYE BYE BIRDIE", "starred_actors", "DICK VAN DYKE" ], [ "CHASING LIBERTY", "has_genre", "COMEDY" ], [ "CHASING LIBERTY", "has_imdb_rating", "GOOD" ], [ "CIAO, PROFESSORE!", "has_genre", "COMEDY" ], [ "CIAO, PROFESSORE!", "has_imdb_rating", "GOOD" ], [ "COLD TURKEY", "directed_by", "NORMAN LEAR" ], [ "COLD TURKEY", "has_genre", "COMEDY" ], [ "COLD TURKEY", "has_imdb_rating", "GOOD" ], [ "COLD TURKEY", "has_imdb_votes", "WELL KNOWN" ], [ "COLD TURKEY", "release_year", "1971" ], [ "COLD TURKEY", "starred_actors", "DICK VAN DYKE" ], [ "COLD TURKEY", "written_by", "NORMAN LEAR" ], [ "COLLEGE", "has_genre", "COMEDY" ], [ "COLLEGE", "has_imdb_rating", "GOOD" ], [ "COME BLOW YOUR HORN", "has_genre", "COMEDY" ], [ "COME BLOW YOUR HORN", "written_by", "NORMAN LEAR" ], [ "COUSIN BETTE", "has_genre", "COMEDY" ], [ "COUSIN BETTE", "has_imdb_rating", "GOOD" ], [ "DELUSIONS OF GRANDEUR", "has_genre", "COMEDY" ], [ "DELUSIONS OF GRANDEUR", "release_year", "1971" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_imdb_rating", "GOOD" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIVORCE AMERICAN STYLE", "has_genre", "COMEDY" ], [ "DIVORCE AMERICAN STYLE", "starred_actors", "DICK VAN DYKE" ], [ "DIVORCE AMERICAN STYLE", "written_by", "NORMAN LEAR" ], [ "DOM HEMINGWAY", "has_genre", "COMEDY" ], [ "DOM HEMINGWAY", "has_genre", "DRAMA" ], [ "DOM HEMINGWAY", "starred_actors", "JUDE LAW" ], [ "DONA FLOR AND HER TWO HUSBANDS", "has_genre", "COMEDY" ], [ "DONA FLOR AND HER TWO HUSBANDS", "has_imdb_rating", "GOOD" ], [ "DOUBLE WEDDING", "has_genre", "COMEDY" ], [ "DOUBLE WEDDING", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_genre", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_tags", "COMEDY" ], [ "GIGANTIC", "has_genre", "COMEDY" ], [ "GIGANTIC", "has_imdb_rating", "GOOD" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD ADVICE", "has_genre", "COMEDY" ], [ "GOOD ADVICE", "has_imdb_rating", "GOOD" ], [ "GOOD HAIR", "has_genre", "COMEDY" ], [ "GOOD HAIR", "has_imdb_rating", "GOOD" ], [ "GOOD MORNING, VIETNAM", "has_genre", "COMEDY" ], [ "GOOD MORNING, VIETNAM", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "has_genre", "COMEDY" ], [ "GOOD NEIGHBOR SAM", "has_imdb_rating", "GOOD" ], [ "GOODBYE CHARLIE", "has_genre", "COMEDY" ], [ "GOODBYE CHARLIE", "has_imdb_rating", "GOOD" ], [ "GOODBYE, COLUMBUS", "has_genre", "COMEDY" ], [ "GOODBYE, COLUMBUS", "has_imdb_rating", "GOOD" ], [ "HAROLD AND MAUDE", "has_genre", "COMEDY" ], [ "HAROLD AND MAUDE", "release_year", "1971" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "COMEDY" ], [ "HE'S JUST NOT THAT INTO YOU", "has_imdb_rating", "GOOD" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_imdb_rating", "GOOD" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "has_genre", "COMEDY" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "release_year", "1971" ], [ "I HEART HUCKABEES", "has_genre", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "JUDE LAW" ], [ "I HEART HUCKABEES", "release_year", "2004" ], [ "IN GOOD COMPANY", "has_genre", "COMEDY" ], [ "IN GOOD COMPANY", "has_imdb_rating", "GOOD" ], [ "INTIMATE RELATIONS", "has_genre", "COMEDY" ], [ "INTIMATE RELATIONS", "has_imdb_rating", "GOOD" ], [ "JERRY MAGUIRE", "has_genre", "COMEDY" ], [ "JERRY MAGUIRE", "has_imdb_rating", "GOOD" ], [ "JERRY MAGUIRE", "has_tags", "COMEDY" ], [ "JOHNNY DANGEROUSLY", "has_genre", "COMEDY" ], [ "JOHNNY DANGEROUSLY", "has_imdb_rating", "GOOD" ], [ "KISS ME GOODBYE", "has_genre", "COMEDY" ], [ "KISS ME GOODBYE", "has_imdb_rating", "GOOD" ], [ "KOTCH", "has_genre", "COMEDY" ], [ "KOTCH", "release_year", "1971" ], [ "LADY LIBERTY", "has_genre", "COMEDY" ], [ "LADY LIBERTY", "release_year", "1971" ], [ "LEAP YEAR", "has_genre", "COMEDY" ], [ "LEAP YEAR", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_genre", "COMEDY" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_tags", "JUDE LAW" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_tags", "ORPHANS" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "release_year", "2004" ], [ "LET IT RIDE", "has_genre", "COMEDY" ], [ "LET IT RIDE", "has_imdb_rating", "GOOD" ], [ "LITTLE MURDERS", "has_genre", "COMEDY" ], [ "LITTLE MURDERS", "release_year", "1971" ], [ "LONESOME JIM", "has_genre", "COMEDY" ], [ "LONESOME JIM", "has_imdb_rating", "GOOD" ], [ "LT. ROBIN CRUSOE, U.S.N.", "has_genre", "COMEDY" ], [ "LT. ROBIN CRUSOE, U.S.N.", "has_tags", "DICK VAN DYKE" ], [ "LT. ROBIN CRUSOE, U.S.N.", "starred_actors", "DICK VAN DYKE" ], [ "MATINEE", "has_genre", "COMEDY" ], [ "MATINEE", "has_imdb_rating", "GOOD" ], [ "MEET THE PARENTS", "has_genre", "COMEDY" ], [ "MEET THE PARENTS", "has_imdb_rating", "GOOD" ], [ "MEET THE PARENTS", "has_tags", "COMEDY" ], [ "MONSTERS UNIVERSITY", "has_genre", "COMEDY" ], [ "MONSTERS UNIVERSITY", "has_imdb_rating", "GOOD" ], [ "MONSTERS UNIVERSITY", "has_tags", "COMEDY" ], [ "MRS. POLLIFAX-SPY", "has_genre", "COMEDY" ], [ "MRS. POLLIFAX-SPY", "release_year", "1971" ], [ "MURDER AT THE GALLOP", "has_genre", "COMEDY" ], [ "MURDER AT THE GALLOP", "has_imdb_rating", "GOOD" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "COMEDY" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "DRAMA" ], [ "MUSIC FROM ANOTHER ROOM", "has_tags", "JUDE LAW" ], [ "MUSIC FROM ANOTHER ROOM", "starred_actors", "JUDE LAW" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "has_imdb_rating", "GOOD" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "has_tags", "DICK VAN DYKE" ], [ "NIGHT AT THE MUSEUM", "starred_actors", "DICK VAN DYKE" ], [ "NO TIME FOR LOVE", "has_genre", "COMEDY" ], [ "NO TIME FOR LOVE", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "has_genre", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "has_imdb_rating", "GOOD" ], [ "ORPHANS", "has_genre", "COMEDY" ], [ "PAPER LION", "has_genre", "COMEDY" ], [ "PAPER LION", "has_imdb_rating", "GOOD" ], [ "PARANORMAN", "has_genre", "COMEDY" ], [ "PARANORMAN", "has_imdb_rating", "GOOD" ], [ "PATCH ADAMS", "has_genre", "COMEDY" ], [ "PATCH ADAMS", "has_imdb_rating", "GOOD" ], [ "PERCHED ON A TREE", "has_genre", "COMEDY" ], [ "PERCHED ON A TREE", "release_year", "1971" ], [ "PLATINUM BLONDE", "has_genre", "COMEDY" ], [ "PLATINUM BLONDE", "has_imdb_votes", "WELL KNOWN" ], [ "PLAZA SUITE", "has_genre", "COMEDY" ], [ "PLAZA SUITE", "release_year", "1971" ], [ "PRETTY MAIDS ALL IN A ROW", "has_genre", "COMEDY" ], [ "PRETTY MAIDS ALL IN A ROW", "release_year", "1971" ], [ "RAISING ARIZONA", "has_genre", "COMEDY" ], [ "RAISING ARIZONA", "has_imdb_rating", "GOOD" ], [ "RAISING ARIZONA", "has_tags", "COMEDY" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_imdb_rating", "GOOD" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "REVENGE OF THE NERDS", "has_genre", "COMEDY" ], [ "REVENGE OF THE NERDS", "has_imdb_rating", "GOOD" ], [ "ROMANTIC COMEDY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_imdb_rating", "GOOD" ], [ "SHERLOCK HOLMES", "has_tags", "COMEDY" ], [ "SHERLOCK HOLMES", "has_tags", "JUDE LAW" ], [ "SHERLOCK HOLMES", "has_tags", "SHERLOCK HOLMES" ], [ "SHERLOCK HOLMES", "starred_actors", "JUDE LAW" ], [ "SKIN GAME", "has_genre", "COMEDY" ], [ "SKIN GAME", "release_year", "1971" ], [ "SPLASH", "has_genre", "COMEDY" ], [ "SPLASH", "has_imdb_rating", "GOOD" ], [ "SUCH GOOD FRIENDS", "has_genre", "COMEDY" ], [ "SUCH GOOD FRIENDS", "has_imdb_rating", "GOOD" ], [ "SUCH GOOD FRIENDS", "release_year", "1971" ], [ "SUMMER OF '42", "has_genre", "COMEDY" ], [ "SUMMER OF '42", "release_year", "1971" ], [ "TAKING OFF", "has_genre", "COMEDY" ], [ "TAKING OFF", "release_year", "1971" ], [ "THE BIG CHILL", "has_genre", "COMEDY" ], [ "THE BIG CHILL", "has_imdb_rating", "GOOD" ], [ "THE BIG STORE", "has_genre", "COMEDY" ], [ "THE BIG STORE", "has_imdb_rating", "GOOD" ], [ "THE BOY FRIEND", "has_genre", "COMEDY" ], [ "THE BOY FRIEND", "release_year", "1971" ], [ "THE GOLD RUSH", "has_genre", "COMEDY" ], [ "THE GOLD RUSH", "has_tags", "COMEDY" ], [ "THE GOLD RUSH", "starred_actors", "TOM MURRAY" ], [ "THE GOOD FAIRY", "has_genre", "COMEDY" ], [ "THE GOOD FAIRY", "has_imdb_rating", "GOOD" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "has_imdb_rating", "GOOD" ], [ "THE GOODBYE GIRL", "has_genre", "COMEDY" ], [ "THE GOODBYE GIRL", "has_imdb_rating", "GOOD" ], [ "THE HOLIDAY", "has_genre", "COMEDY" ], [ "THE HOLIDAY", "has_tags", "BD-R" ], [ "THE HOLIDAY", "has_tags", "JUDE LAW" ], [ "THE HOLIDAY", "has_tags", "ROMANTIC COMEDY" ], [ "THE HOLIDAY", "starred_actors", "JUDE LAW" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "COMEDY" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "SHERLOCK HOLMES" ], [ "THE MILLION DOLLAR DUCK", "has_genre", "COMEDY" ], [ "THE MILLION DOLLAR DUCK", "release_year", "1971" ], [ "THE NIGHT THEY RAIDED MINSKY'S", "has_genre", "COMEDY" ], [ "THE NIGHT THEY RAIDED MINSKY'S", "written_by", "NORMAN LEAR" ], [ "THE OPPOSITE SEX", "has_genre", "COMEDY" ], [ "THE OPPOSITE SEX", "has_imdb_rating", "GOOD" ], [ "THE SURE THING", "has_genre", "COMEDY" ], [ "THE SURE THING", "has_imdb_rating", "GOOD" ], [ "THE TAO OF STEVE", "has_genre", "COMEDY" ], [ "THE TAO OF STEVE", "has_imdb_rating", "GOOD" ], [ "THE WHEELER DEALERS", "has_genre", "COMEDY" ], [ "THE WHEELER DEALERS", "has_imdb_rating", "GOOD" ], [ "THIS IS THE NIGHT", "has_genre", "COMEDY" ], [ "THIS IS THE NIGHT", "has_imdb_rating", "GOOD" ], [ "TRAFIC", "has_genre", "COMEDY" ], [ "TRAFIC", "has_imdb_rating", "GOOD" ], [ "TRAFIC", "release_year", "1971" ], [ "TRUE STORIES", "has_genre", "COMEDY" ], [ "TRUE STORIES", "has_imdb_rating", "GOOD" ], [ "UUNO TURHAPURO ARMEIJAN LEIVISSÄ", "has_genre", "COMEDY" ], [ "UUNO TURHAPURO ARMEIJAN LEIVISSÄ", "has_imdb_votes", "WELL KNOWN" ], [ "WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME?", "has_genre", "COMEDY" ], [ "WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME?", "release_year", "1971" ], [ "WHY BE GOOD?", "has_genre", "COMEDY" ], [ "WHY BE GOOD?", "has_imdb_rating", "GOOD" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "has_imdb_rating", "GOOD" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_imdb_rating", "GOOD" ], [ "YOU'LL NEVER GET RICH", "has_genre", "COMEDY" ], [ "YOU'LL NEVER GET RICH", "has_imdb_rating", "GOOD" ], [ "YOU'RE A GOOD MAN, CHARLIE BROWN", "has_genre", "COMEDY" ], [ "YOU'RE A GOOD MAN, CHARLIE BROWN", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "has_genre", "COMEDY" ], [ "YOU'VE GOT MAIL", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "has_tags", "COMEDY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35187, 1948 3863, 1962 40009, A FOREIGN AFFAIR 16566, A MONKEY IN WINTER 18595, HENRI VERNEUIL 25397, I AS IN ICARUS 12473, PITFALL 17361, THE BRAIN THAT WOULDN'T DIE src, edge_attr, dst 40009, release_year, 35187 16566, directed_by, 18595 16566, has_tags, 18595 16566, release_year, 3863 25397, directed_by, 18595 25397, written_by, 18595 12473, release_year, 35187 12473, release_year, 3863 17361, release_year, 3863 Question: In what context are A FOREIGN AFFAIR, I AS IN ICARUS, and THE BRAIN THAT WOULDN'T DIE connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A FOREIGN AFFAIR", "I AS IN ICARUS", "THE BRAIN THAT WOULDN'T DIE" ], "valid_edges": [ [ "A FOREIGN AFFAIR", "release_year", "1948" ], [ "A MONKEY IN WINTER", "directed_by", "HENRI VERNEUIL" ], [ "A MONKEY IN WINTER", "has_tags", "HENRI VERNEUIL" ], [ "A MONKEY IN WINTER", "release_year", "1962" ], [ "I AS IN ICARUS", "directed_by", "HENRI VERNEUIL" ], [ "I AS IN ICARUS", "written_by", "HENRI VERNEUIL" ], [ "PITFALL", "release_year", "1948" ], [ "PITFALL", "release_year", "1962" ], [ "THE BRAIN THAT WOULDN'T DIE", "release_year", "1962" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 36647, 8 WOMEN 11957, 9 DEAD GAY GUYS 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 68, ADMISSION 33534, AFTERNOON DELIGHT 17111, ALI G INDAHOUSE 22569, ALL ABOUT THE BENJAMINS 28458, ALL IS BRIGHT 16113, ANALYZE THAT 32612, ANNA ODELL 7302, AS COOL AS I AM 35314, AUSTIN POWERS IN GOLDMEMBER 29535, AVENGING ANGELO 23899, BAD COMPANY 36819, BARBERSHOP 15433, BEND IT LIKE BECKHAM 39619, BIG FAT LIAR 8732, BIG TROUBLE 27128, BOAT TRIP 32620, BUBBA HO-TEP 14572, BUYING THE COW 27929, CABIN FEVER 23286, CARNAGE 20073, CHERISH 10349, CHICAGO 32644, CHINESE ODYSSEY 2002 1267, CLOSER TO THE MOON 30463, COMEDY 21391, CRACKERJACK 30019, CROSSROADS 21730, DAY OF THE WACKO 19179, DEATH TO SMOOCHY 29309, DELIVERY MAN 21079, DIRTY DEEDS 33382, DOM HEMINGWAY 13792, DON JON 36212, DRAMA 25651, DUMMY 26815, EIGHT CRAZY NIGHTS 38543, EIGHT LEGGED FREAKS 28256, FILTH 27539, FRANK MCKLUSKY, C.I. 29241, FRIDAY AFTER NEXT 5287, FROZEN 21415, GREGORY GO BOOM 10990, HEARTLANDS 3829, HERO 15629, HOME ALONE 4 21886, HOME ROOM 22069, I SPY 27919, I'M WITH LUCY 16371, ICE AGE 17197, IGBY GOES DOWN 15909, INSTRUCTIONS NOT INCLUDED 33001, JUST A KISS 2204, JUWANNA MANN 31245, KAL HO NAA HO 32010, KISS THE BRIDE 12137, LIFE OR SOMETHING LIKE IT 28832, LIFE WITHOUT DICK 16155, LOVE LIZA 9812, MAID IN MANHATTAN 4270, MEN WITH BROOMS 36083, MIRANDA 20803, MR. DEEDS 22064, MY BIG FAT GREEK WEDDING 4887, MY LEFT EYE SEES GHOSTS 35262, MY MOTHER LIKES WOMEN 35794, NOVO 1493, NOW YOU KNOW 2721, OCCIDENT 4582, ONCE UPON A TIME IN THE MIDLANDS 39121, ONE CHANCE 37178, ORANGE COUNTY 25824, PARADISE 27117, PASSIONADA 9976, PIPE DREAM 7136, PRINCE AVALANCHE 3688, PUMPKIN 34602, PUNCH-DRUNK LOVE 21890, R.S.V.P. 25769, ROGER DODGER 25243, SAVING MR. BANKS 12987, SCOOBY-DOO 15252, SCREWED IN TALLINN 19244, SERVING SARA 6603, SEX IS COMEDY 26261, SHOWTIME 15043, SLACKERS 25151, SNOW DOGS 24961, SORORITY BOYS 35843, SPUN 5170, STEALING HARVARD 15100, SUPER SUCKER 9276, SWEET HOME ALABAMA 26790, SWEPT AWAY 36316, THE ADVENTURES OF PLUTO NASH 3961, THE AMAZING CATFISH 2316, THE ANARCHIST COOKBOOK 304, THE BANGER SISTERS 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 914, THE GOOD GIRL 26531, THE GURU 24302, THE HOT CHICK 13534, THE IMPORTANCE OF BEING EARNEST 2147, THE MAN WITHOUT A PAST 6908, THE MASTER OF DISGUISE 295, THE NEW GUY 1192, THE ONE AND ONLY 4335, THE PRETTY ONE 39078, THE REUNION 31401, THE RULES OF ATTRACTION 30746, THE SECRET LIFE OF WALTER MITTY 32975, THE SPECTACULAR NOW 7052, THE SWEETEST THING 34172, THE TUXEDO 34916, THE WAY WAY BACK 22625, TOGETHER 10720, TRIGGERMEN 26275, TRUST ME 9612, TWO WEEKS NOTICE 13214, UNCONDITIONAL LOVE 16991, UNDERCOVER BROTHER 21576, WAKING UP IN RENO 37568, WELCOME TO COLLINWOOD 39802, WHEN IN ROME src, edge_attr, dst 4310, has_genre, 30463 4310, has_genre, 36212 4310, release_year, 35935 9408, has_genre, 30463 9408, has_tags, 30463 9408, release_year, 35935 36647, has_genre, 30463 36647, release_year, 35935 11957, has_genre, 30463 11957, release_year, 35935 6008, has_genre, 30463 6008, has_genre, 36212 6008, has_tags, 30463 6008, has_tags, 36212 6008, release_year, 35935 37599, has_genre, 30463 37599, has_genre, 36212 37599, has_tags, 30463 37599, has_tags, 36212 37599, release_year, 35935 68, has_genre, 30463 68, has_genre, 36212 68, has_tags, 30463 33534, has_genre, 30463 33534, has_genre, 36212 17111, has_genre, 30463 17111, release_year, 35935 22569, has_genre, 30463 22569, has_tags, 30463 22569, release_year, 35935 28458, has_genre, 30463 28458, has_genre, 36212 16113, has_genre, 30463 16113, has_tags, 30463 16113, release_year, 35935 7302, has_genre, 30463 7302, has_genre, 36212 35314, has_genre, 30463 35314, has_tags, 30463 35314, release_year, 35935 29535, has_genre, 30463 29535, release_year, 35935 23899, has_genre, 30463 23899, release_year, 35935 36819, has_genre, 30463 36819, release_year, 35935 15433, has_genre, 30463 15433, has_genre, 36212 15433, release_year, 35935 39619, has_genre, 30463 39619, release_year, 35935 8732, has_genre, 30463 8732, release_year, 35935 27128, has_genre, 30463 27128, release_year, 35935 32620, has_genre, 30463 32620, has_tags, 30463 32620, release_year, 35935 14572, has_genre, 30463 14572, release_year, 35935 27929, has_genre, 30463 27929, release_year, 35935 23286, has_genre, 30463 23286, has_genre, 36212 23286, release_year, 35935 20073, has_genre, 30463 20073, has_genre, 36212 20073, release_year, 35935 10349, has_genre, 30463 10349, has_genre, 36212 10349, release_year, 35935 32644, has_genre, 30463 32644, release_year, 35935 1267, has_genre, 30463 1267, has_genre, 36212 1267, has_tags, 30463 21391, has_genre, 30463 21391, release_year, 35935 30019, has_genre, 30463 30019, has_genre, 36212 30019, release_year, 35935 21730, has_genre, 30463 21730, has_genre, 36212 21730, release_year, 35935 19179, has_genre, 30463 19179, release_year, 35935 29309, has_genre, 30463 29309, has_genre, 36212 29309, has_tags, 36212 21079, has_genre, 30463 21079, has_tags, 30463 21079, release_year, 35935 33382, has_genre, 30463 33382, has_genre, 36212 13792, has_genre, 30463 13792, has_genre, 36212 25651, has_genre, 30463 25651, has_genre, 36212 25651, release_year, 35935 26815, has_genre, 30463 26815, release_year, 35935 38543, has_genre, 30463 38543, release_year, 35935 28256, has_genre, 30463 28256, has_genre, 36212 27539, has_genre, 30463 27539, release_year, 35935 29241, has_genre, 30463 29241, release_year, 35935 5287, has_genre, 30463 5287, has_genre, 36212 21415, has_genre, 30463 21415, has_genre, 36212 10990, has_genre, 30463 10990, has_genre, 36212 10990, release_year, 35935 3829, has_genre, 30463 3829, has_genre, 36212 3829, release_year, 35935 15629, has_genre, 30463 15629, release_year, 35935 21886, release_year, 35935 22069, has_genre, 30463 22069, has_tags, 30463 22069, release_year, 35935 27919, has_genre, 30463 27919, release_year, 35935 16371, has_genre, 30463 16371, has_tags, 30463 16371, release_year, 35935 17197, has_genre, 30463 17197, has_genre, 36212 17197, release_year, 35935 15909, has_genre, 30463 15909, has_genre, 36212 33001, has_genre, 30463 33001, release_year, 35935 2204, has_genre, 30463 2204, release_year, 35935 31245, has_genre, 30463 31245, has_genre, 36212 32010, has_genre, 30463 32010, release_year, 35935 12137, has_genre, 30463 12137, release_year, 35935 28832, has_genre, 30463 28832, release_year, 35935 16155, has_genre, 30463 16155, release_year, 35935 9812, has_genre, 30463 9812, release_year, 35935 4270, has_genre, 30463 4270, release_year, 35935 36083, has_genre, 30463 36083, release_year, 35935 20803, has_genre, 30463 20803, release_year, 35935 22064, has_genre, 30463 22064, has_tags, 30463 22064, release_year, 35935 4887, has_genre, 30463 4887, release_year, 35935 35262, has_genre, 30463 35262, release_year, 35935 35794, has_genre, 30463 35794, release_year, 35935 1493, has_genre, 30463 1493, release_year, 35935 2721, has_genre, 30463 2721, release_year, 35935 4582, has_genre, 30463 4582, release_year, 35935 39121, has_genre, 30463 39121, has_genre, 36212 37178, has_genre, 30463 37178, release_year, 35935 25824, has_genre, 30463 25824, has_genre, 36212 27117, has_genre, 30463 27117, release_year, 35935 9976, has_genre, 30463 9976, release_year, 35935 7136, has_genre, 30463 7136, has_genre, 36212 3688, has_genre, 30463 3688, release_year, 35935 34602, has_genre, 30463 34602, has_genre, 36212 34602, has_tags, 30463 34602, release_year, 35935 21890, has_genre, 30463 21890, release_year, 35935 25769, has_genre, 30463 25769, has_genre, 36212 25769, release_year, 35935 25243, has_genre, 30463 25243, has_genre, 36212 12987, has_genre, 30463 12987, release_year, 35935 15252, has_genre, 30463 15252, has_genre, 36212 19244, has_genre, 30463 19244, release_year, 35935 6603, has_genre, 30463 6603, release_year, 35935 26261, has_genre, 30463 26261, release_year, 35935 15043, has_genre, 30463 15043, release_year, 35935 25151, has_genre, 30463 25151, release_year, 35935 24961, has_genre, 30463 24961, release_year, 35935 35843, has_genre, 30463 35843, has_genre, 36212 35843, release_year, 35935 5170, has_genre, 30463 5170, release_year, 35935 15100, has_genre, 30463 15100, release_year, 35935 9276, has_genre, 30463 9276, release_year, 35935 26790, has_genre, 30463 26790, has_genre, 36212 26790, release_year, 35935 36316, has_genre, 30463 36316, release_year, 35935 3961, has_genre, 30463 3961, has_genre, 36212 2316, has_genre, 30463 2316, has_genre, 36212 2316, release_year, 35935 304, has_genre, 30463 304, release_year, 35935 11696, has_genre, 30463 11696, has_genre, 36212 11696, release_year, 35935 3324, has_genre, 30463 3324, has_genre, 36212 3324, release_year, 35935 914, has_genre, 30463 914, release_year, 35935 26531, has_genre, 30463 26531, release_year, 35935 24302, has_genre, 30463 24302, has_tags, 30463 24302, release_year, 35935 13534, has_genre, 30463 13534, has_genre, 36212 13534, release_year, 35935 2147, has_genre, 30463 2147, has_genre, 36212 2147, has_tags, 36212 2147, release_year, 35935 6908, has_genre, 30463 6908, release_year, 35935 295, has_genre, 30463 295, release_year, 35935 1192, has_genre, 30463 1192, release_year, 35935 4335, has_genre, 30463 4335, has_genre, 36212 39078, directed_by, 32612 39078, has_genre, 36212 39078, written_by, 32612 31401, has_genre, 30463 31401, has_genre, 36212 31401, release_year, 35935 30746, has_genre, 30463 30746, has_genre, 36212 32975, has_genre, 30463 32975, has_genre, 36212 7052, has_genre, 30463 7052, has_tags, 30463 7052, release_year, 35935 34172, has_genre, 30463 34172, has_tags, 30463 34172, release_year, 35935 34916, has_genre, 30463 34916, has_genre, 36212 34916, has_tags, 36212 22625, has_genre, 30463 22625, has_genre, 36212 10720, has_genre, 30463 10720, release_year, 35935 26275, has_genre, 30463 26275, has_genre, 36212 9612, has_genre, 30463 9612, release_year, 35935 13214, has_genre, 30463 13214, release_year, 35935 16991, has_genre, 30463 16991, release_year, 35935 21576, has_genre, 30463 21576, release_year, 35935 37568, has_genre, 30463 37568, has_tags, 30463 37568, release_year, 35935 39802, has_genre, 30463 39802, release_year, 35935 Question: In what context are ANNA ODELL, HOME ROOM, and KAL HO NAA HO connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANNA ODELL", "HOME ROOM", "KAL HO NAA HO" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "has_genre", "DRAMA" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_genre", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "release_year", "2002" ], [ "9 DEAD GAY GUYS", "has_genre", "COMEDY" ], [ "9 DEAD GAY GUYS", "release_year", "2002" ], [ "ABOUT A BOY", "has_genre", "COMEDY" ], [ "ABOUT A BOY", "has_genre", "DRAMA" ], [ "ABOUT A BOY", "has_tags", "COMEDY" ], [ "ABOUT A BOY", "has_tags", "DRAMA" ], [ "ABOUT A BOY", "release_year", "2002" ], [ "ABOUT SCHMIDT", "has_genre", "COMEDY" ], [ "ABOUT SCHMIDT", "has_genre", "DRAMA" ], [ "ABOUT SCHMIDT", "has_tags", "COMEDY" ], [ "ABOUT SCHMIDT", "has_tags", "DRAMA" ], [ "ABOUT SCHMIDT", "release_year", "2002" ], [ "ADMISSION", "has_genre", "COMEDY" ], [ "ADMISSION", "has_genre", "DRAMA" ], [ "ADMISSION", "has_tags", "COMEDY" ], [ "AFTERNOON DELIGHT", "has_genre", "COMEDY" ], [ "AFTERNOON DELIGHT", "has_genre", "DRAMA" ], [ "ALI G INDAHOUSE", "has_genre", "COMEDY" ], [ "ALI G INDAHOUSE", "release_year", "2002" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "release_year", "2002" ], [ "ALL IS BRIGHT", "has_genre", "COMEDY" ], [ "ALL IS BRIGHT", "has_genre", "DRAMA" ], [ "ANALYZE THAT", "has_genre", "COMEDY" ], [ "ANALYZE THAT", "has_tags", "COMEDY" ], [ "ANALYZE THAT", "release_year", "2002" ], [ "AS COOL AS I AM", "has_genre", "COMEDY" ], [ "AS COOL AS I AM", "has_genre", "DRAMA" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_genre", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_tags", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "release_year", "2002" ], [ "AVENGING ANGELO", "has_genre", "COMEDY" ], [ "AVENGING ANGELO", "release_year", "2002" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "release_year", "2002" ], [ "BARBERSHOP", "has_genre", "COMEDY" ], [ "BARBERSHOP", "release_year", "2002" ], [ "BEND IT LIKE BECKHAM", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "has_genre", "DRAMA" ], [ "BEND IT LIKE BECKHAM", "release_year", "2002" ], [ "BIG FAT LIAR", "has_genre", "COMEDY" ], [ "BIG FAT LIAR", "release_year", "2002" ], [ "BIG TROUBLE", "has_genre", "COMEDY" ], [ "BIG TROUBLE", "release_year", "2002" ], [ "BOAT TRIP", "has_genre", "COMEDY" ], [ "BOAT TRIP", "release_year", "2002" ], [ "BUBBA HO-TEP", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_tags", "COMEDY" ], [ "BUBBA HO-TEP", "release_year", "2002" ], [ "BUYING THE COW", "has_genre", "COMEDY" ], [ "BUYING THE COW", "release_year", "2002" ], [ "CABIN FEVER", "has_genre", "COMEDY" ], [ "CABIN FEVER", "release_year", "2002" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "has_genre", "DRAMA" ], [ "CARNAGE", "release_year", "2002" ], [ "CHERISH", "has_genre", "COMEDY" ], [ "CHERISH", "has_genre", "DRAMA" ], [ "CHERISH", "release_year", "2002" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CHICAGO", "release_year", "2002" ], [ "CHINESE ODYSSEY 2002", "has_genre", "COMEDY" ], [ "CHINESE ODYSSEY 2002", "release_year", "2002" ], [ "CLOSER TO THE MOON", "has_genre", "COMEDY" ], [ "CLOSER TO THE MOON", "has_genre", "DRAMA" ], [ "CLOSER TO THE MOON", "has_tags", "COMEDY" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "2002" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "DRAMA" ], [ "CROSSROADS", "release_year", "2002" ], [ "DAY OF THE WACKO", "has_genre", "COMEDY" ], [ "DAY OF THE WACKO", "has_genre", "DRAMA" ], [ "DAY OF THE WACKO", "release_year", "2002" ], [ "DEATH TO SMOOCHY", "has_genre", "COMEDY" ], [ "DEATH TO SMOOCHY", "release_year", "2002" ], [ "DELIVERY MAN", "has_genre", "COMEDY" ], [ "DELIVERY MAN", "has_genre", "DRAMA" ], [ "DELIVERY MAN", "has_tags", "DRAMA" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIRTY DEEDS", "release_year", "2002" ], [ "DOM HEMINGWAY", "has_genre", "COMEDY" ], [ "DOM HEMINGWAY", "has_genre", "DRAMA" ], [ "DON JON", "has_genre", "COMEDY" ], [ "DON JON", "has_genre", "DRAMA" ], [ "DUMMY", "has_genre", "COMEDY" ], [ "DUMMY", "has_genre", "DRAMA" ], [ "DUMMY", "release_year", "2002" ], [ "EIGHT CRAZY NIGHTS", "has_genre", "COMEDY" ], [ "EIGHT CRAZY NIGHTS", "release_year", "2002" ], [ "EIGHT LEGGED FREAKS", "has_genre", "COMEDY" ], [ "EIGHT LEGGED FREAKS", "release_year", "2002" ], [ "FILTH", "has_genre", "COMEDY" ], [ "FILTH", "has_genre", "DRAMA" ], [ "FRANK MCKLUSKY, C.I.", "has_genre", "COMEDY" ], [ "FRANK MCKLUSKY, C.I.", "release_year", "2002" ], [ "FRIDAY AFTER NEXT", "has_genre", "COMEDY" ], [ "FRIDAY AFTER NEXT", "release_year", "2002" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "GREGORY GO BOOM", "has_genre", "COMEDY" ], [ "GREGORY GO BOOM", "has_genre", "DRAMA" ], [ "HEARTLANDS", "has_genre", "COMEDY" ], [ "HEARTLANDS", "has_genre", "DRAMA" ], [ "HEARTLANDS", "release_year", "2002" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "has_genre", "DRAMA" ], [ "HERO", "release_year", "2002" ], [ "HOME ALONE 4", "has_genre", "COMEDY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "HOME ROOM", "release_year", "2002" ], [ "I SPY", "has_genre", "COMEDY" ], [ "I SPY", "has_tags", "COMEDY" ], [ "I SPY", "release_year", "2002" ], [ "I'M WITH LUCY", "has_genre", "COMEDY" ], [ "I'M WITH LUCY", "release_year", "2002" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "release_year", "2002" ], [ "IGBY GOES DOWN", "has_genre", "COMEDY" ], [ "IGBY GOES DOWN", "has_genre", "DRAMA" ], [ "IGBY GOES DOWN", "release_year", "2002" ], [ "INSTRUCTIONS NOT INCLUDED", "has_genre", "COMEDY" ], [ "INSTRUCTIONS NOT INCLUDED", "has_genre", "DRAMA" ], [ "JUST A KISS", "has_genre", "COMEDY" ], [ "JUST A KISS", "release_year", "2002" ], [ "JUWANNA MANN", "has_genre", "COMEDY" ], [ "JUWANNA MANN", "release_year", "2002" ], [ "KAL HO NAA HO", "has_genre", "COMEDY" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KISS THE BRIDE", "has_genre", "COMEDY" ], [ "KISS THE BRIDE", "release_year", "2002" ], [ "LIFE OR SOMETHING LIKE IT", "has_genre", "COMEDY" ], [ "LIFE OR SOMETHING LIKE IT", "release_year", "2002" ], [ "LIFE WITHOUT DICK", "has_genre", "COMEDY" ], [ "LIFE WITHOUT DICK", "release_year", "2002" ], [ "LOVE LIZA", "has_genre", "COMEDY" ], [ "LOVE LIZA", "release_year", "2002" ], [ "MAID IN MANHATTAN", "has_genre", "COMEDY" ], [ "MAID IN MANHATTAN", "release_year", "2002" ], [ "MEN WITH BROOMS", "has_genre", "COMEDY" ], [ "MEN WITH BROOMS", "release_year", "2002" ], [ "MIRANDA", "has_genre", "COMEDY" ], [ "MIRANDA", "release_year", "2002" ], [ "MR. DEEDS", "has_genre", "COMEDY" ], [ "MR. DEEDS", "release_year", "2002" ], [ "MY BIG FAT GREEK WEDDING", "has_genre", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "has_tags", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "release_year", "2002" ], [ "MY LEFT EYE SEES GHOSTS", "has_genre", "COMEDY" ], [ "MY LEFT EYE SEES GHOSTS", "release_year", "2002" ], [ "MY MOTHER LIKES WOMEN", "has_genre", "COMEDY" ], [ "MY MOTHER LIKES WOMEN", "release_year", "2002" ], [ "NOVO", "has_genre", "COMEDY" ], [ "NOVO", "release_year", "2002" ], [ "NOW YOU KNOW", "has_genre", "COMEDY" ], [ "NOW YOU KNOW", "release_year", "2002" ], [ "OCCIDENT", "has_genre", "COMEDY" ], [ "OCCIDENT", "release_year", "2002" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "has_genre", "COMEDY" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "release_year", "2002" ], [ "ONE CHANCE", "has_genre", "COMEDY" ], [ "ONE CHANCE", "has_genre", "DRAMA" ], [ "ORANGE COUNTY", "has_genre", "COMEDY" ], [ "ORANGE COUNTY", "release_year", "2002" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PASSIONADA", "has_genre", "COMEDY" ], [ "PASSIONADA", "release_year", "2002" ], [ "PIPE DREAM", "has_genre", "COMEDY" ], [ "PIPE DREAM", "release_year", "2002" ], [ "PRINCE AVALANCHE", "has_genre", "COMEDY" ], [ "PRINCE AVALANCHE", "has_genre", "DRAMA" ], [ "PUMPKIN", "has_genre", "COMEDY" ], [ "PUMPKIN", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_genre", "DRAMA" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "R.S.V.P.", "has_genre", "COMEDY" ], [ "R.S.V.P.", "release_year", "2002" ], [ "ROGER DODGER", "has_genre", "COMEDY" ], [ "ROGER DODGER", "has_genre", "DRAMA" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SAVING MR. BANKS", "has_genre", "COMEDY" ], [ "SAVING MR. BANKS", "has_genre", "DRAMA" ], [ "SCOOBY-DOO", "has_genre", "COMEDY" ], [ "SCOOBY-DOO", "release_year", "2002" ], [ "SCREWED IN TALLINN", "has_genre", "COMEDY" ], [ "SCREWED IN TALLINN", "has_genre", "DRAMA" ], [ "SERVING SARA", "has_genre", "COMEDY" ], [ "SERVING SARA", "release_year", "2002" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "SHOWTIME", "has_genre", "COMEDY" ], [ "SHOWTIME", "release_year", "2002" ], [ "SLACKERS", "has_genre", "COMEDY" ], [ "SLACKERS", "release_year", "2002" ], [ "SNOW DOGS", "has_genre", "COMEDY" ], [ "SNOW DOGS", "release_year", "2002" ], [ "SORORITY BOYS", "has_genre", "COMEDY" ], [ "SORORITY BOYS", "release_year", "2002" ], [ "SPUN", "has_genre", "COMEDY" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SUPER SUCKER", "has_genre", "COMEDY" ], [ "SUPER SUCKER", "release_year", "2002" ], [ "SWEET HOME ALABAMA", "has_genre", "COMEDY" ], [ "SWEET HOME ALABAMA", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "THE ADVENTURES OF PLUTO NASH", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PLUTO NASH", "release_year", "2002" ], [ "THE AMAZING CATFISH", "has_genre", "COMEDY" ], [ "THE AMAZING CATFISH", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "COMEDY" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BANGER SISTERS", "has_genre", "COMEDY" ], [ "THE BANGER SISTERS", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "COMEDY" ], [ "THE CUCKOO", "has_genre", "DRAMA" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "COMEDY" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "DRAMA" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "release_year", "2002" ], [ "THE GURU", "has_genre", "COMEDY" ], [ "THE GURU", "release_year", "2002" ], [ "THE HOT CHICK", "has_genre", "COMEDY" ], [ "THE HOT CHICK", "has_tags", "COMEDY" ], [ "THE HOT CHICK", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "COMEDY" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "DRAMA" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE MAN WITHOUT A PAST", "has_genre", "COMEDY" ], [ "THE MAN WITHOUT A PAST", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE MASTER OF DISGUISE", "has_genre", "COMEDY" ], [ "THE MASTER OF DISGUISE", "release_year", "2002" ], [ "THE NEW GUY", "has_genre", "COMEDY" ], [ "THE NEW GUY", "release_year", "2002" ], [ "THE ONE AND ONLY", "has_genre", "COMEDY" ], [ "THE ONE AND ONLY", "release_year", "2002" ], [ "THE PRETTY ONE", "has_genre", "COMEDY" ], [ "THE PRETTY ONE", "has_genre", "DRAMA" ], [ "THE REUNION", "directed_by", "ANNA ODELL" ], [ "THE REUNION", "has_genre", "DRAMA" ], [ "THE REUNION", "written_by", "ANNA ODELL" ], [ "THE RULES OF ATTRACTION", "has_genre", "COMEDY" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SPECTACULAR NOW", "has_genre", "COMEDY" ], [ "THE SPECTACULAR NOW", "has_genre", "DRAMA" ], [ "THE SWEETEST THING", "has_genre", "COMEDY" ], [ "THE SWEETEST THING", "has_tags", "COMEDY" ], [ "THE SWEETEST THING", "release_year", "2002" ], [ "THE TUXEDO", "has_genre", "COMEDY" ], [ "THE TUXEDO", "has_tags", "COMEDY" ], [ "THE TUXEDO", "release_year", "2002" ], [ "THE WAY WAY BACK", "has_genre", "COMEDY" ], [ "THE WAY WAY BACK", "has_genre", "DRAMA" ], [ "THE WAY WAY BACK", "has_tags", "DRAMA" ], [ "TOGETHER", "has_genre", "COMEDY" ], [ "TOGETHER", "has_genre", "DRAMA" ], [ "TRIGGERMEN", "has_genre", "COMEDY" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "TRUST ME", "has_genre", "COMEDY" ], [ "TRUST ME", "has_genre", "DRAMA" ], [ "TWO WEEKS NOTICE", "has_genre", "COMEDY" ], [ "TWO WEEKS NOTICE", "release_year", "2002" ], [ "UNCONDITIONAL LOVE", "has_genre", "COMEDY" ], [ "UNCONDITIONAL LOVE", "release_year", "2002" ], [ "UNDERCOVER BROTHER", "has_genre", "COMEDY" ], [ "UNDERCOVER BROTHER", "release_year", "2002" ], [ "WAKING UP IN RENO", "has_genre", "COMEDY" ], [ "WAKING UP IN RENO", "release_year", "2002" ], [ "WELCOME TO COLLINWOOD", "has_genre", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "has_tags", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "release_year", "2002" ], [ "WHEN IN ROME", "has_genre", "COMEDY" ], [ "WHEN IN ROME", "release_year", "2002" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 10830, JÖRG BUTTGEREIT 14714, K2 38235, NEKROMANTIK 2 24916, PATRICK MEYERS 36578, THE PEOPLE UNDER THE STAIRS src, edge_attr, dst 14714, release_year, 10702 14714, written_by, 24916 38235, directed_by, 10830 38235, release_year, 10702 38235, starred_actors, 10830 38235, written_by, 10830 36578, release_year, 10702 Question: For what reason are JÖRG BUTTGEREIT, PATRICK MEYERS, and THE PEOPLE UNDER THE STAIRS associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JÖRG BUTTGEREIT", "PATRICK MEYERS", "THE PEOPLE UNDER THE STAIRS" ], "valid_edges": [ [ "K2", "release_year", "1991" ], [ "K2", "written_by", "PATRICK MEYERS" ], [ "NEKROMANTIK 2", "directed_by", "JÖRG BUTTGEREIT" ], [ "NEKROMANTIK 2", "release_year", "1991" ], [ "NEKROMANTIK 2", "starred_actors", "JÖRG BUTTGEREIT" ], [ "NEKROMANTIK 2", "written_by", "JÖRG BUTTGEREIT" ], [ "THE PEOPLE UNDER THE STAIRS", "release_year", "1991" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37168, 15TH CENTURY 6925, 1966 39094, ANDREI RUBLEV 30330, CLEAVANT DERRICKS 38118, MOSCOW ON THE HUDSON 30659, PATRICK WYMARK 16206, RUSSIAN 37079, THE PSYCHOPATH src, edge_attr, dst 39094, has_tags, 37168 39094, has_tags, 16206 39094, in_language, 16206 39094, release_year, 6925 38118, in_language, 16206 38118, starred_actors, 30330 37079, release_year, 6925 37079, starred_actors, 30659 Question: For what reason are 15TH CENTURY, CLEAVANT DERRICKS, and PATRICK WYMARK associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "15TH CENTURY", "CLEAVANT DERRICKS", "PATRICK WYMARK" ], "valid_edges": [ [ "ANDREI RUBLEV", "has_tags", "15TH CENTURY" ], [ "ANDREI RUBLEV", "has_tags", "RUSSIAN" ], [ "ANDREI RUBLEV", "in_language", "RUSSIAN" ], [ "ANDREI RUBLEV", "release_year", "1966" ], [ "MOSCOW ON THE HUDSON", "in_language", "RUSSIAN" ], [ "MOSCOW ON THE HUDSON", "starred_actors", "CLEAVANT DERRICKS" ], [ "THE PSYCHOPATH", "release_year", "1966" ], [ "THE PSYCHOPATH", "starred_actors", "PATRICK WYMARK" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 6216, 1952 35063, 1976 1421, 2013 33779, A HAUNTED HOUSE 36766, A HAUNTING AT SILVER FALLS 18644, A RESURRECTION 7327, ALL CHEERLEADERS DIE 36810, AN AMERICAN HAUNTING 9782, BANSHEE CHAPTER 34701, BENEATH 24456, BLOOD GLACIER 8065, BRIAN DE PALMA 5851, BURNT OFFERINGS 24454, CARRIE 32401, CAST A DEADLY SPELL 28328, CAT'S EYE 9241, CHASTITY BITES 5741, CHILDREN OF THE CORN 35713, CHLOË GRACE MORETZ 24443, CHRISTINE 40079, CONTRACTED 22349, CRAWLSPACE 30260, CREEPSHOW 19984, CREEPSHOW 2 25956, CUJO 4964, CURSE OF CHUCKY 33372, DARK SKIES 31257, DARK TOUCH 3093, DEAD IN TOMBSTONE 25528, DEVIL'S PASS 39647, DON PORTER 30262, DRACULA 35978, DREAMCATCHER 35855, ESCAPE FROM TOMORROW 23129, EVIL DEAD 10355, FRANKENSTEIN'S ARMY 23822, GOD TOLD ME TO 33104, HAUNT 14366, HAUNTER 798, HELL BABY 5870, HORROR 10147, HOUSE 32245, I SPIT ON YOUR GRAVE 2 39172, IN FEAR 39767, JUG FACE 14429, JULIANNE MOORE 2687, LAURENCE OLIVIER 29987, LET ME IN 24015, LORD OF TEARS 29898, MAMA 3129, MAXIMUM OVERDRIVE 33165, MISCHIEF NIGHT 7625, MISERY 21188, MR. JONES 13716, NOTHING LEFT TO FEAR 13530, NURSE 3D 848, OCULUS 28917, PET SEMATARY 19296, PROXY 3322, QUICKSILVER HIGHWAY 32894, RIDING THE BULLET 23082, RIGOR MORTIS 19611, SHE-WOLF OF LONDON 30671, SILVER BULLET 29168, SISSY SPACEK 19479, SISTERS 16247, SLEEPWALKERS 16551, SQUIRM 23284, STEPHEN KING 29841, THE BIRDS 16442, THE COLLECTOR 21288, THE COLONY 7853, THE CONJURING 25979, THE DARK HALF 26351, THE DEAD ZONE 28279, THE HUMAN RACE 17331, THE LAST DAYS ON MARS 12833, THE LAST EXORCISM PART II 10379, THE LAWNMOWER MAN 26566, THE MANGLER 33919, THE MIST 21784, THE MONKEY'S PAW 40021, THE NIGHT FLIER 17910, THE OMEN 6427, THE PURGE 13106, THE SACRAMENT 19018, THE SHINING 30502, THE WHITE REINDEER 10423, THE WITCH WHO CAME FROM THE SEA 7808, THINNER 1657, TIPPI HEDREN 20875, TO THE DEVIL A DAUGHTER 27476, TORMENT 17409, TRICK OR TREAT 34305, V/H/S/2 18049, WE ARE WHAT WE ARE 5553, WELCOME TO THE JUNGLE 26506, WER 24046, WEREWOLF WOMAN 22737, WICKED LITTLE THINGS 10486, WILLIAM KATT 29732, WILLIAM WYLER 33045, WOLF CREEK 2 20105, WORLD WAR Z src, edge_attr, dst 35747, has_genre, 5870 35747, has_tags, 5870 35747, has_tags, 23284 35747, written_by, 23284 33779, has_genre, 5870 33779, release_year, 1421 36766, has_genre, 5870 36766, release_year, 1421 18644, has_genre, 5870 18644, release_year, 1421 7327, has_genre, 5870 7327, release_year, 1421 36810, has_genre, 5870 36810, starred_actors, 29168 9782, has_genre, 5870 9782, release_year, 1421 34701, has_genre, 5870 34701, release_year, 1421 24456, has_genre, 5870 24456, release_year, 1421 5851, has_genre, 5870 5851, release_year, 35063 24454, directed_by, 8065 24454, directed_by, 29732 24454, has_genre, 5870 24454, has_tags, 8065 24454, has_tags, 5870 24454, has_tags, 29168 24454, has_tags, 23284 24454, has_tags, 29732 24454, release_year, 6216 24454, release_year, 35063 24454, release_year, 1421 24454, starred_actors, 35713 24454, starred_actors, 14429 24454, starred_actors, 2687 24454, starred_actors, 29168 24454, starred_actors, 10486 24454, written_by, 23284 32401, has_genre, 5870 32401, starred_actors, 14429 28328, has_genre, 5870 28328, has_tags, 23284 28328, written_by, 23284 9241, has_genre, 5870 9241, release_year, 1421 5741, has_genre, 5870 5741, has_tags, 23284 5741, written_by, 23284 24443, has_genre, 5870 24443, has_tags, 23284 24443, written_by, 23284 40079, has_genre, 5870 40079, release_year, 1421 22349, has_genre, 5870 22349, release_year, 1421 30260, has_genre, 5870 30260, written_by, 23284 19984, has_genre, 5870 19984, has_tags, 23284 19984, written_by, 23284 25956, has_genre, 5870 25956, has_tags, 23284 25956, written_by, 23284 4964, has_genre, 5870 4964, has_tags, 5870 4964, release_year, 1421 33372, has_genre, 5870 33372, release_year, 1421 31257, has_genre, 5870 31257, release_year, 1421 3093, has_genre, 5870 3093, release_year, 1421 25528, has_genre, 5870 25528, release_year, 1421 30262, has_genre, 5870 30262, has_tags, 5870 30262, starred_actors, 2687 35978, has_genre, 5870 35978, has_tags, 23284 35978, written_by, 23284 35855, has_genre, 5870 35855, release_year, 1421 23129, has_genre, 5870 23129, has_tags, 5870 23129, release_year, 1421 10355, has_genre, 5870 10355, release_year, 1421 23822, has_genre, 5870 23822, release_year, 35063 33104, has_genre, 5870 33104, release_year, 1421 14366, has_genre, 5870 14366, release_year, 1421 798, has_genre, 5870 798, has_tags, 5870 798, release_year, 1421 10147, has_genre, 5870 10147, starred_actors, 10486 32245, has_genre, 5870 32245, release_year, 1421 39172, has_genre, 5870 39172, release_year, 1421 39767, has_genre, 5870 39767, release_year, 1421 29987, has_genre, 5870 29987, has_tags, 5870 29987, starred_actors, 35713 24015, has_genre, 5870 24015, release_year, 1421 29898, has_genre, 5870 29898, has_tags, 5870 29898, release_year, 1421 3129, directed_by, 23284 3129, has_genre, 5870 3129, has_tags, 23284 3129, written_by, 23284 33165, has_genre, 5870 33165, release_year, 1421 7625, has_tags, 5870 7625, has_tags, 23284 7625, written_by, 23284 21188, has_genre, 5870 21188, release_year, 1421 13716, has_genre, 5870 13716, release_year, 1421 13530, has_genre, 5870 13530, release_year, 1421 848, has_genre, 5870 848, release_year, 1421 28917, has_genre, 5870 28917, has_tags, 5870 28917, has_tags, 23284 28917, written_by, 23284 19296, has_genre, 5870 19296, release_year, 1421 3322, has_genre, 5870 3322, written_by, 23284 32894, has_genre, 5870 32894, has_tags, 23284 32894, written_by, 23284 23082, has_genre, 5870 23082, release_year, 1421 19611, has_genre, 5870 19611, starred_actors, 39647 30671, has_genre, 5870 30671, has_tags, 23284 30671, written_by, 23284 19479, directed_by, 8065 19479, has_genre, 5870 19479, has_tags, 8065 19479, written_by, 8065 16247, has_genre, 5870 16247, has_tags, 5870 16247, has_tags, 23284 16247, written_by, 23284 16551, has_genre, 5870 16551, release_year, 35063 29841, has_genre, 5870 29841, has_tags, 5870 29841, has_tags, 1657 29841, starred_actors, 1657 16442, directed_by, 29732 16442, has_genre, 5870 16442, has_tags, 29732 21288, has_genre, 5870 21288, release_year, 1421 7853, has_genre, 5870 7853, has_tags, 5870 7853, release_year, 1421 25979, has_genre, 5870 25979, has_tags, 23284 25979, written_by, 23284 26351, has_genre, 5870 26351, has_tags, 23284 26351, written_by, 23284 28279, has_genre, 5870 28279, release_year, 1421 17331, has_genre, 5870 17331, release_year, 1421 12833, has_genre, 5870 12833, release_year, 1421 10379, has_genre, 5870 10379, written_by, 23284 26566, has_genre, 5870 26566, has_tags, 5870 26566, has_tags, 23284 26566, written_by, 23284 33919, has_genre, 5870 33919, has_tags, 23284 33919, written_by, 23284 21784, has_genre, 5870 21784, release_year, 1421 40021, has_genre, 5870 40021, written_by, 23284 17910, has_genre, 5870 17910, has_tags, 5870 17910, release_year, 35063 6427, has_genre, 5870 6427, release_year, 1421 13106, has_genre, 5870 13106, has_tags, 5870 13106, release_year, 1421 19018, has_genre, 5870 19018, has_tags, 5870 19018, has_tags, 23284 19018, written_by, 23284 30502, has_genre, 5870 30502, release_year, 6216 10423, has_genre, 5870 10423, release_year, 35063 7808, has_genre, 5870 7808, has_tags, 23284 7808, written_by, 23284 20875, has_genre, 5870 20875, release_year, 35063 27476, has_genre, 5870 27476, release_year, 1421 17409, has_genre, 5870 17409, release_year, 6216 34305, has_genre, 5870 34305, has_tags, 5870 34305, release_year, 1421 18049, has_genre, 5870 18049, has_tags, 5870 18049, release_year, 1421 5553, has_genre, 5870 5553, release_year, 1421 26506, has_genre, 5870 26506, release_year, 1421 24046, has_genre, 5870 24046, release_year, 35063 22737, has_genre, 5870 22737, starred_actors, 35713 33045, has_genre, 5870 33045, release_year, 1421 20105, has_genre, 5870 20105, release_year, 1421 Question: In what context are CARRIE, DON PORTER, and TIPPI HEDREN connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CARRIE", "DON PORTER", "TIPPI HEDREN" ], "valid_edges": [ [ "1408", "has_genre", "HORROR" ], [ "1408", "has_tags", "HORROR" ], [ "1408", "has_tags", "STEPHEN KING" ], [ "1408", "written_by", "STEPHEN KING" ], [ "A HAUNTED HOUSE", "has_genre", "HORROR" ], [ "A HAUNTED HOUSE", "release_year", "2013" ], [ "A HAUNTING AT SILVER FALLS", "has_genre", "HORROR" ], [ "A HAUNTING AT SILVER FALLS", "release_year", "2013" ], [ "A RESURRECTION", "has_genre", "HORROR" ], [ "A RESURRECTION", "release_year", "2013" ], [ "ALL CHEERLEADERS DIE", "has_genre", "HORROR" ], [ "ALL CHEERLEADERS DIE", "release_year", "2013" ], [ "AN AMERICAN HAUNTING", "has_genre", "HORROR" ], [ "AN AMERICAN HAUNTING", "starred_actors", "SISSY SPACEK" ], [ "BANSHEE CHAPTER", "has_genre", "HORROR" ], [ "BANSHEE CHAPTER", "release_year", "2013" ], [ "BENEATH", "has_genre", "HORROR" ], [ "BENEATH", "release_year", "2013" ], [ "BLOOD GLACIER", "has_genre", "HORROR" ], [ "BLOOD GLACIER", "release_year", "2013" ], [ "BURNT OFFERINGS", "has_genre", "HORROR" ], [ "BURNT OFFERINGS", "release_year", "1976" ], [ "CARRIE", "directed_by", "BRIAN DE PALMA" ], [ "CARRIE", "directed_by", "WILLIAM WYLER" ], [ "CARRIE", "has_genre", "HORROR" ], [ "CARRIE", "has_tags", "BRIAN DE PALMA" ], [ "CARRIE", "has_tags", "HORROR" ], [ "CARRIE", "has_tags", "SISSY SPACEK" ], [ "CARRIE", "has_tags", "STEPHEN KING" ], [ "CARRIE", "has_tags", "WILLIAM WYLER" ], [ "CARRIE", "release_year", "1952" ], [ "CARRIE", "release_year", "1976" ], [ "CARRIE", "release_year", "2013" ], [ "CARRIE", "starred_actors", "CHLOË GRACE MORETZ" ], [ "CARRIE", "starred_actors", "JULIANNE MOORE" ], [ "CARRIE", "starred_actors", "LAURENCE OLIVIER" ], [ "CARRIE", "starred_actors", "SISSY SPACEK" ], [ "CARRIE", "starred_actors", "WILLIAM KATT" ], [ "CARRIE", "written_by", "STEPHEN KING" ], [ "CAST A DEADLY SPELL", "has_genre", "HORROR" ], [ "CAST A DEADLY SPELL", "starred_actors", "JULIANNE MOORE" ], [ "CAT'S EYE", "has_genre", "HORROR" ], [ "CAT'S EYE", "has_tags", "STEPHEN KING" ], [ "CAT'S EYE", "written_by", "STEPHEN KING" ], [ "CHASTITY BITES", "has_genre", "HORROR" ], [ "CHASTITY BITES", "release_year", "2013" ], [ "CHILDREN OF THE CORN", "has_genre", "HORROR" ], [ "CHILDREN OF THE CORN", "has_tags", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "written_by", "STEPHEN KING" ], [ "CHRISTINE", "has_genre", "HORROR" ], [ "CHRISTINE", "has_tags", "STEPHEN KING" ], [ "CHRISTINE", "written_by", "STEPHEN KING" ], [ "CONTRACTED", "has_genre", "HORROR" ], [ "CONTRACTED", "release_year", "2013" ], [ "CRAWLSPACE", "has_genre", "HORROR" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "CREEPSHOW", "has_genre", "HORROR" ], [ "CREEPSHOW", "written_by", "STEPHEN KING" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "has_tags", "STEPHEN KING" ], [ "CREEPSHOW 2", "written_by", "STEPHEN KING" ], [ "CUJO", "has_genre", "HORROR" ], [ "CUJO", "has_tags", "STEPHEN KING" ], [ "CUJO", "written_by", "STEPHEN KING" ], [ "CURSE OF CHUCKY", "has_genre", "HORROR" ], [ "CURSE OF CHUCKY", "has_tags", "HORROR" ], [ "CURSE OF CHUCKY", "release_year", "2013" ], [ "DARK SKIES", "has_genre", "HORROR" ], [ "DARK SKIES", "release_year", "2013" ], [ "DARK TOUCH", "has_genre", "HORROR" ], [ "DARK TOUCH", "release_year", "2013" ], [ "DEAD IN TOMBSTONE", "has_genre", "HORROR" ], [ "DEAD IN TOMBSTONE", "release_year", "2013" ], [ "DEVIL'S PASS", "has_genre", "HORROR" ], [ "DEVIL'S PASS", "release_year", "2013" ], [ "DRACULA", "has_genre", "HORROR" ], [ "DRACULA", "has_tags", "HORROR" ], [ "DRACULA", "starred_actors", "LAURENCE OLIVIER" ], [ "DREAMCATCHER", "has_genre", "HORROR" ], [ "DREAMCATCHER", "has_tags", "STEPHEN KING" ], [ "DREAMCATCHER", "written_by", "STEPHEN KING" ], [ "ESCAPE FROM TOMORROW", "has_genre", "HORROR" ], [ "ESCAPE FROM TOMORROW", "release_year", "2013" ], [ "EVIL DEAD", "has_genre", "HORROR" ], [ "EVIL DEAD", "has_tags", "HORROR" ], [ "EVIL DEAD", "release_year", "2013" ], [ "FRANKENSTEIN'S ARMY", "has_genre", "HORROR" ], [ "FRANKENSTEIN'S ARMY", "release_year", "2013" ], [ "GOD TOLD ME TO", "has_genre", "HORROR" ], [ "GOD TOLD ME TO", "release_year", "1976" ], [ "HAUNT", "has_genre", "HORROR" ], [ "HAUNT", "release_year", "2013" ], [ "HAUNTER", "has_genre", "HORROR" ], [ "HAUNTER", "release_year", "2013" ], [ "HELL BABY", "has_genre", "HORROR" ], [ "HELL BABY", "has_tags", "HORROR" ], [ "HELL BABY", "release_year", "2013" ], [ "HOUSE", "has_genre", "HORROR" ], [ "HOUSE", "starred_actors", "WILLIAM KATT" ], [ "I SPIT ON YOUR GRAVE 2", "has_genre", "HORROR" ], [ "I SPIT ON YOUR GRAVE 2", "release_year", "2013" ], [ "IN FEAR", "has_genre", "HORROR" ], [ "IN FEAR", "release_year", "2013" ], [ "JUG FACE", "has_genre", "HORROR" ], [ "JUG FACE", "release_year", "2013" ], [ "LET ME IN", "has_genre", "HORROR" ], [ "LET ME IN", "has_tags", "HORROR" ], [ "LET ME IN", "starred_actors", "CHLOË GRACE MORETZ" ], [ "LORD OF TEARS", "has_genre", "HORROR" ], [ "LORD OF TEARS", "release_year", "2013" ], [ "MAMA", "has_genre", "HORROR" ], [ "MAMA", "has_tags", "HORROR" ], [ "MAMA", "release_year", "2013" ], [ "MAXIMUM OVERDRIVE", "directed_by", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "has_genre", "HORROR" ], [ "MAXIMUM OVERDRIVE", "has_tags", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "written_by", "STEPHEN KING" ], [ "MISCHIEF NIGHT", "has_genre", "HORROR" ], [ "MISCHIEF NIGHT", "release_year", "2013" ], [ "MISERY", "has_tags", "HORROR" ], [ "MISERY", "has_tags", "STEPHEN KING" ], [ "MISERY", "written_by", "STEPHEN KING" ], [ "MR. JONES", "has_genre", "HORROR" ], [ "MR. JONES", "release_year", "2013" ], [ "NOTHING LEFT TO FEAR", "has_genre", "HORROR" ], [ "NOTHING LEFT TO FEAR", "release_year", "2013" ], [ "NURSE 3D", "has_genre", "HORROR" ], [ "NURSE 3D", "release_year", "2013" ], [ "OCULUS", "has_genre", "HORROR" ], [ "OCULUS", "release_year", "2013" ], [ "PET SEMATARY", "has_genre", "HORROR" ], [ "PET SEMATARY", "has_tags", "HORROR" ], [ "PET SEMATARY", "has_tags", "STEPHEN KING" ], [ "PET SEMATARY", "written_by", "STEPHEN KING" ], [ "PROXY", "has_genre", "HORROR" ], [ "PROXY", "release_year", "2013" ], [ "QUICKSILVER HIGHWAY", "has_genre", "HORROR" ], [ "QUICKSILVER HIGHWAY", "written_by", "STEPHEN KING" ], [ "RIDING THE BULLET", "has_genre", "HORROR" ], [ "RIDING THE BULLET", "has_tags", "STEPHEN KING" ], [ "RIDING THE BULLET", "written_by", "STEPHEN KING" ], [ "RIGOR MORTIS", "has_genre", "HORROR" ], [ "RIGOR MORTIS", "release_year", "2013" ], [ "SHE-WOLF OF LONDON", "has_genre", "HORROR" ], [ "SHE-WOLF OF LONDON", "starred_actors", "DON PORTER" ], [ "SILVER BULLET", "has_genre", "HORROR" ], [ "SILVER BULLET", "has_tags", "STEPHEN KING" ], [ "SILVER BULLET", "written_by", "STEPHEN KING" ], [ "SISTERS", "directed_by", "BRIAN DE PALMA" ], [ "SISTERS", "has_genre", "HORROR" ], [ "SISTERS", "has_tags", "BRIAN DE PALMA" ], [ "SISTERS", "written_by", "BRIAN DE PALMA" ], [ "SLEEPWALKERS", "has_genre", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "STEPHEN KING" ], [ "SLEEPWALKERS", "written_by", "STEPHEN KING" ], [ "SQUIRM", "has_genre", "HORROR" ], [ "SQUIRM", "release_year", "1976" ], [ "THE BIRDS", "has_genre", "HORROR" ], [ "THE BIRDS", "has_tags", "HORROR" ], [ "THE BIRDS", "has_tags", "TIPPI HEDREN" ], [ "THE BIRDS", "starred_actors", "TIPPI HEDREN" ], [ "THE COLLECTOR", "directed_by", "WILLIAM WYLER" ], [ "THE COLLECTOR", "has_genre", "HORROR" ], [ "THE COLLECTOR", "has_tags", "WILLIAM WYLER" ], [ "THE COLONY", "has_genre", "HORROR" ], [ "THE COLONY", "release_year", "2013" ], [ "THE CONJURING", "has_genre", "HORROR" ], [ "THE CONJURING", "has_tags", "HORROR" ], [ "THE CONJURING", "release_year", "2013" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "has_tags", "STEPHEN KING" ], [ "THE DARK HALF", "written_by", "STEPHEN KING" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "has_tags", "STEPHEN KING" ], [ "THE DEAD ZONE", "written_by", "STEPHEN KING" ], [ "THE HUMAN RACE", "has_genre", "HORROR" ], [ "THE HUMAN RACE", "release_year", "2013" ], [ "THE LAST DAYS ON MARS", "has_genre", "HORROR" ], [ "THE LAST DAYS ON MARS", "release_year", "2013" ], [ "THE LAST EXORCISM PART II", "has_genre", "HORROR" ], [ "THE LAST EXORCISM PART II", "release_year", "2013" ], [ "THE LAWNMOWER MAN", "has_genre", "HORROR" ], [ "THE LAWNMOWER MAN", "written_by", "STEPHEN KING" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "has_tags", "STEPHEN KING" ], [ "THE MANGLER", "written_by", "STEPHEN KING" ], [ "THE MIST", "has_genre", "HORROR" ], [ "THE MIST", "has_tags", "STEPHEN KING" ], [ "THE MIST", "written_by", "STEPHEN KING" ], [ "THE MONKEY'S PAW", "has_genre", "HORROR" ], [ "THE MONKEY'S PAW", "release_year", "2013" ], [ "THE NIGHT FLIER", "has_genre", "HORROR" ], [ "THE NIGHT FLIER", "written_by", "STEPHEN KING" ], [ "THE OMEN", "has_genre", "HORROR" ], [ "THE OMEN", "has_tags", "HORROR" ], [ "THE OMEN", "release_year", "1976" ], [ "THE PURGE", "has_genre", "HORROR" ], [ "THE PURGE", "release_year", "2013" ], [ "THE SACRAMENT", "has_genre", "HORROR" ], [ "THE SACRAMENT", "has_tags", "HORROR" ], [ "THE SACRAMENT", "release_year", "2013" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "STEPHEN KING" ], [ "THE SHINING", "written_by", "STEPHEN KING" ], [ "THE WHITE REINDEER", "has_genre", "HORROR" ], [ "THE WHITE REINDEER", "release_year", "1952" ], [ "THE WITCH WHO CAME FROM THE SEA", "has_genre", "HORROR" ], [ "THE WITCH WHO CAME FROM THE SEA", "release_year", "1976" ], [ "THINNER", "has_genre", "HORROR" ], [ "THINNER", "has_tags", "STEPHEN KING" ], [ "THINNER", "written_by", "STEPHEN KING" ], [ "TO THE DEVIL A DAUGHTER", "has_genre", "HORROR" ], [ "TO THE DEVIL A DAUGHTER", "release_year", "1976" ], [ "TORMENT", "has_genre", "HORROR" ], [ "TORMENT", "release_year", "2013" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "release_year", "1952" ], [ "V/H/S/2", "has_genre", "HORROR" ], [ "V/H/S/2", "has_tags", "HORROR" ], [ "V/H/S/2", "release_year", "2013" ], [ "WE ARE WHAT WE ARE", "has_genre", "HORROR" ], [ "WE ARE WHAT WE ARE", "has_tags", "HORROR" ], [ "WE ARE WHAT WE ARE", "release_year", "2013" ], [ "WELCOME TO THE JUNGLE", "has_genre", "HORROR" ], [ "WELCOME TO THE JUNGLE", "release_year", "2013" ], [ "WER", "has_genre", "HORROR" ], [ "WER", "release_year", "2013" ], [ "WEREWOLF WOMAN", "has_genre", "HORROR" ], [ "WEREWOLF WOMAN", "release_year", "1976" ], [ "WICKED LITTLE THINGS", "has_genre", "HORROR" ], [ "WICKED LITTLE THINGS", "starred_actors", "CHLOË GRACE MORETZ" ], [ "WOLF CREEK 2", "has_genre", "HORROR" ], [ "WOLF CREEK 2", "release_year", "2013" ], [ "WORLD WAR Z", "has_genre", "HORROR" ], [ "WORLD WAR Z", "release_year", "2013" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1567, 1954 2133, 1998 6094, A CLOCKWORK ORANGE 19635, A TRUE MOB STORY 39208, APPOINTMENT WITH DEATH 30204, BAFFLED! 19633, BIRTHDAY GIRL 10218, BLACK WIDOW 6469, BODY COUNT 40039, BRAVE NEW WORLD 26884, BROWN'S REQUIEM 8313, CAUGHT UP 36568, CLAY PIGEONS 14724, CRIME 19328, CRIME WAVE 31527, DAD SAVAGE 34528, DARK CITY 23396, DIAL M FOR MURDER 20848, EARL CAMERON 8026, END OF THE GAME 31783, ENGLISH 19728, EVILENKO 6943, FALLEN 16516, FIFTY DEAD MEN WALKING 1033, FRACTURE 13308, FREEDOMLAND 3553, GODZILLA 31603, GORILLA AT LARGE 8046, GOSFORD PARK 38953, HIDEOUS KINKY 22006, I WANT YOU 28169, IN THE CUT 978, INFERNAL AFFAIRS 20264, JAIL BAIT 27661, JOHNNY SKIDMARKS 38160, JOURNEY TO ITALY 3743, JUDAS KISS 34878, LADY ON A TRAIN 14601, LES MISÉRABLES 38721, LOCK, STOCK AND TWO SMOKING BARRELS 34362, LULU ON THE BRIDGE 22792, MICHAEL WINTERBOTTOM 1454, MICKEY BLUE EYES 3487, MINORITY REPORT 10883, MONTANA 6137, MONUMENT AVE. 23695, MULAN 11311, MURDER ON THE ORIENT EXPRESS 15145, MYSTERY 35498, MYSTERY OF THE 13TH GUEST 7925, MYSTERY ROAD 30629, NIGHT NURSE 35865, ON THE WATERFRONT 15481, ONE TOUGH COP 4235, OUT OF SIGHT 8509, PASSION 19622, PHOENIX 39462, POOL OF LONDON 28091, PSYCHO 38043, PUSHER 1643, RISE OF THE FOOTSOLDIER 38195, ROBINSON CRUSOE 5362, ROUNDERS 32607, RUSH HOUR 8020, SAFE MEN 32487, SAPPHIRE 8436, SPIRITS OF THE DEAD 33414, SWEET SIXTEEN 32730, TALK OF ANGELS 14696, THE BIG LEBOWSKI 38918, THE FAMILY 4068, THE GENERAL 31283, THE HOUND OF THE BASKERVILLES 6870, THE KILLER INSIDE ME 28177, THE KRAYS 4091, THE LADY VANISHES 13050, THE LEGEND OF 1900 21696, THE MAN FROM LONDON 12887, THE MIRROR CRACK'D 30294, THE NIGHT OF THE GENERALS 37490, THE PERFECT MURDER 40086, THE PLACE BEYOND THE PINES 30014, THE RAID 2 8660, THE RECKONING 3275, THE REPLACEMENT KILLERS 19255, THE VALACHI PAPERS 14962, THE WATCHER IN THE WOODS 33585, THURSDAY 6485, TRIXIE 308, TRUE CRIME 10238, UNDERWORLD 10133, UNKNOWN 4736, WHERE'S MARLOWE? 8390, WHISTLING IN DIXIE 24960, WILD THINGS 31862, WONDERLAND 37210, ZODIAC 17777, ZULU src, edge_attr, dst 6094, has_genre, 14724 6094, in_language, 31783 19635, has_genre, 14724 19635, release_year, 2133 39208, has_genre, 14724 39208, has_genre, 15145 30204, has_genre, 15145 30204, in_language, 31783 19633, has_genre, 14724 19633, in_language, 31783 10218, has_genre, 14724 10218, has_genre, 15145 10218, has_tags, 14724 10218, release_year, 1567 6469, has_genre, 14724 6469, release_year, 2133 40039, in_language, 31783 40039, release_year, 2133 26884, has_genre, 14724 26884, release_year, 2133 8313, has_genre, 14724 8313, release_year, 2133 36568, has_genre, 14724 36568, release_year, 2133 19328, has_genre, 14724 19328, release_year, 1567 31527, in_language, 31783 31527, release_year, 2133 34528, has_genre, 15145 34528, release_year, 2133 23396, has_genre, 14724 23396, in_language, 31783 23396, release_year, 1567 8026, has_genre, 14724 8026, in_language, 31783 19728, has_genre, 14724 19728, in_language, 31783 6943, has_genre, 14724 6943, release_year, 2133 16516, has_tags, 14724 16516, in_language, 31783 1033, has_genre, 14724 1033, has_genre, 15145 13308, has_genre, 14724 13308, has_genre, 15145 3553, release_year, 1567 3553, release_year, 2133 31603, has_genre, 15145 31603, release_year, 1567 8046, has_genre, 15145 8046, in_language, 31783 38953, in_language, 31783 38953, release_year, 2133 22006, directed_by, 22792 22006, has_genre, 14724 22006, in_language, 31783 22006, release_year, 2133 28169, has_genre, 15145 28169, in_language, 31783 978, has_genre, 14724 978, in_language, 31783 20264, has_genre, 14724 20264, release_year, 1567 27661, has_genre, 15145 27661, release_year, 2133 38160, in_language, 31783 38160, release_year, 1567 3743, has_genre, 14724 3743, release_year, 2133 34878, has_genre, 14724 34878, has_genre, 15145 14601, in_language, 31783 14601, release_year, 2133 38721, has_genre, 14724 38721, has_tags, 14724 38721, release_year, 2133 34362, has_genre, 15145 34362, release_year, 2133 1454, has_genre, 14724 1454, in_language, 31783 3487, has_genre, 15145 3487, has_tags, 14724 3487, has_tags, 15145 10883, has_genre, 14724 10883, release_year, 2133 6137, has_genre, 14724 6137, release_year, 2133 23695, in_language, 31783 23695, release_year, 2133 11311, has_genre, 14724 11311, has_genre, 15145 11311, has_tags, 15145 35498, has_genre, 14724 35498, has_genre, 15145 7925, has_genre, 14724 7925, has_genre, 15145 30629, has_genre, 14724 30629, has_genre, 15145 35865, has_genre, 14724 35865, release_year, 1567 15481, has_genre, 14724 15481, release_year, 2133 4235, has_genre, 14724 4235, release_year, 2133 8509, has_genre, 14724 8509, in_language, 31783 19622, has_genre, 14724 19622, release_year, 2133 39462, has_genre, 14724 39462, starred_actors, 20848 28091, has_genre, 15145 28091, has_tags, 15145 28091, release_year, 2133 38043, has_genre, 14724 38043, in_language, 31783 1643, has_genre, 14724 1643, has_tags, 14724 1643, in_language, 31783 38195, in_language, 31783 38195, release_year, 1567 5362, has_genre, 14724 5362, release_year, 2133 32607, has_tags, 14724 32607, release_year, 2133 8020, has_genre, 14724 8020, release_year, 2133 32487, has_genre, 14724 32487, has_genre, 15145 32487, in_language, 31783 8436, has_genre, 15145 8436, in_language, 31783 33414, has_genre, 14724 33414, in_language, 31783 32730, in_language, 31783 32730, release_year, 2133 14696, has_genre, 14724 14696, has_tags, 14724 14696, release_year, 2133 38918, has_genre, 14724 38918, in_language, 31783 4068, has_genre, 14724 4068, release_year, 2133 31283, has_genre, 14724 31283, has_genre, 15145 6870, directed_by, 22792 6870, has_genre, 14724 6870, has_tags, 22792 28177, has_genre, 14724 28177, in_language, 31783 4091, has_genre, 15145 4091, in_language, 31783 13050, in_language, 31783 13050, release_year, 2133 21696, has_genre, 14724 21696, in_language, 31783 12887, has_genre, 14724 12887, has_genre, 15145 30294, has_genre, 14724 30294, has_genre, 15145 37490, has_tags, 14724 37490, in_language, 31783 40086, has_genre, 14724 40086, in_language, 31783 30014, has_genre, 14724 30014, in_language, 31783 8660, has_genre, 14724 8660, has_genre, 15145 3275, has_genre, 14724 3275, release_year, 2133 19255, has_genre, 14724 19255, in_language, 31783 14962, has_genre, 15145 14962, in_language, 31783 33585, has_genre, 14724 33585, release_year, 2133 6485, has_genre, 14724 6485, has_genre, 15145 308, has_genre, 14724 308, has_genre, 15145 10238, has_genre, 14724 10238, in_language, 31783 10133, has_genre, 14724 10133, in_language, 31783 4736, has_genre, 15145 4736, release_year, 2133 8390, has_genre, 14724 8390, has_genre, 15145 24960, has_genre, 14724 24960, release_year, 2133 31862, directed_by, 22792 31862, has_genre, 14724 31862, has_tags, 22792 37210, has_genre, 14724 37210, has_genre, 15145 37210, has_tags, 14724 17777, has_genre, 14724 17777, in_language, 31783 Question: In what context are EARL CAMERON, GORILLA AT LARGE, and I WANT YOU connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "EARL CAMERON", "GORILLA AT LARGE", "I WANT YOU" ], "valid_edges": [ [ "A CLOCKWORK ORANGE", "has_genre", "CRIME" ], [ "A CLOCKWORK ORANGE", "in_language", "ENGLISH" ], [ "A TRUE MOB STORY", "has_genre", "CRIME" ], [ "A TRUE MOB STORY", "release_year", "1998" ], [ "APPOINTMENT WITH DEATH", "has_genre", "CRIME" ], [ "APPOINTMENT WITH DEATH", "has_genre", "MYSTERY" ], [ "BAFFLED!", "has_genre", "MYSTERY" ], [ "BAFFLED!", "in_language", "ENGLISH" ], [ "BIRTHDAY GIRL", "has_genre", "CRIME" ], [ "BIRTHDAY GIRL", "in_language", "ENGLISH" ], [ "BLACK WIDOW", "has_genre", "CRIME" ], [ "BLACK WIDOW", "has_genre", "MYSTERY" ], [ "BLACK WIDOW", "has_tags", "CRIME" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BODY COUNT", "has_genre", "CRIME" ], [ "BODY COUNT", "release_year", "1998" ], [ "BRAVE NEW WORLD", "in_language", "ENGLISH" ], [ "BRAVE NEW WORLD", "release_year", "1998" ], [ "BROWN'S REQUIEM", "has_genre", "CRIME" ], [ "BROWN'S REQUIEM", "release_year", "1998" ], [ "CAUGHT UP", "has_genre", "CRIME" ], [ "CAUGHT UP", "release_year", "1998" ], [ "CLAY PIGEONS", "has_genre", "CRIME" ], [ "CLAY PIGEONS", "release_year", "1998" ], [ "CRIME WAVE", "has_genre", "CRIME" ], [ "CRIME WAVE", "release_year", "1954" ], [ "DAD SAVAGE", "in_language", "ENGLISH" ], [ "DAD SAVAGE", "release_year", "1998" ], [ "DARK CITY", "has_genre", "MYSTERY" ], [ "DARK CITY", "release_year", "1998" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DIAL M FOR MURDER", "release_year", "1954" ], [ "END OF THE GAME", "has_genre", "CRIME" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "EVILENKO", "has_genre", "CRIME" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "FALLEN", "has_genre", "CRIME" ], [ "FALLEN", "release_year", "1998" ], [ "FIFTY DEAD MEN WALKING", "has_tags", "CRIME" ], [ "FIFTY DEAD MEN WALKING", "in_language", "ENGLISH" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_genre", "MYSTERY" ], [ "FREEDOMLAND", "has_genre", "CRIME" ], [ "FREEDOMLAND", "has_genre", "MYSTERY" ], [ "GODZILLA", "release_year", "1954" ], [ "GODZILLA", "release_year", "1998" ], [ "GORILLA AT LARGE", "has_genre", "MYSTERY" ], [ "GORILLA AT LARGE", "release_year", "1954" ], [ "GOSFORD PARK", "has_genre", "MYSTERY" ], [ "GOSFORD PARK", "in_language", "ENGLISH" ], [ "HIDEOUS KINKY", "in_language", "ENGLISH" ], [ "HIDEOUS KINKY", "release_year", "1998" ], [ "I WANT YOU", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "I WANT YOU", "has_genre", "CRIME" ], [ "I WANT YOU", "in_language", "ENGLISH" ], [ "I WANT YOU", "release_year", "1998" ], [ "IN THE CUT", "has_genre", "MYSTERY" ], [ "IN THE CUT", "in_language", "ENGLISH" ], [ "INFERNAL AFFAIRS", "has_genre", "CRIME" ], [ "INFERNAL AFFAIRS", "in_language", "ENGLISH" ], [ "JAIL BAIT", "has_genre", "CRIME" ], [ "JAIL BAIT", "release_year", "1954" ], [ "JOHNNY SKIDMARKS", "has_genre", "MYSTERY" ], [ "JOHNNY SKIDMARKS", "release_year", "1998" ], [ "JOURNEY TO ITALY", "in_language", "ENGLISH" ], [ "JOURNEY TO ITALY", "release_year", "1954" ], [ "JUDAS KISS", "has_genre", "CRIME" ], [ "JUDAS KISS", "release_year", "1998" ], [ "LADY ON A TRAIN", "has_genre", "CRIME" ], [ "LADY ON A TRAIN", "has_genre", "MYSTERY" ], [ "LES MISÉRABLES", "in_language", "ENGLISH" ], [ "LES MISÉRABLES", "release_year", "1998" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_genre", "CRIME" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_tags", "CRIME" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "release_year", "1998" ], [ "LULU ON THE BRIDGE", "has_genre", "MYSTERY" ], [ "LULU ON THE BRIDGE", "release_year", "1998" ], [ "MICKEY BLUE EYES", "has_genre", "CRIME" ], [ "MICKEY BLUE EYES", "in_language", "ENGLISH" ], [ "MINORITY REPORT", "has_genre", "MYSTERY" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "MYSTERY" ], [ "MONTANA", "has_genre", "CRIME" ], [ "MONTANA", "release_year", "1998" ], [ "MONUMENT AVE.", "has_genre", "CRIME" ], [ "MONUMENT AVE.", "release_year", "1998" ], [ "MULAN", "in_language", "ENGLISH" ], [ "MULAN", "release_year", "1998" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "CRIME" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "MYSTERY" ], [ "MURDER ON THE ORIENT EXPRESS", "has_tags", "MYSTERY" ], [ "MYSTERY OF THE 13TH GUEST", "has_genre", "CRIME" ], [ "MYSTERY OF THE 13TH GUEST", "has_genre", "MYSTERY" ], [ "MYSTERY ROAD", "has_genre", "CRIME" ], [ "MYSTERY ROAD", "has_genre", "MYSTERY" ], [ "NIGHT NURSE", "has_genre", "CRIME" ], [ "NIGHT NURSE", "has_genre", "MYSTERY" ], [ "ON THE WATERFRONT", "has_genre", "CRIME" ], [ "ON THE WATERFRONT", "release_year", "1954" ], [ "ONE TOUGH COP", "has_genre", "CRIME" ], [ "ONE TOUGH COP", "release_year", "1998" ], [ "OUT OF SIGHT", "has_genre", "CRIME" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "PASSION", "has_genre", "CRIME" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PHOENIX", "has_genre", "CRIME" ], [ "PHOENIX", "release_year", "1998" ], [ "POOL OF LONDON", "has_genre", "CRIME" ], [ "POOL OF LONDON", "starred_actors", "EARL CAMERON" ], [ "PSYCHO", "has_genre", "MYSTERY" ], [ "PSYCHO", "has_tags", "MYSTERY" ], [ "PSYCHO", "release_year", "1998" ], [ "PUSHER", "has_genre", "CRIME" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "RISE OF THE FOOTSOLDIER", "has_genre", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "has_tags", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "ROBINSON CRUSOE", "in_language", "ENGLISH" ], [ "ROBINSON CRUSOE", "release_year", "1954" ], [ "ROUNDERS", "has_genre", "CRIME" ], [ "ROUNDERS", "release_year", "1998" ], [ "RUSH HOUR", "has_tags", "CRIME" ], [ "RUSH HOUR", "release_year", "1998" ], [ "SAFE MEN", "has_genre", "CRIME" ], [ "SAFE MEN", "release_year", "1998" ], [ "SAPPHIRE", "has_genre", "CRIME" ], [ "SAPPHIRE", "has_genre", "MYSTERY" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "has_genre", "MYSTERY" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SWEET SIXTEEN", "has_genre", "CRIME" ], [ "SWEET SIXTEEN", "in_language", "ENGLISH" ], [ "TALK OF ANGELS", "in_language", "ENGLISH" ], [ "TALK OF ANGELS", "release_year", "1998" ], [ "THE BIG LEBOWSKI", "has_genre", "CRIME" ], [ "THE BIG LEBOWSKI", "has_tags", "CRIME" ], [ "THE BIG LEBOWSKI", "release_year", "1998" ], [ "THE FAMILY", "has_genre", "CRIME" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE GENERAL", "has_genre", "CRIME" ], [ "THE GENERAL", "release_year", "1998" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "CRIME" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "MYSTERY" ], [ "THE KILLER INSIDE ME", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "THE KILLER INSIDE ME", "has_genre", "CRIME" ], [ "THE KILLER INSIDE ME", "has_tags", "MICHAEL WINTERBOTTOM" ], [ "THE KRAYS", "has_genre", "CRIME" ], [ "THE KRAYS", "in_language", "ENGLISH" ], [ "THE LADY VANISHES", "has_genre", "MYSTERY" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LEGEND OF 1900", "in_language", "ENGLISH" ], [ "THE LEGEND OF 1900", "release_year", "1998" ], [ "THE MAN FROM LONDON", "has_genre", "CRIME" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MIRROR CRACK'D", "has_genre", "CRIME" ], [ "THE MIRROR CRACK'D", "has_genre", "MYSTERY" ], [ "THE NIGHT OF THE GENERALS", "has_genre", "CRIME" ], [ "THE NIGHT OF THE GENERALS", "has_genre", "MYSTERY" ], [ "THE PERFECT MURDER", "has_tags", "CRIME" ], [ "THE PERFECT MURDER", "in_language", "ENGLISH" ], [ "THE PLACE BEYOND THE PINES", "has_genre", "CRIME" ], [ "THE PLACE BEYOND THE PINES", "in_language", "ENGLISH" ], [ "THE RAID 2", "has_genre", "CRIME" ], [ "THE RAID 2", "in_language", "ENGLISH" ], [ "THE RECKONING", "has_genre", "CRIME" ], [ "THE RECKONING", "has_genre", "MYSTERY" ], [ "THE REPLACEMENT KILLERS", "has_genre", "CRIME" ], [ "THE REPLACEMENT KILLERS", "release_year", "1998" ], [ "THE VALACHI PAPERS", "has_genre", "CRIME" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "has_genre", "MYSTERY" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THURSDAY", "has_genre", "CRIME" ], [ "THURSDAY", "release_year", "1998" ], [ "TRIXIE", "has_genre", "CRIME" ], [ "TRIXIE", "has_genre", "MYSTERY" ], [ "TRUE CRIME", "has_genre", "CRIME" ], [ "TRUE CRIME", "has_genre", "MYSTERY" ], [ "UNDERWORLD", "has_genre", "CRIME" ], [ "UNDERWORLD", "in_language", "ENGLISH" ], [ "UNKNOWN", "has_genre", "CRIME" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "WHERE'S MARLOWE?", "has_genre", "MYSTERY" ], [ "WHERE'S MARLOWE?", "release_year", "1998" ], [ "WHISTLING IN DIXIE", "has_genre", "CRIME" ], [ "WHISTLING IN DIXIE", "has_genre", "MYSTERY" ], [ "WILD THINGS", "has_genre", "CRIME" ], [ "WILD THINGS", "release_year", "1998" ], [ "WONDERLAND", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "WONDERLAND", "has_genre", "CRIME" ], [ "WONDERLAND", "has_tags", "MICHAEL WINTERBOTTOM" ], [ "ZODIAC", "has_genre", "CRIME" ], [ "ZODIAC", "has_genre", "MYSTERY" ], [ "ZODIAC", "has_tags", "CRIME" ], [ "ZULU", "has_genre", "CRIME" ], [ "ZULU", "in_language", "ENGLISH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 1006, 1996 35798, 2010 7698, ANIMATED 24177, ANIMATION 14271, BEETHOVEN 19826, BLACK DEATH 15757, BRIAN LEVANT 722, CHARACTERS 14728, CLASSIC 20883, DEATH 37059, DEATH AT A FUNERAL 10509, FAMILY 22958, FAMOUS 36066, FANTASY 18521, FLY AWAY HOME 15959, FRANK OZ 11565, GOOD 28307, HARRY AND THE HENDERSONS 34869, HOTEL TRANSYLVANIA 16200, ITALIAN 4798, JINGLE ALL THE WAY 7690, JOHN LITHGOW 26784, LITTLE WOMEN 4011, LOST IN SPACE 3764, MARMADUKE 19691, MAUDE T. HOWELL 15413, MONSTERS 37497, NATIONAL FILM REGISTRY 14026, PINOCCHIO 13081, R 32533, SCIENCE FICTION 24467, SPEED RACER 30812, THE DARK CRYSTAL 26726, THE DIARY OF ANNE FRANK 17956, THE FLINTSTONES 35551, THE GODFATHER 37999, THE MAN WHO PLAYED GOD 18537, THE SPY NEXT DOOR 12162, YOU CAN COUNT ON ME src, edge_attr, dst 35798, has_tags, 7690 35798, has_tags, 32533 35798, starred_actors, 7690 14271, directed_by, 15757 14271, has_genre, 10509 14271, has_tags, 15757 14271, has_tags, 10509 19826, release_year, 35798 37059, directed_by, 15959 37059, has_tags, 20883 37059, has_tags, 10509 37059, has_tags, 15959 37059, has_tags, 13081 37059, release_year, 35798 18521, has_genre, 10509 18521, has_tags, 20883 18521, release_year, 1006 28307, has_genre, 10509 28307, has_genre, 36066 28307, has_tags, 10509 28307, has_tags, 7690 28307, starred_actors, 7690 34869, has_genre, 24177 34869, has_genre, 10509 34869, has_imdb_votes, 22958 34869, has_tags, 7698 34869, has_tags, 24177 34869, has_tags, 15413 4798, directed_by, 15757 4798, has_genre, 10509 4798, has_tags, 15757 4798, release_year, 1006 26784, has_genre, 10509 26784, has_imdb_rating, 11565 26784, has_tags, 722 26784, has_tags, 14728 26784, release_year, 26257 4011, has_genre, 10509 4011, has_tags, 32533 3764, has_genre, 10509 3764, release_year, 35798 15413, release_year, 35798 14026, has_genre, 24177 14026, has_genre, 10509 14026, has_genre, 36066 14026, has_imdb_rating, 11565 14026, has_tags, 7698 14026, has_tags, 24177 14026, has_tags, 722 14026, has_tags, 14728 14026, has_tags, 36066 14026, has_tags, 37497 14026, in_language, 16200 24467, has_genre, 10509 24467, has_imdb_rating, 11565 30812, directed_by, 15959 30812, has_genre, 10509 30812, has_imdb_votes, 22958 30812, has_tags, 36066 30812, has_tags, 15959 30812, starred_actors, 15959 26726, has_genre, 10509 26726, has_imdb_rating, 11565 17956, directed_by, 15757 17956, has_genre, 10509 17956, has_tags, 15757 17956, release_year, 26257 35551, has_tags, 10509 35551, has_tags, 16200 35551, has_tags, 37497 35551, has_tags, 13081 35551, in_language, 16200 37999, has_imdb_rating, 11565 37999, written_by, 19691 18537, directed_by, 15757 18537, has_genre, 10509 18537, release_year, 35798 12162, has_tags, 10509 12162, has_tags, 13081 Question: How are BLACK DEATH, FAMILY, and MAUDE T. HOWELL related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BLACK DEATH", "FAMILY", "MAUDE T. HOWELL" ], "valid_edges": [ [ "2010", "has_tags", "JOHN LITHGOW" ], [ "2010", "has_tags", "SCIENCE FICTION" ], [ "2010", "starred_actors", "JOHN LITHGOW" ], [ "BEETHOVEN", "directed_by", "BRIAN LEVANT" ], [ "BEETHOVEN", "has_genre", "FAMILY" ], [ "BEETHOVEN", "has_tags", "BRIAN LEVANT" ], [ "BEETHOVEN", "has_tags", "FAMILY" ], [ "BLACK DEATH", "release_year", "2010" ], [ "DEATH AT A FUNERAL", "directed_by", "FRANK OZ" ], [ "DEATH AT A FUNERAL", "has_tags", "DEATH" ], [ "DEATH AT A FUNERAL", "has_tags", "FAMILY" ], [ "DEATH AT A FUNERAL", "has_tags", "FRANK OZ" ], [ "DEATH AT A FUNERAL", "has_tags", "R" ], [ "DEATH AT A FUNERAL", "release_year", "2010" ], [ "FLY AWAY HOME", "has_genre", "FAMILY" ], [ "FLY AWAY HOME", "has_tags", "DEATH" ], [ "FLY AWAY HOME", "release_year", "1996" ], [ "HARRY AND THE HENDERSONS", "has_genre", "FAMILY" ], [ "HARRY AND THE HENDERSONS", "has_genre", "FANTASY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "FAMILY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "JOHN LITHGOW" ], [ "HARRY AND THE HENDERSONS", "starred_actors", "JOHN LITHGOW" ], [ "HOTEL TRANSYLVANIA", "has_genre", "ANIMATION" ], [ "HOTEL TRANSYLVANIA", "has_genre", "FAMILY" ], [ "HOTEL TRANSYLVANIA", "has_imdb_votes", "FAMOUS" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANIMATED" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANIMATION" ], [ "HOTEL TRANSYLVANIA", "has_tags", "MONSTERS" ], [ "JINGLE ALL THE WAY", "directed_by", "BRIAN LEVANT" ], [ "JINGLE ALL THE WAY", "has_genre", "FAMILY" ], [ "JINGLE ALL THE WAY", "has_tags", "BRIAN LEVANT" ], [ "JINGLE ALL THE WAY", "release_year", "1996" ], [ "LITTLE WOMEN", "has_genre", "FAMILY" ], [ "LITTLE WOMEN", "has_imdb_rating", "GOOD" ], [ "LITTLE WOMEN", "has_tags", "CHARACTERS" ], [ "LITTLE WOMEN", "has_tags", "CLASSIC" ], [ "LITTLE WOMEN", "release_year", "1994" ], [ "LOST IN SPACE", "has_genre", "FAMILY" ], [ "LOST IN SPACE", "has_tags", "SCIENCE FICTION" ], [ "MARMADUKE", "has_genre", "FAMILY" ], [ "MARMADUKE", "release_year", "2010" ], [ "MONSTERS", "release_year", "2010" ], [ "PINOCCHIO", "has_genre", "ANIMATION" ], [ "PINOCCHIO", "has_genre", "FAMILY" ], [ "PINOCCHIO", "has_genre", "FANTASY" ], [ "PINOCCHIO", "has_imdb_rating", "GOOD" ], [ "PINOCCHIO", "has_tags", "ANIMATED" ], [ "PINOCCHIO", "has_tags", "ANIMATION" ], [ "PINOCCHIO", "has_tags", "CHARACTERS" ], [ "PINOCCHIO", "has_tags", "CLASSIC" ], [ "PINOCCHIO", "has_tags", "FANTASY" ], [ "PINOCCHIO", "has_tags", "NATIONAL FILM REGISTRY" ], [ "PINOCCHIO", "in_language", "ITALIAN" ], [ "SPEED RACER", "has_genre", "FAMILY" ], [ "SPEED RACER", "has_imdb_rating", "GOOD" ], [ "THE DARK CRYSTAL", "directed_by", "FRANK OZ" ], [ "THE DARK CRYSTAL", "has_genre", "FAMILY" ], [ "THE DARK CRYSTAL", "has_imdb_votes", "FAMOUS" ], [ "THE DARK CRYSTAL", "has_tags", "FANTASY" ], [ "THE DARK CRYSTAL", "has_tags", "FRANK OZ" ], [ "THE DARK CRYSTAL", "starred_actors", "FRANK OZ" ], [ "THE DIARY OF ANNE FRANK", "has_genre", "FAMILY" ], [ "THE DIARY OF ANNE FRANK", "has_imdb_rating", "GOOD" ], [ "THE FLINTSTONES", "directed_by", "BRIAN LEVANT" ], [ "THE FLINTSTONES", "has_genre", "FAMILY" ], [ "THE FLINTSTONES", "has_tags", "BRIAN LEVANT" ], [ "THE FLINTSTONES", "release_year", "1994" ], [ "THE GODFATHER", "has_tags", "FAMILY" ], [ "THE GODFATHER", "has_tags", "ITALIAN" ], [ "THE GODFATHER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "in_language", "ITALIAN" ], [ "THE MAN WHO PLAYED GOD", "has_imdb_rating", "GOOD" ], [ "THE MAN WHO PLAYED GOD", "written_by", "MAUDE T. HOWELL" ], [ "THE SPY NEXT DOOR", "directed_by", "BRIAN LEVANT" ], [ "THE SPY NEXT DOOR", "has_genre", "FAMILY" ], [ "THE SPY NEXT DOOR", "release_year", "2010" ], [ "YOU CAN COUNT ON ME", "has_tags", "FAMILY" ], [ "YOU CAN COUNT ON ME", "has_tags", "R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 32646, AT LONG LAST LOVE 30463, COMEDY 12489, CRAZY MAMA 2221, DOLEMITE 4649, HAPPY TEARS 35856, HEARTS OF THE WEST 13183, LOVE AND DEATH 33190, MAX SCHOTT 32834, MONTY PYTHON AND THE HOLY GRAIL 5237, MURPHY'S ROMANCE 32916, MY FRIENDS 18416, ONE OF OUR DINOSAURS IS MISSING 34930, RANCHO DELUXE 1045, SMILE 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 32237, THE FORTUNE 21920, THE OLSEN GANG ON THE TRACK 21459, THE PASSENGER 10721, THE ROCKY HORROR PICTURE SHOW 23847, THE STEPFORD WIVES 26081, THE SUNSHINE BOYS src, edge_attr, dst 32646, has_genre, 30463 32646, release_year, 39435 12489, has_genre, 30463 12489, release_year, 39435 2221, has_genre, 30463 2221, release_year, 39435 4649, has_genre, 30463 35856, has_genre, 30463 35856, release_year, 39435 13183, has_genre, 30463 13183, has_tags, 30463 13183, release_year, 39435 32834, has_genre, 30463 32834, has_tags, 30463 32834, release_year, 39435 5237, has_genre, 30463 5237, written_by, 33190 32916, has_genre, 30463 32916, release_year, 39435 18416, has_genre, 30463 18416, release_year, 39435 34930, has_genre, 30463 34930, release_year, 39435 1045, has_genre, 30463 1045, release_year, 39435 10409, has_genre, 30463 10409, release_year, 39435 32237, has_genre, 30463 32237, release_year, 39435 21920, has_genre, 30463 21920, release_year, 39435 21459, release_year, 39435 10721, has_genre, 30463 10721, release_year, 39435 23847, has_genre, 30463 23847, release_year, 39435 26081, has_genre, 30463 26081, release_year, 39435 Question: How are HAPPY TEARS, MAX SCHOTT, and THE PASSENGER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "HAPPY TEARS", "MAX SCHOTT", "THE PASSENGER" ], "valid_edges": [ [ "AT LONG LAST LOVE", "has_genre", "COMEDY" ], [ "AT LONG LAST LOVE", "release_year", "1975" ], [ "CRAZY MAMA", "has_genre", "COMEDY" ], [ "CRAZY MAMA", "release_year", "1975" ], [ "DOLEMITE", "has_genre", "COMEDY" ], [ "DOLEMITE", "release_year", "1975" ], [ "HAPPY TEARS", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "release_year", "1975" ], [ "LOVE AND DEATH", "has_genre", "COMEDY" ], [ "LOVE AND DEATH", "has_tags", "COMEDY" ], [ "LOVE AND DEATH", "release_year", "1975" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_genre", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_tags", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "release_year", "1975" ], [ "MURPHY'S ROMANCE", "has_genre", "COMEDY" ], [ "MURPHY'S ROMANCE", "written_by", "MAX SCHOTT" ], [ "MY FRIENDS", "has_genre", "COMEDY" ], [ "MY FRIENDS", "release_year", "1975" ], [ "ONE OF OUR DINOSAURS IS MISSING", "has_genre", "COMEDY" ], [ "ONE OF OUR DINOSAURS IS MISSING", "release_year", "1975" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "release_year", "1975" ], [ "SMILE", "has_genre", "COMEDY" ], [ "SMILE", "release_year", "1975" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "COMEDY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "release_year", "1975" ], [ "THE FORTUNE", "has_genre", "COMEDY" ], [ "THE FORTUNE", "release_year", "1975" ], [ "THE OLSEN GANG ON THE TRACK", "has_genre", "COMEDY" ], [ "THE OLSEN GANG ON THE TRACK", "release_year", "1975" ], [ "THE PASSENGER", "release_year", "1975" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "release_year", "1975" ], [ "THE STEPFORD WIVES", "has_genre", "COMEDY" ], [ "THE STEPFORD WIVES", "release_year", "1975" ], [ "THE SUNSHINE BOYS", "has_genre", "COMEDY" ], [ "THE SUNSHINE BOYS", "release_year", "1975" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 37484, 2004 1421, 2013 7603, CARY GRANT 847, JACK THE GIANT KILLER 37050, SHARKNADO 17493, SOUL PLANE 24322, THAT TOUCH OF MINK 38611, THE INTRUDER 32881, TOUCH OF PINK src, edge_attr, dst 847, release_year, 3863 847, release_year, 1421 37050, release_year, 1421 17493, release_year, 37484 24322, has_tags, 7603 24322, release_year, 3863 24322, starred_actors, 7603 38611, release_year, 3863 38611, release_year, 37484 32881, has_tags, 7603 32881, release_year, 37484 Question: For what reason are SHARKNADO, SOUL PLANE, and THAT TOUCH OF MINK associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "SHARKNADO", "SOUL PLANE", "THAT TOUCH OF MINK" ], "valid_edges": [ [ "JACK THE GIANT KILLER", "release_year", "1962" ], [ "JACK THE GIANT KILLER", "release_year", "2013" ], [ "SHARKNADO", "release_year", "2013" ], [ "SOUL PLANE", "release_year", "2004" ], [ "THAT TOUCH OF MINK", "has_tags", "CARY GRANT" ], [ "THAT TOUCH OF MINK", "release_year", "1962" ], [ "THAT TOUCH OF MINK", "starred_actors", "CARY GRANT" ], [ "THE INTRUDER", "release_year", "1962" ], [ "THE INTRUDER", "release_year", "2004" ], [ "TOUCH OF PINK", "has_tags", "CARY GRANT" ], [ "TOUCH OF PINK", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24004, 10 21931, 1941 724, 1979 1188, A FORCE OF ONE 12649, A LITTLE ROMANCE 4763, ADVENTURE 1216, AMERICATHON 34744, BEING THERE 37601, BREAKING AWAY 13302, CHAPTER TWO 38678, CHILLY SCENES OF WINTER 30463, COMEDY 15436, EPIC 19367, ESCAPE TO ATHENA 35760, H.O.T.S. 20263, HAIR 15547, HOMER 11331, LOVE AT FIRST BITE 33790, MANHATTAN 6108, MEATBALLS 26484, MORE AMERICAN GRAFFITI 14797, O BROTHER, WHERE ART THOU? 6773, REAL LIFE 22107, ROCK 'N' ROLL HIGH SCHOOL 27231, STARTING OVER 16018, THE APPLE DUMPLING GANG RIDES AGAIN 28510, THE FRISCO KID 19104, THE IN-LAWS 33024, THE JERK 4091, THE LADY VANISHES 32382, THE MAIN EVENT 12809, THE MUPPET MOVIE 31851, THE PRISONER OF ZENDA 26036, THE TEMPEST 33449, THE WEDDING PLANNER 5729, TROY 32079, ULYSSES 31435, UNCLE MARIN, THE BILLIONAIRE 22774, WISE BLOOD src, edge_attr, dst 24004, has_genre, 30463 24004, release_year, 724 21931, has_genre, 30463 21931, release_year, 724 1188, release_year, 724 12649, has_genre, 30463 12649, release_year, 724 1216, has_genre, 30463 1216, release_year, 724 34744, has_genre, 30463 34744, release_year, 724 37601, has_genre, 30463 37601, release_year, 724 13302, has_genre, 30463 13302, release_year, 724 38678, has_genre, 30463 38678, release_year, 724 19367, has_genre, 30463 19367, release_year, 724 35760, has_genre, 30463 35760, release_year, 724 20263, has_genre, 30463 20263, release_year, 724 11331, has_genre, 30463 11331, release_year, 724 33790, has_genre, 30463 33790, has_tags, 30463 33790, release_year, 724 6108, has_genre, 30463 6108, release_year, 724 26484, has_genre, 30463 26484, release_year, 724 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 14797, has_tags, 15436 14797, written_by, 15547 6773, has_genre, 30463 6773, release_year, 724 22107, has_genre, 30463 22107, release_year, 724 27231, has_genre, 30463 27231, release_year, 724 16018, has_genre, 30463 16018, release_year, 724 28510, has_genre, 30463 28510, release_year, 724 19104, has_genre, 30463 19104, release_year, 724 33024, has_genre, 30463 33024, release_year, 724 4091, has_genre, 30463 4091, release_year, 724 32382, has_genre, 30463 32382, release_year, 724 12809, has_genre, 30463 12809, release_year, 724 31851, has_genre, 30463 31851, release_year, 724 26036, has_genre, 30463 26036, release_year, 724 33449, has_genre, 30463 5729, has_genre, 4763 5729, has_tags, 15436 5729, has_tags, 15547 5729, written_by, 15547 32079, has_genre, 4763 32079, has_tags, 15547 32079, written_by, 15547 31435, has_genre, 30463 31435, release_year, 724 22774, has_genre, 30463 22774, release_year, 724 Question: In what context are A FORCE OF ONE, HOMER, and THE WEDDING PLANNER connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A FORCE OF ONE", "HOMER", "THE WEDDING PLANNER" ], "valid_edges": [ [ "10", "has_genre", "COMEDY" ], [ "10", "release_year", "1979" ], [ "1941", "has_genre", "COMEDY" ], [ "1941", "release_year", "1979" ], [ "A FORCE OF ONE", "release_year", "1979" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "release_year", "1979" ], [ "AMERICATHON", "has_genre", "COMEDY" ], [ "AMERICATHON", "release_year", "1979" ], [ "BEING THERE", "has_genre", "COMEDY" ], [ "BEING THERE", "release_year", "1979" ], [ "BREAKING AWAY", "has_genre", "COMEDY" ], [ "BREAKING AWAY", "release_year", "1979" ], [ "CHAPTER TWO", "has_genre", "COMEDY" ], [ "CHAPTER TWO", "release_year", "1979" ], [ "CHILLY SCENES OF WINTER", "has_genre", "COMEDY" ], [ "CHILLY SCENES OF WINTER", "release_year", "1979" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "ESCAPE TO ATHENA", "release_year", "1979" ], [ "H.O.T.S.", "has_genre", "COMEDY" ], [ "H.O.T.S.", "release_year", "1979" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "release_year", "1979" ], [ "LOVE AT FIRST BITE", "has_genre", "COMEDY" ], [ "LOVE AT FIRST BITE", "release_year", "1979" ], [ "MANHATTAN", "has_genre", "COMEDY" ], [ "MANHATTAN", "has_tags", "COMEDY" ], [ "MANHATTAN", "release_year", "1979" ], [ "MEATBALLS", "has_genre", "COMEDY" ], [ "MEATBALLS", "release_year", "1979" ], [ "MORE AMERICAN GRAFFITI", "has_genre", "COMEDY" ], [ "MORE AMERICAN GRAFFITI", "release_year", "1979" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "EPIC" ], [ "O BROTHER, WHERE ART THOU?", "written_by", "HOMER" ], [ "REAL LIFE", "has_genre", "COMEDY" ], [ "REAL LIFE", "release_year", "1979" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "release_year", "1979" ], [ "STARTING OVER", "has_genre", "COMEDY" ], [ "STARTING OVER", "release_year", "1979" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "has_genre", "COMEDY" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "release_year", "1979" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "release_year", "1979" ], [ "THE IN-LAWS", "has_genre", "COMEDY" ], [ "THE IN-LAWS", "release_year", "1979" ], [ "THE JERK", "has_genre", "COMEDY" ], [ "THE JERK", "release_year", "1979" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1979" ], [ "THE MAIN EVENT", "has_genre", "COMEDY" ], [ "THE MAIN EVENT", "release_year", "1979" ], [ "THE MUPPET MOVIE", "has_genre", "COMEDY" ], [ "THE MUPPET MOVIE", "release_year", "1979" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "release_year", "1979" ], [ "THE TEMPEST", "has_genre", "COMEDY" ], [ "THE TEMPEST", "release_year", "1979" ], [ "THE WEDDING PLANNER", "has_genre", "COMEDY" ], [ "TROY", "has_genre", "ADVENTURE" ], [ "TROY", "has_tags", "EPIC" ], [ "TROY", "has_tags", "HOMER" ], [ "TROY", "written_by", "HOMER" ], [ "ULYSSES", "has_genre", "ADVENTURE" ], [ "ULYSSES", "has_tags", "HOMER" ], [ "ULYSSES", "written_by", "HOMER" ], [ "UNCLE MARIN, THE BILLIONAIRE", "has_genre", "COMEDY" ], [ "UNCLE MARIN, THE BILLIONAIRE", "release_year", "1979" ], [ "WISE BLOOD", "has_genre", "COMEDY" ], [ "WISE BLOOD", "release_year", "1979" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21136, 10 MINUTES 3458, 1951 35935, 2002 4310, 24 HOUR PARTY PEOPLE 11069, 25TH HOUR 37315, A BRONX TALE 30846, A WALK TO REMEMBER 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 27949, AKA 35288, ALL OR NOTHING 20584, AMERICAN GANGSTER 26599, AMERICAN GUN 28374, ANTWONE FISHER 24409, ARARAT 23513, ASH WEDNESDAY 20199, AUTO FOCUS 12144, BAD BOYS 10516, BANG BANG YOU'RE DEAD 10045, BD-R 12954, BEAR'S KISS 15433, BEND IT LIKE BECKHAM 12228, BETTER LUCK TOMORROW 36708, BLUE CAR 22703, BOMB THE SYSTEM 16809, BOYS' NIGHT OUT 1637, BOYZ N THE HOOD 23286, CARNAGE 27059, CATCH ME IF YOU CAN 26946, CHANGING LANES 20073, CHERISH 10349, CHICAGO 61, CITY OF GHOSTS 33387, CITY OF GOD 30463, COMEDY 14724, CRIME 30019, CROSSROADS 16536, CYRANO DE BERGERAC 21730, DAY OF THE WACKO 24410, DEMONLOVER 30729, DENZEL WASHINGTON 30734, DEREK LUKE 23027, DEUCES WILD 31163, DIRECTORIAL DEBUT 9641, DIRTY PRETTY THINGS 32958, DIVINE SECRETS OF THE YA-YA SISTERHOOD 38750, DRAGONFLY 36212, DRAMA 25651, DUMMY 26714, EDGE OF MADNESS 12259, ENOUGH 11866, EVELYN 11422, FAR FROM HEAVEN 5563, FLIGHT 6012, FRENCH 23808, G 17400, GANGS OF NEW YORK 34145, GEORGES DARIEN 9759, GLORY 14023, GLORY ROAD 36646, HE GOT GAME 951, HEART OF AMERICA 10990, HEARTLANDS 39351, HEAVY 1292, HEDWIG AND THE ANGRY INCH 17118, HENRY V 3829, HERO 19943, HOUSE OF FOOLS 22024, I CAN GET IT FOR YOU WHOLESALE 17197, IGBY GOES DOWN 19412, IN AMERICA 25271, IN THIS WORLD 6092, INTERVIEW WITH THE ASSASSIN 6713, KAMCHATKA 30206, KEN PARK 29840, LAUREL CANYON 26893, LITTLE MAN TATE 26784, LITTLE WOMEN 39755, LIVE FROM BAGHDAD 17395, LUSTER 10058, MADAME SATÃ 19549, MALCOLM X 2445, MAX 23502, MICHAEL GORDON 14165, MISSISSIPPI MASALA 37076, MO' BETTER BLUES 1052, MOONLIGHT MILE 34696, MORVERN CALLAR 35534, MUJHSE DOSTI KAROGE! 38585, NICHOLAS NICKLEBY 25269, NINE LIVES 26644, OK 11093, OPEN HEARTS 22991, OUT OF THE BLUE 32999, PAID IN FULL 11222, PATHER PANCHALI 14744, PEOPLE I KNOW 3389, PHILADELPHIA 6579, PILLOW TALK 5286, POOLHALL JUNKIES 31588, PORTRAIT IN BLACK 39284, POSSESSION 34602, PUNCH-DRUNK LOVE 25023, QUARTET 24073, RABBIT-PROOF FENCE 5193, REMEMBER THE TITANS 25769, ROGER DODGER 10881, SAFE CONDUCT 22312, SAY ANYTHING... 25921, SOAP GIRL 6014, SOLARIS 7083, SONNY 35843, SPUN 39016, STOLEN SUMMER 28935, SUNSHINE STATE 33414, SWEET SIXTEEN 26790, SWEPT AWAY 32105, SYNECDOCHE, NEW YORK 9972, TALK TO HER 34235, TEXAS ACROSS THE RIVER 40106, THE ADVERSARY 2316, THE ANARCHIST COOKBOOK 38704, THE BRIDGE TO NOWHERE 19351, THE COUNT OF MONTE CRISTO 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 13044, THE EMPEROR'S CLUB 9522, THE ESCAPIST 11635, THE FOUR FEATHERS 10213, THE GREAT DEBATERS 31443, THE GUYS 11713, THE HOURS 13534, THE IMPORTANCE OF BEING EARNEST 32805, THE INTENDED 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23502 28829, has_genre, 36026 28829, release_year, 3458 8251, has_genre, 36212 8251, has_tags, 31163 11654, has_genre, 14724 11654, in_language, 6012 11654, written_by, 34145 27415, has_genre, 36212 27415, release_year, 35935 39555, has_genre, 36212 39555, release_year, 35935 32772, has_genre, 36212 32772, release_year, 35935 4705, has_genre, 36212 4705, release_year, 35935 8949, has_genre, 36212 8949, release_year, 35935 40043, has_genre, 36212 40043, has_tags, 36212 40043, release_year, 35935 19262, has_genre, 36212 19262, has_tags, 31163 13026, has_genre, 36212 13026, release_year, 35935 18995, has_genre, 36212 18995, release_year, 35935 Question: For what reason are ANTWONE FISHER, GEORGES DARIEN, and MICHAEL GORDON associated? 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PARK", "has_genre", "DRAMA" ], [ "KEN PARK", "release_year", "2002" ], [ "LAUREL CANYON", "has_genre", "DRAMA" ], [ "LAUREL CANYON", "release_year", "2002" ], [ "LITTLE MAN TATE", "has_genre", "DRAMA" ], [ "LITTLE MAN TATE", "has_tags", "DIRECTORIAL DEBUT" ], [ "LITTLE WOMEN", "has_genre", "DRAMA" ], [ "LITTLE WOMEN", "has_tags", "DRAMA" ], [ "LITTLE WOMEN", "has_tags", "OK" ], [ "LIVE FROM BAGHDAD", "has_genre", "DRAMA" ], [ "LIVE FROM BAGHDAD", "release_year", "2002" ], [ "LUSTER", "has_genre", "DRAMA" ], [ "LUSTER", "release_year", "2002" ], [ "MADAME SATÃ", "has_genre", "DRAMA" ], [ "MADAME SATÃ", "release_year", "2002" ], [ "MALCOLM X", "has_genre", "DRAMA" ], [ "MALCOLM X", "has_tags", "DENZEL WASHINGTON" ], [ "MALCOLM X", "starred_actors", "DENZEL WASHINGTON" ], [ "MAX", "has_genre", "DRAMA" ], [ "MAX", "release_year", "2002" ], [ "MISSISSIPPI MASALA", "has_genre", "DRAMA" ], [ "MISSISSIPPI MASALA", "starred_actors", "DENZEL WASHINGTON" ], [ "MO' BETTER BLUES", "has_genre", "DRAMA" ], [ "MO' BETTER BLUES", "starred_actors", "DENZEL WASHINGTON" ], [ "MOONLIGHT MILE", "has_genre", "DRAMA" ], [ "MOONLIGHT MILE", "release_year", "2002" ], [ "MORVERN CALLAR", "has_genre", "DRAMA" ], [ "MORVERN CALLAR", "release_year", "2002" ], [ "MUJHSE DOSTI KAROGE!", "has_genre", "DRAMA" ], [ "MUJHSE DOSTI KAROGE!", "release_year", "2002" ], [ "NICHOLAS NICKLEBY", "has_genre", "DRAMA" ], [ "NICHOLAS NICKLEBY", "release_year", "2002" ], [ "NINE LIVES", "has_genre", "DRAMA" ], [ "NINE LIVES", "release_year", "2002" ], [ "OPEN HEARTS", "has_genre", "DRAMA" ], [ "OPEN HEARTS", "has_tags", "DRAMA" ], [ "OPEN HEARTS", "release_year", "2002" ], [ "OUT OF THE BLUE", "has_genre", "DRAMA" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PAID IN FULL", "has_genre", "DRAMA" ], [ "PAID IN FULL", "release_year", "2002" ], [ "PATHER PANCHALI", "has_genre", "DRAMA" ], [ "PATHER PANCHALI", "has_tags", "DIRECTORIAL DEBUT" ], [ "PEOPLE I KNOW", "has_genre", "DRAMA" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "PHILADELPHIA", "has_genre", "DRAMA" ], [ "PHILADELPHIA", "has_tags", "DENZEL WASHINGTON" ], [ "PHILADELPHIA", "starred_actors", "DENZEL WASHINGTON" ], [ "PILLOW TALK", "directed_by", "MICHAEL GORDON" ], [ "PILLOW TALK", "has_genre", "COMEDY" ], [ "PILLOW TALK", "has_tags", "BD-R" ], [ "PILLOW TALK", "has_tags", "COMEDY" ], [ "PILLOW TALK", "has_tags", "MICHAEL GORDON" ], [ "POOLHALL JUNKIES", "has_genre", "DRAMA" ], [ "POOLHALL JUNKIES", "release_year", "2002" ], [ "PORTRAIT IN BLACK", "directed_by", "MICHAEL GORDON" ], [ "PORTRAIT IN BLACK", "has_genre", "CRIME" ], [ "PORTRAIT IN BLACK", "has_genre", "DRAMA" ], [ "POSSESSION", "has_genre", "DRAMA" ], [ "POSSESSION", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "DRAMA" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "QUARTET", "has_genre", "DRAMA" ], [ "QUARTET", "has_tags", "DIRECTORIAL DEBUT" ], [ "RABBIT-PROOF FENCE", "has_genre", "DRAMA" ], [ "RABBIT-PROOF FENCE", "release_year", "2002" ], [ "REMEMBER THE TITANS", "has_genre", "DRAMA" ], [ "REMEMBER THE TITANS", "has_tags", "DENZEL WASHINGTON" ], [ "REMEMBER THE TITANS", "has_tags", "DRAMA" ], [ "REMEMBER THE TITANS", "starred_actors", "DENZEL WASHINGTON" ], [ "ROGER DODGER", "has_genre", "DRAMA" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SAFE CONDUCT", "has_genre", "DRAMA" ], [ "SAFE CONDUCT", "release_year", "2002" ], [ "SAY ANYTHING...", "has_genre", "DRAMA" ], [ "SAY ANYTHING...", "has_tags", "DIRECTORIAL DEBUT" ], [ "SOAP GIRL", "has_genre", "DRAMA" ], [ "SOAP GIRL", "release_year", "2002" ], [ "SOLARIS", "has_genre", "DRAMA" ], [ "SOLARIS", "release_year", "2002" ], [ "SONNY", "has_genre", "DRAMA" ], [ "SONNY", "release_year", "2002" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "release_year", "2002" ], [ "STOLEN SUMMER", "has_genre", "DRAMA" ], [ "STOLEN SUMMER", "release_year", "2002" ], [ "SUNSHINE STATE", "has_genre", "DRAMA" ], [ "SUNSHINE STATE", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_genre", "DRAMA" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "SYNECDOCHE, NEW YORK", "has_genre", "DRAMA" ], [ "SYNECDOCHE, NEW YORK", "has_tags", "DIRECTORIAL DEBUT" ], [ "TALK TO HER", "has_genre", "DRAMA" ], [ "TALK TO HER", "has_tags", "DRAMA" ], [ "TALK TO HER", "release_year", "2002" ], [ "TEXAS ACROSS THE RIVER", "directed_by", "MICHAEL GORDON" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "COMEDY" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "WESTERN" ], [ "THE ADVERSARY", "has_genre", "DRAMA" ], [ "THE ADVERSARY", "release_year", "2002" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BRIDGE TO NOWHERE", "has_genre", "DRAMA" ], [ "THE BRIDGE TO NOWHERE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "DRAMA" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "DRAMA" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE EMPEROR'S CLUB", "has_genre", "DRAMA" ], [ "THE EMPEROR'S CLUB", "release_year", "2002" ], [ "THE ESCAPIST", "has_genre", "DRAMA" ], [ "THE ESCAPIST", "release_year", "2002" ], [ "THE FOUR FEATHERS", "has_genre", "DRAMA" ], [ "THE FOUR FEATHERS", "release_year", "2002" ], [ "THE GREAT DEBATERS", "directed_by", "DENZEL WASHINGTON" ], [ "THE GREAT DEBATERS", "has_genre", "DRAMA" ], [ "THE GREAT DEBATERS", "has_tags", "DENZEL WASHINGTON" ], [ "THE GREAT DEBATERS", "starred_actors", "DENZEL WASHINGTON" ], [ "THE GUYS", "has_genre", "DRAMA" ], [ "THE GUYS", "release_year", "2002" ], [ "THE HOURS", "has_genre", "DRAMA" ], [ "THE HOURS", "has_tags", "DRAMA" ], [ "THE HOURS", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "DRAMA" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE INTENDED", "has_genre", "DRAMA" ], [ "THE INTENDED", "release_year", "2002" ], [ "THE LARAMIE PROJECT", "has_genre", "DRAMA" ], [ "THE LARAMIE PROJECT", "release_year", "2002" ], [ "THE MAN WITHOUT A FACE", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A FACE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE MAN WITHOUT A FACE", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE PIANIST", "has_genre", "DRAMA" ], [ "THE PIANIST", "has_tags", "DRAMA" ], [ "THE PIANIST", "release_year", "2002" ], [ "THE ROOKIE", "has_genre", "DRAMA" ], [ "THE ROOKIE", "release_year", "2002" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SECRET LIFE OF ZOEY", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF ZOEY", "release_year", "2002" ], [ "THE SECRET LIVES OF DENTISTS", "has_genre", "DRAMA" ], [ "THE SECRET LIVES OF DENTISTS", "release_year", "2002" ], [ "THE SECRET OF CONVICT LAKE", "directed_by", "MICHAEL GORDON" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "release_year", "1951" ], [ "THE SECRET OF NIMH", "has_genre", "DRAMA" ], [ "THE SECRET OF NIMH", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE THIEF OF PARIS", "has_genre", "CRIME" ], [ "THE THIEF OF PARIS", "in_language", "FRENCH" ], [ "THE THIEF OF PARIS", "written_by", "GEORGES DARIEN" ], [ "THE THREE MARIAS", "has_genre", "DRAMA" ], [ "THE THREE MARIAS", "release_year", "2002" ], [ "THE TRACKER", "has_genre", "DRAMA" ], [ "THE TRACKER", "release_year", "2002" ], [ "UNFAITHFUL", "has_genre", "DRAMA" ], [ "UNFAITHFUL", "release_year", "2002" ], [ "WAITING FOR HAPPINESS", "has_genre", "DRAMA" ], [ "WAITING FOR HAPPINESS", "release_year", "2002" ], [ "WE WERE SOLDIERS", "has_genre", "DRAMA" ], [ "WE WERE SOLDIERS", "release_year", "2002" ], [ "WHALE RIDER", "has_genre", "DRAMA" ], [ "WHALE RIDER", "has_tags", "DRAMA" ], [ "WHALE RIDER", "release_year", "2002" ], [ "WHIP IT", "has_genre", "DRAMA" ], [ "WHIP IT", "has_tags", "DIRECTORIAL DEBUT" ], [ "WHITE OLEANDER", "has_genre", "DRAMA" ], [ "WHITE OLEANDER", "release_year", "2002" ], [ "XX/XY", "has_genre", "DRAMA" ], [ "XX/XY", "release_year", "2002" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 7977, 1969 30643, ACROSS THE UNIVERSE 8284, ANTHONY QUINN 14405, CHANGE OF HABIT 36000, CLAUDE CHABROL 22519, LAST TRAIN FROM GUN HILL 39572, LES COUSINS 22845, MUSIC 30889, ON THE BEACH 36122, STANLEY KRAMER 24926, SWEET CHARITY 25988, THE SECRET OF SANTA VITTORIA 10179, THIS MAN MUST DIE 10352, WARLOCK src, edge_attr, dst 30643, has_tags, 22845 14405, has_genre, 22845 14405, release_year, 7977 22519, release_year, 33637 22519, starred_actors, 8284 39572, directed_by, 36000 39572, has_tags, 36000 39572, release_year, 33637 39572, written_by, 36000 30889, directed_by, 36122 30889, has_tags, 36122 30889, release_year, 33637 24926, has_genre, 22845 24926, release_year, 7977 25988, directed_by, 36122 25988, has_tags, 36122 25988, release_year, 7977 25988, starred_actors, 8284 10179, directed_by, 36000 10179, has_tags, 36000 10179, release_year, 7977 10179, written_by, 36000 10352, release_year, 33637 10352, starred_actors, 8284 Question: For what reason are ACROSS THE UNIVERSE, LES COUSINS, and THE SECRET OF SANTA VITTORIA associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ACROSS THE UNIVERSE", "LES COUSINS", "THE SECRET OF SANTA VITTORIA" ], "valid_edges": [ [ "ACROSS THE UNIVERSE", "has_tags", "MUSIC" ], [ "CHANGE OF HABIT", "has_genre", "MUSIC" ], [ "CHANGE OF HABIT", "release_year", "1969" ], [ "LAST TRAIN FROM GUN HILL", "release_year", "1959" ], [ "LAST TRAIN FROM GUN HILL", "starred_actors", "ANTHONY QUINN" ], [ "LES COUSINS", "directed_by", "CLAUDE CHABROL" ], [ "LES COUSINS", "has_tags", "CLAUDE CHABROL" ], [ "LES COUSINS", "release_year", "1959" ], [ "LES COUSINS", "written_by", "CLAUDE CHABROL" ], [ "ON THE BEACH", "directed_by", "STANLEY KRAMER" ], [ "ON THE BEACH", "has_tags", "STANLEY KRAMER" ], [ "ON THE BEACH", "release_year", "1959" ], [ "SWEET CHARITY", "has_genre", "MUSIC" ], [ "SWEET CHARITY", "release_year", "1969" ], [ "THE SECRET OF SANTA VITTORIA", "directed_by", "STANLEY KRAMER" ], [ "THE SECRET OF SANTA VITTORIA", "has_tags", "STANLEY KRAMER" ], [ "THE SECRET OF SANTA VITTORIA", "release_year", "1969" ], [ "THE SECRET OF SANTA VITTORIA", "starred_actors", "ANTHONY QUINN" ], [ "THIS MAN MUST DIE", "directed_by", "CLAUDE CHABROL" ], [ "THIS MAN MUST DIE", "has_tags", "CLAUDE CHABROL" ], [ "THIS MAN MUST DIE", "release_year", "1969" ], [ "THIS MAN MUST DIE", "written_by", "CLAUDE CHABROL" ], [ "WARLOCK", "release_year", "1959" ], [ "WARLOCK", "starred_actors", "ANTHONY QUINN" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11112, 1939 10393, ALLEGHENY UPRISING 15585, CITY SLICKERS 31347, DANIEL STERN 7159, DESTRY RIDES AGAIN 28651, DODGE CITY 32474, EMMANUELLE 33897, EMMANUELLE ARSAN 4691, ERROL FLYNN 6012, FRENCH 13889, MICHAEL CURTIZ 31613, SAN ANTONIO 3226, STAGECOACH 23804, THE COMANCHEROS 37528, THE OKLAHOMA KID 33147, UNION PACIFIC 36026, WESTERN src, edge_attr, dst 10393, has_genre, 36026 10393, release_year, 11112 15585, has_genre, 36026 15585, has_tags, 31347 15585, starred_actors, 31347 7159, has_genre, 36026 7159, release_year, 11112 28651, directed_by, 13889 28651, has_genre, 36026 28651, has_tags, 13889 28651, release_year, 11112 28651, starred_actors, 4691 32474, in_language, 6012 32474, written_by, 33897 31613, has_genre, 36026 31613, starred_actors, 4691 3226, has_genre, 36026 3226, has_tags, 36026 3226, release_year, 11112 23804, directed_by, 13889 23804, has_genre, 36026 37528, has_genre, 36026 37528, has_tags, 36026 37528, release_year, 11112 33147, has_genre, 36026 33147, release_year, 11112 36026, in_language, 6012 Question: How are DANIEL STERN, DODGE CITY, and EMMANUELLE ARSAN related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DANIEL STERN", "DODGE CITY", "EMMANUELLE ARSAN" ], "valid_edges": [ [ "ALLEGHENY UPRISING", "has_genre", "WESTERN" ], [ "ALLEGHENY UPRISING", "release_year", "1939" ], [ "CITY SLICKERS", "has_genre", "WESTERN" ], [ "CITY SLICKERS", "has_tags", "DANIEL STERN" ], [ "CITY SLICKERS", "starred_actors", "DANIEL STERN" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "release_year", "1939" ], [ "DODGE CITY", "directed_by", "MICHAEL CURTIZ" ], [ "DODGE CITY", "has_genre", "WESTERN" ], [ "DODGE CITY", "has_tags", "MICHAEL CURTIZ" ], [ "DODGE CITY", "release_year", "1939" ], [ "DODGE CITY", "starred_actors", "ERROL FLYNN" ], [ "EMMANUELLE", "in_language", "FRENCH" ], [ "EMMANUELLE", "written_by", "EMMANUELLE ARSAN" ], [ "SAN ANTONIO", "has_genre", "WESTERN" ], [ "SAN ANTONIO", "starred_actors", "ERROL FLYNN" ], [ "STAGECOACH", "has_genre", "WESTERN" ], [ "STAGECOACH", "has_tags", "WESTERN" ], [ "STAGECOACH", "release_year", "1939" ], [ "THE COMANCHEROS", "directed_by", "MICHAEL CURTIZ" ], [ "THE COMANCHEROS", "has_genre", "WESTERN" ], [ "THE OKLAHOMA KID", "has_genre", "WESTERN" ], [ "THE OKLAHOMA KID", "has_tags", "WESTERN" ], [ "THE OKLAHOMA KID", "release_year", "1939" ], [ "UNION PACIFIC", "has_genre", "WESTERN" ], [ "UNION PACIFIC", "release_year", "1939" ], [ "WESTERN", "in_language", "FRENCH" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16363, ACROSS THE WIDE MISSOURI 39480, CHARLTON HESTON 31362, CLARK GABLE 37236, EDWARD DMYTRYK 20693, GONE WITH THE WIND 19802, LOVE 30629, NIGHT NURSE 20748, RECKLESS 655, SOLDIER OF FORTUNE 38416, SUSAN HAYWARD 572, THE CALL OF THE WILD 7272, THE PRESIDENT'S LADY 29044, WHERE LOVE HAS GONE 24706, WILLIAM A. WELLMAN src, edge_attr, dst 16363, directed_by, 24706 16363, starred_actors, 31362 20693, has_tags, 31362 20693, has_tags, 19802 30629, directed_by, 24706 30629, has_tags, 31362 30629, has_tags, 24706 30629, starred_actors, 31362 20748, has_tags, 19802 655, directed_by, 37236 655, starred_actors, 31362 655, starred_actors, 38416 572, directed_by, 24706 572, starred_actors, 39480 572, starred_actors, 31362 7272, starred_actors, 39480 7272, starred_actors, 38416 29044, directed_by, 37236 29044, starred_actors, 38416 Question: How are RECKLESS, SUSAN HAYWARD, and THE CALL OF THE WILD related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "RECKLESS", "SUSAN HAYWARD", "THE CALL OF THE WILD" ], "valid_edges": [ [ "ACROSS THE WIDE MISSOURI", "directed_by", "WILLIAM A. WELLMAN" ], [ "ACROSS THE WIDE MISSOURI", "starred_actors", "CLARK GABLE" ], [ "GONE WITH THE WIND", "has_tags", "CLARK GABLE" ], [ "GONE WITH THE WIND", "has_tags", "LOVE" ], [ "NIGHT NURSE", "directed_by", "WILLIAM A. WELLMAN" ], [ "NIGHT NURSE", "has_tags", "CLARK GABLE" ], [ "NIGHT NURSE", "has_tags", "WILLIAM A. WELLMAN" ], [ "NIGHT NURSE", "starred_actors", "CLARK GABLE" ], [ "RECKLESS", "has_tags", "LOVE" ], [ "SOLDIER OF FORTUNE", "directed_by", "EDWARD DMYTRYK" ], [ "SOLDIER OF FORTUNE", "starred_actors", "CLARK GABLE" ], [ "SOLDIER OF FORTUNE", "starred_actors", "SUSAN HAYWARD" ], [ "THE CALL OF THE WILD", "directed_by", "WILLIAM A. WELLMAN" ], [ "THE CALL OF THE WILD", "starred_actors", "CHARLTON HESTON" ], [ "THE CALL OF THE WILD", "starred_actors", "CLARK GABLE" ], [ "THE PRESIDENT'S LADY", "starred_actors", "CHARLTON HESTON" ], [ "THE PRESIDENT'S LADY", "starred_actors", "SUSAN HAYWARD" ], [ "WHERE LOVE HAS GONE", "directed_by", "EDWARD DMYTRYK" ], [ "WHERE LOVE HAS GONE", "starred_actors", "SUSAN HAYWARD" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 36212, DRAMA 25651, DUMMY 12847, EDITH EVANS 23543, LOOK BACK IN ANGER 825, THE LIFEGUARD 23973, THE NUN'S STORY src, edge_attr, dst 25651, has_genre, 36212 23543, has_genre, 36212 23543, release_year, 33637 23543, starred_actors, 12847 825, has_genre, 36212 23973, release_year, 33637 23973, starred_actors, 12847 Question: How are DUMMY, EDITH EVANS, and THE LIFEGUARD related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DUMMY", "EDITH EVANS", "THE LIFEGUARD" ], "valid_edges": [ [ "DUMMY", "has_genre", "DRAMA" ], [ "LOOK BACK IN ANGER", "has_genre", "DRAMA" ], [ "LOOK BACK IN ANGER", "release_year", "1959" ], [ "LOOK BACK IN ANGER", "starred_actors", "EDITH EVANS" ], [ "THE LIFEGUARD", "has_genre", "DRAMA" ], [ "THE NUN'S STORY", "release_year", "1959" ], [ "THE NUN'S STORY", "starred_actors", "EDITH EVANS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11479, BAPSI SIDHWA 29159, BENOÎT JAUBERT 36212, DRAMA 26751, EARTH 1321, IRON ISLAND 33870, MOHAMMAD RASOULOF 39594, REBELLION src, edge_attr, dst 26751, has_genre, 36212 26751, has_tags, 26751 26751, written_by, 11479 1321, directed_by, 33870 1321, has_genre, 36212 1321, written_by, 33870 39594, has_genre, 36212 39594, written_by, 29159 Question: How are BAPSI SIDHWA, BENOÎT JAUBERT, and MOHAMMAD RASOULOF related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "BAPSI SIDHWA", "BENOÎT JAUBERT", "MOHAMMAD RASOULOF" ], "valid_edges": [ [ "EARTH", "has_genre", "DRAMA" ], [ "EARTH", "has_tags", "EARTH" ], [ "EARTH", "written_by", "BAPSI SIDHWA" ], [ "IRON ISLAND", "directed_by", "MOHAMMAD RASOULOF" ], [ "IRON ISLAND", "has_genre", "DRAMA" ], [ "IRON ISLAND", "written_by", "MOHAMMAD RASOULOF" ], [ "REBELLION", "has_genre", "DRAMA" ], [ "REBELLION", "written_by", "BENOÎT JAUBERT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29598, AKI KAURISMÄKI 4017, ARIEL 30463, COMEDY 2246, CRITERION 36212, DRAMA 6666, FINNISH 28101, JACK TREVOR STORY 38003, KINYARWANDA 6838, MATTI PELLONPÄÄ 14976, MUNYURANGABO 64, PROLETARIAT TRILOGY 37803, SHADOWS IN PARADISE 13187, THE TROUBLE WITH HARRY src, edge_attr, dst 4017, directed_by, 29598 4017, has_genre, 36212 4017, has_tags, 29598 4017, has_tags, 2246 4017, has_tags, 6666 4017, has_tags, 64 4017, in_language, 6666 4017, starred_actors, 6838 4017, written_by, 29598 38003, has_genre, 36212 38003, in_language, 38003 14976, in_language, 38003 37803, directed_by, 29598 37803, has_genre, 30463 37803, has_genre, 36212 37803, has_tags, 29598 37803, has_tags, 2246 37803, has_tags, 64 37803, in_language, 6666 37803, starred_actors, 6838 37803, written_by, 29598 13187, has_genre, 30463 13187, written_by, 28101 Question: For what reason are JACK TREVOR STORY, MUNYURANGABO, and PROLETARIAT TRILOGY associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JACK TREVOR STORY", "MUNYURANGABO", "PROLETARIAT TRILOGY" ], "valid_edges": [ [ "ARIEL", "directed_by", "AKI KAURISMÄKI" ], [ "ARIEL", "has_genre", "DRAMA" ], [ "ARIEL", "has_tags", "AKI KAURISMÄKI" ], [ "ARIEL", "has_tags", "CRITERION" ], [ "ARIEL", "has_tags", "FINNISH" ], [ "ARIEL", "has_tags", "PROLETARIAT TRILOGY" ], [ "ARIEL", "in_language", "FINNISH" ], [ "ARIEL", "starred_actors", "MATTI PELLONPÄÄ" ], [ "ARIEL", "written_by", "AKI KAURISMÄKI" ], [ "KINYARWANDA", "has_genre", "DRAMA" ], [ "KINYARWANDA", "in_language", "KINYARWANDA" ], [ "MUNYURANGABO", "in_language", "KINYARWANDA" ], [ "SHADOWS IN PARADISE", "directed_by", "AKI KAURISMÄKI" ], [ "SHADOWS IN PARADISE", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "DRAMA" ], [ "SHADOWS IN PARADISE", "has_tags", "AKI KAURISMÄKI" ], [ "SHADOWS IN PARADISE", "has_tags", "CRITERION" ], [ "SHADOWS IN PARADISE", "has_tags", "PROLETARIAT TRILOGY" ], [ "SHADOWS IN PARADISE", "in_language", "FINNISH" ], [ "SHADOWS IN PARADISE", "starred_actors", "MATTI PELLONPÄÄ" ], [ "SHADOWS IN PARADISE", "written_by", "AKI KAURISMÄKI" ], [ "THE TROUBLE WITH HARRY", "has_genre", "COMEDY" ], [ "THE TROUBLE WITH HARRY", "written_by", "JACK TREVOR STORY" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6540, 12 25221, 1981 24438, 1993 17315, 2007 29424, 2011 20033, ANGEL 21731, BETRAYED 14984, BLOW OUT 28956, DEBRA WINGER 12628, EASTERN PROMISES 31783, ENGLISH 22423, GEORG 38465, HITMAN 27999, JOHN TRAVOLTA 22527, LANA TURNER 35491, LOOK WHO'S TALKING NOW 38169, MAD CITY 2990, MERMAID 17474, MICHAEL 34978, OLD DOGS 16206, RUSSIAN 30385, THE BANISHMENT 14131, THE POSTMAN ALWAYS RINGS TWICE 7816, THE THREE MUSKETEERS 13388, URBAN COWBOY 12255, WALT BECKER 18586, WILD HOGS src, edge_attr, dst 6540, in_language, 16206 6540, release_year, 17315 20033, release_year, 17315 21731, starred_actors, 28956 21731, starred_actors, 22527 14984, release_year, 25221 14984, starred_actors, 27999 12628, has_tags, 16206 12628, in_language, 16206 12628, release_year, 17315 22423, in_language, 16206 22423, release_year, 17315 38465, in_language, 16206 38465, release_year, 17315 35491, release_year, 24438 35491, starred_actors, 27999 38169, in_language, 31783 38169, starred_actors, 27999 2990, in_language, 16206 2990, release_year, 17315 17474, has_tags, 20033 17474, has_tags, 27999 17474, release_year, 29424 17474, starred_actors, 27999 34978, directed_by, 12255 34978, has_tags, 27999 34978, starred_actors, 27999 30385, in_language, 16206 30385, release_year, 17315 14131, in_language, 31783 14131, release_year, 25221 14131, starred_actors, 22527 7816, release_year, 24438 7816, release_year, 29424 7816, starred_actors, 22527 13388, starred_actors, 28956 13388, starred_actors, 27999 18586, directed_by, 12255 18586, has_tags, 27999 18586, release_year, 17315 18586, starred_actors, 27999 Question: For what reason are JOHN TRAVOLTA, LANA TURNER, and THE BANISHMENT associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOHN TRAVOLTA", "LANA TURNER", "THE BANISHMENT" ], "valid_edges": [ [ "12", "in_language", "RUSSIAN" ], [ "12", "release_year", "2007" ], [ "ANGEL", "release_year", "2007" ], [ "BETRAYED", "starred_actors", "DEBRA WINGER" ], [ "BETRAYED", "starred_actors", "LANA TURNER" ], [ "BLOW OUT", "release_year", "1981" ], [ "BLOW OUT", "starred_actors", "JOHN TRAVOLTA" ], [ "EASTERN PROMISES", "has_tags", "RUSSIAN" ], [ "EASTERN PROMISES", "in_language", "RUSSIAN" ], [ "EASTERN PROMISES", "release_year", "2007" ], [ "GEORG", "in_language", "RUSSIAN" ], [ "GEORG", "release_year", "2007" ], [ "HITMAN", "in_language", "RUSSIAN" ], [ "HITMAN", "release_year", "2007" ], [ "LOOK WHO'S TALKING NOW", "release_year", "1993" ], [ "LOOK WHO'S TALKING NOW", "starred_actors", "JOHN TRAVOLTA" ], [ "MAD CITY", "in_language", "ENGLISH" ], [ "MAD CITY", "starred_actors", "JOHN TRAVOLTA" ], [ "MERMAID", "in_language", "RUSSIAN" ], [ "MERMAID", "release_year", "2007" ], [ "MICHAEL", "has_tags", "ANGEL" ], [ "MICHAEL", "has_tags", "JOHN TRAVOLTA" ], [ "MICHAEL", "release_year", "2011" ], [ "MICHAEL", "starred_actors", "JOHN TRAVOLTA" ], [ "OLD DOGS", "directed_by", "WALT BECKER" ], [ "OLD DOGS", "has_tags", "JOHN TRAVOLTA" ], [ "OLD DOGS", "starred_actors", "JOHN TRAVOLTA" ], [ "THE BANISHMENT", "in_language", "RUSSIAN" ], [ "THE BANISHMENT", "release_year", "2007" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "in_language", "ENGLISH" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "release_year", "1981" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "starred_actors", "LANA TURNER" ], [ "THE THREE MUSKETEERS", "release_year", "1993" ], [ "THE THREE MUSKETEERS", "release_year", "2011" ], [ "THE THREE MUSKETEERS", "starred_actors", "LANA TURNER" ], [ "URBAN COWBOY", "starred_actors", "DEBRA WINGER" ], [ "URBAN COWBOY", "starred_actors", "JOHN TRAVOLTA" ], [ "WILD HOGS", "directed_by", "WALT BECKER" ], [ "WILD HOGS", "has_tags", "JOHN TRAVOLTA" ], [ "WILD HOGS", "release_year", "2007" ], [ "WILD HOGS", "starred_actors", "JOHN TRAVOLTA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 18598, APPLESEED 2182, BLOOD AND BONES 231, CASSHERN 5113, DEAD LEAVES 23809, DOG NAIL CLIPPER 13409, HANA AND ALICE 12087, HOWL'S MOVING CASTLE 34710, IN THE REALM OF THE SENSES 13174, INFECTION 8164, IZO 36874, JAPANESE 15150, KAMIKAZE GIRLS 30532, MIND GAME 25709, NOBODY KNOWS 6302, ONIBABA 31842, SURVIVE STYLE 5+ 786, THE GRUDGE 9554, THROW DOWN 28132, TONY TAKITANI 12437, VITAL src, edge_attr, dst 18598, in_language, 36874 18598, release_year, 37484 2182, in_language, 36874 2182, release_year, 37484 231, has_tags, 36874 231, in_language, 36874 231, release_year, 37484 5113, in_language, 36874 5113, release_year, 37484 23809, release_year, 37484 13409, in_language, 36874 13409, release_year, 37484 12087, in_language, 36874 12087, release_year, 37484 34710, has_tags, 36874 34710, in_language, 36874 13174, in_language, 36874 13174, release_year, 37484 8164, in_language, 36874 8164, release_year, 37484 15150, has_tags, 36874 15150, in_language, 36874 15150, release_year, 37484 30532, in_language, 36874 30532, release_year, 37484 25709, in_language, 36874 25709, release_year, 37484 6302, in_language, 36874 31842, has_tags, 36874 31842, in_language, 36874 31842, release_year, 37484 786, in_language, 36874 786, release_year, 37484 9554, in_language, 36874 9554, release_year, 37484 28132, in_language, 36874 28132, release_year, 37484 12437, in_language, 36874 12437, release_year, 37484 Question: In what context are DOG NAIL CLIPPER, IN THE REALM OF THE SENSES, and ONIBABA connected? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "DOG NAIL CLIPPER", "IN THE REALM OF THE SENSES", "ONIBABA" ], "valid_edges": [ [ "APPLESEED", "in_language", "JAPANESE" ], [ "APPLESEED", "release_year", "2004" ], [ "BLOOD AND BONES", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "release_year", "2004" ], [ "CASSHERN", "has_tags", "JAPANESE" ], [ "CASSHERN", "in_language", "JAPANESE" ], [ "CASSHERN", "release_year", "2004" ], [ "DEAD LEAVES", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "release_year", "2004" ], [ "DOG NAIL CLIPPER", "release_year", "2004" ], [ "HANA AND ALICE", "in_language", "JAPANESE" ], [ "HANA AND ALICE", "release_year", "2004" ], [ "HOWL'S MOVING CASTLE", "in_language", "JAPANESE" ], [ "HOWL'S MOVING CASTLE", "release_year", "2004" ], [ "IN THE REALM OF THE SENSES", "has_tags", "JAPANESE" ], [ "IN THE REALM OF THE SENSES", "in_language", "JAPANESE" ], [ "INFECTION", "in_language", "JAPANESE" ], [ "INFECTION", "release_year", "2004" ], [ "IZO", "in_language", "JAPANESE" ], [ "IZO", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "has_tags", "JAPANESE" ], [ "KAMIKAZE GIRLS", "in_language", "JAPANESE" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "MIND GAME", "in_language", "JAPANESE" ], [ "MIND GAME", "release_year", "2004" ], [ "NOBODY KNOWS", "in_language", "JAPANESE" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "ONIBABA", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "has_tags", "JAPANESE" ], [ "SURVIVE STYLE 5+", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "release_year", "2004" ], [ "THE GRUDGE", "in_language", "JAPANESE" ], [ "THE GRUDGE", "release_year", "2004" ], [ "THROW DOWN", "in_language", "JAPANESE" ], [ "THROW DOWN", "release_year", "2004" ], [ "TONY TAKITANI", "in_language", "JAPANESE" ], [ "TONY TAKITANI", "release_year", "2004" ], [ "VITAL", "in_language", "JAPANESE" ], [ "VITAL", "release_year", "2004" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 19407, 8½ 9677, ANATOMY OF A MURDER 19978, BEN GAZZARA 13577, CITY OF WOMEN 22958, FAMOUS 3353, FEDERICO FELLINI 34311, GENA ROWLANDS 15135, GINGER AND FRED 17549, MARCELLO MASTROIANNI 5343, OPENING NIGHT 6002, PAULIE src, edge_attr, dst 19407, directed_by, 3353 19407, has_imdb_votes, 22958 19407, has_tags, 3353 19407, starred_actors, 17549 19407, written_by, 3353 9677, has_imdb_votes, 22958 9677, starred_actors, 19978 13577, directed_by, 3353 13577, starred_actors, 17549 13577, written_by, 3353 15135, directed_by, 3353 15135, starred_actors, 17549 15135, written_by, 3353 5343, starred_actors, 19978 5343, starred_actors, 34311 6002, starred_actors, 34311 Question: How are ANATOMY OF A MURDER, GINGER AND FRED, and PAULIE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ANATOMY OF A MURDER", "GINGER AND FRED", "PAULIE" ], "valid_edges": [ [ "8½", "directed_by", "FEDERICO FELLINI" ], [ "8½", "has_imdb_votes", "FAMOUS" ], [ "8½", "has_tags", "FEDERICO FELLINI" ], [ "8½", "starred_actors", "MARCELLO MASTROIANNI" ], [ "8½", "written_by", "FEDERICO FELLINI" ], [ "ANATOMY OF A MURDER", "has_imdb_votes", "FAMOUS" ], [ "ANATOMY OF A MURDER", "starred_actors", "BEN GAZZARA" ], [ "CITY OF WOMEN", "directed_by", "FEDERICO FELLINI" ], [ "CITY OF WOMEN", "starred_actors", "MARCELLO MASTROIANNI" ], [ "CITY OF WOMEN", "written_by", "FEDERICO FELLINI" ], [ "GINGER AND FRED", "directed_by", "FEDERICO FELLINI" ], [ "GINGER AND FRED", "starred_actors", "MARCELLO MASTROIANNI" ], [ "GINGER AND FRED", "written_by", "FEDERICO FELLINI" ], [ "OPENING NIGHT", "starred_actors", "BEN GAZZARA" ], [ "OPENING NIGHT", "starred_actors", "GENA ROWLANDS" ], [ "PAULIE", "starred_actors", "GENA ROWLANDS" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6750, 10 RILLINGTON PLACE 30146, A CHRISTMAS CAROL 1698, ALFIE 9677, ANATOMY OF A MURDER 10045, BD-R 15771, BENGAZI 19826, BLACK DEATH 39111, BORN FREE 38680, COMPULSION 2149, DOG DAY AFTERNOON 36212, DRAMA 17986, GABRIEL OVER THE WHITE HOUSE 24900, JOHN RICHARDSON 35463, JUSTIN CHON 14209, KING OF HEARTS 36639, LADIES THEY TALK ABOUT 30029, LAWRENCE OF ARABIA 5996, MEET JOHN DOE 30629, NIGHT NURSE 35865, ON THE WATERFRONT 27496, ONE MILLION YEARS B.C. 29534, REVENGE OF THE GREEN DRAGONS 35586, SAHARA 6056, SCARFACE 15003, THE BATTLE OF ALGIERS 33978, THE BRIBE 11635, THE FOUR FEATHERS 37567, THE OSCAR 31851, THE PRISONER OF ZENDA 7478, THE RACKET 30746, THE SECRET LIFE OF WALTER MITTY 31647, THE SON OF THE SHEIK 7816, THE THREE MUSKETEERS 983, THE TREASURE OF THE SIERRA MADRE 28744, THE UNHOLY THREE 34407, THE WRONG MAN 873, THEY MADE ME A CRIMINAL 18596, THREE ON A MATCH 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 297, WINGS src, edge_attr, dst 6750, has_genre, 36212 6750, has_tags, 10045 30146, has_genre, 36212 30146, has_tags, 10045 1698, has_genre, 36212 1698, has_tags, 10045 9677, has_genre, 36212 9677, has_tags, 10045 15771, has_genre, 36212 15771, has_tags, 10045 19826, has_genre, 36212 19826, has_tags, 10045 39111, has_genre, 36212 39111, has_tags, 10045 38680, has_genre, 36212 38680, has_tags, 10045 2149, has_genre, 36212 2149, has_tags, 10045 17986, has_genre, 36212 17986, has_tags, 10045 14209, has_genre, 36212 14209, has_tags, 10045 36639, has_genre, 36212 36639, has_tags, 10045 30029, has_genre, 36212 30029, has_tags, 10045 5996, has_genre, 36212 5996, has_tags, 10045 30629, has_genre, 36212 30629, has_tags, 10045 35865, has_genre, 36212 35865, has_tags, 10045 27496, has_tags, 10045 27496, starred_actors, 24900 29534, has_genre, 36212 29534, starred_actors, 35463 35586, has_genre, 36212 35586, has_tags, 10045 6056, has_genre, 36212 6056, has_tags, 10045 6056, has_tags, 36212 15003, has_genre, 36212 15003, has_tags, 10045 33978, has_genre, 36212 33978, has_tags, 10045 11635, has_genre, 36212 11635, has_tags, 10045 37567, has_genre, 36212 37567, has_tags, 10045 31851, has_genre, 36212 31851, has_tags, 10045 7478, has_genre, 36212 7478, has_tags, 10045 30746, has_genre, 36212 30746, has_tags, 10045 31647, has_genre, 36212 31647, has_tags, 10045 7816, has_genre, 36212 7816, has_tags, 10045 983, has_genre, 36212 983, has_tags, 10045 28744, has_genre, 36212 28744, has_tags, 10045 34407, has_genre, 36212 34407, has_tags, 10045 873, has_genre, 36212 873, has_tags, 10045 18596, has_genre, 36212 18596, has_tags, 10045 35212, has_genre, 36212 35212, has_tags, 10045 297, has_genre, 36212 297, has_tags, 10045 Question: How are JOHN RICHARDSON, JUSTIN CHON, and MEET JOHN DOE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "JOHN RICHARDSON", "JUSTIN CHON", "MEET JOHN DOE" ], "valid_edges": [ [ "10 RILLINGTON PLACE", "has_genre", "DRAMA" ], [ "10 RILLINGTON PLACE", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "has_tags", "BD-R" ], [ "ANATOMY OF A MURDER", "has_genre", "DRAMA" ], [ "ANATOMY OF A MURDER", "has_tags", "BD-R" ], [ "BENGAZI", "has_genre", "DRAMA" ], [ "BENGAZI", "has_tags", "BD-R" ], [ "BLACK DEATH", "has_genre", "DRAMA" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BORN FREE", "has_genre", "DRAMA" ], [ "BORN FREE", "has_tags", "BD-R" ], [ "COMPULSION", "has_genre", "DRAMA" ], [ "COMPULSION", "has_tags", "BD-R" ], [ "DOG DAY AFTERNOON", "has_genre", "DRAMA" ], [ "DOG DAY AFTERNOON", "has_tags", "BD-R" ], [ "GABRIEL OVER THE WHITE HOUSE", "has_genre", "DRAMA" ], [ "GABRIEL OVER THE WHITE HOUSE", "has_tags", "BD-R" ], [ "KING OF HEARTS", "has_genre", "DRAMA" ], [ "KING OF HEARTS", "has_tags", "BD-R" ], [ "LADIES THEY TALK ABOUT", "has_genre", "DRAMA" ], [ "LADIES THEY TALK ABOUT", "has_tags", "BD-R" ], [ "LAWRENCE OF ARABIA", "has_genre", "DRAMA" ], [ "LAWRENCE OF ARABIA", "has_tags", "BD-R" ], [ "MEET JOHN DOE", "has_genre", "DRAMA" ], [ "MEET JOHN DOE", "has_tags", "BD-R" ], [ "NIGHT NURSE", "has_genre", "DRAMA" ], [ "NIGHT NURSE", "has_tags", "BD-R" ], [ "ON THE WATERFRONT", "has_genre", "DRAMA" ], [ "ON THE WATERFRONT", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "starred_actors", "JOHN RICHARDSON" ], [ "REVENGE OF THE GREEN DRAGONS", "has_genre", "DRAMA" ], [ "REVENGE OF THE GREEN DRAGONS", "starred_actors", "JUSTIN CHON" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SCARFACE", "has_genre", "DRAMA" ], [ "SCARFACE", "has_tags", "BD-R" ], [ "SCARFACE", "has_tags", "DRAMA" ], [ "THE BATTLE OF ALGIERS", "has_genre", "DRAMA" ], [ "THE BATTLE OF ALGIERS", "has_tags", "BD-R" ], [ "THE BRIBE", "has_genre", "DRAMA" ], [ "THE BRIBE", "has_tags", "BD-R" ], [ "THE FOUR FEATHERS", "has_genre", "DRAMA" ], [ "THE FOUR FEATHERS", "has_tags", "BD-R" ], [ "THE OSCAR", "has_genre", "DRAMA" ], [ "THE OSCAR", "has_tags", "BD-R" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE PRISONER OF ZENDA", "has_tags", "BD-R" ], [ "THE RACKET", "has_genre", "DRAMA" ], [ "THE RACKET", "has_tags", "BD-R" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_tags", "BD-R" ], [ "THE SON OF THE SHEIK", "has_genre", "DRAMA" ], [ "THE SON OF THE SHEIK", "has_tags", "BD-R" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE THREE MUSKETEERS", "has_tags", "BD-R" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_genre", "DRAMA" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_tags", "BD-R" ], [ "THE UNHOLY THREE", "has_genre", "DRAMA" ], [ "THE UNHOLY THREE", "has_tags", "BD-R" ], [ "THE WRONG MAN", "has_genre", "DRAMA" ], [ "THE WRONG MAN", "has_tags", "BD-R" ], [ "THEY MADE ME A CRIMINAL", "has_genre", "DRAMA" ], [ "THEY MADE ME A CRIMINAL", "has_tags", "BD-R" ], [ "THREE ON A MATCH", "has_genre", "DRAMA" ], [ "THREE ON A MATCH", "has_tags", "BD-R" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_genre", "DRAMA" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_tags", "BD-R" ], [ "WINGS", "has_genre", "DRAMA" ], [ "WINGS", "has_tags", "BD-R" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 20720, BLACK LIKE ME 755, CHARLES MATTHAU 36212, DRAMA 6274, FRANK CRAVEN 10869, GERDA LERNER 23553, OUR TOWN 39138, THE GRASS HARP src, edge_attr, dst 20720, has_genre, 36212 20720, written_by, 10869 23553, has_genre, 36212 23553, written_by, 6274 39138, directed_by, 755 39138, has_genre, 36212 Question: How are CHARLES MATTHAU, FRANK CRAVEN, and GERDA LERNER related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHARLES MATTHAU", "FRANK CRAVEN", "GERDA LERNER" ], "valid_edges": [ [ "BLACK LIKE ME", "has_genre", "DRAMA" ], [ "BLACK LIKE ME", "written_by", "GERDA LERNER" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "written_by", "FRANK CRAVEN" ], [ "THE GRASS HARP", "directed_by", "CHARLES MATTHAU" ], [ "THE GRASS HARP", "has_genre", "DRAMA" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 9377, 2014 10023, 99 HOMES 10054, A WALK AMONG THE TOMBSTONES 23806, ADDICTED 38361, AFFLUENZA 17534, ALOFT 34713, AN EDUCATION 37270, AND SO IT GOES 39876, ANNIE 18725, BAREFOOT 28764, BEGIN AGAIN 25930, BETTER LIVING THROUGH CHEMISTRY 36169, BEYOND THE LIGHTS 22684, BIG EYES 2975, BIRD PEOPLE 28685, BLIND 16290, BOYHOOD 37883, BROKEN EMBRACES 19993, C.O.G. 19004, CAKE 13812, CALVARY 17633, CAMP X-RAY 14816, CHARMING 20757, CLOUDS OF SILS MARIA 34890, COMET 9864, COMMON 33976, DAYS AND NIGHTS 10518, DEAR WHITE PEOPLE 17921, DRAFT DAY 36212, DRAMA 4838, EAT PRAY LOVE 7480, EDEN 13700, ENDLESS LOVE 34996, FORCE MAJEURE 32235, FOXCATCHER 38339, FRANK 5287, FROZEN 39145, FURY 25582, GIRLHOOD 7291, GOD HELP THE GIRL 24733, GOD'S NOT DEAD 31512, GOD'S POCKET 7319, GOODBYE TO LANGUAGE 28947, HAIDER 8617, HAPPY CHRISTMAS 6599, HEALING 9610, HEAVEN IS FOR REAL 20139, HELLION 29012, HER 6025, HIGHWAY 16788, INBETWEEN WORLDS 9748, INHERENT VICE 8793, JAMESY BOY 12031, JAMIE MARKS IS DEAD 21080, JAUJA 4246, JERSEY BOYS 17871, JONATHAN GROFF 1073, KILL THE MESSENGER 29887, KUMIKO, THE TREASURE HUNTER 37258, LARRY KRAMER 12760, LATE PHASES 824, LATITUDES 36329, LEVIATHAN 35542, LILTING 21502, LISTEN UP PHILIP 27480, LITTLE ACCIDENTS 24601, LOST HORIZON 31635, LOVE IS STRANGE 13249, LULLABY 7203, MAPS TO THE STARS 6592, MARGARET 5032, MARK RUFFALO 35271, MELODRAMA 35465, MILLION DOLLAR ARM 1911, MOMMY 9635, MR. TURNER 12944, MY LIFE WITHOUT ME 40064, MY OLD LADY 6766, PERFECT SISTERS 34922, PK 23152, PRIDE 12428, RAGE 17082, RESERVATION ROAD 28797, ROB THE MOB 3126, ROSEWATER 30895, RUDDERLESS 5766, RUNNING WITH SCISSORS 31492, RYAN MURPHY 32252, SAINT LAURENT 33939, SALTING THE BATTLEFIELD 38319, SELMA 26687, SENSO 3096, SERENA 19715, ST. VINCENT 23194, STATIONS OF THE CROSS 13635, STILL ALICE 34516, SYMPATHY FOR DELICIOUS 21160, THANK YOU A LOT 19501, THANKS FOR SHARING 9114, THE ANGRIEST MAN IN BROOKLYN 29460, THE BEST OF ME 5013, THE CIRCLE 11375, THE COBBLER 23306, THE DROP 4766, THE FAULT IN OUR STARS 32416, THE GOOD LIE 14626, THE HOMESMAN 36793, THE HUNDRED-FOOT JOURNEY 9406, THE IMITATION GAME 19629, THE JUDGE 4143, THE LAST CASTLE 30805, THE NEW GIRLFRIEND 35470, THE NORMAL HEART 3765, THE OTHER WOMAN 14064, THE OUTSIDER 8660, THE RECKONING 14115, THE ROVER 1492, THE SINGLE MOMS CLUB 9568, THE SKELETON TWINS 2559, THE THEORY OF EVERYTHING 31381, THE WAY HE LOOKS 34649, THE WONDERS 14919, THERE'S ALWAYS TOMORROW 698, THIS IS WHERE I LEAVE YOU 7969, TIMBUKTU 17726, TUSK 14504, UNBROKEN 36178, VERONICA MARS 10185, WELCOME TO NEW YORK 5465, WHAT DOESN'T KILL YOU 15726, WHEN ANIMALS DREAM 38804, WHIPLASH 14840, WHITE GOD 142, WILD 26235, WINTER SLEEP 4820, WISH I WAS HERE 37252, WOMEN IN LOVE 18995, XX/XY 12162, YOU CAN COUNT ON ME 5209, YVES SAINT LAURENT src, edge_attr, dst 10023, has_genre, 36212 10023, release_year, 9377 10054, has_genre, 36212 10054, release_year, 9377 23806, has_genre, 36212 23806, release_year, 9377 38361, has_genre, 36212 38361, release_year, 9377 17534, has_genre, 36212 17534, release_year, 9377 34713, has_genre, 36212 34713, has_tags, 14816 34713, release_year, 27261 37270, has_genre, 36212 37270, release_year, 9377 39876, has_genre, 36212 39876, release_year, 9377 18725, has_genre, 36212 18725, release_year, 9377 28764, has_genre, 36212 28764, has_tags, 5032 28764, starred_actors, 5032 25930, has_genre, 36212 25930, release_year, 9377 36169, has_genre, 36212 36169, release_year, 9377 22684, has_genre, 36212 22684, release_year, 9377 2975, has_genre, 36212 2975, release_year, 9377 28685, has_genre, 36212 28685, release_year, 9377 16290, has_genre, 36212 16290, has_tags, 9377 16290, release_year, 9377 37883, has_genre, 36212 37883, has_tags, 35271 37883, release_year, 27261 19993, has_genre, 36212 19993, starred_actors, 17871 19004, has_genre, 36212 19004, release_year, 9377 13812, has_genre, 36212 13812, release_year, 9377 17633, has_genre, 36212 17633, release_year, 9377 20757, has_genre, 36212 20757, release_year, 9377 34890, has_genre, 36212 34890, release_year, 9377 9864, has_genre, 36212 9864, release_year, 9377 33976, has_genre, 36212 33976, release_year, 9377 10518, has_genre, 36212 10518, release_year, 9377 17921, has_genre, 36212 17921, release_year, 9377 4838, directed_by, 31492 4838, has_genre, 36212 4838, written_by, 31492 7480, has_genre, 36212 7480, release_year, 9377 13700, has_genre, 36212 13700, release_year, 9377 34996, has_genre, 36212 34996, has_tags, 9377 34996, release_year, 9377 32235, has_genre, 36212 32235, has_tags, 5032 32235, release_year, 9377 32235, starred_actors, 5032 38339, has_genre, 36212 38339, release_year, 9377 5287, has_genre, 36212 5287, starred_actors, 17871 39145, has_genre, 36212 39145, release_year, 9377 25582, has_genre, 36212 25582, release_year, 9377 7291, has_genre, 36212 7291, release_year, 9377 24733, has_genre, 36212 24733, release_year, 9377 31512, has_genre, 36212 31512, release_year, 9377 7319, has_genre, 36212 7319, release_year, 9377 28947, has_genre, 36212 28947, release_year, 9377 8617, has_genre, 36212 8617, release_year, 9377 6599, has_genre, 36212 6599, release_year, 9377 9610, has_genre, 36212 9610, release_year, 9377 20139, has_genre, 36212 20139, release_year, 9377 29012, has_genre, 36212 29012, has_tags, 9377 6025, has_genre, 36212 6025, release_year, 9377 16788, has_genre, 36212 16788, release_year, 9377 9748, has_genre, 36212 9748, release_year, 9377 8793, has_genre, 36212 8793, release_year, 9377 12031, has_genre, 36212 12031, release_year, 9377 21080, has_genre, 36212 21080, release_year, 9377 4246, has_genre, 36212 4246, release_year, 9377 1073, has_genre, 36212 1073, release_year, 9377 29887, has_genre, 36212 29887, release_year, 9377 12760, has_genre, 36212 12760, release_year, 9377 824, has_genre, 36212 824, release_year, 9377 36329, has_genre, 36212 36329, release_year, 9377 35542, has_genre, 36212 35542, release_year, 9377 21502, has_genre, 36212 21502, release_year, 9377 27480, has_genre, 36212 27480, release_year, 9377 24601, has_genre, 36212 24601, written_by, 37258 31635, has_genre, 36212 31635, release_year, 9377 13249, has_genre, 36212 13249, release_year, 9377 7203, has_genre, 36212 7203, has_tags, 36212 7203, release_year, 9377 6592, has_genre, 36212 6592, has_tags, 36212 6592, starred_actors, 5032 35465, has_genre, 36212 35465, release_year, 9377 1911, has_genre, 36212 1911, release_year, 9377 9635, has_genre, 36212 9635, release_year, 9377 12944, has_genre, 36212 12944, has_tags, 5032 40064, has_genre, 36212 40064, release_year, 9377 6766, has_genre, 36212 6766, release_year, 9377 34922, has_genre, 36212 34922, release_year, 9377 23152, has_genre, 36212 23152, release_year, 9377 12428, has_genre, 36212 12428, release_year, 9377 17082, has_genre, 36212 17082, has_tags, 5032 28797, has_genre, 36212 28797, release_year, 9377 3126, has_genre, 36212 3126, release_year, 9377 30895, has_genre, 36212 30895, release_year, 9377 5766, directed_by, 31492 5766, has_genre, 36212 5766, written_by, 31492 32252, has_genre, 36212 32252, release_year, 9377 33939, has_genre, 36212 33939, release_year, 9377 38319, has_genre, 36212 38319, release_year, 9377 26687, has_genre, 36212 26687, has_tags, 35271 3096, has_genre, 36212 3096, release_year, 9377 19715, has_genre, 36212 19715, release_year, 9377 23194, has_genre, 36212 23194, release_year, 9377 13635, has_genre, 36212 13635, release_year, 9377 34516, directed_by, 5032 34516, has_genre, 36212 34516, starred_actors, 5032 21160, has_genre, 36212 21160, release_year, 9377 19501, has_genre, 36212 19501, starred_actors, 5032 9114, has_genre, 36212 9114, release_year, 9377 29460, has_genre, 36212 29460, release_year, 9377 5013, has_genre, 36212 5013, release_year, 9377 11375, has_genre, 36212 11375, release_year, 9377 23306, has_genre, 36212 23306, release_year, 9377 4766, has_genre, 36212 4766, has_tags, 36212 4766, release_year, 9377 32416, has_genre, 36212 32416, release_year, 9377 14626, has_genre, 36212 14626, release_year, 9377 36793, has_genre, 36212 36793, release_year, 9377 9406, has_genre, 36212 9406, release_year, 9377 19629, has_genre, 36212 19629, release_year, 9377 4143, has_genre, 36212 4143, starred_actors, 5032 30805, has_genre, 36212 30805, release_year, 9377 35470, directed_by, 31492 35470, has_genre, 36212 35470, release_year, 9377 35470, starred_actors, 17871 35470, starred_actors, 5032 35470, written_by, 37258 3765, has_genre, 36212 3765, release_year, 9377 14064, has_genre, 36212 14064, release_year, 9377 8660, has_genre, 36212 8660, release_year, 9377 14115, has_genre, 36212 14115, release_year, 9377 1492, has_genre, 36212 1492, release_year, 9377 9568, has_genre, 36212 9568, release_year, 9377 2559, has_genre, 36212 2559, release_year, 9377 31381, has_genre, 36212 31381, has_tags, 36212 31381, release_year, 9377 34649, has_genre, 36212 34649, release_year, 9377 14919, has_genre, 36212 14919, has_tags, 35271 698, has_genre, 36212 698, release_year, 9377 7969, has_genre, 36212 7969, release_year, 9377 17726, has_genre, 36212 17726, release_year, 9377 14504, has_genre, 36212 14504, release_year, 9377 36178, has_genre, 36212 36178, release_year, 9377 10185, has_genre, 36212 10185, release_year, 9377 5465, has_genre, 36212 5465, has_tags, 5032 5465, starred_actors, 5032 15726, has_genre, 36212 15726, release_year, 9377 38804, has_genre, 36212 38804, release_year, 9377 14840, has_genre, 36212 14840, release_year, 9377 142, has_genre, 36212 142, release_year, 9377 26235, has_genre, 36212 26235, release_year, 9377 4820, has_genre, 36212 4820, release_year, 9377 37252, has_genre, 36212 37252, written_by, 37258 18995, has_genre, 36212 18995, starred_actors, 5032 12162, has_genre, 36212 12162, has_tags, 5032 12162, starred_actors, 5032 5209, has_genre, 36212 5209, release_year, 9377 Question: For what reason are CHARMING, MELODRAMA, and THE NORMAL HEART associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "CHARMING", "MELODRAMA", "THE NORMAL HEART" ], "valid_edges": [ [ "99 HOMES", "has_genre", "DRAMA" ], [ "99 HOMES", "release_year", "2014" ], [ "A WALK AMONG THE TOMBSTONES", "has_genre", "DRAMA" ], [ "A WALK AMONG THE TOMBSTONES", "release_year", "2014" ], [ "ADDICTED", "has_genre", "DRAMA" ], [ "ADDICTED", "release_year", "2014" ], [ "AFFLUENZA", "has_genre", "DRAMA" ], [ "AFFLUENZA", "release_year", "2014" ], [ "ALOFT", "has_genre", "DRAMA" ], [ "ALOFT", "release_year", "2014" ], [ "AN EDUCATION", "has_genre", "DRAMA" ], [ "AN EDUCATION", "has_tags", "CHARMING" ], [ "AN EDUCATION", "release_year", "2009" ], [ "AND SO IT GOES", "has_genre", "DRAMA" ], [ "AND SO IT GOES", "release_year", "2014" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "release_year", "2014" ], [ "BAREFOOT", "has_genre", "DRAMA" ], [ "BAREFOOT", "release_year", "2014" ], [ "BEGIN AGAIN", "has_genre", "DRAMA" ], [ "BEGIN AGAIN", "has_tags", "MARK RUFFALO" ], [ "BEGIN AGAIN", "starred_actors", "MARK RUFFALO" ], [ "BETTER LIVING THROUGH CHEMISTRY", "has_genre", "DRAMA" ], [ "BETTER LIVING THROUGH CHEMISTRY", "release_year", "2014" ], [ "BEYOND THE LIGHTS", "has_genre", "DRAMA" ], [ "BEYOND THE LIGHTS", "release_year", "2014" ], [ "BIG EYES", "has_genre", "DRAMA" ], [ "BIG EYES", "release_year", "2014" ], [ "BIRD PEOPLE", "has_genre", "DRAMA" ], [ "BIRD PEOPLE", "release_year", "2014" ], [ "BLIND", "has_genre", "DRAMA" ], [ "BLIND", "release_year", "2014" ], [ "BOYHOOD", "has_genre", "DRAMA" ], [ "BOYHOOD", "has_tags", "2014" ], [ "BOYHOOD", "release_year", "2014" ], [ "BROKEN EMBRACES", "has_genre", "DRAMA" ], [ "BROKEN EMBRACES", "has_tags", "MELODRAMA" ], [ "BROKEN EMBRACES", "release_year", "2009" ], [ "C.O.G.", "has_genre", "DRAMA" ], [ "C.O.G.", "starred_actors", "JONATHAN GROFF" ], [ "CAKE", "has_genre", "DRAMA" ], [ "CAKE", "release_year", "2014" ], [ "CALVARY", "has_genre", "DRAMA" ], [ "CALVARY", "release_year", "2014" ], [ "CAMP X-RAY", "has_genre", "DRAMA" ], [ "CAMP X-RAY", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "has_genre", "DRAMA" ], [ "CLOUDS OF SILS MARIA", "release_year", "2014" ], [ "COMET", "has_genre", "DRAMA" ], [ "COMET", "release_year", "2014" ], [ "COMMON", "has_genre", "DRAMA" ], [ "COMMON", "release_year", "2014" ], [ "DAYS AND NIGHTS", "has_genre", "DRAMA" ], [ "DAYS AND NIGHTS", "release_year", "2014" ], [ "DEAR WHITE PEOPLE", "has_genre", "DRAMA" ], [ "DEAR WHITE PEOPLE", "release_year", "2014" ], [ "DRAFT DAY", "has_genre", "DRAMA" ], [ "DRAFT DAY", "release_year", "2014" ], [ "EAT PRAY LOVE", "directed_by", "RYAN MURPHY" ], [ "EAT PRAY LOVE", "has_genre", "DRAMA" ], [ "EAT PRAY LOVE", "written_by", "RYAN MURPHY" ], [ "EDEN", "has_genre", "DRAMA" ], [ "EDEN", "release_year", "2014" ], [ "ENDLESS LOVE", "has_genre", "DRAMA" ], [ "ENDLESS LOVE", "release_year", "2014" ], [ "FORCE MAJEURE", "has_genre", "DRAMA" ], [ "FORCE MAJEURE", "has_tags", "2014" ], [ "FORCE MAJEURE", "release_year", "2014" ], [ "FOXCATCHER", "has_genre", "DRAMA" ], [ "FOXCATCHER", "has_tags", "MARK RUFFALO" ], [ "FOXCATCHER", "release_year", "2014" ], [ "FOXCATCHER", "starred_actors", "MARK RUFFALO" ], [ "FRANK", "has_genre", "DRAMA" ], [ "FRANK", "release_year", "2014" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "FROZEN", "starred_actors", "JONATHAN GROFF" ], [ "FURY", "has_genre", "DRAMA" ], [ "FURY", "release_year", "2014" ], [ "GIRLHOOD", "has_genre", "DRAMA" ], [ "GIRLHOOD", "release_year", "2014" ], [ "GOD HELP THE GIRL", "has_genre", "DRAMA" ], [ "GOD HELP THE GIRL", "release_year", "2014" ], [ "GOD'S NOT DEAD", "has_genre", "DRAMA" ], [ "GOD'S NOT DEAD", "release_year", "2014" ], [ "GOD'S POCKET", "has_genre", "DRAMA" ], [ "GOD'S POCKET", "release_year", "2014" ], [ "GOODBYE TO LANGUAGE", "has_genre", "DRAMA" ], [ "GOODBYE TO LANGUAGE", "release_year", "2014" ], [ "HAIDER", "has_genre", "DRAMA" ], [ "HAIDER", "release_year", "2014" ], [ "HAPPY CHRISTMAS", "has_genre", "DRAMA" ], [ "HAPPY CHRISTMAS", "release_year", "2014" ], [ "HEALING", "has_genre", "DRAMA" ], [ "HEALING", "release_year", "2014" ], [ "HEAVEN IS FOR REAL", "has_genre", "DRAMA" ], [ "HEAVEN IS FOR REAL", "release_year", "2014" ], [ "HELLION", "has_genre", "DRAMA" ], [ "HELLION", "release_year", "2014" ], [ "HER", "has_genre", "DRAMA" ], [ "HER", "has_tags", "2014" ], [ "HIGHWAY", "has_genre", "DRAMA" ], [ "HIGHWAY", "release_year", "2014" ], [ "INBETWEEN WORLDS", "has_genre", "DRAMA" ], [ "INBETWEEN WORLDS", "release_year", "2014" ], [ "INHERENT VICE", "has_genre", "DRAMA" ], [ "INHERENT VICE", "release_year", "2014" ], [ "JAMESY BOY", "has_genre", "DRAMA" ], [ "JAMESY BOY", "release_year", "2014" ], [ "JAMIE MARKS IS DEAD", "has_genre", "DRAMA" ], [ "JAMIE MARKS IS DEAD", "release_year", "2014" ], [ "JAUJA", "has_genre", "DRAMA" ], [ "JAUJA", "release_year", "2014" ], [ "JERSEY BOYS", "has_genre", "DRAMA" ], [ "JERSEY BOYS", "release_year", "2014" ], [ "KILL THE MESSENGER", "has_genre", "DRAMA" ], [ "KILL THE MESSENGER", "release_year", "2014" ], [ "KUMIKO, THE TREASURE HUNTER", "has_genre", "DRAMA" ], [ "KUMIKO, THE TREASURE HUNTER", "release_year", "2014" ], [ "LATE PHASES", "has_genre", "DRAMA" ], [ "LATE PHASES", "release_year", "2014" ], [ "LATITUDES", "has_genre", "DRAMA" ], [ "LATITUDES", "release_year", "2014" ], [ "LEVIATHAN", "has_genre", "DRAMA" ], [ "LEVIATHAN", "release_year", "2014" ], [ "LILTING", "has_genre", "DRAMA" ], [ "LILTING", "release_year", "2014" ], [ "LISTEN UP PHILIP", "has_genre", "DRAMA" ], [ "LISTEN UP PHILIP", "release_year", "2014" ], [ "LITTLE ACCIDENTS", "has_genre", "DRAMA" ], [ "LITTLE ACCIDENTS", "release_year", "2014" ], [ "LOST HORIZON", "has_genre", "DRAMA" ], [ "LOST HORIZON", "written_by", "LARRY KRAMER" ], [ "LOVE IS STRANGE", "has_genre", "DRAMA" ], [ "LOVE IS STRANGE", "release_year", "2014" ], [ "LULLABY", "has_genre", "DRAMA" ], [ "LULLABY", "release_year", "2014" ], [ "MAPS TO THE STARS", "has_genre", "DRAMA" ], [ "MAPS TO THE STARS", "has_tags", "DRAMA" ], [ "MAPS TO THE STARS", "release_year", "2014" ], [ "MARGARET", "has_genre", "DRAMA" ], [ "MARGARET", "has_tags", "DRAMA" ], [ "MARGARET", "starred_actors", "MARK RUFFALO" ], [ "MILLION DOLLAR ARM", "has_genre", "DRAMA" ], [ "MILLION DOLLAR ARM", "release_year", "2014" ], [ "MOMMY", "has_genre", "DRAMA" ], [ "MOMMY", "release_year", "2014" ], [ "MR. TURNER", "has_genre", "DRAMA" ], [ "MR. TURNER", "release_year", "2014" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "has_tags", "MARK RUFFALO" ], [ "MY OLD LADY", "has_genre", "DRAMA" ], [ "MY OLD LADY", "release_year", "2014" ], [ "PERFECT SISTERS", "has_genre", "DRAMA" ], [ "PERFECT SISTERS", "release_year", "2014" ], [ "PK", "has_genre", "DRAMA" ], [ "PK", "release_year", "2014" ], [ "PRIDE", "has_genre", "DRAMA" ], [ "PRIDE", "release_year", "2014" ], [ "RAGE", "has_genre", "DRAMA" ], [ "RAGE", "release_year", "2014" ], [ "RESERVATION ROAD", "has_genre", "DRAMA" ], [ "RESERVATION ROAD", "has_tags", "MARK RUFFALO" ], [ "ROB THE MOB", "has_genre", "DRAMA" ], [ "ROB THE MOB", "release_year", "2014" ], [ "ROSEWATER", "has_genre", "DRAMA" ], [ "ROSEWATER", "release_year", "2014" ], [ "RUDDERLESS", "has_genre", "DRAMA" ], [ "RUDDERLESS", "release_year", "2014" ], [ "RUNNING WITH SCISSORS", "directed_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "has_genre", "DRAMA" ], [ "RUNNING WITH SCISSORS", "written_by", "RYAN MURPHY" ], [ "SAINT LAURENT", "has_genre", "DRAMA" ], [ "SAINT LAURENT", "release_year", "2014" ], [ "SALTING THE BATTLEFIELD", "has_genre", "DRAMA" ], [ "SALTING THE BATTLEFIELD", "release_year", "2014" ], [ "SELMA", "has_genre", "DRAMA" ], [ "SELMA", "release_year", "2014" ], [ "SENSO", "has_genre", "DRAMA" ], [ "SENSO", "has_tags", "MELODRAMA" ], [ "SERENA", "has_genre", "DRAMA" ], [ "SERENA", "release_year", "2014" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "release_year", "2014" ], [ "STATIONS OF THE CROSS", "has_genre", "DRAMA" ], [ "STATIONS OF THE CROSS", "release_year", "2014" ], [ "STILL ALICE", "has_genre", "DRAMA" ], [ "STILL ALICE", "release_year", "2014" ], [ "SYMPATHY FOR DELICIOUS", "directed_by", "MARK RUFFALO" ], [ "SYMPATHY FOR DELICIOUS", "has_genre", "DRAMA" ], [ "SYMPATHY FOR DELICIOUS", "starred_actors", "MARK RUFFALO" ], [ "THANK YOU A LOT", "has_genre", "DRAMA" ], [ "THANK YOU A LOT", "release_year", "2014" ], [ "THANKS FOR SHARING", "has_genre", "DRAMA" ], [ "THANKS FOR SHARING", "starred_actors", "MARK RUFFALO" ], [ "THE ANGRIEST MAN IN BROOKLYN", "has_genre", "DRAMA" ], [ "THE ANGRIEST MAN IN BROOKLYN", "release_year", "2014" ], [ "THE BEST OF ME", "has_genre", "DRAMA" ], [ "THE BEST OF ME", "release_year", "2014" ], [ "THE CIRCLE", "has_genre", "DRAMA" ], [ "THE CIRCLE", "release_year", "2014" ], [ "THE COBBLER", "has_genre", "DRAMA" ], [ "THE COBBLER", "release_year", "2014" ], [ "THE DROP", "has_genre", "DRAMA" ], [ "THE DROP", "release_year", "2014" ], [ "THE FAULT IN OUR STARS", "has_genre", "DRAMA" ], [ "THE FAULT IN OUR STARS", "has_tags", "DRAMA" ], [ "THE FAULT IN OUR STARS", "release_year", "2014" ], [ "THE GOOD LIE", "has_genre", "DRAMA" ], [ "THE GOOD LIE", "release_year", "2014" ], [ "THE HOMESMAN", "has_genre", "DRAMA" ], [ "THE HOMESMAN", "release_year", "2014" ], [ "THE HUNDRED-FOOT JOURNEY", "has_genre", "DRAMA" ], [ "THE HUNDRED-FOOT JOURNEY", "release_year", "2014" ], [ "THE IMITATION GAME", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "release_year", "2014" ], [ "THE JUDGE", "has_genre", "DRAMA" ], [ "THE JUDGE", "release_year", "2014" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "starred_actors", "MARK RUFFALO" ], [ "THE NEW GIRLFRIEND", "has_genre", "DRAMA" ], [ "THE NEW GIRLFRIEND", "release_year", "2014" ], [ "THE NORMAL HEART", "directed_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "has_genre", "DRAMA" ], [ "THE NORMAL HEART", "release_year", "2014" ], [ "THE NORMAL HEART", "starred_actors", "JONATHAN GROFF" ], [ "THE NORMAL HEART", "starred_actors", "MARK RUFFALO" ], [ "THE NORMAL HEART", "written_by", "LARRY KRAMER" ], [ "THE OTHER WOMAN", "has_genre", "DRAMA" ], [ "THE OTHER WOMAN", "release_year", "2014" ], [ "THE OUTSIDER", "has_genre", "DRAMA" ], [ "THE OUTSIDER", "release_year", "2014" ], [ "THE RECKONING", "has_genre", "DRAMA" ], [ "THE RECKONING", "release_year", "2014" ], [ "THE ROVER", "has_genre", "DRAMA" ], [ "THE ROVER", "release_year", "2014" ], [ "THE SINGLE MOMS CLUB", "has_genre", "DRAMA" ], [ "THE SINGLE MOMS CLUB", "release_year", "2014" ], [ "THE SKELETON TWINS", "has_genre", "DRAMA" ], [ "THE SKELETON TWINS", "release_year", "2014" ], [ "THE THEORY OF EVERYTHING", "has_genre", "DRAMA" ], [ "THE THEORY OF EVERYTHING", "release_year", "2014" ], [ "THE WAY HE LOOKS", "has_genre", "DRAMA" ], [ "THE WAY HE LOOKS", "has_tags", "DRAMA" ], [ "THE WAY HE LOOKS", "release_year", "2014" ], [ "THE WONDERS", "has_genre", "DRAMA" ], [ "THE WONDERS", "release_year", "2014" ], [ "THERE'S ALWAYS TOMORROW", "has_genre", "DRAMA" ], [ "THERE'S ALWAYS TOMORROW", "has_tags", "MELODRAMA" ], [ "THIS IS WHERE I LEAVE YOU", "has_genre", "DRAMA" ], [ "THIS IS WHERE I LEAVE YOU", "release_year", "2014" ], [ "TIMBUKTU", "has_genre", "DRAMA" ], [ "TIMBUKTU", "release_year", "2014" ], [ "TUSK", "has_genre", "DRAMA" ], [ "TUSK", "release_year", "2014" ], [ "UNBROKEN", "has_genre", "DRAMA" ], [ "UNBROKEN", "release_year", "2014" ], [ "VERONICA MARS", "has_genre", "DRAMA" ], [ "VERONICA MARS", "release_year", "2014" ], [ "WELCOME TO NEW YORK", "has_genre", "DRAMA" ], [ "WELCOME TO NEW YORK", "release_year", "2014" ], [ "WHAT DOESN'T KILL YOU", "has_genre", "DRAMA" ], [ "WHAT DOESN'T KILL YOU", "has_tags", "MARK RUFFALO" ], [ "WHAT DOESN'T KILL YOU", "starred_actors", "MARK RUFFALO" ], [ "WHEN ANIMALS DREAM", "has_genre", "DRAMA" ], [ "WHEN ANIMALS DREAM", "release_year", "2014" ], [ "WHIPLASH", "has_genre", "DRAMA" ], [ "WHIPLASH", "release_year", "2014" ], [ "WHITE GOD", "has_genre", "DRAMA" ], [ "WHITE GOD", "release_year", "2014" ], [ "WILD", "has_genre", "DRAMA" ], [ "WILD", "release_year", "2014" ], [ "WINTER SLEEP", "has_genre", "DRAMA" ], [ "WINTER SLEEP", "release_year", "2014" ], [ "WISH I WAS HERE", "has_genre", "DRAMA" ], [ "WISH I WAS HERE", "release_year", "2014" ], [ "WOMEN IN LOVE", "has_genre", "DRAMA" ], [ "WOMEN IN LOVE", "written_by", "LARRY KRAMER" ], [ "XX/XY", "has_genre", "DRAMA" ], [ "XX/XY", "starred_actors", "MARK RUFFALO" ], [ "YOU CAN COUNT ON ME", "has_genre", "DRAMA" ], [ "YOU CAN COUNT ON ME", "has_tags", "MARK RUFFALO" ], [ "YOU CAN COUNT ON ME", "starred_actors", "MARK RUFFALO" ], [ "YVES SAINT LAURENT", "has_genre", "DRAMA" ], [ "YVES SAINT LAURENT", "release_year", "2014" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 35845, 2006 39289, ACTION 40074, BLACK BOOK 16664, BLOOD DIAMOND 22435, CHILDREN OF MEN 17602, DAS MILLIONENSPIEL 3567, DAYS OF GLORY 10315, FLAGS OF OUR FATHERS 36601, FLANDERS 1273, FLYBOYS 3990, GETTYSBURG 18934, LETTERS FROM IWO JIMA 39852, PAN'S LABYRINTH 34732, PLATOON 16772, SNIPER 11124, STALINGRAD 9355, THE MARSH 32618, THE RAPE OF EUROPA 4294, THE SUBSTITUTE 2783, THE WIND THAT SHAKES THE BARLEY 2930, TOM BERENGER 11413, TOM TOELLE 22214, WAR src, edge_attr, dst 40074, has_genre, 22214 40074, release_year, 35845 16664, has_tags, 22214 16664, release_year, 35845 22435, has_tags, 22214 22435, release_year, 35845 17602, directed_by, 11413 17602, has_genre, 39289 3567, has_genre, 22214 3567, has_tags, 22214 3567, release_year, 35845 10315, has_genre, 22214 10315, has_tags, 22214 10315, release_year, 35845 36601, has_genre, 22214 36601, release_year, 35845 1273, has_tags, 22214 1273, release_year, 35845 3990, has_genre, 22214 3990, release_year, 24438 3990, starred_actors, 2930 18934, has_genre, 22214 18934, has_tags, 22214 18934, release_year, 35845 39852, has_genre, 22214 39852, has_tags, 22214 39852, release_year, 35845 34732, has_genre, 22214 34732, has_tags, 2930 34732, has_tags, 22214 34732, starred_actors, 2930 16772, release_year, 24438 16772, starred_actors, 2930 11124, has_genre, 22214 11124, release_year, 24438 9355, release_year, 35845 32618, has_genre, 22214 32618, release_year, 35845 4294, release_year, 24438 4294, starred_actors, 2930 2783, has_genre, 22214 2783, release_year, 35845 22214, has_genre, 39289 Question: How are GETTYSBURG, THE MARSH, and TOM TOELLE related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "GETTYSBURG", "THE MARSH", "TOM TOELLE" ], "valid_edges": [ [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "WAR" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "WAR" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "DAS MILLIONENSPIEL", "directed_by", "TOM TOELLE" ], [ "DAS MILLIONENSPIEL", "has_genre", "ACTION" ], [ "DAYS OF GLORY", "has_genre", "WAR" ], [ "DAYS OF GLORY", "has_tags", "WAR" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FLANDERS", "has_genre", "WAR" ], [ "FLANDERS", "release_year", "2006" ], [ "FLYBOYS", "has_tags", "WAR" ], [ "FLYBOYS", "release_year", "2006" ], [ "GETTYSBURG", "has_genre", "WAR" ], [ "GETTYSBURG", "release_year", "1993" ], [ "GETTYSBURG", "starred_actors", "TOM BERENGER" ], [ "LETTERS FROM IWO JIMA", "has_genre", "WAR" ], [ "LETTERS FROM IWO JIMA", "has_tags", "WAR" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_genre", "WAR" ], [ "PAN'S LABYRINTH", "has_tags", "WAR" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PLATOON", "has_genre", "WAR" ], [ "PLATOON", "has_tags", "TOM BERENGER" ], [ "PLATOON", "has_tags", "WAR" ], [ "PLATOON", "starred_actors", "TOM BERENGER" ], [ "SNIPER", "release_year", "1993" ], [ "SNIPER", "starred_actors", "TOM BERENGER" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "release_year", "1993" ], [ "THE MARSH", "release_year", "2006" ], [ "THE RAPE OF EUROPA", "has_genre", "WAR" ], [ "THE RAPE OF EUROPA", "release_year", "2006" ], [ "THE SUBSTITUTE", "release_year", "1993" ], [ "THE SUBSTITUTE", "starred_actors", "TOM BERENGER" ], [ "THE WIND THAT SHAKES THE BARLEY", "has_genre", "WAR" ], [ "THE WIND THAT SHAKES THE BARLEY", "release_year", "2006" ], [ "WAR", "has_genre", "ACTION" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 34443, 31 NORTH 62 EAST 28568, A PERFECT GETAWAY 12694, A PISTOL FOR RINGO 12088, ACCIDENT 22144, ALEC BALDWIN 29167, AMER 23227, ARMORED 6891, BAARÌA 31895, BERBERIAN SOUND STUDIO 2570, BLACK SUNDAY 39539, BLOOD AND BLACK LACE 20961, BLOOD RIVER 4197, BLUEBEARD 37883, BROKEN EMBRACES 37594, BROTHERHOOD 6283, CARGO 7143, CHLOE 31844, COSMONAUT 8438, CUT AND RUN 10313, DEAD AGAIN 3645, DEADLINE 8381, DETOUR 6692, DISTRICT 9 17274, DOLAN'S CADILLAC 11127, DON MCKAY 27842, DON'T LOOK NOW 30123, DORIAN GRAY 23387, EVERYBODY'S FINE 14585, EXAM 8176, FAREWELL 4159, FEAR ISLAND 31919, FORMOSA BETRAYED 3724, GAMER 12638, GLORIOUS 39 3345, HEAVEN'S PRISONERS 27937, HIERRO 37563, HOMECOMING 23780, HURT 4749, I AM LOVE 24167, INFERNO 16200, ITALIAN 30872, KILL THEORY 14653, LAW ABIDING CITIZEN 11652, LONELY STREET 38786, MALICE 14537, NOT FORGOTTEN 36387, OBSESSED 1827, ORPHAN 738, PLOT OF FEAR 25809, PUSH 12428, RAGE 2010, RAMPAGE 3091, SCOTT FRANK 6119, SLEUTH 40102, THE CANYON 16442, THE COLLECTOR 4337, THE CRY OF THE OWL 15205, THE DISAPPEARANCE OF ALICE CREED 32932, THE DOUBLE HOUR 24006, THE FIFTH CORD 19760, THE FRIENDS AT THE MARGHERITA CAFE 35772, THE GIRL BY THE LAKE 36893, THE GIRL ON THE TRAIN 38083, THE GIRL WHO KICKED THE HORNETS' NEST 21338, THE GIRL WHO PLAYED WITH FIRE 7240, THE GIRL WITH THE DRAGON TATTOO 23333, THE HOLE 28886, THE KILLING ROOM 11542, THE LAUGHING WOMAN 37148, THE SECRET IN THEIR EYES 35993, THE STEPFATHER 17719, THE THAW 24489, THE TOURNAMENT 25030, THE UNKNOWN WOMAN 5463, THE WAGES OF FEAR 24811, THRILLER 17396, TORSO 37099, TRIANGLE 8129, VIDEOCRACY 15645, VINCERE 15036, WHITEOUT src, edge_attr, dst 34443, has_genre, 24811 34443, release_year, 27261 28568, has_genre, 24811 28568, release_year, 27261 12694, in_language, 16200 12088, has_genre, 24811 12088, release_year, 27261 29167, has_genre, 24811 29167, release_year, 27261 23227, has_genre, 24811 23227, release_year, 27261 6891, in_language, 16200 6891, release_year, 27261 31895, has_genre, 24811 31895, in_language, 16200 2570, has_genre, 24811 2570, in_language, 16200 39539, has_genre, 24811 39539, in_language, 16200 20961, has_genre, 24811 20961, release_year, 27261 4197, has_genre, 24811 4197, release_year, 27261 37883, has_genre, 24811 37883, release_year, 27261 37594, has_genre, 24811 37594, release_year, 27261 6283, has_genre, 24811 6283, release_year, 27261 7143, has_genre, 24811 7143, release_year, 27261 31844, in_language, 16200 31844, release_year, 27261 8438, has_genre, 24811 8438, in_language, 16200 10313, has_genre, 24811 10313, written_by, 3091 3645, has_genre, 24811 3645, release_year, 27261 8381, has_genre, 24811 8381, release_year, 27261 6692, has_genre, 24811 6692, has_tags, 24811 6692, release_year, 27261 17274, has_genre, 24811 17274, release_year, 27261 11127, has_genre, 24811 11127, release_year, 27261 27842, has_genre, 24811 27842, in_language, 16200 30123, has_genre, 24811 30123, release_year, 27261 23387, in_language, 16200 23387, release_year, 27261 14585, has_genre, 24811 14585, release_year, 27261 8176, has_genre, 24811 8176, release_year, 27261 4159, has_genre, 24811 4159, release_year, 27261 31919, has_genre, 24811 31919, release_year, 27261 3724, has_genre, 24811 3724, release_year, 27261 12638, has_genre, 24811 12638, release_year, 27261 3345, has_genre, 24811 3345, starred_actors, 22144 3345, written_by, 3091 27937, has_genre, 24811 27937, release_year, 27261 37563, has_genre, 24811 37563, release_year, 27261 23780, has_genre, 24811 23780, release_year, 27261 4749, in_language, 16200 4749, release_year, 27261 24167, has_genre, 24811 24167, in_language, 16200 30872, has_genre, 24811 30872, release_year, 27261 14653, has_genre, 24811 14653, release_year, 27261 11652, has_genre, 24811 11652, release_year, 27261 38786, has_genre, 24811 38786, starred_actors, 22144 38786, written_by, 3091 14537, has_genre, 24811 14537, release_year, 27261 36387, has_genre, 24811 36387, release_year, 27261 1827, has_genre, 24811 1827, release_year, 27261 738, has_genre, 24811 738, in_language, 16200 25809, has_genre, 24811 25809, release_year, 27261 12428, has_genre, 24811 12428, release_year, 27261 2010, has_genre, 24811 2010, release_year, 27261 6119, has_genre, 24811 6119, in_language, 16200 40102, has_genre, 24811 40102, release_year, 27261 16442, has_genre, 24811 16442, release_year, 27261 4337, has_genre, 24811 4337, release_year, 27261 15205, has_genre, 24811 15205, release_year, 27261 32932, in_language, 16200 32932, release_year, 27261 24006, has_genre, 24811 24006, in_language, 16200 19760, in_language, 16200 19760, release_year, 27261 35772, has_genre, 24811 35772, in_language, 16200 36893, has_genre, 24811 36893, release_year, 27261 38083, has_genre, 24811 38083, has_tags, 24811 38083, release_year, 27261 21338, has_tags, 24811 21338, release_year, 27261 7240, has_tags, 24811 7240, release_year, 27261 23333, has_genre, 24811 23333, release_year, 27261 28886, has_genre, 24811 28886, release_year, 27261 11542, has_genre, 24811 11542, in_language, 16200 37148, has_genre, 24811 37148, release_year, 27261 35993, has_genre, 24811 35993, release_year, 27261 17719, has_genre, 24811 17719, release_year, 27261 24489, has_genre, 24811 24489, release_year, 27261 25030, has_genre, 24811 25030, in_language, 16200 5463, has_genre, 24811 5463, in_language, 16200 17396, has_genre, 24811 17396, in_language, 16200 37099, has_genre, 24811 37099, release_year, 27261 8129, in_language, 16200 8129, release_year, 27261 15645, in_language, 16200 15645, release_year, 27261 15036, has_tags, 24811 15036, release_year, 27261 Question: For what reason are A PISTOL FOR RINGO, SCOTT FRANK, and THE CANYON associated? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A PISTOL FOR RINGO", "SCOTT FRANK", "THE CANYON" ], "valid_edges": [ [ "31 NORTH 62 EAST", "has_genre", "THRILLER" ], [ "31 NORTH 62 EAST", "release_year", "2009" ], [ "A PERFECT GETAWAY", "has_genre", "THRILLER" ], [ "A PERFECT GETAWAY", "release_year", "2009" ], [ "A PISTOL FOR RINGO", "in_language", "ITALIAN" ], [ "ACCIDENT", "has_genre", "THRILLER" ], [ "ACCIDENT", "release_year", "2009" ], [ "AMER", "has_genre", "THRILLER" ], [ "AMER", "release_year", "2009" ], [ "ARMORED", "has_genre", "THRILLER" ], [ "ARMORED", "release_year", "2009" ], [ "BAARÌA", "in_language", "ITALIAN" ], [ "BAARÌA", "release_year", "2009" ], [ "BERBERIAN SOUND STUDIO", "has_genre", "THRILLER" ], [ "BERBERIAN SOUND STUDIO", "in_language", "ITALIAN" ], [ "BLACK SUNDAY", "has_genre", "THRILLER" ], [ "BLACK SUNDAY", "in_language", "ITALIAN" ], [ "BLOOD AND BLACK LACE", "has_genre", "THRILLER" ], [ "BLOOD AND BLACK LACE", "in_language", "ITALIAN" ], [ "BLOOD RIVER", "has_genre", "THRILLER" ], [ "BLOOD RIVER", "release_year", "2009" ], [ "BLUEBEARD", "has_genre", "THRILLER" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BROKEN EMBRACES", "has_genre", "THRILLER" ], [ "BROKEN EMBRACES", "release_year", "2009" ], [ "BROTHERHOOD", "has_genre", "THRILLER" ], [ "BROTHERHOOD", "release_year", "2009" ], [ "CARGO", "has_genre", "THRILLER" ], [ "CARGO", "release_year", "2009" ], [ "CHLOE", "has_genre", "THRILLER" ], [ "CHLOE", "release_year", "2009" ], [ "COSMONAUT", "in_language", "ITALIAN" ], [ "COSMONAUT", "release_year", "2009" ], [ "CUT AND RUN", "has_genre", "THRILLER" ], [ "CUT AND RUN", "in_language", "ITALIAN" ], [ "DEAD AGAIN", "has_genre", "THRILLER" ], [ "DEAD AGAIN", "written_by", "SCOTT FRANK" ], [ "DEADLINE", "has_genre", "THRILLER" ], [ "DEADLINE", "release_year", "2009" ], [ "DETOUR", "has_genre", "THRILLER" ], [ "DETOUR", "release_year", "2009" ], [ "DISTRICT 9", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_tags", "THRILLER" ], [ "DISTRICT 9", "release_year", "2009" ], [ "DOLAN'S CADILLAC", "has_genre", "THRILLER" ], [ "DOLAN'S CADILLAC", "release_year", "2009" ], [ "DON MCKAY", "has_genre", "THRILLER" ], [ "DON MCKAY", "release_year", "2009" ], [ "DON'T LOOK NOW", "has_genre", "THRILLER" ], [ "DON'T LOOK NOW", "in_language", "ITALIAN" ], [ "DORIAN GRAY", "has_genre", "THRILLER" ], [ "DORIAN GRAY", "release_year", "2009" ], [ "EVERYBODY'S FINE", "in_language", "ITALIAN" ], [ "EVERYBODY'S FINE", "release_year", "2009" ], [ "EXAM", "has_genre", "THRILLER" ], [ "EXAM", "release_year", "2009" ], [ "FAREWELL", "has_genre", "THRILLER" ], [ "FAREWELL", "release_year", "2009" ], [ "FEAR ISLAND", "has_genre", "THRILLER" ], [ "FEAR ISLAND", "release_year", "2009" ], [ "FORMOSA BETRAYED", "has_genre", "THRILLER" ], [ "FORMOSA BETRAYED", "release_year", "2009" ], [ "GAMER", "has_genre", "THRILLER" ], [ "GAMER", "release_year", "2009" ], [ "GLORIOUS 39", "has_genre", "THRILLER" ], [ "GLORIOUS 39", "release_year", "2009" ], [ "HEAVEN'S PRISONERS", "has_genre", "THRILLER" ], [ "HEAVEN'S PRISONERS", "starred_actors", "ALEC BALDWIN" ], [ "HEAVEN'S PRISONERS", "written_by", "SCOTT FRANK" ], [ "HIERRO", "has_genre", "THRILLER" ], [ "HIERRO", "release_year", "2009" ], [ "HOMECOMING", "has_genre", "THRILLER" ], [ "HOMECOMING", "release_year", "2009" ], [ "HURT", "has_genre", "THRILLER" ], [ "HURT", "release_year", "2009" ], [ "I AM LOVE", "in_language", "ITALIAN" ], [ "I AM LOVE", "release_year", "2009" ], [ "INFERNO", "has_genre", "THRILLER" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "KILL THEORY", "has_genre", "THRILLER" ], [ "KILL THEORY", "release_year", "2009" ], [ "LAW ABIDING CITIZEN", "has_genre", "THRILLER" ], [ "LAW ABIDING CITIZEN", "release_year", "2009" ], [ "LONELY STREET", "has_genre", "THRILLER" ], [ "LONELY STREET", "release_year", "2009" ], [ "MALICE", "has_genre", "THRILLER" ], [ "MALICE", "starred_actors", "ALEC BALDWIN" ], [ "MALICE", "written_by", "SCOTT FRANK" ], [ "NOT FORGOTTEN", "has_genre", "THRILLER" ], [ "NOT FORGOTTEN", "release_year", "2009" ], [ "OBSESSED", "has_genre", "THRILLER" ], [ "OBSESSED", "release_year", "2009" ], [ "ORPHAN", "has_genre", "THRILLER" ], [ "ORPHAN", "release_year", "2009" ], [ "PLOT OF FEAR", "has_genre", "THRILLER" ], [ "PLOT OF FEAR", "in_language", "ITALIAN" ], [ "PUSH", "has_genre", "THRILLER" ], [ "PUSH", "release_year", "2009" ], [ "RAGE", "has_genre", "THRILLER" ], [ "RAGE", "release_year", "2009" ], [ "RAMPAGE", "has_genre", "THRILLER" ], [ "RAMPAGE", "release_year", "2009" ], [ "SLEUTH", "has_genre", "THRILLER" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "THE CANYON", "has_genre", "THRILLER" ], [ "THE CANYON", "release_year", "2009" ], [ "THE COLLECTOR", "has_genre", "THRILLER" ], [ "THE COLLECTOR", "release_year", "2009" ], [ "THE CRY OF THE OWL", "has_genre", "THRILLER" ], [ "THE CRY OF THE OWL", "release_year", "2009" ], [ "THE DISAPPEARANCE OF ALICE CREED", "has_genre", "THRILLER" ], [ "THE DISAPPEARANCE OF ALICE CREED", "release_year", "2009" ], [ "THE DOUBLE HOUR", "in_language", "ITALIAN" ], [ "THE DOUBLE HOUR", "release_year", "2009" ], [ "THE FIFTH CORD", "has_genre", "THRILLER" ], [ "THE FIFTH CORD", "in_language", "ITALIAN" ], [ "THE FRIENDS AT THE MARGHERITA CAFE", "in_language", "ITALIAN" ], [ "THE FRIENDS AT THE MARGHERITA CAFE", "release_year", "2009" ], [ "THE GIRL BY THE LAKE", "has_genre", "THRILLER" ], [ "THE GIRL BY THE LAKE", "in_language", "ITALIAN" ], [ "THE GIRL ON THE TRAIN", "has_genre", "THRILLER" ], [ "THE GIRL ON THE TRAIN", "release_year", "2009" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "has_genre", "THRILLER" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "has_tags", "THRILLER" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "release_year", "2009" ], [ "THE GIRL WHO PLAYED WITH FIRE", "has_tags", "THRILLER" ], [ "THE GIRL WHO PLAYED WITH FIRE", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "THRILLER" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE HOLE", "has_genre", "THRILLER" ], [ "THE HOLE", "release_year", "2009" ], [ "THE KILLING ROOM", "has_genre", "THRILLER" ], [ "THE KILLING ROOM", "release_year", "2009" ], [ "THE LAUGHING WOMAN", "has_genre", "THRILLER" ], [ "THE LAUGHING WOMAN", "in_language", "ITALIAN" ], [ "THE SECRET IN THEIR EYES", "has_genre", "THRILLER" ], [ "THE SECRET IN THEIR EYES", "release_year", "2009" ], [ "THE STEPFATHER", "has_genre", "THRILLER" ], [ "THE STEPFATHER", "release_year", "2009" ], [ "THE THAW", "has_genre", "THRILLER" ], [ "THE THAW", "release_year", "2009" ], [ "THE TOURNAMENT", "has_genre", "THRILLER" ], [ "THE TOURNAMENT", "release_year", "2009" ], [ "THE UNKNOWN WOMAN", "has_genre", "THRILLER" ], [ "THE UNKNOWN WOMAN", "in_language", "ITALIAN" ], [ "THE WAGES OF FEAR", "has_genre", "THRILLER" ], [ "THE WAGES OF FEAR", "in_language", "ITALIAN" ], [ "TORSO", "has_genre", "THRILLER" ], [ "TORSO", "in_language", "ITALIAN" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TRIANGLE", "release_year", "2009" ], [ "VIDEOCRACY", "in_language", "ITALIAN" ], [ "VIDEOCRACY", "release_year", "2009" ], [ "VINCERE", "in_language", "ITALIAN" ], [ "VINCERE", "release_year", "2009" ], [ "WHITEOUT", "has_tags", "THRILLER" ], [ "WHITEOUT", "release_year", "2009" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 5478, 30 YEARS TO LIFE 8200, ALL OVER THE GUY 32427, ALL THE QUEEN'S MEN 17687, AMERICA'S SWEETHEARTS 34899, AMERICAN PIE 2 12224, AMÉLIE 5593, BABY BOY 23952, BANDITS 13418, BARTLEBY 9654, BLACK KNIGHT 35213, BLOW DRY 18692, BOB THE BUTLER 23128, BRIDGET JONES'S DIARY 19026, BUBBLE BOY 17892, CAMOUFLAGE 30463, COMEDY 2605, CORKY ROMANO 18980, CROCODILE DUNDEE IN LOS ANGELES 1915, DIL CHAHTA HAI 12217, DON'T TEMPT ME 7023, DOUBLE TAKE 19756, DOWN TO EARTH 8704, DR. DOLITTLE 2 28808, ESCANABA IN DA MOONLIGHT 23470, EVOLUTION 6915, FOCUS 21322, FREDDY GOT FINGERED 30712, FREEBIE AND THE BEAN 5287, FROZEN 23511, GAUDI AFTERNOON 37949, GET OVER IT 12664, GHOST WORLD 18445, GOD IS GREAT AND I'M NOT 10113, GOOD ADVICE 8648, HAPPY CAMPERS 21060, HARVARD MAN 37229, HE DIED WITH A FELAFEL IN HIS HAND 11344, HEARTBREAKERS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 10703, HOW HIGH 35625, HUMAN NATURE 4358, ICE 16371, ICE AGE 23526, JACKPOT 263, JAY AND SILENT BOB STRIKE BACK 32383, JOE DIRT 12610, JOE SOMEBODY 10109, JOSIE AND THE PUSSYCATS 30384, JUMP TOMORROW 16839, JUST VISITING 7699, KINGDOM COME 20428, KISSING JESSICA STEIN 17559, LEGALLY BLONDE 29734, LITTLE SECRETS 26731, LUCKY BREAK 28660, MADE 6068, MAX KEEBLE'S BIG MOVE 33714, MEAN MACHINE 33853, MONKEYBONE 20003, MONSTERS, INC. 24616, MOSTLY MARTHA 26151, NOBODY'S BABY 5731, NOT ANOTHER TEEN MOVIE 29029, NOVOCAINE 21875, OCEAN'S ELEVEN 6959, ON THE LINE 32186, ONE MAN UP 8935, ONE NIGHT AT MCCOOL'S 28044, PAULINE AND PAULETTE 31445, PONTEROSA 13381, POOTIE TANG 28182, RARE BIRDS 32180, RAT RACE 30422, RICHARD RUSH 38381, ROCK STAR 9530, RUSH HOUR 2 1789, SAVING SILVERMAN 37244, SAY IT ISN'T SO 5880, SERENDIPITY 35100, SHALLOW HAL 7519, SHAOLIN SOCCER 36159, SHREK 30089, SIDEWALKS OF NEW YORK 2407, SON OF THE BRIDE 24221, SPEAKING OF SEX 5170, STEALING HARVARD 7949, STORYTELLING 2235, SUMMER CATCH 4783, SUPER TROOPERS 27762, SWEET NOVEMBER 345, TANGUY 23280, THE ANIMAL 15795, THE ANNIVERSARY PARTY 25674, THE BROTHERS 30164, THE CLOSET 4927, THE CURSE OF THE JADE SCORPION 17778, THE HAPPINESS OF THE KATAKURIS 28107, THE LAST KISS 10353, THE MAN WHO SUED GOD 27713, THE MEXICAN 23086, THE PRINCESS DIARIES 20728, THE ROYAL TENENBAUMS 36231, THE SHRINK IS IN 37184, THE TRIUMPH OF LOVE 33449, THE WEDDING PLANNER 8644, TOM GREEN 11027, TOMCATS 35988, TORTILLA SOUP 19451, TWO CAN PLAY THAT GAME 21790, VERY ANNIE MARY 3137, VISITOR Q 35443, VIZONTELE 29077, WASABI 25414, WATERBOYS 27083, WET HOT AMERICAN SUMMER 37358, WHAT'S THE WORST THAT COULD HAPPEN? 23844, WHO IS CLETIS TOUT? 4063, ZOOLANDER src, edge_attr, dst 13747, has_genre, 30463 13747, release_year, 13408 5478, has_genre, 30463 5478, release_year, 13408 8200, has_genre, 30463 8200, release_year, 13408 32427, has_genre, 30463 32427, release_year, 13408 17687, has_genre, 30463 17687, release_year, 13408 34899, has_genre, 30463 34899, has_tags, 30463 34899, release_year, 13408 12224, has_genre, 30463 12224, has_tags, 30463 12224, release_year, 13408 5593, has_genre, 30463 5593, release_year, 13408 23952, has_genre, 30463 23952, release_year, 13408 13418, has_genre, 30463 13418, release_year, 13408 9654, has_genre, 30463 9654, has_tags, 30463 9654, release_year, 13408 35213, has_genre, 30463 35213, release_year, 13408 18692, has_genre, 30463 18692, starred_actors, 8644 23128, has_genre, 30463 23128, has_tags, 30463 23128, release_year, 13408 19026, has_genre, 30463 19026, release_year, 13408 17892, has_genre, 30463 17892, release_year, 13408 2605, has_genre, 30463 2605, release_year, 13408 18980, has_genre, 30463 18980, release_year, 13408 1915, has_genre, 30463 1915, has_tags, 30463 1915, release_year, 13408 12217, has_genre, 30463 12217, release_year, 13408 7023, has_genre, 30463 7023, release_year, 13408 19756, has_genre, 30463 19756, release_year, 13408 8704, has_genre, 30463 8704, release_year, 13408 28808, has_genre, 30463 28808, release_year, 13408 23470, has_genre, 30463 23470, has_tags, 30463 23470, release_year, 13408 6915, has_genre, 30463 6915, release_year, 13408 21322, directed_by, 8644 21322, has_genre, 30463 21322, has_tags, 8644 21322, release_year, 13408 21322, starred_actors, 8644 21322, written_by, 8644 30712, directed_by, 30422 30712, has_genre, 30463 5287, has_genre, 30463 5287, has_tags, 4358 23511, has_genre, 30463 23511, release_year, 13408 37949, has_genre, 30463 37949, has_tags, 30463 37949, release_year, 13408 12664, has_genre, 30463 12664, release_year, 13408 18445, has_genre, 30463 18445, release_year, 13408 10113, has_genre, 30463 10113, release_year, 13408 8648, has_genre, 30463 8648, release_year, 13408 21060, has_genre, 30463 21060, release_year, 13408 37229, has_genre, 30463 37229, release_year, 13408 11344, has_genre, 30463 11344, release_year, 13408 1292, has_genre, 30463 1292, release_year, 13408 38901, has_genre, 30463 38901, release_year, 13408 10703, has_genre, 30463 10703, release_year, 13408 35625, has_genre, 30463 35625, release_year, 13408 16371, has_genre, 30463 16371, has_tags, 30463 16371, has_tags, 4358 23526, has_genre, 30463 23526, release_year, 13408 263, has_genre, 30463 263, has_tags, 30463 263, release_year, 13408 32383, has_genre, 30463 32383, release_year, 13408 12610, has_genre, 30463 12610, release_year, 13408 10109, has_genre, 30463 10109, release_year, 13408 30384, has_genre, 30463 30384, release_year, 13408 16839, has_genre, 30463 16839, release_year, 13408 7699, has_genre, 30463 7699, release_year, 13408 20428, has_genre, 30463 20428, release_year, 13408 17559, has_genre, 30463 17559, has_tags, 30463 17559, release_year, 13408 29734, has_genre, 30463 29734, release_year, 13408 26731, has_genre, 30463 26731, release_year, 13408 28660, has_genre, 30463 28660, release_year, 13408 6068, has_genre, 30463 6068, release_year, 13408 33714, has_genre, 30463 33714, release_year, 13408 33853, has_genre, 30463 33853, release_year, 13408 20003, has_genre, 30463 20003, has_tags, 30463 20003, release_year, 13408 24616, has_genre, 30463 24616, release_year, 13408 26151, has_genre, 30463 26151, release_year, 13408 5731, has_genre, 30463 5731, release_year, 13408 29029, has_genre, 30463 29029, release_year, 13408 21875, has_tags, 30463 21875, release_year, 13408 6959, has_genre, 30463 6959, release_year, 13408 32186, has_genre, 30463 32186, release_year, 13408 8935, has_genre, 30463 8935, release_year, 13408 28044, has_genre, 30463 28044, release_year, 13408 31445, has_genre, 30463 31445, has_tags, 30463 31445, release_year, 13408 13381, has_genre, 30463 13381, release_year, 13408 28182, has_genre, 30463 28182, release_year, 13408 32180, has_genre, 30463 32180, has_tags, 30463 32180, release_year, 13408 38381, has_genre, 30463 38381, release_year, 13408 9530, has_genre, 30463 9530, has_tags, 30463 9530, release_year, 13408 1789, has_genre, 30463 1789, has_tags, 30463 1789, release_year, 13408 37244, has_genre, 30463 37244, release_year, 13408 5880, has_genre, 30463 5880, release_year, 13408 35100, has_genre, 30463 35100, release_year, 13408 7519, has_genre, 30463 7519, release_year, 13408 36159, has_genre, 30463 36159, has_tags, 30463 36159, release_year, 13408 30089, has_genre, 30463 30089, release_year, 13408 2407, has_genre, 30463 2407, release_year, 13408 24221, has_genre, 30463 24221, release_year, 13408 5170, has_genre, 30463 5170, starred_actors, 8644 7949, has_genre, 30463 7949, release_year, 13408 2235, has_genre, 30463 2235, release_year, 13408 4783, has_genre, 30463 4783, has_tags, 30463 4783, release_year, 13408 27762, has_genre, 30463 27762, release_year, 13408 345, has_genre, 30463 345, release_year, 13408 23280, has_genre, 30463 23280, release_year, 13408 15795, has_genre, 30463 15795, release_year, 13408 25674, has_genre, 30463 25674, release_year, 13408 30164, has_genre, 30463 30164, has_tags, 30463 30164, release_year, 13408 4927, has_genre, 30463 4927, release_year, 13408 17778, has_genre, 30463 17778, release_year, 13408 28107, has_genre, 30463 28107, release_year, 13408 10353, has_genre, 30463 10353, release_year, 13408 27713, has_genre, 30463 27713, has_tags, 30463 27713, release_year, 13408 23086, has_genre, 30463 23086, has_tags, 30463 23086, release_year, 13408 20728, has_genre, 30463 20728, has_tags, 30463 20728, release_year, 13408 36231, has_genre, 30463 36231, release_year, 13408 37184, has_genre, 30463 37184, release_year, 13408 33449, has_genre, 30463 33449, release_year, 13408 11027, has_genre, 30463 11027, release_year, 13408 35988, has_genre, 30463 35988, release_year, 13408 19451, has_genre, 30463 19451, release_year, 13408 21790, has_genre, 30463 21790, release_year, 13408 3137, has_genre, 30463 3137, release_year, 13408 35443, has_genre, 30463 35443, has_tags, 30463 35443, release_year, 13408 29077, has_genre, 30463 29077, has_tags, 30463 29077, release_year, 13408 25414, has_genre, 30463 25414, release_year, 13408 27083, has_genre, 30463 27083, release_year, 13408 37358, has_genre, 30463 37358, release_year, 13408 23844, has_genre, 30463 23844, release_year, 13408 4063, has_genre, 30463 4063, has_tags, 30463 4063, release_year, 13408 Question: How are FREDDY GOT FINGERED, ICE, and RICHARD RUSH related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "FREDDY GOT FINGERED", "ICE", "RICHARD RUSH" ], "valid_edges": [ [ "25 WATTS", "has_genre", "COMEDY" ], [ "25 WATTS", "release_year", "2001" ], [ "30 YEARS TO LIFE", "has_genre", "COMEDY" ], [ "30 YEARS TO LIFE", "release_year", "2001" ], [ "ALL OVER THE GUY", "has_genre", "COMEDY" ], [ "ALL OVER THE GUY", "release_year", "2001" ], [ "ALL THE QUEEN'S MEN", "has_genre", "COMEDY" ], [ "ALL THE QUEEN'S MEN", "release_year", "2001" ], [ "AMERICA'S SWEETHEARTS", "has_genre", "COMEDY" ], [ "AMERICA'S SWEETHEARTS", "release_year", "2001" ], [ "AMERICAN PIE 2", "has_genre", "COMEDY" ], [ "AMERICAN PIE 2", "has_tags", "COMEDY" ], [ "AMERICAN PIE 2", "release_year", "2001" ], [ "AMÉLIE", "has_genre", "COMEDY" ], [ "AMÉLIE", "has_tags", "COMEDY" ], [ "AMÉLIE", "release_year", "2001" ], [ "BABY BOY", "has_genre", "COMEDY" ], [ "BABY BOY", "release_year", "2001" ], [ "BANDITS", "has_genre", "COMEDY" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "COMEDY" ], [ "BARTLEBY", "release_year", "2001" ], [ "BLACK KNIGHT", "has_genre", "COMEDY" ], [ "BLACK KNIGHT", "has_tags", "COMEDY" ], [ "BLACK KNIGHT", "release_year", "2001" ], [ "BLOW DRY", "has_genre", "COMEDY" ], [ "BLOW DRY", "release_year", "2001" ], [ "BOB THE BUTLER", "has_genre", "COMEDY" ], [ "BOB THE BUTLER", "starred_actors", "TOM GREEN" ], [ "BRIDGET JONES'S DIARY", "has_genre", "COMEDY" ], [ "BRIDGET JONES'S DIARY", "has_tags", "COMEDY" ], [ "BRIDGET JONES'S DIARY", "release_year", "2001" ], [ "BUBBLE BOY", "has_genre", "COMEDY" ], [ "BUBBLE BOY", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "COMEDY" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CORKY ROMANO", "has_genre", "COMEDY" ], [ "CORKY ROMANO", "release_year", "2001" ], [ "CROCODILE DUNDEE IN LOS ANGELES", "has_genre", "COMEDY" ], [ "CROCODILE DUNDEE IN LOS ANGELES", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "COMEDY" ], [ "DIL CHAHTA HAI", "has_tags", "COMEDY" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'T TEMPT ME", "has_genre", "COMEDY" ], [ "DON'T TEMPT ME", "release_year", "2001" ], [ "DOUBLE TAKE", "has_genre", "COMEDY" ], [ "DOUBLE TAKE", "release_year", "2001" ], [ "DOWN TO EARTH", "has_genre", "COMEDY" ], [ "DOWN TO EARTH", "release_year", "2001" ], [ "DR. DOLITTLE 2", "has_genre", "COMEDY" ], [ "DR. DOLITTLE 2", "release_year", "2001" ], [ "ESCANABA IN DA MOONLIGHT", "has_genre", "COMEDY" ], [ "ESCANABA IN DA MOONLIGHT", "release_year", "2001" ], [ "EVOLUTION", "has_genre", "COMEDY" ], [ "EVOLUTION", "has_tags", "COMEDY" ], [ "EVOLUTION", "release_year", "2001" ], [ "FOCUS", "has_genre", "COMEDY" ], [ "FOCUS", "release_year", "2001" ], [ "FREDDY GOT FINGERED", "directed_by", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "has_genre", "COMEDY" ], [ "FREDDY GOT FINGERED", "has_tags", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "release_year", "2001" ], [ "FREDDY GOT FINGERED", "starred_actors", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "written_by", "TOM GREEN" ], [ "FREEBIE AND THE BEAN", "directed_by", "RICHARD RUSH" ], [ "FREEBIE AND THE BEAN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_tags", "ICE" ], [ "GAUDI AFTERNOON", "has_genre", "COMEDY" ], [ "GAUDI AFTERNOON", "release_year", "2001" ], [ "GET OVER IT", "has_genre", "COMEDY" ], [ "GET OVER IT", "has_tags", "COMEDY" ], [ "GET OVER IT", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "COMEDY" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GOD IS GREAT AND I'M NOT", "has_genre", "COMEDY" ], [ "GOD IS GREAT AND I'M NOT", "release_year", "2001" ], [ "GOOD ADVICE", "has_genre", "COMEDY" ], [ "GOOD ADVICE", "release_year", "2001" ], [ "HAPPY CAMPERS", "has_genre", "COMEDY" ], [ "HAPPY CAMPERS", "release_year", "2001" ], [ "HARVARD MAN", "has_genre", "COMEDY" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HE DIED WITH A FELAFEL IN HIS HAND", "has_genre", "COMEDY" ], [ "HE DIED WITH A FELAFEL IN HIS HAND", "release_year", "2001" ], [ "HEARTBREAKERS", "has_genre", "COMEDY" ], [ "HEARTBREAKERS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "COMEDY" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HOW HIGH", "has_genre", "COMEDY" ], [ "HOW HIGH", "release_year", "2001" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "has_tags", "ICE" ], [ "JACKPOT", "has_genre", "COMEDY" ], [ "JACKPOT", "release_year", "2001" ], [ "JAY AND SILENT BOB STRIKE BACK", "has_genre", "COMEDY" ], [ "JAY AND SILENT BOB STRIKE BACK", "has_tags", "COMEDY" ], [ "JAY AND SILENT BOB STRIKE BACK", "release_year", "2001" ], [ "JOE DIRT", "has_genre", "COMEDY" ], [ "JOE DIRT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "COMEDY" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "COMEDY" ], [ "JOSIE AND THE PUSSYCATS", "release_year", "2001" ], [ "JUMP TOMORROW", "has_genre", "COMEDY" ], [ "JUMP TOMORROW", "release_year", "2001" ], [ "JUST VISITING", "has_genre", "COMEDY" ], [ "JUST VISITING", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "COMEDY" ], [ "KINGDOM COME", "release_year", "2001" ], [ "KISSING JESSICA STEIN", "has_genre", "COMEDY" ], [ "KISSING JESSICA STEIN", "release_year", "2001" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEGALLY BLONDE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "COMEDY" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LUCKY BREAK", "has_genre", "COMEDY" ], [ "LUCKY BREAK", "release_year", "2001" ], [ "MADE", "has_genre", "COMEDY" ], [ "MADE", "release_year", "2001" ], [ "MAX KEEBLE'S BIG MOVE", "has_genre", "COMEDY" ], [ "MAX KEEBLE'S BIG MOVE", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "COMEDY" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONKEYBONE", "has_genre", "COMEDY" ], [ "MONKEYBONE", "release_year", "2001" ], [ "MONSTERS, INC.", "has_genre", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "COMEDY" ], [ "MONSTERS, INC.", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "COMEDY" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "NOBODY'S BABY", "has_genre", "COMEDY" ], [ "NOBODY'S BABY", "release_year", "2001" ], [ "NOT ANOTHER TEEN MOVIE", "has_genre", "COMEDY" ], [ "NOT ANOTHER TEEN MOVIE", "release_year", "2001" ], [ "NOVOCAINE", "has_genre", "COMEDY" ], [ "NOVOCAINE", "release_year", "2001" ], [ "OCEAN'S ELEVEN", "has_tags", "COMEDY" ], [ "OCEAN'S ELEVEN", "release_year", "2001" ], [ "ON THE LINE", "has_genre", "COMEDY" ], [ "ON THE LINE", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "COMEDY" ], [ "ONE MAN UP", "release_year", "2001" ], [ "ONE NIGHT AT MCCOOL'S", "has_genre", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "release_year", "2001" ], [ "PAULINE AND PAULETTE", "has_genre", "COMEDY" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PONTEROSA", "has_genre", "COMEDY" ], [ "PONTEROSA", "has_tags", "COMEDY" ], [ "PONTEROSA", "release_year", "2001" ], [ "POOTIE TANG", "has_genre", "COMEDY" ], [ "POOTIE TANG", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "COMEDY" ], [ "RARE BIRDS", "release_year", "2001" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "release_year", "2001" ], [ "RUSH HOUR 2", "has_genre", "COMEDY" ], [ "RUSH HOUR 2", "has_tags", "COMEDY" ], [ "RUSH HOUR 2", "release_year", "2001" ], [ "SAVING SILVERMAN", "has_genre", "COMEDY" ], [ "SAVING SILVERMAN", "has_tags", "COMEDY" ], [ "SAVING SILVERMAN", "release_year", "2001" ], [ "SAY IT ISN'T SO", "has_genre", "COMEDY" ], [ "SAY IT ISN'T SO", "release_year", "2001" ], [ "SERENDIPITY", "has_genre", "COMEDY" ], [ "SERENDIPITY", "release_year", "2001" ], [ "SHALLOW HAL", "has_genre", "COMEDY" ], [ "SHALLOW HAL", "release_year", "2001" ], [ "SHAOLIN SOCCER", "has_genre", "COMEDY" ], [ "SHAOLIN SOCCER", "release_year", "2001" ], [ "SHREK", "has_genre", "COMEDY" ], [ "SHREK", "has_tags", "COMEDY" ], [ "SHREK", "release_year", "2001" ], [ "SIDEWALKS OF NEW YORK", "has_genre", "COMEDY" ], [ "SIDEWALKS OF NEW YORK", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "COMEDY" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "SPEAKING OF SEX", "has_genre", "COMEDY" ], [ "SPEAKING OF SEX", "release_year", "2001" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "starred_actors", "TOM GREEN" ], [ "STORYTELLING", "has_genre", "COMEDY" ], [ "STORYTELLING", "release_year", "2001" ], [ "SUMMER CATCH", "has_genre", "COMEDY" ], [ "SUMMER CATCH", "release_year", "2001" ], [ "SUPER TROOPERS", "has_genre", "COMEDY" ], [ "SUPER TROOPERS", "has_tags", "COMEDY" ], [ "SUPER TROOPERS", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "COMEDY" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TANGUY", "has_genre", "COMEDY" ], [ "TANGUY", "release_year", "2001" ], [ "THE ANIMAL", "has_genre", "COMEDY" ], [ "THE ANIMAL", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "COMEDY" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "COMEDY" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE CLOSET", "release_year", "2001" ], [ "THE CURSE OF THE JADE SCORPION", "has_genre", "COMEDY" ], [ "THE CURSE OF THE JADE SCORPION", "release_year", "2001" ], [ "THE HAPPINESS OF THE KATAKURIS", "has_genre", "COMEDY" ], [ "THE HAPPINESS OF THE KATAKURIS", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAN WHO SUED GOD", "has_genre", "COMEDY" ], [ "THE MAN WHO SUED GOD", "release_year", "2001" ], [ "THE MEXICAN", "has_genre", "COMEDY" ], [ "THE MEXICAN", "has_tags", "COMEDY" ], [ "THE MEXICAN", "release_year", "2001" ], [ "THE PRINCESS DIARIES", "has_genre", "COMEDY" ], [ "THE PRINCESS DIARIES", "has_tags", "COMEDY" ], [ "THE PRINCESS DIARIES", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "has_tags", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHRINK IS IN", "has_genre", "COMEDY" ], [ "THE SHRINK IS IN", "release_year", "2001" ], [ "THE TRIUMPH OF LOVE", "has_genre", "COMEDY" ], [ "THE TRIUMPH OF LOVE", "release_year", "2001" ], [ "THE WEDDING PLANNER", "has_genre", "COMEDY" ], [ "THE WEDDING PLANNER", "release_year", "2001" ], [ "TOMCATS", "has_genre", "COMEDY" ], [ "TOMCATS", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "COMEDY" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TWO CAN PLAY THAT GAME", "has_genre", "COMEDY" ], [ "TWO CAN PLAY THAT GAME", "release_year", "2001" ], [ "VERY ANNIE MARY", "has_genre", "COMEDY" ], [ "VERY ANNIE MARY", "release_year", "2001" ], [ "VISITOR Q", "has_genre", "COMEDY" ], [ "VISITOR Q", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "COMEDY" ], [ "VIZONTELE", "has_tags", "COMEDY" ], [ "VIZONTELE", "release_year", "2001" ], [ "WASABI", "has_genre", "COMEDY" ], [ "WASABI", "has_tags", "COMEDY" ], [ "WASABI", "release_year", "2001" ], [ "WATERBOYS", "has_genre", "COMEDY" ], [ "WATERBOYS", "release_year", "2001" ], [ "WET HOT AMERICAN SUMMER", "has_genre", "COMEDY" ], [ "WET HOT AMERICAN SUMMER", "release_year", "2001" ], [ "WHAT'S THE WORST THAT COULD HAPPEN?", "has_genre", "COMEDY" ], [ "WHAT'S THE WORST THAT COULD HAPPEN?", "release_year", "2001" ], [ "WHO IS CLETIS TOUT?", "has_genre", "COMEDY" ], [ "WHO IS CLETIS TOUT?", "release_year", "2001" ], [ "ZOOLANDER", "has_genre", "COMEDY" ], [ "ZOOLANDER", "has_tags", "COMEDY" ], [ "ZOOLANDER", "release_year", "2001" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 8165, BAD 10987, HALEY JOEL OSMENT 1919, ROLLING THUNDER 1725, THE BEAST OF YUCCA FLATS 7013, THE COUNTRY BEARS 14626, THE HOMESMAN 38537, TOMMY LEE JONES 17726, TUSK src, edge_attr, dst 1919, starred_actors, 38537 1725, has_imdb_rating, 8165 7013, has_imdb_rating, 8165 7013, starred_actors, 10987 14626, directed_by, 38537 14626, has_tags, 38537 14626, release_year, 9377 14626, starred_actors, 38537 14626, written_by, 38537 17726, release_year, 9377 17726, starred_actors, 10987 Question: How are ROLLING THUNDER, THE BEAST OF YUCCA FLATS, and TUSK related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "ROLLING THUNDER", "THE BEAST OF YUCCA FLATS", "TUSK" ], "valid_edges": [ [ "ROLLING THUNDER", "starred_actors", "TOMMY LEE JONES" ], [ "THE BEAST OF YUCCA FLATS", "has_imdb_rating", "BAD" ], [ "THE COUNTRY BEARS", "has_imdb_rating", "BAD" ], [ "THE COUNTRY BEARS", "starred_actors", "HALEY JOEL OSMENT" ], [ "THE HOMESMAN", "directed_by", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "has_tags", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "release_year", "2014" ], [ "THE HOMESMAN", "starred_actors", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "written_by", "TOMMY LEE JONES" ], [ "TUSK", "release_year", "2014" ], [ "TUSK", "starred_actors", "HALEY JOEL OSMENT" ] ] }
metaqa	You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"\|predicate\|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18366, 1960 10825, 1973 22798, A RAGE IN HARLEM 25522, A WARM DECEMBER 34348, ALL THE YOUNG MEN 16346, DRACULA A.D. 1972 34032, HARLEM 5810, HELL UP IN HARLEM 26647, NOTHING BUT THE NIGHT 23249, PETER CUSHING 1777, SIDNEY POITIER 2709, THE BRIDES OF DRACULA 38676, THE CREEPING FLESH 14162, THE SATANIC RITES OF DRACULA 19088, VAN HELSING src, edge_attr, dst 22798, has_tags, 34032 25522, directed_by, 1777 25522, release_year, 10825 25522, starred_actors, 1777 34348, release_year, 18366 34348, starred_actors, 1777 16346, has_tags, 23249 16346, has_tags, 19088 16346, starred_actors, 23249 5810, has_tags, 34032 5810, release_year, 10825 26647, release_year, 10825 26647, starred_actors, 23249 2709, has_tags, 23249 2709, has_tags, 19088 2709, release_year, 18366 2709, starred_actors, 23249 38676, release_year, 10825 38676, starred_actors, 23249 14162, has_tags, 23249 14162, has_tags, 19088 14162, release_year, 10825 14162, starred_actors, 23249 19088, has_tags, 19088 Question: How are A RAGE IN HARLEM, A WARM DECEMBER, and THE BRIDES OF DRACULA related? Your output must be ONLY the PATH block.	graph_path	{ "style": "rule" }	{ "entities": [ "A RAGE IN HARLEM", "A WARM DECEMBER", "THE BRIDES OF DRACULA" ], "valid_edges": [ [ "A RAGE IN HARLEM", "has_tags", "HARLEM" ], [ "A WARM DECEMBER", "directed_by", "SIDNEY POITIER" ], [ "A WARM DECEMBER", "release_year", "1973" ], [ "A WARM DECEMBER", "starred_actors", "SIDNEY POITIER" ], [ "ALL THE YOUNG MEN", "release_year", "1960" ], [ "ALL THE YOUNG MEN", "starred_actors", "SIDNEY POITIER" ], [ "DRACULA A.D. 1972", "has_tags", "PETER CUSHING" ], [ "DRACULA A.D. 1972", "has_tags", "VAN HELSING" ], [ "DRACULA A.D. 1972", "starred_actors", "PETER CUSHING" ], [ "HELL UP IN HARLEM", "has_tags", "HARLEM" ], [ "HELL UP IN HARLEM", "release_year", "1973" ], [ "NOTHING BUT THE NIGHT", "release_year", "1973" ], [ "NOTHING BUT THE NIGHT", "starred_actors", "PETER CUSHING" ], [ "THE BRIDES OF DRACULA", "has_tags", "PETER CUSHING" ], [ "THE BRIDES OF DRACULA", "has_tags", "VAN HELSING" ], [ "THE BRIDES OF DRACULA", "release_year", "1960" ], [ "THE BRIDES OF DRACULA", "starred_actors", "PETER CUSHING" ], [ "THE CREEPING FLESH", "release_year", "1973" ], [ "THE CREEPING FLESH", "starred_actors", "PETER CUSHING" ], [ "THE SATANIC RITES OF DRACULA", "has_tags", "PETER CUSHING" ], [ "THE SATANIC RITES OF DRACULA", "has_tags", "VAN HELSING" ], [ "THE SATANIC RITES OF DRACULA", "release_year", "1973" ], [ "THE SATANIC RITES OF DRACULA", "starred_actors", "PETER CUSHING" ], [ "VAN HELSING", "has_tags", "VAN HELSING" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36212, DRAMA 16138, JACOB GENTRY 6180, LOVE STORY 19613, MICHAEL HALL D'ADDARIO 19916, MONSIEUR LAZHAR 31312, PEOPLE LIKE US 28095, THE SIGNAL src, edge_attr, dst 6180, has_genre, 36212 19916, has_genre, 36212 31312, has_genre, 36212 31312, has_tags, 36212 31312, starred_actors, 19613 28095, directed_by, 16138 28095, has_tags, 6180 28095, written_by, 16138 Question: For what reason are JACOB GENTRY, MICHAEL HALL D'ADDARIO, and MONSIEUR LAZHAR associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JACOB GENTRY", "MICHAEL HALL D'ADDARIO", "MONSIEUR LAZHAR" ], "valid_edges": [ [ "LOVE STORY", "has_genre", "DRAMA" ], [ "MONSIEUR LAZHAR", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_genre", "DRAMA" ], [ "PEOPLE LIKE US", "has_tags", "DRAMA" ], [ "PEOPLE LIKE US", "starred_actors", "MICHAEL HALL D'ADDARIO" ], [ "THE SIGNAL", "directed_by", "JACOB GENTRY" ], [ "THE SIGNAL", "has_tags", "LOVE STORY" ], [ "THE SIGNAL", "written_by", "JACOB GENTRY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8486, 1999 17254, AMERICAN BEAUTY 30463, COMEDY 7373, DALE VAN EVERY 36212, DRAMA 9624, IT'S A BOY GIRL THING 1555, LITTLE BLACK BOOK 5252, MID-LIFE CRISIS 37544, NICK HURRAN 3627, THE TALK OF THE TOWN 5147, VIRTUAL SEXUALITY src, edge_attr, dst 17254, has_genre, 36212 17254, has_tags, 36212 17254, has_tags, 5252 17254, release_year, 8486 9624, directed_by, 37544 9624, has_genre, 30463 1555, directed_by, 37544 1555, has_genre, 30463 3627, has_genre, 30463 3627, has_genre, 36212 3627, written_by, 7373 5147, directed_by, 37544 5147, release_year, 8486 Question: How are DALE VAN EVERY, MID-LIFE CRISIS, and NICK HURRAN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DALE VAN EVERY", "MID-LIFE CRISIS", "NICK HURRAN" ], "valid_edges": [ [ "AMERICAN BEAUTY", "has_genre", "DRAMA" ], [ "AMERICAN BEAUTY", "has_tags", "DRAMA" ], [ "AMERICAN BEAUTY", "has_tags", "MID-LIFE CRISIS" ], [ "AMERICAN BEAUTY", "release_year", "1999" ], [ "IT'S A BOY GIRL THING", "directed_by", "NICK HURRAN" ], [ "IT'S A BOY GIRL THING", "has_genre", "COMEDY" ], [ "LITTLE BLACK BOOK", "directed_by", "NICK HURRAN" ], [ "LITTLE BLACK BOOK", "has_genre", "COMEDY" ], [ "THE TALK OF THE TOWN", "has_genre", "COMEDY" ], [ "THE TALK OF THE TOWN", "has_genre", "DRAMA" ], [ "THE TALK OF THE TOWN", "written_by", "DALE VAN EVERY" ], [ "VIRTUAL SEXUALITY", "directed_by", "NICK HURRAN" ], [ "VIRTUAL SEXUALITY", "release_year", "1999" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6776, 2000 20719, A TIME FOR DRUNKEN HORSES 23160, BELLY 32815, BLACKBOARDS 36212, DRAMA 35079, HYPE WILLIAMS 15321, JUN FALKENSTEIN 13725, KURDISH 37753, THE TIGGER MOVIE 23247, TRIAGE 29947, TURTLES CAN FLY 22214, WAR src, edge_attr, dst 20719, has_genre, 22214 20719, in_language, 13725 20719, release_year, 6776 23160, directed_by, 35079 23160, has_genre, 36212 23160, written_by, 35079 32815, has_genre, 22214 32815, in_language, 13725 32815, release_year, 6776 37753, directed_by, 15321 37753, release_year, 6776 37753, written_by, 15321 23247, has_genre, 36212 23247, has_genre, 22214 23247, in_language, 13725 29947, has_genre, 36212 29947, has_genre, 22214 29947, in_language, 13725 Question: For what reason are HYPE WILLIAMS, JUN FALKENSTEIN, and KURDISH associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HYPE WILLIAMS", "JUN FALKENSTEIN", "KURDISH" ], "valid_edges": [ [ "A TIME FOR DRUNKEN HORSES", "has_genre", "WAR" ], [ "A TIME FOR DRUNKEN HORSES", "in_language", "KURDISH" ], [ "A TIME FOR DRUNKEN HORSES", "release_year", "2000" ], [ "BELLY", "directed_by", "HYPE WILLIAMS" ], [ "BELLY", "has_genre", "DRAMA" ], [ "BELLY", "written_by", "HYPE WILLIAMS" ], [ "BLACKBOARDS", "has_genre", "WAR" ], [ "BLACKBOARDS", "in_language", "KURDISH" ], [ "BLACKBOARDS", "release_year", "2000" ], [ "THE TIGGER MOVIE", "directed_by", "JUN FALKENSTEIN" ], [ "THE TIGGER MOVIE", "release_year", "2000" ], [ "THE TIGGER MOVIE", "written_by", "JUN FALKENSTEIN" ], [ "TRIAGE", "has_genre", "DRAMA" ], [ "TRIAGE", "has_genre", "WAR" ], [ "TRIAGE", "in_language", "KURDISH" ], [ "TURTLES CAN FLY", "has_genre", "DRAMA" ], [ "TURTLES CAN FLY", "has_genre", "WAR" ], [ "TURTLES CAN FLY", "in_language", "KURDISH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4981, 1965 11832, A CHARLIE BROWN CHRISTMAS 6718, A FAREWELL TO ARMS 12649, A LITTLE ROMANCE 8221, A MAN ESCAPED 24319, A PASSAGE TO INDIA 4763, ADVENTURE 16054, ADVENTURES IN BABYSITTING 10341, ADVENTURES OF DON JUAN 28463, AFTER THE FOX 26641, ALBERT CAMUS 29638, ALICE IN WONDERLAND 13573, ANNA CHRISTIE 17157, ARABIAN NIGHTS 34734, BATTLE OF THE BULGE 10045, BD-R 38657, BEAT THE DEVIL 4592, BEAU TRAVAIL 15771, BENGAZI 27938, BRIGITTE BARDOT 21584, BUNNY LAKE IS MISSING 1040, CAPTAIN BLOOD 5840, CERTIFIED COPY 6903, CHARIOTS OF FIRE 25344, CONFIDENTIALLY YOURS 34792, CONTEMPT 16536, CYRANO DE BERGERAC 23205, DARLING 21286, DAVID COPPERFIELD 23396, DIAL M FOR MURDER 11249, DIARY OF A COUNTRY PRIEST 16041, DJANGO UNCHAINED 5881, ELEPHANT BOY 31783, ENGLISH 24540, EYES WITHOUT A FACE 819, FIST OF THE NORTH STAR 26308, FLIPPER 6012, FRENCH 9003, FUNNY GAMES 5527, GIGI 17384, GUNGA DIN 20941, HAMLET 15896, HOW TO STUFF A WILD BIKINI 12087, HOWL'S MOVING CASTLE 26383, I CONFESS 27285, I WAS A MALE WAR BRIDE 7539, IVANHOE 847, JACK THE GIANT KILLER 21922, JANE EYRE 2527, JEANNE MOREAU 803, JERRY LEWIS 20567, JOHN CARTER 35705, JOURNEY TO THE CENTER OF THE EARTH 38986, JUNGLE BOOK 19098, KING KONG 14209, KING OF HEARTS 14156, KING SOLOMON'S MINES 26649, KISMET 37100, KNIGHTS OF THE ROUND TABLE 33519, LA HAINE 36940, LABYRINTH 30029, LAWRENCE OF ARABIA 35149, LE BEAU SERGE 39572, LES COUSINS 30157, LOLA 32275, LORD OF THE FLIES 14433, LOUIS MALLE 27050, MAN OF LA MANCHA 20579, MARAT/SADE 16925, MAYERLING 6543, MODEL SHOP 31657, MON ONCLE 31661, MY FAIR LADY 12358, MY FAVORITE SEASON 14797, O BROTHER, WHERE ART THOU? 27496, ONE MILLION YEARS B.C. 36988, OPERATION CROSSBOW 29693, PICKPOCKET 33032, PORT OF SHADOWS 15651, PREHISTORIC WOMEN 24745, PURPLE NOON 5897, REPULSION 15938, RIFIFI 15873, ROBIN AND MARIAN 2738, ROMEO AND JULIET 35586, SAHARA 6603, SEX IS COMEDY 27626, SHEENA 31316, SHERLOCK HOLMES AND THE SECRET WEAPON 8436, SPIRITS OF THE DEAD 15194, STORY OF WOMEN 11699, TARZAN THE APE MAN 18715, TARZAN'S NEW YORK ADVENTURE 21608, THE ADVENTURES OF HUCKLEBERRY FINN 24625, THE APARTMENT 15003, THE BATTLE OF ALGIERS 37980, THE BEDFORD INCIDENT 34737, THE BRIDE WORE BLACK 3354, THE BROTHERS GRIMM 18855, THE CADDY 14222, THE CANTERVILLE GHOST 7639, THE CHARGE OF THE LIGHT BRIGADE 18651, THE CORSICAN BROTHERS 21330, THE CRIMSON PIRATE 24990, THE CURSE OF FRANKENSTEIN 16800, THE DECEIVERS 39794, THE DISORDERLY ORDERLY 15154, THE FAMILY JEWELS 38631, THE FLAME AND THE ARROW 11635, THE FOUR FEATHERS 9166, THE GUNS OF NAVARONE 15600, THE HALLELUJAH TRAIL 38257, THE HAPPY TIME 15198, THE HUNCHBACK OF NOTRE DAME 25529, THE ILLUSIONIST 6836, THE IMMORTAL STORY 4091, THE LADY VANISHES 32231, THE LAND THAT TIME FORGOT 31569, THE LOVE PARADE 34018, THE LOVED ONE 4182, THE MAN IN THE IRON MASK 33513, THE MAN WHO LOVED WOMEN 13295, THE MARK OF ZORRO 4029, THE MASK OF FU MANCHU 2432, THE MASTER OF BALLANTRAE 32297, THE MERRY WIDOW 26820, THE MUMMY 1295, THE NUTTY PROFESSOR 5575, THE PEOPLE THAT TIME FORGOT 24512, THE PHANTOM TOLLBOOTH 22486, THE PRINCE AND THE PAUPER 31851, THE PRISONER OF ZENDA 18274, THE ROSE TATTOO 8477, THE SCARLET PIMPERNEL 11265, THE SEA HAWK 30746, THE SECRET LIFE OF WALTER MITTY 25495, THE SHOP ON MAIN STREET 8304, THE SILVER CHALICE 31647, THE SON OF THE SHEIK 34579, THE SPY WHO CAME IN FROM THE COLD 17143, THE STRANGER 7816, THE THREE MUSKETEERS 38808, THE TRAIN 983, THE TREASURE OF THE SIERRA MADRE 30491, THE TRIAL 13722, THE TRIAL OF JOAN OF ARC 29678, THE UMBRELLAS OF CHERBOURG 19255, THE VALACHI PAPERS 17568, THE VANISHING 12308, THE VIKINGS 27609, THE WIND AND THE LION 14471, THIS HAPPY BREED 24789, TO HAVE AND HAVE NOT 25443, TOM JONES 6724, TOM SAWYER 3029, TRIPLE CROSS 4378, VICTIM 30965, VILLAGE OF THE GIANTS 11659, VIVA MARIA! 22844, WENT THE DAY WELL? 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 6037, WITCHFINDER GENERAL 38760, Z 23675, ZERO FOR CONDUCT src, edge_attr, dst 11832, has_tags, 10045 11832, release_year, 4981 6718, has_tags, 10045 6718, in_language, 31783 12649, has_tags, 10045 12649, in_language, 6012 8221, has_tags, 10045 8221, has_tags, 6012 8221, in_language, 6012 24319, has_tags, 10045 24319, in_language, 31783 16054, has_genre, 4763 16054, has_tags, 4763 16054, has_tags, 10045 10341, has_genre, 4763 10341, has_tags, 10045 28463, has_tags, 10045 28463, in_language, 31783 29638, has_genre, 4763 29638, has_tags, 10045 29638, in_language, 31783 13573, has_tags, 10045 13573, in_language, 31783 17157, has_genre, 4763 17157, has_tags, 10045 34734, has_tags, 10045 34734, release_year, 4981 38657, has_genre, 4763 38657, has_tags, 10045 4592, has_tags, 10045 4592, in_language, 6012 15771, has_genre, 4763 15771, has_tags, 10045 21584, has_tags, 10045 21584, release_year, 4981 1040, has_genre, 4763 1040, has_tags, 4763 1040, has_tags, 10045 5840, in_language, 31783 5840, in_language, 6012 6903, has_tags, 10045 6903, in_language, 31783 25344, has_tags, 10045 25344, in_language, 6012 34792, has_tags, 10045 34792, starred_actors, 27938 16536, has_tags, 10045 16536, has_tags, 6012 16536, in_language, 31783 16536, in_language, 6012 23205, has_tags, 10045 23205, release_year, 4981 21286, has_genre, 4763 21286, has_tags, 10045 23396, has_tags, 10045 23396, in_language, 31783 11249, has_tags, 10045 11249, in_language, 6012 16041, has_tags, 10045 16041, in_language, 31783 5881, has_genre, 4763 5881, has_tags, 10045 24540, has_tags, 10045 24540, in_language, 6012 819, has_tags, 10045 819, in_language, 31783 26308, has_genre, 4763 26308, has_tags, 10045 9003, has_tags, 10045 9003, in_language, 31783 5527, has_tags, 10045 5527, in_language, 31783 5527, in_language, 6012 17384, has_genre, 4763 17384, has_tags, 10045 20941, has_tags, 10045 20941, in_language, 31783 15896, has_tags, 10045 15896, release_year, 4981 12087, has_genre, 4763 12087, has_tags, 4763 12087, has_tags, 10045 26383, has_tags, 10045 26383, in_language, 6012 27285, has_tags, 10045 27285, in_language, 6012 7539, has_genre, 4763 7539, has_tags, 10045 847, has_genre, 4763 847, has_tags, 10045 847, in_language, 31783 21922, has_tags, 10045 21922, in_language, 31783 21922, in_language, 6012 20567, has_genre, 4763 20567, has_tags, 10045 35705, has_genre, 4763 35705, has_tags, 4763 35705, has_tags, 10045 38986, has_genre, 4763 38986, has_tags, 10045 19098, has_genre, 4763 19098, has_tags, 4763 19098, has_tags, 10045 14209, has_tags, 10045 14209, in_language, 6012 14156, has_genre, 4763 14156, has_tags, 4763 14156, has_tags, 10045 26649, has_tags, 10045 26649, in_language, 31783 37100, has_genre, 4763 37100, has_tags, 10045 33519, has_tags, 10045 33519, has_tags, 6012 33519, in_language, 6012 36940, has_genre, 4763 36940, has_tags, 4763 36940, has_tags, 10045 30029, has_genre, 4763 30029, has_tags, 10045 35149, has_tags, 10045 35149, in_language, 6012 39572, has_tags, 10045 39572, in_language, 6012 30157, has_tags, 10045 30157, in_language, 6012 32275, has_tags, 10045 32275, in_language, 31783 27050, has_tags, 10045 27050, in_language, 31783 20579, has_tags, 10045 20579, in_language, 31783 16925, has_tags, 10045 16925, in_language, 31783 16925, in_language, 6012 6543, has_tags, 10045 6543, in_language, 31783 31657, has_tags, 10045 31657, in_language, 6012 31661, has_tags, 10045 31661, in_language, 31783 12358, has_tags, 10045 12358, in_language, 6012 14797, has_genre, 4763 14797, has_tags, 4763 14797, has_tags, 10045 27496, has_genre, 4763 27496, has_tags, 10045 36988, has_tags, 10045 36988, release_year, 4981 29693, has_tags, 10045 29693, in_language, 6012 33032, has_tags, 10045 33032, in_language, 6012 15651, has_genre, 4763 15651, has_tags, 10045 24745, has_tags, 10045 24745, in_language, 6012 5897, has_tags, 10045 5897, in_language, 31783 5897, release_year, 4981 15938, has_tags, 10045 15938, in_language, 6012 15873, has_genre, 4763 15873, has_tags, 10045 2738, has_tags, 10045 2738, in_language, 31783 35586, has_genre, 4763 35586, has_tags, 10045 6603, has_tags, 10045 6603, in_language, 6012 27626, has_genre, 4763 27626, has_tags, 10045 31316, has_genre, 4763 31316, has_tags, 10045 8436, directed_by, 14433 8436, has_tags, 10045 8436, in_language, 31783 8436, in_language, 6012 8436, starred_actors, 27938 8436, written_by, 14433 15194, has_tags, 10045 15194, in_language, 6012 11699, has_genre, 4763 11699, has_tags, 10045 18715, has_genre, 4763 18715, has_tags, 10045 21608, has_genre, 4763 21608, has_tags, 10045 24625, has_tags, 10045 24625, in_language, 6012 15003, has_tags, 10045 15003, has_tags, 6012 15003, in_language, 6012 37980, has_tags, 10045 37980, release_year, 4981 34737, has_tags, 10045 34737, in_language, 6012 34737, starred_actors, 2527 3354, has_genre, 4763 3354, has_tags, 4763 3354, has_tags, 10045 3354, in_language, 6012 18855, has_tags, 10045 18855, starred_actors, 803 14222, has_tags, 10045 14222, in_language, 31783 7639, has_genre, 4763 7639, has_tags, 10045 18651, has_tags, 10045 18651, in_language, 31783 21330, has_genre, 4763 21330, has_tags, 10045 24990, has_tags, 10045 24990, in_language, 31783 16800, has_genre, 4763 16800, has_tags, 10045 39794, starred_actors, 803 15154, directed_by, 803 15154, release_year, 4981 15154, starred_actors, 803 15154, written_by, 803 38631, has_genre, 4763 38631, has_tags, 10045 11635, has_genre, 4763 11635, has_tags, 10045 9166, has_genre, 4763 9166, has_tags, 10045 15600, has_tags, 10045 15600, release_year, 4981 38257, has_tags, 10045 38257, in_language, 6012 15198, has_tags, 10045 15198, in_language, 31783 15198, in_language, 6012 25529, has_tags, 10045 25529, in_language, 6012 6836, has_tags, 10045 6836, in_language, 6012 6836, starred_actors, 2527 4091, has_tags, 10045 4091, in_language, 31783 32231, has_genre, 4763 32231, has_tags, 4763 32231, has_tags, 10045 31569, has_tags, 10045 31569, in_language, 6012 34018, has_tags, 10045 34018, release_year, 4981 4182, has_genre, 4763 4182, has_tags, 4763 4182, has_tags, 10045 33513, has_tags, 10045 33513, in_language, 6012 13295, has_genre, 4763 13295, has_tags, 10045 4029, has_genre, 4763 4029, has_tags, 10045 2432, has_genre, 4763 2432, has_tags, 10045 32297, has_tags, 10045 32297, in_language, 6012 26820, has_genre, 4763 26820, has_tags, 4763 26820, has_tags, 10045 1295, directed_by, 803 1295, has_tags, 10045 1295, has_tags, 803 1295, starred_actors, 803 1295, written_by, 803 5575, has_genre, 4763 5575, has_tags, 10045 24512, has_genre, 4763 24512, has_tags, 10045 22486, has_genre, 4763 22486, has_tags, 10045 31851, has_genre, 4763 31851, has_tags, 10045 18274, has_tags, 10045 18274, in_language, 31783 8477, has_genre, 4763 8477, has_tags, 10045 8477, in_language, 31783 8477, in_language, 6012 11265, has_tags, 10045 11265, in_language, 31783 30746, has_genre, 4763 30746, has_tags, 10045 30746, in_language, 31783 25495, has_tags, 10045 25495, release_year, 4981 8304, has_tags, 10045 8304, in_language, 31783 31647, has_genre, 4763 31647, has_tags, 10045 34579, has_tags, 10045 34579, in_language, 31783 34579, release_year, 4981 17143, has_tags, 10045 17143, written_by, 26641 7816, has_genre, 4763 7816, has_tags, 10045 38808, has_tags, 10045 38808, starred_actors, 2527 983, has_genre, 4763 983, has_tags, 10045 983, in_language, 31783 30491, has_tags, 10045 30491, starred_actors, 2527 13722, has_tags, 10045 13722, in_language, 6012 29678, has_tags, 10045 29678, has_tags, 6012 29678, in_language, 6012 19255, has_tags, 10045 19255, in_language, 31783 17568, has_tags, 10045 17568, in_language, 31783 17568, in_language, 6012 12308, has_genre, 4763 12308, has_tags, 10045 27609, has_genre, 4763 27609, has_tags, 10045 14471, has_tags, 10045 14471, in_language, 31783 24789, has_genre, 4763 24789, has_tags, 10045 25443, has_genre, 4763 25443, has_tags, 10045 6724, has_genre, 4763 6724, has_tags, 10045 3029, has_tags, 10045 3029, in_language, 6012 4378, has_tags, 10045 4378, in_language, 31783 30965, has_tags, 10045 30965, release_year, 4981 11659, directed_by, 14433 11659, has_genre, 4763 11659, has_tags, 10045 11659, has_tags, 27938 11659, has_tags, 6012 11659, has_tags, 2527 11659, has_tags, 14433 11659, in_language, 31783 11659, in_language, 6012 11659, release_year, 4981 11659, starred_actors, 27938 11659, starred_actors, 2527 11659, written_by, 14433 22844, has_tags, 10045 22844, in_language, 31783 35212, has_tags, 10045 35212, in_language, 31783 6037, has_tags, 10045 6037, in_language, 31783 38760, has_tags, 10045 38760, in_language, 6012 23675, has_tags, 10045 23675, has_tags, 6012 23675, in_language, 6012 Question: In what context are ALBERT CAMUS, THE DISORDERLY ORDERLY, and VIVA MARIA! connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALBERT CAMUS", "THE DISORDERLY ORDERLY", "VIVA MARIA!" ], "valid_edges": [ [ "A CHARLIE BROWN CHRISTMAS", "has_tags", "BD-R" ], [ "A CHARLIE BROWN CHRISTMAS", "release_year", "1965" ], [ "A FAREWELL TO ARMS", "has_tags", "BD-R" ], [ "A FAREWELL TO ARMS", "in_language", "ENGLISH" ], [ "A LITTLE ROMANCE", "has_tags", "BD-R" ], [ "A LITTLE ROMANCE", "in_language", "FRENCH" ], [ "A MAN ESCAPED", "has_tags", "BD-R" ], [ "A MAN ESCAPED", "has_tags", "FRENCH" ], [ "A MAN ESCAPED", "in_language", "FRENCH" ], [ "A PASSAGE TO INDIA", "has_tags", "BD-R" ], [ "A PASSAGE TO INDIA", "in_language", "ENGLISH" ], [ "ADVENTURES IN BABYSITTING", "has_genre", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "ADVENTURE" ], [ "ADVENTURES IN BABYSITTING", "has_tags", "BD-R" ], [ "ADVENTURES OF DON JUAN", "has_genre", "ADVENTURE" ], [ "ADVENTURES OF DON JUAN", "has_tags", "BD-R" ], [ "AFTER THE FOX", "has_tags", "BD-R" ], [ "AFTER THE FOX", "in_language", "ENGLISH" ], [ "ALICE IN WONDERLAND", "has_genre", "ADVENTURE" ], [ "ALICE IN WONDERLAND", "has_tags", "BD-R" ], [ "ALICE IN WONDERLAND", "in_language", "ENGLISH" ], [ "ANNA CHRISTIE", "has_tags", "BD-R" ], [ "ANNA CHRISTIE", "in_language", "ENGLISH" ], [ "ARABIAN NIGHTS", "has_genre", "ADVENTURE" ], [ "ARABIAN NIGHTS", "has_tags", "BD-R" ], [ "BATTLE OF THE BULGE", "has_tags", "BD-R" ], [ "BATTLE OF THE BULGE", "release_year", "1965" ], [ "BEAT THE DEVIL", "has_genre", "ADVENTURE" ], [ "BEAT THE DEVIL", "has_tags", "BD-R" ], [ "BEAU TRAVAIL", "has_tags", "BD-R" ], [ "BEAU TRAVAIL", "in_language", "FRENCH" ], [ "BENGAZI", "has_genre", "ADVENTURE" ], [ "BENGAZI", "has_tags", "BD-R" ], [ "BUNNY LAKE IS MISSING", "has_tags", "BD-R" ], [ "BUNNY LAKE IS MISSING", "release_year", "1965" ], [ "CAPTAIN BLOOD", "has_genre", "ADVENTURE" ], [ "CAPTAIN BLOOD", "has_tags", "ADVENTURE" ], [ "CAPTAIN BLOOD", "has_tags", "BD-R" ], [ "CERTIFIED COPY", "in_language", "ENGLISH" ], [ "CERTIFIED COPY", "in_language", "FRENCH" ], [ "CHARIOTS OF FIRE", "has_tags", "BD-R" ], [ "CHARIOTS OF FIRE", "in_language", "ENGLISH" ], [ "CONFIDENTIALLY YOURS", "has_tags", "BD-R" ], [ "CONFIDENTIALLY YOURS", "in_language", "FRENCH" ], [ "CONTEMPT", "has_tags", "BD-R" ], [ "CONTEMPT", "starred_actors", "BRIGITTE BARDOT" ], [ "CYRANO DE BERGERAC", "has_tags", "BD-R" ], [ "CYRANO DE BERGERAC", "has_tags", "FRENCH" ], [ "CYRANO DE BERGERAC", "in_language", "ENGLISH" ], [ "CYRANO DE BERGERAC", "in_language", "FRENCH" ], [ "DARLING", "has_tags", "BD-R" ], [ "DARLING", "release_year", "1965" ], [ "DAVID COPPERFIELD", "has_genre", "ADVENTURE" ], [ "DAVID COPPERFIELD", "has_tags", "BD-R" ], [ "DIAL M FOR MURDER", "has_tags", "BD-R" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DIARY OF A COUNTRY PRIEST", "has_tags", "BD-R" ], [ "DIARY OF A COUNTRY PRIEST", "in_language", "FRENCH" ], [ "DJANGO UNCHAINED", "has_tags", "BD-R" ], [ "DJANGO UNCHAINED", "in_language", "ENGLISH" ], [ "ELEPHANT BOY", "has_genre", "ADVENTURE" ], [ "ELEPHANT BOY", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "has_tags", "BD-R" ], [ "EYES WITHOUT A FACE", "in_language", "FRENCH" ], [ "FIST OF THE NORTH STAR", "has_tags", "BD-R" ], [ "FIST OF THE NORTH STAR", "in_language", "ENGLISH" ], [ "FLIPPER", "has_genre", "ADVENTURE" ], [ "FLIPPER", "has_tags", "BD-R" ], [ "FUNNY GAMES", "has_tags", "BD-R" ], [ "FUNNY GAMES", "in_language", "ENGLISH" ], [ "GIGI", "has_tags", "BD-R" ], [ "GIGI", "in_language", "ENGLISH" ], [ "GIGI", "in_language", "FRENCH" ], [ "GUNGA DIN", "has_genre", "ADVENTURE" ], [ "GUNGA DIN", "has_tags", "BD-R" ], [ "HAMLET", "has_tags", "BD-R" ], [ "HAMLET", "in_language", "ENGLISH" ], [ "HOW TO STUFF A WILD BIKINI", "has_tags", "BD-R" ], [ "HOW TO STUFF A WILD BIKINI", "release_year", "1965" ], [ "HOWL'S MOVING CASTLE", "has_genre", "ADVENTURE" ], [ "HOWL'S MOVING CASTLE", "has_tags", "ADVENTURE" ], [ "HOWL'S MOVING CASTLE", "has_tags", "BD-R" ], [ "I CONFESS", "has_tags", "BD-R" ], [ "I CONFESS", "in_language", "FRENCH" ], [ "I WAS A MALE WAR BRIDE", "has_tags", "BD-R" ], [ "I WAS A MALE WAR BRIDE", "in_language", "FRENCH" ], [ "IVANHOE", "has_genre", "ADVENTURE" ], [ "IVANHOE", "has_tags", "BD-R" ], [ "JACK THE GIANT KILLER", "has_genre", "ADVENTURE" ], [ "JACK THE GIANT KILLER", "has_tags", "BD-R" ], [ "JACK THE GIANT KILLER", "in_language", "ENGLISH" ], [ "JANE EYRE", "has_tags", "BD-R" ], [ "JANE EYRE", "in_language", "ENGLISH" ], [ "JANE EYRE", "in_language", "FRENCH" ], [ "JOHN CARTER", "has_genre", "ADVENTURE" ], [ "JOHN CARTER", "has_tags", "BD-R" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_genre", "ADVENTURE" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_tags", "ADVENTURE" ], [ "JOURNEY TO THE CENTER OF THE EARTH", "has_tags", "BD-R" ], [ "JUNGLE BOOK", "has_genre", "ADVENTURE" ], [ "JUNGLE BOOK", "has_tags", "BD-R" ], [ "KING KONG", "has_genre", "ADVENTURE" ], [ "KING KONG", "has_tags", "ADVENTURE" ], [ "KING KONG", "has_tags", "BD-R" ], [ "KING OF HEARTS", "has_tags", "BD-R" ], [ "KING OF HEARTS", "in_language", "FRENCH" ], [ "KING SOLOMON'S MINES", "has_genre", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "ADVENTURE" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KISMET", "has_tags", "BD-R" ], [ "KISMET", "in_language", "ENGLISH" ], [ "KNIGHTS OF THE ROUND TABLE", "has_genre", "ADVENTURE" ], [ "KNIGHTS OF THE ROUND TABLE", "has_tags", "BD-R" ], [ "LA HAINE", "has_tags", "BD-R" ], [ "LA HAINE", "has_tags", "FRENCH" ], [ "LA HAINE", "in_language", "FRENCH" ], [ "LABYRINTH", "has_genre", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "BD-R" ], [ "LAWRENCE OF ARABIA", "has_genre", "ADVENTURE" ], [ "LAWRENCE OF ARABIA", "has_tags", "BD-R" ], [ "LE BEAU SERGE", "has_tags", "BD-R" ], [ "LE BEAU SERGE", "in_language", "FRENCH" ], [ "LES COUSINS", "has_tags", "BD-R" ], [ "LES COUSINS", "in_language", "FRENCH" ], [ "LOLA", "has_tags", "BD-R" ], [ "LOLA", "in_language", "FRENCH" ], [ "LORD OF THE FLIES", "has_tags", "BD-R" ], [ "LORD OF THE FLIES", "in_language", "ENGLISH" ], [ "MAN OF LA MANCHA", "has_tags", "BD-R" ], [ "MAN OF LA MANCHA", "in_language", "ENGLISH" ], [ "MARAT/SADE", "has_tags", "BD-R" ], [ "MARAT/SADE", "in_language", "ENGLISH" ], [ "MAYERLING", "has_tags", "BD-R" ], [ "MAYERLING", "in_language", "ENGLISH" ], [ "MAYERLING", "in_language", "FRENCH" ], [ "MODEL SHOP", "has_tags", "BD-R" ], [ "MODEL SHOP", "in_language", "ENGLISH" ], [ "MON ONCLE", "has_tags", "BD-R" ], [ "MON ONCLE", "in_language", "FRENCH" ], [ "MY FAIR LADY", "has_tags", "BD-R" ], [ "MY FAIR LADY", "in_language", "ENGLISH" ], [ "MY FAVORITE SEASON", "has_tags", "BD-R" ], [ "MY FAVORITE SEASON", "in_language", "FRENCH" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "has_genre", "ADVENTURE" ], [ "ONE MILLION YEARS B.C.", "has_tags", "BD-R" ], [ "OPERATION CROSSBOW", "has_tags", "BD-R" ], [ "OPERATION CROSSBOW", "release_year", "1965" ], [ "PICKPOCKET", "has_tags", "BD-R" ], [ "PICKPOCKET", "in_language", "FRENCH" ], [ "PORT OF SHADOWS", "has_tags", "BD-R" ], [ "PORT OF SHADOWS", "in_language", "FRENCH" ], [ "PREHISTORIC WOMEN", "has_genre", "ADVENTURE" ], [ "PREHISTORIC WOMEN", "has_tags", "BD-R" ], [ "PURPLE NOON", "has_tags", "BD-R" ], [ "PURPLE NOON", "in_language", "FRENCH" ], [ "REPULSION", "has_tags", "BD-R" ], [ "REPULSION", "in_language", "ENGLISH" ], [ "REPULSION", "release_year", "1965" ], [ "RIFIFI", "has_tags", "BD-R" ], [ "RIFIFI", "in_language", "FRENCH" ], [ "ROBIN AND MARIAN", "has_genre", "ADVENTURE" ], [ "ROBIN AND MARIAN", "has_tags", "BD-R" ], [ "ROMEO AND JULIET", "has_tags", "BD-R" ], [ "ROMEO AND JULIET", "in_language", "ENGLISH" ], [ "SAHARA", "has_genre", "ADVENTURE" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SEX IS COMEDY", "has_tags", "BD-R" ], [ "SEX IS COMEDY", "in_language", "FRENCH" ], [ "SHEENA", "has_genre", "ADVENTURE" ], [ "SHEENA", "has_tags", "BD-R" ], [ "SHERLOCK HOLMES AND THE SECRET WEAPON", "has_genre", "ADVENTURE" ], [ "SHERLOCK HOLMES AND THE SECRET WEAPON", "has_tags", "BD-R" ], [ "SPIRITS OF THE DEAD", "directed_by", "LOUIS MALLE" ], [ "SPIRITS OF THE DEAD", "has_tags", "BD-R" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "in_language", "FRENCH" ], [ "SPIRITS OF THE DEAD", "starred_actors", "BRIGITTE BARDOT" ], [ "SPIRITS OF THE DEAD", "written_by", "LOUIS MALLE" ], [ "STORY OF WOMEN", "has_tags", "BD-R" ], [ "STORY OF WOMEN", "in_language", "FRENCH" ], [ "TARZAN THE APE MAN", "has_genre", "ADVENTURE" ], [ "TARZAN THE APE MAN", "has_tags", "BD-R" ], [ "TARZAN'S NEW YORK ADVENTURE", "has_genre", "ADVENTURE" ], [ "TARZAN'S NEW YORK ADVENTURE", "has_tags", "BD-R" ], [ "THE ADVENTURES OF HUCKLEBERRY FINN", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF HUCKLEBERRY FINN", "has_tags", "BD-R" ], [ "THE APARTMENT", "has_tags", "BD-R" ], [ "THE APARTMENT", "in_language", "FRENCH" ], [ "THE BATTLE OF ALGIERS", "has_tags", "BD-R" ], [ "THE BATTLE OF ALGIERS", "has_tags", "FRENCH" ], [ "THE BATTLE OF ALGIERS", "in_language", "FRENCH" ], [ "THE BEDFORD INCIDENT", "has_tags", "BD-R" ], [ "THE BEDFORD INCIDENT", "release_year", "1965" ], [ "THE BRIDE WORE BLACK", "has_tags", "BD-R" ], [ "THE BRIDE WORE BLACK", "in_language", "FRENCH" ], [ "THE BRIDE WORE BLACK", "starred_actors", "JEANNE MOREAU" ], [ "THE BROTHERS GRIMM", "has_genre", "ADVENTURE" ], [ "THE BROTHERS GRIMM", "has_tags", "ADVENTURE" ], [ "THE BROTHERS GRIMM", "has_tags", "BD-R" ], [ "THE BROTHERS GRIMM", "in_language", "FRENCH" ], [ "THE CADDY", "has_tags", "BD-R" ], [ "THE CADDY", "starred_actors", "JERRY LEWIS" ], [ "THE CANTERVILLE GHOST", "has_tags", "BD-R" ], [ "THE CANTERVILLE GHOST", "in_language", "ENGLISH" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_genre", "ADVENTURE" ], [ "THE CHARGE OF THE LIGHT BRIGADE", "has_tags", "BD-R" ], [ "THE CORSICAN BROTHERS", "has_tags", "BD-R" ], [ "THE CORSICAN BROTHERS", "in_language", "ENGLISH" ], [ "THE CRIMSON PIRATE", "has_genre", "ADVENTURE" ], [ "THE CRIMSON PIRATE", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "has_tags", "BD-R" ], [ "THE CURSE OF FRANKENSTEIN", "in_language", "ENGLISH" ], [ "THE DECEIVERS", "has_genre", "ADVENTURE" ], [ "THE DECEIVERS", "has_tags", "BD-R" ], [ "THE DISORDERLY ORDERLY", "starred_actors", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "directed_by", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "release_year", "1965" ], [ "THE FAMILY JEWELS", "starred_actors", "JERRY LEWIS" ], [ "THE FAMILY JEWELS", "written_by", "JERRY LEWIS" ], [ "THE FLAME AND THE ARROW", "has_genre", "ADVENTURE" ], [ "THE FLAME AND THE ARROW", "has_tags", "BD-R" ], [ "THE FOUR FEATHERS", "has_genre", "ADVENTURE" ], [ "THE FOUR FEATHERS", "has_tags", "BD-R" ], [ "THE GUNS OF NAVARONE", "has_genre", "ADVENTURE" ], [ "THE GUNS OF NAVARONE", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "has_tags", "BD-R" ], [ "THE HALLELUJAH TRAIL", "release_year", "1965" ], [ "THE HAPPY TIME", "has_tags", "BD-R" ], [ "THE HAPPY TIME", "in_language", "FRENCH" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_tags", "BD-R" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "ENGLISH" ], [ "THE HUNCHBACK OF NOTRE DAME", "in_language", "FRENCH" ], [ "THE ILLUSIONIST", "has_tags", "BD-R" ], [ "THE ILLUSIONIST", "in_language", "FRENCH" ], [ "THE IMMORTAL STORY", "has_tags", "BD-R" ], [ "THE IMMORTAL STORY", "in_language", "FRENCH" ], [ "THE IMMORTAL STORY", "starred_actors", "JEANNE MOREAU" ], [ "THE LADY VANISHES", "has_tags", "BD-R" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LAND THAT TIME FORGOT", "has_genre", "ADVENTURE" ], [ "THE LAND THAT TIME FORGOT", "has_tags", "ADVENTURE" ], [ "THE LAND THAT TIME FORGOT", "has_tags", "BD-R" ], [ "THE LOVE PARADE", "has_tags", "BD-R" ], [ "THE LOVE PARADE", "in_language", "FRENCH" ], [ "THE LOVED ONE", "has_tags", "BD-R" ], [ "THE LOVED ONE", "release_year", "1965" ], [ "THE MAN IN THE IRON MASK", "has_genre", "ADVENTURE" ], [ "THE MAN IN THE IRON MASK", "has_tags", "ADVENTURE" ], [ "THE MAN IN THE IRON MASK", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "has_tags", "BD-R" ], [ "THE MAN WHO LOVED WOMEN", "in_language", "FRENCH" ], [ "THE MARK OF ZORRO", "has_genre", "ADVENTURE" ], [ "THE MARK OF ZORRO", "has_tags", "BD-R" ], [ "THE MASK OF FU MANCHU", "has_genre", "ADVENTURE" ], [ "THE MASK OF FU MANCHU", "has_tags", "BD-R" ], [ "THE MASTER OF BALLANTRAE", "has_genre", "ADVENTURE" ], [ "THE MASTER OF BALLANTRAE", "has_tags", "BD-R" ], [ "THE MERRY WIDOW", "has_tags", "BD-R" ], [ "THE MERRY WIDOW", "in_language", "FRENCH" ], [ "THE MUMMY", "has_genre", "ADVENTURE" ], [ "THE MUMMY", "has_tags", "ADVENTURE" ], [ "THE MUMMY", "has_tags", "BD-R" ], [ "THE NUTTY PROFESSOR", "directed_by", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "has_tags", "BD-R" ], [ "THE NUTTY PROFESSOR", "has_tags", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "starred_actors", "JERRY LEWIS" ], [ "THE NUTTY PROFESSOR", "written_by", "JERRY LEWIS" ], [ "THE PEOPLE THAT TIME FORGOT", "has_genre", "ADVENTURE" ], [ "THE PEOPLE THAT TIME FORGOT", "has_tags", "BD-R" ], [ "THE PHANTOM TOLLBOOTH", "has_genre", "ADVENTURE" ], [ "THE PHANTOM TOLLBOOTH", "has_tags", "BD-R" ], [ "THE PRINCE AND THE PAUPER", "has_genre", "ADVENTURE" ], [ "THE PRINCE AND THE PAUPER", "has_tags", "BD-R" ], [ "THE PRISONER OF ZENDA", "has_genre", "ADVENTURE" ], [ "THE PRISONER OF ZENDA", "has_tags", "BD-R" ], [ "THE ROSE TATTOO", "has_tags", "BD-R" ], [ "THE ROSE TATTOO", "in_language", "ENGLISH" ], [ "THE SCARLET PIMPERNEL", "has_genre", "ADVENTURE" ], [ "THE SCARLET PIMPERNEL", "has_tags", "BD-R" ], [ "THE SCARLET PIMPERNEL", "in_language", "ENGLISH" ], [ "THE SCARLET PIMPERNEL", "in_language", "FRENCH" ], [ "THE SEA HAWK", "has_tags", "BD-R" ], [ "THE SEA HAWK", "in_language", "ENGLISH" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "ADVENTURE" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_tags", "BD-R" ], [ "THE SECRET LIFE OF WALTER MITTY", "in_language", "ENGLISH" ], [ "THE SHOP ON MAIN STREET", "has_tags", "BD-R" ], [ "THE SHOP ON MAIN STREET", "release_year", "1965" ], [ "THE SILVER CHALICE", "has_tags", "BD-R" ], [ "THE SILVER CHALICE", "in_language", "ENGLISH" ], [ "THE SON OF THE SHEIK", "has_genre", "ADVENTURE" ], [ "THE SON OF THE SHEIK", "has_tags", "BD-R" ], [ "THE SPY WHO CAME IN FROM THE COLD", "has_tags", "BD-R" ], [ "THE SPY WHO CAME IN FROM THE COLD", "in_language", "ENGLISH" ], [ "THE SPY WHO CAME IN FROM THE COLD", "release_year", "1965" ], [ "THE STRANGER", "has_tags", "BD-R" ], [ "THE STRANGER", "written_by", "ALBERT CAMUS" ], [ "THE THREE MUSKETEERS", "has_genre", "ADVENTURE" ], [ "THE THREE MUSKETEERS", "has_tags", "BD-R" ], [ "THE TRAIN", "has_tags", "BD-R" ], [ "THE TRAIN", "starred_actors", "JEANNE MOREAU" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_genre", "ADVENTURE" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_tags", "BD-R" ], [ "THE TREASURE OF THE SIERRA MADRE", "in_language", "ENGLISH" ], [ "THE TRIAL", "has_tags", "BD-R" ], [ "THE TRIAL", "starred_actors", "JEANNE MOREAU" ], [ "THE TRIAL OF JOAN OF ARC", "has_tags", "BD-R" ], [ "THE TRIAL OF JOAN OF ARC", "in_language", "FRENCH" ], [ "THE UMBRELLAS OF CHERBOURG", "has_tags", "BD-R" ], [ "THE UMBRELLAS OF CHERBOURG", "has_tags", "FRENCH" ], [ "THE UMBRELLAS OF CHERBOURG", "in_language", "FRENCH" ], [ "THE VALACHI PAPERS", "has_tags", "BD-R" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE VANISHING", "has_tags", "BD-R" ], [ "THE VANISHING", "in_language", "ENGLISH" ], [ "THE VANISHING", "in_language", "FRENCH" ], [ "THE VIKINGS", "has_genre", "ADVENTURE" ], [ "THE VIKINGS", "has_tags", "BD-R" ], [ "THE WIND AND THE LION", "has_genre", "ADVENTURE" ], [ "THE WIND AND THE LION", "has_tags", "BD-R" ], [ "THIS HAPPY BREED", "has_tags", "BD-R" ], [ "THIS HAPPY BREED", "in_language", "ENGLISH" ], [ "TO HAVE AND HAVE NOT", "has_genre", "ADVENTURE" ], [ "TO HAVE AND HAVE NOT", "has_tags", "BD-R" ], [ "TOM JONES", "has_genre", "ADVENTURE" ], [ "TOM JONES", "has_tags", "BD-R" ], [ "TOM SAWYER", "has_genre", "ADVENTURE" ], [ "TOM SAWYER", "has_tags", "BD-R" ], [ "TRIPLE CROSS", "has_tags", "BD-R" ], [ "TRIPLE CROSS", "in_language", "FRENCH" ], [ "VICTIM", "has_tags", "BD-R" ], [ "VICTIM", "in_language", "ENGLISH" ], [ "VILLAGE OF THE GIANTS", "has_tags", "BD-R" ], [ "VILLAGE OF THE GIANTS", "release_year", "1965" ], [ "VIVA MARIA!", "directed_by", "LOUIS MALLE" ], [ "VIVA MARIA!", "has_genre", "ADVENTURE" ], [ "VIVA MARIA!", "has_tags", "BD-R" ], [ "VIVA MARIA!", "has_tags", "BRIGITTE BARDOT" ], [ "VIVA MARIA!", "has_tags", "FRENCH" ], [ "VIVA MARIA!", "has_tags", "JEANNE MOREAU" ], [ "VIVA MARIA!", "has_tags", "LOUIS MALLE" ], [ "VIVA MARIA!", "in_language", "ENGLISH" ], [ "VIVA MARIA!", "in_language", "FRENCH" ], [ "VIVA MARIA!", "release_year", "1965" ], [ "VIVA MARIA!", "starred_actors", "BRIGITTE BARDOT" ], [ "VIVA MARIA!", "starred_actors", "JEANNE MOREAU" ], [ "VIVA MARIA!", "written_by", "LOUIS MALLE" ], [ "WENT THE DAY WELL?", "has_tags", "BD-R" ], [ "WENT THE DAY WELL?", "in_language", "ENGLISH" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_tags", "BD-R" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "in_language", "ENGLISH" ], [ "WITCHFINDER GENERAL", "has_tags", "BD-R" ], [ "WITCHFINDER GENERAL", "in_language", "ENGLISH" ], [ "Z", "has_tags", "BD-R" ], [ "Z", "in_language", "FRENCH" ], [ "ZERO FOR CONDUCT", "has_tags", "BD-R" ], [ "ZERO FOR CONDUCT", "has_tags", "FRENCH" ], [ "ZERO FOR CONDUCT", "in_language", "FRENCH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 5438, 1931 18132, 1938 35063, 1976 1092, ARROWSMITH 3706, BEULAH BONDI 32354, FOUR MEN AND A PRAYER 7736, JAMES STEWART 13255, JOHN FORD 15311, OF HUMAN HEARTS 31805, SEAS BENEATH 28357, ST. IVES 7352, STREET SCENE 19417, THE CRIMINAL CODE 36235, THE MAN WHO SHOT LIBERTY VALANCE 31357, THE SHOOTIST 32860, THE SHOPWORN ANGEL 30453, THE STAR WITNESS 37207, TWO RODE TOGETHER 13631, VIVACIOUS LADY 27356, WALTER HUSTON 8184, YOU CAN'T TAKE IT WITH YOU src, edge_attr, dst 1092, directed_by, 13255 1092, release_year, 5438 32354, directed_by, 13255 32354, release_year, 18132 15311, release_year, 18132 15311, starred_actors, 3706 15311, starred_actors, 7736 15311, starred_actors, 27356 31805, directed_by, 13255 31805, release_year, 5438 28357, release_year, 35063 7352, release_year, 5438 7352, starred_actors, 3706 19417, release_year, 5438 19417, starred_actors, 27356 36235, directed_by, 13255 36235, has_tags, 7736 36235, has_tags, 13255 36235, starred_actors, 7736 31357, release_year, 35063 31357, starred_actors, 7736 32860, release_year, 18132 32860, starred_actors, 7736 30453, release_year, 5438 30453, starred_actors, 27356 37207, directed_by, 13255 37207, starred_actors, 7736 13631, release_year, 18132 13631, starred_actors, 3706 13631, starred_actors, 7736 8184, has_tags, 7736 8184, release_year, 18132 8184, starred_actors, 7736 Question: For what reason are ARROWSMITH, OF HUMAN HEARTS, and ST. IVES associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ARROWSMITH", "OF HUMAN HEARTS", "ST. IVES" ], "valid_edges": [ [ "ARROWSMITH", "directed_by", "JOHN FORD" ], [ "ARROWSMITH", "release_year", "1931" ], [ "FOUR MEN AND A PRAYER", "directed_by", "JOHN FORD" ], [ "FOUR MEN AND A PRAYER", "release_year", "1938" ], [ "OF HUMAN HEARTS", "release_year", "1938" ], [ "OF HUMAN HEARTS", "starred_actors", "BEULAH BONDI" ], [ "OF HUMAN HEARTS", "starred_actors", "JAMES STEWART" ], [ "OF HUMAN HEARTS", "starred_actors", "WALTER HUSTON" ], [ "SEAS BENEATH", "directed_by", "JOHN FORD" ], [ "SEAS BENEATH", "release_year", "1931" ], [ "ST. IVES", "release_year", "1976" ], [ "STREET SCENE", "release_year", "1931" ], [ "STREET SCENE", "starred_actors", "BEULAH BONDI" ], [ "THE CRIMINAL CODE", "release_year", "1931" ], [ "THE CRIMINAL CODE", "starred_actors", "WALTER HUSTON" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "directed_by", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JAMES STEWART" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "has_tags", "JOHN FORD" ], [ "THE MAN WHO SHOT LIBERTY VALANCE", "starred_actors", "JAMES STEWART" ], [ "THE SHOOTIST", "release_year", "1976" ], [ "THE SHOOTIST", "starred_actors", "JAMES STEWART" ], [ "THE SHOPWORN ANGEL", "release_year", "1938" ], [ "THE SHOPWORN ANGEL", "starred_actors", "JAMES STEWART" ], [ "THE STAR WITNESS", "release_year", "1931" ], [ "THE STAR WITNESS", "starred_actors", "WALTER HUSTON" ], [ "TWO RODE TOGETHER", "directed_by", "JOHN FORD" ], [ "TWO RODE TOGETHER", "starred_actors", "JAMES STEWART" ], [ "VIVACIOUS LADY", "release_year", "1938" ], [ "VIVACIOUS LADY", "starred_actors", "BEULAH BONDI" ], [ "VIVACIOUS LADY", "starred_actors", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_tags", "JAMES STEWART" ], [ "YOU CAN'T TAKE IT WITH YOU", "release_year", "1938" ], [ "YOU CAN'T TAKE IT WITH YOU", "starred_actors", "JAMES STEWART" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36173, 1946 30146, A CHRISTMAS CAROL 16150, A CHRISTMAS STORY 19697, ALAIN RESNAIS 9677, ANATOMY OF A MURDER 25570, BEAUTY AND THE BEAST 2313, BEN-HUR 17280, CHRISTMAS 14728, CLASSIC 22958, FAMOUS 1331, IT'S A WONDERFUL LIFE 7736, JAMES STEWART 30057, LAST YEAR AT MARIENBAD 39471, LETTERS TO JULIET 25534, LONG 13672, LOVE ACTUALLY 1994, NOTORIOUS 15644, OLIVER TWIST 37135, REAR WINDOW 38875, ROMANTIC 40066, THE JUNGLE BOOK 28776, THE WIZARD OF OZ 7957, VERTIGO 33318, YOU AIN'T SEEN NOTHIN' YET src, edge_attr, dst 30146, has_imdb_votes, 22958 30146, has_tags, 17280 30146, has_tags, 14728 16150, has_tags, 17280 16150, has_tags, 14728 9677, has_imdb_votes, 22958 9677, has_tags, 7736 9677, starred_actors, 7736 25570, has_imdb_votes, 22958 25570, has_tags, 14728 25570, release_year, 36173 2313, has_imdb_votes, 22958 2313, has_tags, 25534 1331, has_tags, 17280 1331, has_tags, 14728 1331, has_tags, 7736 1331, has_tags, 25534 1331, release_year, 36173 1331, starred_actors, 7736 30057, directed_by, 19697 30057, has_imdb_votes, 22958 30057, has_tags, 19697 39471, has_imdb_votes, 22958 39471, has_tags, 38875 13672, has_tags, 17280 13672, has_tags, 38875 1994, has_imdb_votes, 22958 1994, release_year, 36173 15644, has_imdb_votes, 22958 15644, has_tags, 14728 37135, has_tags, 14728 37135, has_tags, 7736 37135, starred_actors, 7736 40066, has_imdb_votes, 22958 40066, has_tags, 14728 28776, has_imdb_votes, 22958 28776, has_tags, 14728 7957, has_tags, 14728 7957, has_tags, 7736 7957, starred_actors, 7736 33318, directed_by, 19697 33318, has_tags, 19697 33318, written_by, 19697 Question: How are IT'S A WONDERFUL LIFE, LETTERS TO JULIET, and YOU AIN'T SEEN NOTHIN' YET related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "IT'S A WONDERFUL LIFE", "LETTERS TO JULIET", "YOU AIN'T SEEN NOTHIN' YET" ], "valid_edges": [ [ "A CHRISTMAS CAROL", "has_imdb_votes", "FAMOUS" ], [ "A CHRISTMAS CAROL", "has_tags", "CHRISTMAS" ], [ "A CHRISTMAS CAROL", "has_tags", "CLASSIC" ], [ "A CHRISTMAS STORY", "has_tags", "CHRISTMAS" ], [ "A CHRISTMAS STORY", "has_tags", "CLASSIC" ], [ "ANATOMY OF A MURDER", "has_imdb_votes", "FAMOUS" ], [ "ANATOMY OF A MURDER", "has_tags", "JAMES STEWART" ], [ "ANATOMY OF A MURDER", "starred_actors", "JAMES STEWART" ], [ "BEAUTY AND THE BEAST", "has_imdb_votes", "FAMOUS" ], [ "BEAUTY AND THE BEAST", "has_tags", "CLASSIC" ], [ "BEAUTY AND THE BEAST", "release_year", "1946" ], [ "BEN-HUR", "has_imdb_votes", "FAMOUS" ], [ "BEN-HUR", "has_tags", "LONG" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CHRISTMAS" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "CLASSIC" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "JAMES STEWART" ], [ "IT'S A WONDERFUL LIFE", "has_tags", "LONG" ], [ "IT'S A WONDERFUL LIFE", "release_year", "1946" ], [ "IT'S A WONDERFUL LIFE", "starred_actors", "JAMES STEWART" ], [ "LAST YEAR AT MARIENBAD", "directed_by", "ALAIN RESNAIS" ], [ "LAST YEAR AT MARIENBAD", "has_imdb_votes", "FAMOUS" ], [ "LAST YEAR AT MARIENBAD", "has_tags", "ALAIN RESNAIS" ], [ "LETTERS TO JULIET", "has_imdb_votes", "FAMOUS" ], [ "LETTERS TO JULIET", "has_tags", "ROMANTIC" ], [ "LOVE ACTUALLY", "has_tags", "CHRISTMAS" ], [ "LOVE ACTUALLY", "has_tags", "ROMANTIC" ], [ "NOTORIOUS", "has_imdb_votes", "FAMOUS" ], [ "NOTORIOUS", "release_year", "1946" ], [ "OLIVER TWIST", "has_imdb_votes", "FAMOUS" ], [ "OLIVER TWIST", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "CLASSIC" ], [ "REAR WINDOW", "has_tags", "JAMES STEWART" ], [ "REAR WINDOW", "starred_actors", "JAMES STEWART" ], [ "THE JUNGLE BOOK", "has_imdb_votes", "FAMOUS" ], [ "THE JUNGLE BOOK", "has_tags", "CLASSIC" ], [ "THE WIZARD OF OZ", "has_imdb_votes", "FAMOUS" ], [ "THE WIZARD OF OZ", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "CLASSIC" ], [ "VERTIGO", "has_tags", "JAMES STEWART" ], [ "VERTIGO", "starred_actors", "JAMES STEWART" ], [ "YOU AIN'T SEEN NOTHIN' YET", "directed_by", "ALAIN RESNAIS" ], [ "YOU AIN'T SEEN NOTHIN' YET", "has_tags", "ALAIN RESNAIS" ], [ "YOU AIN'T SEEN NOTHIN' YET", "written_by", "ALAIN RESNAIS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1421, 2013 3560, A FIELD IN ENGLAND 20723, ALAN PARTRIDGE 30870, BEAUTIFUL CREATURES 8381, DETOUR 31783, ENGLISH 37158, ERIC HEISSERER 21573, GIRL ON A BICYCLE 12776, GRAND PIANO 33776, HOURS 847, JACK THE GIANT KILLER 37407, JACK THE GIANT SLAYER 29418, JEREMY IRONS 24015, LORD OF TEARS 31324, NIGHT TRAIN TO LISBON 16883, NORWEGIAN 25824, PARADISE 8352, PARANOIA 39135, REACHING FOR THE MOON 38271, SNOWPIERCER 18443, SONDRE KROGTOFT LARSEN 30357, STOKER 6949, SUNSHINE ON LEITH 38107, THE EAST 24306, THE ENGLISH TEACHER 38918, THE FAMILY 2872, THE GREAT GATSBY 30746, THE SECRET LIFE OF WALTER MITTY 19624, THE THING 30209, YEH JAWAANI HAI DEEWANI 17777, ZULU src, edge_attr, dst 3560, in_language, 31783 3560, release_year, 1421 20723, in_language, 31783 20723, release_year, 1421 30870, release_year, 1421 30870, starred_actors, 29418 8381, in_language, 16883 8381, starred_actors, 18443 21573, in_language, 31783 21573, release_year, 1421 12776, in_language, 31783 12776, release_year, 1421 33776, directed_by, 37158 33776, release_year, 1421 33776, written_by, 37158 847, in_language, 31783 847, release_year, 1421 37407, in_language, 31783 37407, release_year, 1421 24015, in_language, 31783 24015, release_year, 1421 31324, has_tags, 29418 31324, in_language, 31783 31324, release_year, 1421 31324, starred_actors, 29418 25824, in_language, 31783 25824, release_year, 1421 8352, release_year, 1421 39135, in_language, 31783 39135, release_year, 1421 38271, in_language, 31783 38271, release_year, 1421 30357, in_language, 31783 30357, release_year, 1421 6949, in_language, 31783 6949, release_year, 1421 38107, in_language, 31783 38107, release_year, 1421 24306, has_tags, 31783 24306, in_language, 31783 24306, release_year, 1421 38918, in_language, 31783 38918, release_year, 1421 2872, in_language, 31783 2872, release_year, 1421 30746, in_language, 31783 30746, release_year, 1421 19624, has_tags, 16883 19624, has_tags, 8352 19624, in_language, 16883 19624, written_by, 37158 30209, in_language, 31783 30209, release_year, 1421 17777, in_language, 31783 17777, release_year, 1421 Question: In what context are ERIC HEISSERER, NIGHT TRAIN TO LISBON, and SONDRE KROGTOFT LARSEN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ERIC HEISSERER", "NIGHT TRAIN TO LISBON", "SONDRE KROGTOFT LARSEN" ], "valid_edges": [ [ "A FIELD IN ENGLAND", "in_language", "ENGLISH" ], [ "A FIELD IN ENGLAND", "release_year", "2013" ], [ "ALAN PARTRIDGE", "in_language", "ENGLISH" ], [ "ALAN PARTRIDGE", "release_year", "2013" ], [ "BEAUTIFUL CREATURES", "release_year", "2013" ], [ "BEAUTIFUL CREATURES", "starred_actors", "JEREMY IRONS" ], [ "DETOUR", "in_language", "NORWEGIAN" ], [ "DETOUR", "starred_actors", "SONDRE KROGTOFT LARSEN" ], [ "GIRL ON A BICYCLE", "in_language", "ENGLISH" ], [ "GIRL ON A BICYCLE", "release_year", "2013" ], [ "GRAND PIANO", "in_language", "ENGLISH" ], [ "GRAND PIANO", "release_year", "2013" ], [ "HOURS", "directed_by", "ERIC HEISSERER" ], [ "HOURS", "release_year", "2013" ], [ "HOURS", "written_by", "ERIC HEISSERER" ], [ "JACK THE GIANT KILLER", "in_language", "ENGLISH" ], [ "JACK THE GIANT KILLER", "release_year", "2013" ], [ "JACK THE GIANT SLAYER", "in_language", "ENGLISH" ], [ "JACK THE GIANT SLAYER", "release_year", "2013" ], [ "LORD OF TEARS", "in_language", "ENGLISH" ], [ "LORD OF TEARS", "release_year", "2013" ], [ "NIGHT TRAIN TO LISBON", "has_tags", "JEREMY IRONS" ], [ "NIGHT TRAIN TO LISBON", "in_language", "ENGLISH" ], [ "NIGHT TRAIN TO LISBON", "release_year", "2013" ], [ "NIGHT TRAIN TO LISBON", "starred_actors", "JEREMY IRONS" ], [ "PARADISE", "in_language", "ENGLISH" ], [ "PARADISE", "release_year", "2013" ], [ "PARANOIA", "release_year", "2013" ], [ "REACHING FOR THE MOON", "in_language", "ENGLISH" ], [ "REACHING FOR THE MOON", "release_year", "2013" ], [ "SNOWPIERCER", "in_language", "ENGLISH" ], [ "SNOWPIERCER", "release_year", "2013" ], [ "STOKER", "in_language", "ENGLISH" ], [ "STOKER", "release_year", "2013" ], [ "SUNSHINE ON LEITH", "in_language", "ENGLISH" ], [ "SUNSHINE ON LEITH", "release_year", "2013" ], [ "THE EAST", "in_language", "ENGLISH" ], [ "THE EAST", "release_year", "2013" ], [ "THE ENGLISH TEACHER", "has_tags", "ENGLISH" ], [ "THE ENGLISH TEACHER", "in_language", "ENGLISH" ], [ "THE ENGLISH TEACHER", "release_year", "2013" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE FAMILY", "release_year", "2013" ], [ "THE GREAT GATSBY", "in_language", "ENGLISH" ], [ "THE GREAT GATSBY", "release_year", "2013" ], [ "THE SECRET LIFE OF WALTER MITTY", "in_language", "ENGLISH" ], [ "THE SECRET LIFE OF WALTER MITTY", "release_year", "2013" ], [ "THE THING", "has_tags", "NORWEGIAN" ], [ "THE THING", "has_tags", "PARANOIA" ], [ "THE THING", "in_language", "NORWEGIAN" ], [ "THE THING", "written_by", "ERIC HEISSERER" ], [ "YEH JAWAANI HAI DEEWANI", "in_language", "ENGLISH" ], [ "YEH JAWAANI HAI DEEWANI", "release_year", "2013" ], [ "ZULU", "in_language", "ENGLISH" ], [ "ZULU", "release_year", "2013" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36279, 10 YEARS 29424, 2011 23250, 50/50 5158, A BAG OF HAMMERS 10158, A PRINCESS FOR CHRISTMAS 37154, ALAN JACOBS 26599, AMERICAN GUN 29881, AMERICANO 188, ANOTHER HAPPY DAY 23286, CARNAGE 28503, CLOUDBURST 23452, DARK HORSE 6375, DELICACY 14132, DESI BOYZ 36212, DRAMA 17854, GOING DOWN IN LA-LA LAND 13198, HOLY FLYING CIRCUS 21922, JANE EYRE 37830, JEFF, WHO LIVES AT HOME 15175, LE HAVRE 3800, LOSERS' CLUB 19802, LOVE 4234, MADEA'S BIG HAPPY FAMILY 35399, MICHAEL BRANDT 33300, NATURAL SELECTION 20537, NEWLYWEDS 10021, OUR IDIOT BROTHER 35664, RESTLESS 12301, SALMON FISHING IN THE YEMEN 23708, SUICIDE ROOM 18005, TAKE THIS WALTZ 26586, THAT'S WHAT I AM 39795, THE ARTIST 5838, THE CLOWN 11393, THE DESCENDANTS 32295, THE DILEMMA 3680, THE DOUBLE 6289, THE INTOUCHABLES 7816, THE THREE MUSKETEERS 13003, THE WELL-DIGGER'S DAUGHTER 5529, THIN ICE 8957, WE BOUGHT A ZOO 35511, WE HAVE A POPE 33483, WEEKEND 36565, WIN WIN 11924, YOUNG ADULT 16822, YOUR SISTER'S SISTER 28489, ZINDAGI NA MILEGI DOBARA src, edge_attr, dst 36279, has_genre, 36212 36279, release_year, 29424 23250, has_genre, 36212 23250, release_year, 29424 5158, has_genre, 36212 5158, release_year, 29424 10158, has_genre, 36212 10158, release_year, 29424 26599, directed_by, 37154 26599, has_genre, 36212 26599, written_by, 37154 29881, has_genre, 36212 29881, release_year, 29424 188, has_genre, 36212 188, release_year, 29424 23286, has_genre, 36212 23286, release_year, 29424 28503, has_genre, 36212 28503, release_year, 29424 23452, has_genre, 36212 23452, release_year, 29424 6375, has_genre, 36212 6375, release_year, 29424 14132, has_genre, 36212 14132, release_year, 29424 17854, has_genre, 36212 17854, release_year, 29424 13198, has_genre, 36212 13198, release_year, 29424 21922, has_genre, 36212 21922, release_year, 29424 37830, has_genre, 36212 37830, release_year, 29424 15175, has_genre, 36212 15175, release_year, 29424 3800, has_genre, 36212 3800, release_year, 29424 19802, has_genre, 36212 19802, release_year, 29424 4234, has_genre, 36212 4234, release_year, 29424 33300, has_genre, 36212 33300, release_year, 29424 20537, has_genre, 36212 20537, release_year, 29424 10021, has_genre, 36212 10021, release_year, 29424 35664, has_genre, 36212 35664, release_year, 29424 12301, has_genre, 36212 12301, release_year, 29424 23708, has_genre, 36212 23708, release_year, 29424 18005, has_genre, 36212 18005, release_year, 29424 26586, has_genre, 36212 26586, release_year, 29424 39795, has_genre, 36212 39795, has_tags, 36212 39795, release_year, 29424 5838, has_genre, 36212 5838, release_year, 29424 11393, has_genre, 36212 11393, has_tags, 36212 11393, release_year, 29424 32295, has_genre, 36212 32295, release_year, 29424 3680, directed_by, 35399 3680, release_year, 29424 3680, written_by, 35399 6289, has_genre, 36212 6289, release_year, 29424 7816, has_genre, 36212 7816, release_year, 29424 13003, has_genre, 36212 13003, release_year, 29424 5529, has_genre, 36212 5529, release_year, 29424 8957, has_genre, 36212 8957, release_year, 29424 35511, has_genre, 36212 35511, release_year, 29424 33483, has_genre, 36212 33483, release_year, 29424 36565, has_genre, 36212 36565, release_year, 29424 11924, has_genre, 36212 11924, has_tags, 36212 11924, release_year, 29424 16822, has_genre, 36212 16822, release_year, 29424 28489, has_genre, 36212 28489, release_year, 29424 Question: How are ALAN JACOBS, MICHAEL BRANDT, and SUICIDE ROOM related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALAN JACOBS", "MICHAEL BRANDT", "SUICIDE ROOM" ], "valid_edges": [ [ "10 YEARS", "has_genre", "DRAMA" ], [ "10 YEARS", "release_year", "2011" ], [ "50/50", "has_genre", "DRAMA" ], [ "50/50", "release_year", "2011" ], [ "A BAG OF HAMMERS", "has_genre", "DRAMA" ], [ "A BAG OF HAMMERS", "release_year", "2011" ], [ "A PRINCESS FOR CHRISTMAS", "has_genre", "DRAMA" ], [ "A PRINCESS FOR CHRISTMAS", "release_year", "2011" ], [ "AMERICAN GUN", "directed_by", "ALAN JACOBS" ], [ "AMERICAN GUN", "has_genre", "DRAMA" ], [ "AMERICAN GUN", "written_by", "ALAN JACOBS" ], [ "AMERICANO", "has_genre", "DRAMA" ], [ "AMERICANO", "release_year", "2011" ], [ "ANOTHER HAPPY DAY", "has_genre", "DRAMA" ], [ "ANOTHER HAPPY DAY", "release_year", "2011" ], [ "CARNAGE", "has_genre", "DRAMA" ], [ "CARNAGE", "release_year", "2011" ], [ "CLOUDBURST", "has_genre", "DRAMA" ], [ "CLOUDBURST", "release_year", "2011" ], [ "DARK HORSE", "has_genre", "DRAMA" ], [ "DARK HORSE", "release_year", "2011" ], [ "DELICACY", "has_genre", "DRAMA" ], [ "DELICACY", "release_year", "2011" ], [ "DESI BOYZ", "has_genre", "DRAMA" ], [ "DESI BOYZ", "release_year", "2011" ], [ "GOING DOWN IN LA-LA LAND", "has_genre", "DRAMA" ], [ "GOING DOWN IN LA-LA LAND", "release_year", "2011" ], [ "HOLY FLYING CIRCUS", "has_genre", "DRAMA" ], [ "HOLY FLYING CIRCUS", "release_year", "2011" ], [ "JANE EYRE", "has_genre", "DRAMA" ], [ "JANE EYRE", "release_year", "2011" ], [ "JEFF, WHO LIVES AT HOME", "has_genre", "DRAMA" ], [ "JEFF, WHO LIVES AT HOME", "release_year", "2011" ], [ "LE HAVRE", "has_genre", "DRAMA" ], [ "LE HAVRE", "release_year", "2011" ], [ "LOSERS' CLUB", "has_genre", "DRAMA" ], [ "LOSERS' CLUB", "release_year", "2011" ], [ "LOVE", "has_genre", "DRAMA" ], [ "LOVE", "release_year", "2011" ], [ "MADEA'S BIG HAPPY FAMILY", "has_genre", "DRAMA" ], [ "MADEA'S BIG HAPPY FAMILY", "release_year", "2011" ], [ "NATURAL SELECTION", "has_genre", "DRAMA" ], [ "NATURAL SELECTION", "release_year", "2011" ], [ "NEWLYWEDS", "has_genre", "DRAMA" ], [ "NEWLYWEDS", "release_year", "2011" ], [ "OUR IDIOT BROTHER", "has_genre", "DRAMA" ], [ "OUR IDIOT BROTHER", "release_year", "2011" ], [ "RESTLESS", "has_genre", "DRAMA" ], [ "RESTLESS", "release_year", "2011" ], [ "SALMON FISHING IN THE YEMEN", "has_genre", "DRAMA" ], [ "SALMON FISHING IN THE YEMEN", "release_year", "2011" ], [ "SUICIDE ROOM", "has_genre", "DRAMA" ], [ "SUICIDE ROOM", "release_year", "2011" ], [ "TAKE THIS WALTZ", "has_genre", "DRAMA" ], [ "TAKE THIS WALTZ", "release_year", "2011" ], [ "THAT'S WHAT I AM", "has_genre", "DRAMA" ], [ "THAT'S WHAT I AM", "release_year", "2011" ], [ "THE ARTIST", "has_genre", "DRAMA" ], [ "THE ARTIST", "has_tags", "DRAMA" ], [ "THE ARTIST", "release_year", "2011" ], [ "THE CLOWN", "has_genre", "DRAMA" ], [ "THE CLOWN", "release_year", "2011" ], [ "THE DESCENDANTS", "has_genre", "DRAMA" ], [ "THE DESCENDANTS", "has_tags", "DRAMA" ], [ "THE DESCENDANTS", "release_year", "2011" ], [ "THE DILEMMA", "has_genre", "DRAMA" ], [ "THE DILEMMA", "release_year", "2011" ], [ "THE DOUBLE", "directed_by", "MICHAEL BRANDT" ], [ "THE DOUBLE", "release_year", "2011" ], [ "THE DOUBLE", "written_by", "MICHAEL BRANDT" ], [ "THE INTOUCHABLES", "has_genre", "DRAMA" ], [ "THE INTOUCHABLES", "release_year", "2011" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE THREE MUSKETEERS", "release_year", "2011" ], [ "THE WELL-DIGGER'S DAUGHTER", "has_genre", "DRAMA" ], [ "THE WELL-DIGGER'S DAUGHTER", "release_year", "2011" ], [ "THIN ICE", "has_genre", "DRAMA" ], [ "THIN ICE", "release_year", "2011" ], [ "WE BOUGHT A ZOO", "has_genre", "DRAMA" ], [ "WE BOUGHT A ZOO", "release_year", "2011" ], [ "WE HAVE A POPE", "has_genre", "DRAMA" ], [ "WE HAVE A POPE", "release_year", "2011" ], [ "WEEKEND", "has_genre", "DRAMA" ], [ "WEEKEND", "release_year", "2011" ], [ "WIN WIN", "has_genre", "DRAMA" ], [ "WIN WIN", "release_year", "2011" ], [ "YOUNG ADULT", "has_genre", "DRAMA" ], [ "YOUNG ADULT", "has_tags", "DRAMA" ], [ "YOUNG ADULT", "release_year", "2011" ], [ "YOUR SISTER'S SISTER", "has_genre", "DRAMA" ], [ "YOUR SISTER'S SISTER", "release_year", "2011" ], [ "ZINDAGI NA MILEGI DOBARA", "has_genre", "DRAMA" ], [ "ZINDAGI NA MILEGI DOBARA", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24525, 1984 4763, ADVENTURE 524, CHARLIE'S ANGELS 36066, FANTASY 36940, LABYRINTH 18795, MARY CROSBY 21057, QUEST 19740, RYAN ROWE 25296, THE ICE PIRATES 24404, THE NEVERENDING STORY src, edge_attr, dst 524, has_genre, 4763 524, written_by, 19740 36940, has_genre, 4763 36940, has_genre, 36066 36940, has_tags, 4763 36940, has_tags, 36066 36940, has_tags, 21057 25296, release_year, 24525 25296, starred_actors, 18795 24404, has_tags, 36066 24404, has_tags, 21057 24404, release_year, 24525 Question: In what context are MARY CROSBY, QUEST, and RYAN ROWE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MARY CROSBY", "QUEST", "RYAN ROWE" ], "valid_edges": [ [ "CHARLIE'S ANGELS", "has_genre", "ADVENTURE" ], [ "CHARLIE'S ANGELS", "written_by", "RYAN ROWE" ], [ "LABYRINTH", "has_genre", "ADVENTURE" ], [ "LABYRINTH", "has_genre", "FANTASY" ], [ "LABYRINTH", "has_tags", "ADVENTURE" ], [ "LABYRINTH", "has_tags", "FANTASY" ], [ "LABYRINTH", "has_tags", "QUEST" ], [ "THE ICE PIRATES", "release_year", "1984" ], [ "THE ICE PIRATES", "starred_actors", "MARY CROSBY" ], [ "THE NEVERENDING STORY", "has_tags", "FANTASY" ], [ "THE NEVERENDING STORY", "has_tags", "QUEST" ], [ "THE NEVERENDING STORY", "release_year", "1984" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2493, 13 35798, 2010 24480, A NIGHTMARE ON ELM STREET 2201, ANTICHRIST 26267, CINEMATOGRAPHY 27843, CLASH OF THE TITANS 37059, DEATH AT A FUNERAL 13272, DON'T BE AFRAID OF THE DARK 15439, I SPIT ON YOUR GRAVE 29987, LET ME IN 37521, OWEN DAVIS 23228, PUTTY HILL 28729, REMAKE 25463, THE CRAZIES 2599, THE EXPERIMENT 2872, THE GREAT GATSBY 13329, THE KARATE KID 1208, THE NEXT THREE DAYS 17910, THE OMEN src, edge_attr, dst 2493, has_tags, 28729 2493, release_year, 35798 24480, has_tags, 28729 24480, release_year, 35798 2201, has_tags, 26267 27843, has_tags, 28729 27843, release_year, 35798 37059, has_tags, 28729 37059, release_year, 35798 13272, has_tags, 28729 13272, release_year, 35798 15439, has_tags, 28729 15439, release_year, 35798 29987, has_tags, 28729 29987, release_year, 35798 23228, release_year, 35798 25463, has_tags, 28729 25463, release_year, 35798 2599, has_tags, 28729 2599, release_year, 35798 2872, has_tags, 26267 2872, written_by, 37521 13329, has_tags, 28729 13329, release_year, 35798 1208, has_tags, 28729 1208, release_year, 35798 17910, has_tags, 2201 17910, has_tags, 28729 Question: In what context are OWEN DAVIS, PUTTY HILL, and THE OMEN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "OWEN DAVIS", "PUTTY HILL", "THE OMEN" ], "valid_edges": [ [ "13", "has_tags", "REMAKE" ], [ "13", "release_year", "2010" ], [ "A NIGHTMARE ON ELM STREET", "has_tags", "REMAKE" ], [ "A NIGHTMARE ON ELM STREET", "release_year", "2010" ], [ "ANTICHRIST", "has_tags", "CINEMATOGRAPHY" ], [ "CLASH OF THE TITANS", "has_tags", "REMAKE" ], [ "CLASH OF THE TITANS", "release_year", "2010" ], [ "DEATH AT A FUNERAL", "has_tags", "REMAKE" ], [ "DEATH AT A FUNERAL", "release_year", "2010" ], [ "DON'T BE AFRAID OF THE DARK", "has_tags", "REMAKE" ], [ "DON'T BE AFRAID OF THE DARK", "release_year", "2010" ], [ "I SPIT ON YOUR GRAVE", "has_tags", "REMAKE" ], [ "I SPIT ON YOUR GRAVE", "release_year", "2010" ], [ "LET ME IN", "has_tags", "REMAKE" ], [ "LET ME IN", "release_year", "2010" ], [ "PUTTY HILL", "release_year", "2010" ], [ "THE CRAZIES", "has_tags", "REMAKE" ], [ "THE CRAZIES", "release_year", "2010" ], [ "THE EXPERIMENT", "has_tags", "REMAKE" ], [ "THE EXPERIMENT", "release_year", "2010" ], [ "THE GREAT GATSBY", "has_tags", "CINEMATOGRAPHY" ], [ "THE GREAT GATSBY", "written_by", "OWEN DAVIS" ], [ "THE KARATE KID", "has_tags", "REMAKE" ], [ "THE KARATE KID", "release_year", "2010" ], [ "THE NEXT THREE DAYS", "has_tags", "REMAKE" ], [ "THE NEXT THREE DAYS", "release_year", "2010" ], [ "THE OMEN", "has_tags", "ANTICHRIST" ], [ "THE OMEN", "has_tags", "REMAKE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 30665, 7 DAYS IN HAVANA 21289, ENTITY 6221, FRIENDS WITH BENEFITS 11565, GOOD 5722, HUMAN RESOURCES 2722, INSIDE LLEWYN DAVIS 17585, JOHN GOODMAN 14768, JUSTIN TIMBERLAKE 8795, LAURENT CANTET 17451, TROUBLE WITH THE CURVE 16982, WOODY HARRELSON src, edge_attr, dst 658, has_tags, 16982 30665, directed_by, 8795 30665, release_year, 658 30665, written_by, 8795 21289, release_year, 658 6221, has_tags, 14768 6221, has_tags, 16982 6221, starred_actors, 14768 5722, directed_by, 8795 5722, has_tags, 8795 5722, written_by, 8795 2722, has_imdb_rating, 11565 2722, has_tags, 17585 2722, has_tags, 14768 2722, starred_actors, 14768 17451, has_imdb_rating, 11565 17451, has_tags, 17585 17451, has_tags, 14768 17451, release_year, 658 Question: How are ENTITY, HUMAN RESOURCES, and JUSTIN TIMBERLAKE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ENTITY", "HUMAN RESOURCES", "JUSTIN TIMBERLAKE" ], "valid_edges": [ [ "2012", "has_tags", "WOODY HARRELSON" ], [ "7 DAYS IN HAVANA", "directed_by", "LAURENT CANTET" ], [ "7 DAYS IN HAVANA", "release_year", "2012" ], [ "7 DAYS IN HAVANA", "written_by", "LAURENT CANTET" ], [ "ENTITY", "release_year", "2012" ], [ "FRIENDS WITH BENEFITS", "has_tags", "JUSTIN TIMBERLAKE" ], [ "FRIENDS WITH BENEFITS", "has_tags", "WOODY HARRELSON" ], [ "FRIENDS WITH BENEFITS", "starred_actors", "JUSTIN TIMBERLAKE" ], [ "HUMAN RESOURCES", "directed_by", "LAURENT CANTET" ], [ "HUMAN RESOURCES", "has_tags", "LAURENT CANTET" ], [ "HUMAN RESOURCES", "written_by", "LAURENT CANTET" ], [ "INSIDE LLEWYN DAVIS", "has_imdb_rating", "GOOD" ], [ "INSIDE LLEWYN DAVIS", "has_tags", "JOHN GOODMAN" ], [ "INSIDE LLEWYN DAVIS", "has_tags", "JUSTIN TIMBERLAKE" ], [ "INSIDE LLEWYN DAVIS", "starred_actors", "JUSTIN TIMBERLAKE" ], [ "TROUBLE WITH THE CURVE", "has_imdb_rating", "GOOD" ], [ "TROUBLE WITH THE CURVE", "has_tags", "JOHN GOODMAN" ], [ "TROUBLE WITH THE CURVE", "has_tags", "JUSTIN TIMBERLAKE" ], [ "TROUBLE WITH THE CURVE", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 8779, 1945 35798, 2010 29638, ALICE IN WONDERLAND 32479, BEWITCHED 13225, BLITHE SPIRIT 39570, BUNRAKU 27843, CLASH OF THE TITANS 13272, DON'T BE AFRAID OF THE DARK 36066, FANTASY 12817, FRANK BORZAGE 5387, HEREAFTER 13549, HOW TO TRAIN YOUR DRAGON 26991, JONAH HEX 32481, MANNEQUIN 36999, MAUREEN O'HARA 32823, MIRACLE ON 34TH STREET 6952, MY JOY 10344, THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC 38073, THE LAST AIRBENDER 8168, THE SPANISH MAIN 15218, THE SWORD AND THE SORCERER 26036, THE TEMPEST 37516, THE WARRIOR'S WAY 14716, TROLLHUNTER 15472, YOLANDA AND THE THIEF src, edge_attr, dst 29638, has_genre, 36066 29638, has_tags, 36066 29638, release_year, 35798 32479, has_genre, 36066 32479, release_year, 8779 13225, has_genre, 36066 13225, release_year, 8779 39570, has_tags, 36066 39570, release_year, 35798 27843, has_genre, 36066 27843, has_tags, 36066 27843, release_year, 35798 13272, has_genre, 36066 13272, release_year, 35798 5387, has_genre, 36066 5387, release_year, 35798 13549, has_tags, 36066 13549, release_year, 35798 26991, has_genre, 36066 26991, release_year, 35798 32481, directed_by, 12817 32481, has_genre, 36066 32823, has_genre, 36066 32823, has_tags, 36999 32823, starred_actors, 36999 6952, release_year, 35798 10344, has_genre, 36066 10344, release_year, 35798 38073, has_tags, 36066 38073, release_year, 35798 8168, directed_by, 12817 8168, release_year, 8779 8168, starred_actors, 36999 15218, has_genre, 36066 26036, has_genre, 36066 26036, release_year, 35798 37516, has_genre, 36066 37516, release_year, 35798 14716, has_genre, 36066 14716, has_tags, 36066 14716, release_year, 35798 15472, has_genre, 36066 15472, release_year, 8779 Question: For what reason are MY JOY, THE SPANISH MAIN, and THE SWORD AND THE SORCERER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "MY JOY", "THE SPANISH MAIN", "THE SWORD AND THE SORCERER" ], "valid_edges": [ [ "ALICE IN WONDERLAND", "has_genre", "FANTASY" ], [ "ALICE IN WONDERLAND", "has_tags", "FANTASY" ], [ "ALICE IN WONDERLAND", "release_year", "2010" ], [ "BEWITCHED", "has_genre", "FANTASY" ], [ "BEWITCHED", "release_year", "1945" ], [ "BLITHE SPIRIT", "has_genre", "FANTASY" ], [ "BLITHE SPIRIT", "release_year", "1945" ], [ "BUNRAKU", "has_tags", "FANTASY" ], [ "BUNRAKU", "release_year", "2010" ], [ "CLASH OF THE TITANS", "has_genre", "FANTASY" ], [ "CLASH OF THE TITANS", "has_tags", "FANTASY" ], [ "CLASH OF THE TITANS", "release_year", "2010" ], [ "DON'T BE AFRAID OF THE DARK", "has_genre", "FANTASY" ], [ "DON'T BE AFRAID OF THE DARK", "release_year", "2010" ], [ "HEREAFTER", "has_genre", "FANTASY" ], [ "HEREAFTER", "release_year", "2010" ], [ "HOW TO TRAIN YOUR DRAGON", "has_tags", "FANTASY" ], [ "HOW TO TRAIN YOUR DRAGON", "release_year", "2010" ], [ "JONAH HEX", "has_genre", "FANTASY" ], [ "JONAH HEX", "release_year", "2010" ], [ "MANNEQUIN", "directed_by", "FRANK BORZAGE" ], [ "MANNEQUIN", "has_genre", "FANTASY" ], [ "MIRACLE ON 34TH STREET", "has_genre", "FANTASY" ], [ "MIRACLE ON 34TH STREET", "has_tags", "MAUREEN O'HARA" ], [ "MIRACLE ON 34TH STREET", "starred_actors", "MAUREEN O'HARA" ], [ "MY JOY", "release_year", "2010" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "has_genre", "FANTASY" ], [ "THE EXTRAORDINARY ADVENTURES OF ADÈLE BLANC-SEC", "release_year", "2010" ], [ "THE LAST AIRBENDER", "has_tags", "FANTASY" ], [ "THE LAST AIRBENDER", "release_year", "2010" ], [ "THE SPANISH MAIN", "directed_by", "FRANK BORZAGE" ], [ "THE SPANISH MAIN", "release_year", "1945" ], [ "THE SPANISH MAIN", "starred_actors", "MAUREEN O'HARA" ], [ "THE SWORD AND THE SORCERER", "has_genre", "FANTASY" ], [ "THE TEMPEST", "has_genre", "FANTASY" ], [ "THE TEMPEST", "release_year", "2010" ], [ "THE WARRIOR'S WAY", "has_genre", "FANTASY" ], [ "THE WARRIOR'S WAY", "release_year", "2010" ], [ "TROLLHUNTER", "has_genre", "FANTASY" ], [ "TROLLHUNTER", "has_tags", "FANTASY" ], [ "TROLLHUNTER", "release_year", "2010" ], [ "YOLANDA AND THE THIEF", "has_genre", "FANTASY" ], [ "YOLANDA AND THE THIEF", "release_year", "1945" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9177, 1956 29424, 2011 37908, AFRICAN CATS 39613, BEAUTY DAY 26510, BORN TO BE WILD 29342, BULLY 17035, DEBTOCRACY 12841, DOCUMENTARY 1519, DREAMS OF A LIFE 39366, HAPPY 28468, MAGIC TRIP 7839, MISS REPRESENTATION 23408, OF TIME AND THE CITY 29488, ONE DAY 35524, ONE LIFE 2108, PEARL JAM TWENTY 29086, PINA 10984, REVENGE OF THE ELECTRIC CAR 12599, SURVIVING PROGRESS 2588, THE AMBASSADOR 11259, THE BLACK POWER MIXTAPE 1967-1975 20837, THE CAPTAINS 20969, THE FLAT 30700, THE INTERRUPTERS 38461, THE LAST LIONS 27444, THE LAST MOUNTAIN 39587, THE OTHER F WORD 30593, THE VIOLENT YEARS 29052, THESE AMAZING SHADOWS 36765, THIS IS NOT A FILM 8476, TOUTE LA MÉMOIRE DU MONDE 16214, UNLAWFUL KILLING 4896, WHORES' GLORY 9056, YOU'VE BEEN TRUMPED src, edge_attr, dst 37908, has_genre, 12841 37908, release_year, 29424 39613, has_genre, 12841 39613, release_year, 29424 26510, has_genre, 12841 26510, release_year, 29424 29342, has_genre, 12841 29342, release_year, 29424 17035, has_genre, 12841 17035, release_year, 29424 1519, has_genre, 12841 1519, release_year, 29424 39366, has_genre, 12841 39366, has_tags, 12841 39366, release_year, 29424 28468, has_genre, 12841 28468, release_year, 29424 7839, has_genre, 12841 7839, release_year, 29424 23408, has_genre, 12841 29488, release_year, 29424 35524, has_genre, 12841 35524, release_year, 29424 2108, has_genre, 12841 2108, release_year, 29424 29086, has_genre, 12841 29086, has_tags, 12841 29086, release_year, 29424 10984, has_genre, 12841 10984, release_year, 29424 12599, has_genre, 12841 12599, has_tags, 12841 12599, release_year, 29424 2588, has_genre, 12841 2588, release_year, 29424 11259, has_genre, 12841 11259, release_year, 29424 20837, has_genre, 12841 20837, release_year, 29424 20969, has_genre, 12841 20969, release_year, 29424 30700, has_genre, 12841 30700, release_year, 29424 38461, has_genre, 12841 38461, release_year, 29424 27444, has_genre, 12841 27444, release_year, 29424 39587, has_genre, 12841 39587, release_year, 29424 30593, release_year, 9177 29052, has_genre, 12841 29052, release_year, 29424 36765, has_genre, 12841 36765, release_year, 29424 8476, has_genre, 12841 8476, release_year, 9177 16214, has_genre, 12841 16214, release_year, 29424 4896, has_genre, 12841 4896, has_tags, 12841 4896, release_year, 29424 9056, has_genre, 12841 9056, release_year, 29424 Question: For what reason are OF TIME AND THE CITY, ONE DAY, and THE VIOLENT YEARS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "OF TIME AND THE CITY", "ONE DAY", "THE VIOLENT YEARS" ], "valid_edges": [ [ "AFRICAN CATS", "has_genre", "DOCUMENTARY" ], [ "AFRICAN CATS", "release_year", "2011" ], [ "BEAUTY DAY", "has_genre", "DOCUMENTARY" ], [ "BEAUTY DAY", "release_year", "2011" ], [ "BORN TO BE WILD", "has_genre", "DOCUMENTARY" ], [ "BORN TO BE WILD", "release_year", "2011" ], [ "BULLY", "has_genre", "DOCUMENTARY" ], [ "BULLY", "release_year", "2011" ], [ "DEBTOCRACY", "has_genre", "DOCUMENTARY" ], [ "DEBTOCRACY", "release_year", "2011" ], [ "DREAMS OF A LIFE", "has_genre", "DOCUMENTARY" ], [ "DREAMS OF A LIFE", "release_year", "2011" ], [ "HAPPY", "has_genre", "DOCUMENTARY" ], [ "HAPPY", "has_tags", "DOCUMENTARY" ], [ "HAPPY", "release_year", "2011" ], [ "MAGIC TRIP", "has_genre", "DOCUMENTARY" ], [ "MAGIC TRIP", "release_year", "2011" ], [ "MISS REPRESENTATION", "has_genre", "DOCUMENTARY" ], [ "MISS REPRESENTATION", "release_year", "2011" ], [ "OF TIME AND THE CITY", "has_genre", "DOCUMENTARY" ], [ "ONE DAY", "release_year", "2011" ], [ "ONE LIFE", "has_genre", "DOCUMENTARY" ], [ "ONE LIFE", "release_year", "2011" ], [ "PEARL JAM TWENTY", "has_genre", "DOCUMENTARY" ], [ "PEARL JAM TWENTY", "release_year", "2011" ], [ "PINA", "has_genre", "DOCUMENTARY" ], [ "PINA", "has_tags", "DOCUMENTARY" ], [ "PINA", "release_year", "2011" ], [ "REVENGE OF THE ELECTRIC CAR", "has_genre", "DOCUMENTARY" ], [ "REVENGE OF THE ELECTRIC CAR", "release_year", "2011" ], [ "SURVIVING PROGRESS", "has_genre", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "has_tags", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "release_year", "2011" ], [ "THE AMBASSADOR", "has_genre", "DOCUMENTARY" ], [ "THE AMBASSADOR", "release_year", "2011" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "has_genre", "DOCUMENTARY" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "release_year", "2011" ], [ "THE CAPTAINS", "has_genre", "DOCUMENTARY" ], [ "THE CAPTAINS", "release_year", "2011" ], [ "THE FLAT", "has_genre", "DOCUMENTARY" ], [ "THE FLAT", "release_year", "2011" ], [ "THE INTERRUPTERS", "has_genre", "DOCUMENTARY" ], [ "THE INTERRUPTERS", "release_year", "2011" ], [ "THE LAST LIONS", "has_genre", "DOCUMENTARY" ], [ "THE LAST LIONS", "release_year", "2011" ], [ "THE LAST MOUNTAIN", "has_genre", "DOCUMENTARY" ], [ "THE LAST MOUNTAIN", "release_year", "2011" ], [ "THE OTHER F WORD", "has_genre", "DOCUMENTARY" ], [ "THE OTHER F WORD", "release_year", "2011" ], [ "THE VIOLENT YEARS", "release_year", "1956" ], [ "THESE AMAZING SHADOWS", "has_genre", "DOCUMENTARY" ], [ "THESE AMAZING SHADOWS", "release_year", "2011" ], [ "THIS IS NOT A FILM", "has_genre", "DOCUMENTARY" ], [ "THIS IS NOT A FILM", "release_year", "2011" ], [ "TOUTE LA MÉMOIRE DU MONDE", "has_genre", "DOCUMENTARY" ], [ "TOUTE LA MÉMOIRE DU MONDE", "release_year", "1956" ], [ "UNLAWFUL KILLING", "has_genre", "DOCUMENTARY" ], [ "UNLAWFUL KILLING", "release_year", "2011" ], [ "WHORES' GLORY", "has_genre", "DOCUMENTARY" ], [ "WHORES' GLORY", "has_tags", "DOCUMENTARY" ], [ "WHORES' GLORY", "release_year", "2011" ], [ "YOU'VE BEEN TRUMPED", "has_genre", "DOCUMENTARY" ], [ "YOU'VE BEEN TRUMPED", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 36647, 8 WOMEN 11957, 9 DEAD GAY GUYS 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 17111, ALI G INDAHOUSE 22569, ALL ABOUT THE BENJAMINS 16113, ANALYZE THAT 35314, AUSTIN POWERS IN GOLDMEMBER 29535, AVENGING ANGELO 23899, BAD COMPANY 36819, BARBERSHOP 19159, BEER FOR MY HORSES 15433, BEND IT LIKE BECKHAM 39619, BIG FAT LIAR 8732, BIG TROUBLE 27128, BOAT TRIP 9565, BOYS AND GIRLS 32620, BUBBA HO-TEP 14572, BUYING THE COW 27929, CABIN FEVER 23286, CARNAGE 20073, CHERISH 10349, CHICAGO 32644, CHINESE ODYSSEY 2002 30463, COMEDY 21391, CRACKERJACK 30019, CROSSROADS 21730, DAY OF THE WACKO 14292, DEAD IN THE WATER 19179, DEATH TO SMOOCHY 21079, DIRTY DEEDS 25651, DUMMY 26815, EIGHT CRAZY NIGHTS 38543, EIGHT LEGGED FREAKS 27539, FRANK MCKLUSKY, C.I. 29241, FRIDAY AFTER NEXT 10990, HEARTLANDS 3829, HERO 15629, HOME ALONE 4 22069, I SPY 27919, I'M WITH LUCY 16371, ICE AGE 17197, IGBY GOES DOWN 33001, JUST A KISS 2204, JUWANNA MANN 32010, KISS THE BRIDE 12137, LIFE OR SOMETHING LIKE IT 28832, LIFE WITHOUT DICK 16155, LOVE LIZA 9812, MAID IN MANHATTAN 4270, MEN WITH BROOMS 39368, MICHAEL SALOMON 36083, MIRANDA 20803, MR. DEEDS 22064, MY BIG FAT GREEK WEDDING 4887, MY LEFT EYE SEES GHOSTS 35262, MY MOTHER LIKES WOMEN 35794, NOVO 1493, NOW YOU KNOW 2721, OCCIDENT 4582, ONCE UPON A TIME IN THE MIDLANDS 37178, ORANGE COUNTY 27117, PASSIONADA 9976, PIPE DREAM 3688, PUMPKIN 34602, PUNCH-DRUNK LOVE 21890, R.S.V.P. 25769, ROGER DODGER 12987, SCOOBY-DOO 19244, SERVING SARA 6603, SEX IS COMEDY 26261, SHOWTIME 15043, SLACKERS 25151, SNOW DOGS 24961, SORORITY BOYS 35843, SPUN 5170, STEALING HARVARD 15100, SUPER SUCKER 9276, SWEET HOME ALABAMA 26790, SWEPT AWAY 36316, THE ADVENTURES OF PLUTO NASH 2316, THE ANARCHIST COOKBOOK 304, THE BANGER SISTERS 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 914, THE GOOD GIRL 26531, THE GURU 24302, THE HOT CHICK 13534, THE IMPORTANCE OF BEING EARNEST 2147, THE MAN WITHOUT A PAST 6908, THE MASTER OF DISGUISE 295, THE NEW GUY 1192, THE ONE AND ONLY 31401, THE RULES OF ATTRACTION 7052, THE SWEETEST THING 34172, THE TUXEDO 10720, TRIGGERMEN 9612, TWO WEEKS NOTICE 13214, UNCONDITIONAL LOVE 16991, UNDERCOVER BROTHER 21576, WAKING UP IN RENO 37568, WELCOME TO COLLINWOOD 39802, WHEN IN ROME src, edge_attr, dst 4310, has_genre, 30463 4310, release_year, 35935 9408, has_genre, 30463 9408, has_tags, 30463 9408, release_year, 35935 36647, has_genre, 30463 36647, release_year, 35935 11957, has_genre, 30463 11957, release_year, 35935 6008, has_genre, 30463 6008, has_tags, 30463 6008, release_year, 35935 37599, has_genre, 30463 37599, has_tags, 30463 37599, release_year, 35935 17111, has_genre, 30463 17111, release_year, 35935 22569, has_genre, 30463 22569, has_tags, 30463 22569, release_year, 35935 16113, has_genre, 30463 16113, has_tags, 30463 16113, release_year, 35935 35314, has_genre, 30463 35314, has_tags, 30463 35314, release_year, 35935 29535, has_genre, 30463 29535, release_year, 35935 23899, has_genre, 30463 23899, release_year, 35935 36819, has_genre, 30463 36819, release_year, 35935 19159, directed_by, 39368 19159, has_genre, 30463 15433, has_genre, 30463 15433, release_year, 35935 39619, has_genre, 30463 39619, release_year, 35935 8732, has_genre, 30463 8732, release_year, 35935 27128, has_genre, 30463 27128, release_year, 35935 9565, has_genre, 30463 32620, has_genre, 30463 32620, has_tags, 30463 32620, release_year, 35935 14572, has_genre, 30463 14572, release_year, 35935 27929, has_genre, 30463 27929, release_year, 35935 23286, has_genre, 30463 23286, release_year, 35935 20073, has_genre, 30463 20073, release_year, 35935 10349, has_genre, 30463 10349, release_year, 35935 32644, has_genre, 30463 32644, release_year, 35935 21391, has_genre, 30463 21391, release_year, 35935 30019, has_genre, 30463 30019, release_year, 35935 21730, has_genre, 30463 21730, release_year, 35935 14292, release_year, 35935 19179, has_genre, 30463 19179, release_year, 35935 21079, has_genre, 30463 21079, has_tags, 30463 21079, release_year, 35935 25651, has_genre, 30463 25651, release_year, 35935 26815, has_genre, 30463 26815, release_year, 35935 38543, has_genre, 30463 38543, release_year, 35935 27539, has_genre, 30463 27539, release_year, 35935 29241, has_genre, 30463 29241, release_year, 35935 10990, has_genre, 30463 10990, release_year, 35935 3829, has_genre, 30463 3829, release_year, 35935 15629, has_genre, 30463 15629, release_year, 35935 22069, has_genre, 30463 22069, has_tags, 30463 22069, release_year, 35935 27919, has_genre, 30463 27919, release_year, 35935 16371, has_genre, 30463 16371, has_tags, 30463 16371, release_year, 35935 17197, has_genre, 30463 17197, release_year, 35935 33001, has_genre, 30463 33001, release_year, 35935 2204, has_genre, 30463 2204, release_year, 35935 32010, has_genre, 30463 32010, release_year, 35935 12137, has_genre, 30463 12137, release_year, 35935 28832, has_genre, 30463 28832, release_year, 35935 16155, has_genre, 30463 16155, release_year, 35935 9812, has_genre, 30463 9812, release_year, 35935 4270, has_genre, 30463 4270, release_year, 35935 36083, has_genre, 30463 36083, release_year, 35935 20803, has_genre, 30463 20803, release_year, 35935 22064, has_genre, 30463 22064, has_tags, 30463 22064, release_year, 35935 4887, has_genre, 30463 4887, release_year, 35935 35262, has_genre, 30463 35262, release_year, 35935 35794, has_genre, 30463 35794, release_year, 35935 1493, has_genre, 30463 1493, release_year, 35935 2721, has_genre, 30463 2721, release_year, 35935 4582, has_genre, 30463 4582, release_year, 35935 37178, has_genre, 30463 37178, release_year, 35935 27117, has_genre, 30463 27117, release_year, 35935 9976, has_genre, 30463 9976, release_year, 35935 3688, has_genre, 30463 3688, release_year, 35935 34602, has_genre, 30463 34602, has_tags, 30463 34602, release_year, 35935 21890, has_genre, 30463 21890, release_year, 35935 25769, has_genre, 30463 25769, release_year, 35935 12987, has_genre, 30463 12987, release_year, 35935 19244, has_genre, 30463 19244, release_year, 35935 6603, has_genre, 30463 6603, release_year, 35935 26261, has_genre, 30463 26261, release_year, 35935 15043, has_genre, 30463 15043, release_year, 35935 25151, has_genre, 30463 25151, release_year, 35935 24961, has_genre, 30463 24961, release_year, 35935 35843, has_genre, 30463 35843, release_year, 35935 5170, has_genre, 30463 5170, release_year, 35935 15100, has_genre, 30463 15100, release_year, 35935 9276, has_genre, 30463 9276, release_year, 35935 26790, has_genre, 30463 26790, release_year, 35935 36316, has_genre, 30463 36316, release_year, 35935 2316, has_genre, 30463 2316, release_year, 35935 304, has_genre, 30463 304, release_year, 35935 11696, has_genre, 30463 11696, release_year, 35935 3324, has_genre, 30463 3324, release_year, 35935 914, has_genre, 30463 914, release_year, 35935 26531, has_genre, 30463 26531, release_year, 35935 24302, has_genre, 30463 24302, has_tags, 30463 24302, release_year, 35935 13534, has_genre, 30463 13534, release_year, 35935 2147, has_genre, 30463 2147, release_year, 35935 6908, has_genre, 30463 6908, release_year, 35935 295, has_genre, 30463 295, release_year, 35935 1192, has_genre, 30463 1192, release_year, 35935 31401, has_genre, 30463 31401, release_year, 35935 7052, has_genre, 30463 7052, has_tags, 30463 7052, release_year, 35935 34172, has_genre, 30463 34172, has_tags, 30463 34172, release_year, 35935 10720, has_genre, 30463 10720, release_year, 35935 9612, has_genre, 30463 9612, release_year, 35935 13214, has_genre, 30463 13214, release_year, 35935 16991, has_genre, 30463 16991, release_year, 35935 21576, has_genre, 30463 21576, release_year, 35935 37568, has_genre, 30463 37568, has_tags, 30463 37568, release_year, 35935 39802, has_genre, 30463 39802, release_year, 35935 Question: How are BOYS AND GIRLS, DEAD IN THE WATER, and MICHAEL SALOMON related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BOYS AND GIRLS", "DEAD IN THE WATER", "MICHAEL SALOMON" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_genre", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "release_year", "2002" ], [ "9 DEAD GAY GUYS", "has_genre", "COMEDY" ], [ "9 DEAD GAY GUYS", "release_year", "2002" ], [ "ABOUT A BOY", "has_genre", "COMEDY" ], [ "ABOUT A BOY", "has_tags", "COMEDY" ], [ "ABOUT A BOY", "release_year", "2002" ], [ "ABOUT SCHMIDT", "has_genre", "COMEDY" ], [ "ABOUT SCHMIDT", "has_tags", "COMEDY" ], [ "ABOUT SCHMIDT", "release_year", "2002" ], [ "ALI G INDAHOUSE", "has_genre", "COMEDY" ], [ "ALI G INDAHOUSE", "release_year", "2002" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "release_year", "2002" ], [ "ANALYZE THAT", "has_genre", "COMEDY" ], [ "ANALYZE THAT", "has_tags", "COMEDY" ], [ "ANALYZE THAT", "release_year", "2002" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_genre", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_tags", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "release_year", "2002" ], [ "AVENGING ANGELO", "has_genre", "COMEDY" ], [ "AVENGING ANGELO", "release_year", "2002" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "release_year", "2002" ], [ "BARBERSHOP", "has_genre", "COMEDY" ], [ "BARBERSHOP", "release_year", "2002" ], [ "BEER FOR MY HORSES", "directed_by", "MICHAEL SALOMON" ], [ "BEER FOR MY HORSES", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "release_year", "2002" ], [ "BIG FAT LIAR", "has_genre", "COMEDY" ], [ "BIG FAT LIAR", "release_year", "2002" ], [ "BIG TROUBLE", "has_genre", "COMEDY" ], [ "BIG TROUBLE", "release_year", "2002" ], [ "BOAT TRIP", "has_genre", "COMEDY" ], [ "BOAT TRIP", "release_year", "2002" ], [ "BOYS AND GIRLS", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_tags", "COMEDY" ], [ "BUBBA HO-TEP", "release_year", "2002" ], [ "BUYING THE COW", "has_genre", "COMEDY" ], [ "BUYING THE COW", "release_year", "2002" ], [ "CABIN FEVER", "has_genre", "COMEDY" ], [ "CABIN FEVER", "release_year", "2002" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "release_year", "2002" ], [ "CHERISH", "has_genre", "COMEDY" ], [ "CHERISH", "release_year", "2002" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "release_year", "2002" ], [ "CHINESE ODYSSEY 2002", "has_genre", "COMEDY" ], [ "CHINESE ODYSSEY 2002", "release_year", "2002" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "2002" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "release_year", "2002" ], [ "DAY OF THE WACKO", "has_genre", "COMEDY" ], [ "DAY OF THE WACKO", "release_year", "2002" ], [ "DEAD IN THE WATER", "release_year", "2002" ], [ "DEATH TO SMOOCHY", "has_genre", "COMEDY" ], [ "DEATH TO SMOOCHY", "release_year", "2002" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIRTY DEEDS", "release_year", "2002" ], [ "DUMMY", "has_genre", "COMEDY" ], [ "DUMMY", "release_year", "2002" ], [ "EIGHT CRAZY NIGHTS", "has_genre", "COMEDY" ], [ "EIGHT CRAZY NIGHTS", "release_year", "2002" ], [ "EIGHT LEGGED FREAKS", "has_genre", "COMEDY" ], [ "EIGHT LEGGED FREAKS", "release_year", "2002" ], [ "FRANK MCKLUSKY, C.I.", "has_genre", "COMEDY" ], [ "FRANK MCKLUSKY, C.I.", "release_year", "2002" ], [ "FRIDAY AFTER NEXT", "has_genre", "COMEDY" ], [ "FRIDAY AFTER NEXT", "release_year", "2002" ], [ "HEARTLANDS", "has_genre", "COMEDY" ], [ "HEARTLANDS", "release_year", "2002" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "release_year", "2002" ], [ "HOME ALONE 4", "has_genre", "COMEDY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "I SPY", "has_genre", "COMEDY" ], [ "I SPY", "has_tags", "COMEDY" ], [ "I SPY", "release_year", "2002" ], [ "I'M WITH LUCY", "has_genre", "COMEDY" ], [ "I'M WITH LUCY", "release_year", "2002" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "release_year", "2002" ], [ "IGBY GOES DOWN", "has_genre", "COMEDY" ], [ "IGBY GOES DOWN", "release_year", "2002" ], [ "JUST A KISS", "has_genre", "COMEDY" ], [ "JUST A KISS", "release_year", "2002" ], [ "JUWANNA MANN", "has_genre", "COMEDY" ], [ "JUWANNA MANN", "release_year", "2002" ], [ "KISS THE BRIDE", "has_genre", "COMEDY" ], [ "KISS THE BRIDE", "release_year", "2002" ], [ "LIFE OR SOMETHING LIKE IT", "has_genre", "COMEDY" ], [ "LIFE OR SOMETHING LIKE IT", "release_year", "2002" ], [ "LIFE WITHOUT DICK", "has_genre", "COMEDY" ], [ "LIFE WITHOUT DICK", "release_year", "2002" ], [ "LOVE LIZA", "has_genre", "COMEDY" ], [ "LOVE LIZA", "release_year", "2002" ], [ "MAID IN MANHATTAN", "has_genre", "COMEDY" ], [ "MAID IN MANHATTAN", "release_year", "2002" ], [ "MEN WITH BROOMS", "has_genre", "COMEDY" ], [ "MEN WITH BROOMS", "release_year", "2002" ], [ "MIRANDA", "has_genre", "COMEDY" ], [ "MIRANDA", "release_year", "2002" ], [ "MR. DEEDS", "has_genre", "COMEDY" ], [ "MR. DEEDS", "release_year", "2002" ], [ "MY BIG FAT GREEK WEDDING", "has_genre", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "has_tags", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "release_year", "2002" ], [ "MY LEFT EYE SEES GHOSTS", "has_genre", "COMEDY" ], [ "MY LEFT EYE SEES GHOSTS", "release_year", "2002" ], [ "MY MOTHER LIKES WOMEN", "has_genre", "COMEDY" ], [ "MY MOTHER LIKES WOMEN", "release_year", "2002" ], [ "NOVO", "has_genre", "COMEDY" ], [ "NOVO", "release_year", "2002" ], [ "NOW YOU KNOW", "has_genre", "COMEDY" ], [ "NOW YOU KNOW", "release_year", "2002" ], [ "OCCIDENT", "has_genre", "COMEDY" ], [ "OCCIDENT", "release_year", "2002" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "has_genre", "COMEDY" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "release_year", "2002" ], [ "ORANGE COUNTY", "has_genre", "COMEDY" ], [ "ORANGE COUNTY", "release_year", "2002" ], [ "PASSIONADA", "has_genre", "COMEDY" ], [ "PASSIONADA", "release_year", "2002" ], [ "PIPE DREAM", "has_genre", "COMEDY" ], [ "PIPE DREAM", "release_year", "2002" ], [ "PUMPKIN", "has_genre", "COMEDY" ], [ "PUMPKIN", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "R.S.V.P.", "has_genre", "COMEDY" ], [ "R.S.V.P.", "release_year", "2002" ], [ "ROGER DODGER", "has_genre", "COMEDY" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SCOOBY-DOO", "has_genre", "COMEDY" ], [ "SCOOBY-DOO", "release_year", "2002" ], [ "SERVING SARA", "has_genre", "COMEDY" ], [ "SERVING SARA", "release_year", "2002" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "SHOWTIME", "has_genre", "COMEDY" ], [ "SHOWTIME", "release_year", "2002" ], [ "SLACKERS", "has_genre", "COMEDY" ], [ "SLACKERS", "release_year", "2002" ], [ "SNOW DOGS", "has_genre", "COMEDY" ], [ "SNOW DOGS", "release_year", "2002" ], [ "SORORITY BOYS", "has_genre", "COMEDY" ], [ "SORORITY BOYS", "release_year", "2002" ], [ "SPUN", "has_genre", "COMEDY" ], [ "SPUN", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SUPER SUCKER", "has_genre", "COMEDY" ], [ "SUPER SUCKER", "release_year", "2002" ], [ "SWEET HOME ALABAMA", "has_genre", "COMEDY" ], [ "SWEET HOME ALABAMA", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "THE ADVENTURES OF PLUTO NASH", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PLUTO NASH", "release_year", "2002" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "COMEDY" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BANGER SISTERS", "has_genre", "COMEDY" ], [ "THE BANGER SISTERS", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "COMEDY" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "COMEDY" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "release_year", "2002" ], [ "THE GURU", "has_genre", "COMEDY" ], [ "THE GURU", "release_year", "2002" ], [ "THE HOT CHICK", "has_genre", "COMEDY" ], [ "THE HOT CHICK", "has_tags", "COMEDY" ], [ "THE HOT CHICK", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "COMEDY" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE MAN WITHOUT A PAST", "has_genre", "COMEDY" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE MASTER OF DISGUISE", "has_genre", "COMEDY" ], [ "THE MASTER OF DISGUISE", "release_year", "2002" ], [ "THE NEW GUY", "has_genre", "COMEDY" ], [ "THE NEW GUY", "release_year", "2002" ], [ "THE ONE AND ONLY", "has_genre", "COMEDY" ], [ "THE ONE AND ONLY", "release_year", "2002" ], [ "THE RULES OF ATTRACTION", "has_genre", "COMEDY" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SWEETEST THING", "has_genre", "COMEDY" ], [ "THE SWEETEST THING", "has_tags", "COMEDY" ], [ "THE SWEETEST THING", "release_year", "2002" ], [ "THE TUXEDO", "has_genre", "COMEDY" ], [ "THE TUXEDO", "has_tags", "COMEDY" ], [ "THE TUXEDO", "release_year", "2002" ], [ "TRIGGERMEN", "has_genre", "COMEDY" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "TWO WEEKS NOTICE", "has_genre", "COMEDY" ], [ "TWO WEEKS NOTICE", "release_year", "2002" ], [ "UNCONDITIONAL LOVE", "has_genre", "COMEDY" ], [ "UNCONDITIONAL LOVE", "release_year", "2002" ], [ "UNDERCOVER BROTHER", "has_genre", "COMEDY" ], [ "UNDERCOVER BROTHER", "release_year", "2002" ], [ "WAKING UP IN RENO", "has_genre", "COMEDY" ], [ "WAKING UP IN RENO", "release_year", "2002" ], [ "WELCOME TO COLLINWOOD", "has_genre", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "has_tags", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "release_year", "2002" ], [ "WHEN IN ROME", "has_genre", "COMEDY" ], [ "WHEN IN ROME", "release_year", "2002" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15374, 2005 4763, ADVENTURE 5155, DANNY DYER 7498, FLIGHTPLAN 37073, MRS. PALFREY AT THE CLAREMONT 24949, NICK LOVE 24746, NOAH RINGER 13539, OUTLAW 21756, RUPERT FRIEND 11043, SEAN BEAN 29129, THE ADVENTURES OF ROBIN HOOD 35282, THE BUSINESS 32465, THE FOOTBALL FACTORY 38073, THE LAST AIRBENDER 4786, THE WILLOW TREE src, edge_attr, dst 7498, release_year, 15374 7498, starred_actors, 11043 37073, release_year, 15374 37073, starred_actors, 21756 13539, directed_by, 24949 13539, starred_actors, 5155 13539, starred_actors, 21756 13539, starred_actors, 11043 13539, written_by, 24949 29129, has_genre, 4763 29129, has_tags, 13539 35282, directed_by, 24949 35282, release_year, 15374 35282, starred_actors, 5155 35282, written_by, 24949 32465, directed_by, 24949 32465, starred_actors, 5155 32465, written_by, 24949 38073, has_genre, 4763 38073, starred_actors, 24746 4786, release_year, 15374 Question: In what context are NOAH RINGER, OUTLAW, and THE WILLOW TREE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "NOAH RINGER", "OUTLAW", "THE WILLOW TREE" ], "valid_edges": [ [ "FLIGHTPLAN", "release_year", "2005" ], [ "FLIGHTPLAN", "starred_actors", "SEAN BEAN" ], [ "MRS. PALFREY AT THE CLAREMONT", "release_year", "2005" ], [ "MRS. PALFREY AT THE CLAREMONT", "starred_actors", "RUPERT FRIEND" ], [ "OUTLAW", "directed_by", "NICK LOVE" ], [ "OUTLAW", "starred_actors", "DANNY DYER" ], [ "OUTLAW", "starred_actors", "RUPERT FRIEND" ], [ "OUTLAW", "starred_actors", "SEAN BEAN" ], [ "OUTLAW", "written_by", "NICK LOVE" ], [ "THE ADVENTURES OF ROBIN HOOD", "has_genre", "ADVENTURE" ], [ "THE ADVENTURES OF ROBIN HOOD", "has_tags", "OUTLAW" ], [ "THE BUSINESS", "directed_by", "NICK LOVE" ], [ "THE BUSINESS", "release_year", "2005" ], [ "THE BUSINESS", "starred_actors", "DANNY DYER" ], [ "THE BUSINESS", "written_by", "NICK LOVE" ], [ "THE FOOTBALL FACTORY", "directed_by", "NICK LOVE" ], [ "THE FOOTBALL FACTORY", "starred_actors", "DANNY DYER" ], [ "THE FOOTBALL FACTORY", "written_by", "NICK LOVE" ], [ "THE LAST AIRBENDER", "has_genre", "ADVENTURE" ], [ "THE LAST AIRBENDER", "starred_actors", "NOAH RINGER" ], [ "THE WILLOW TREE", "release_year", "2005" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 9377, 2014 5906, ANDREW WIGHT 31095, BRIDESMAIDS 33773, BÉBÉ'S KIDS 13812, CALVARY 33403, CHRIS O'DOWD 30463, COMEDY 36212, DRAMA 26412, FRIENDS WITH KIDS 17037, HOUSE PARTY 22972, MAYA RUDOLPH 29527, MELISSA MCCARTHY 22173, REGINALD HUDLIN 29173, ROBIN HARRIS 7209, SANCTUM 19715, ST. VINCENT src, edge_attr, dst 31095, has_genre, 30463 31095, has_tags, 33403 31095, has_tags, 30463 31095, has_tags, 22972 31095, has_tags, 29527 31095, release_year, 29424 31095, starred_actors, 22972 33773, has_genre, 30463 33773, starred_actors, 29173 33773, written_by, 22173 33773, written_by, 29173 13812, has_genre, 36212 13812, has_tags, 33403 13812, release_year, 9377 13812, starred_actors, 33403 26412, has_genre, 30463 26412, has_tags, 33403 26412, has_tags, 22972 26412, release_year, 29424 26412, starred_actors, 33403 26412, starred_actors, 22972 17037, directed_by, 22173 17037, has_genre, 30463 17037, has_tags, 22173 17037, starred_actors, 29173 17037, written_by, 22173 7209, has_genre, 36212 7209, release_year, 29424 7209, written_by, 5906 19715, has_genre, 30463 19715, has_genre, 36212 19715, has_tags, 33403 19715, has_tags, 29527 19715, release_year, 9377 19715, starred_actors, 33403 19715, starred_actors, 29527 Question: In what context are ANDREW WIGHT, CHRIS O'DOWD, and ROBIN HARRIS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANDREW WIGHT", "CHRIS O'DOWD", "ROBIN HARRIS" ], "valid_edges": [ [ "BRIDESMAIDS", "has_genre", "COMEDY" ], [ "BRIDESMAIDS", "has_tags", "CHRIS O'DOWD" ], [ "BRIDESMAIDS", "has_tags", "COMEDY" ], [ "BRIDESMAIDS", "has_tags", "MAYA RUDOLPH" ], [ "BRIDESMAIDS", "has_tags", "MELISSA MCCARTHY" ], [ "BRIDESMAIDS", "release_year", "2011" ], [ "BRIDESMAIDS", "starred_actors", "MAYA RUDOLPH" ], [ "BÉBÉ'S KIDS", "has_genre", "COMEDY" ], [ "BÉBÉ'S KIDS", "starred_actors", "ROBIN HARRIS" ], [ "BÉBÉ'S KIDS", "written_by", "REGINALD HUDLIN" ], [ "BÉBÉ'S KIDS", "written_by", "ROBIN HARRIS" ], [ "CALVARY", "has_genre", "DRAMA" ], [ "CALVARY", "has_tags", "CHRIS O'DOWD" ], [ "CALVARY", "release_year", "2014" ], [ "CALVARY", "starred_actors", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "has_genre", "COMEDY" ], [ "FRIENDS WITH KIDS", "has_tags", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "has_tags", "MAYA RUDOLPH" ], [ "FRIENDS WITH KIDS", "release_year", "2011" ], [ "FRIENDS WITH KIDS", "starred_actors", "CHRIS O'DOWD" ], [ "FRIENDS WITH KIDS", "starred_actors", "MAYA RUDOLPH" ], [ "HOUSE PARTY", "directed_by", "REGINALD HUDLIN" ], [ "HOUSE PARTY", "has_genre", "COMEDY" ], [ "HOUSE PARTY", "has_tags", "REGINALD HUDLIN" ], [ "HOUSE PARTY", "starred_actors", "ROBIN HARRIS" ], [ "HOUSE PARTY", "written_by", "REGINALD HUDLIN" ], [ "SANCTUM", "has_genre", "DRAMA" ], [ "SANCTUM", "release_year", "2011" ], [ "SANCTUM", "written_by", "ANDREW WIGHT" ], [ "ST. VINCENT", "has_genre", "COMEDY" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "has_tags", "CHRIS O'DOWD" ], [ "ST. VINCENT", "has_tags", "MELISSA MCCARTHY" ], [ "ST. VINCENT", "release_year", "2014" ], [ "ST. VINCENT", "starred_actors", "CHRIS O'DOWD" ], [ "ST. VINCENT", "starred_actors", "MELISSA MCCARTHY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26002, 10 TO MIDNIGHT 25221, 1981 15206, ANTHOLOGY 35575, CHARLES BRONSON 2979, DEATH HUNT 32864, GHOST STORY 27238, HAPPY BIRTHDAY TO ME 25412, HOOD OF HORROR 19805, J. LEE THOMPSON 4418, KWAIDAN 30157, LOLA 10823, MESSENGER OF DEATH 156, MURPHY'S LAW 28357, ST. IVES 2878, THE EVIL THAT MEN DO src, edge_attr, dst 26002, directed_by, 19805 26002, starred_actors, 35575 2979, release_year, 25221 2979, starred_actors, 35575 32864, release_year, 25221 27238, directed_by, 19805 27238, release_year, 25221 25412, has_tags, 15206 4418, has_tags, 15206 4418, has_tags, 32864 30157, release_year, 25221 30157, starred_actors, 35575 10823, directed_by, 19805 10823, starred_actors, 35575 156, directed_by, 19805 156, starred_actors, 35575 28357, directed_by, 19805 28357, starred_actors, 35575 2878, directed_by, 19805 2878, starred_actors, 35575 Question: In what context are GHOST STORY, HOOD OF HORROR, and MURPHY'S LAW connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GHOST STORY", "HOOD OF HORROR", "MURPHY'S LAW" ], "valid_edges": [ [ "10 TO MIDNIGHT", "directed_by", "J. LEE THOMPSON" ], [ "10 TO MIDNIGHT", "starred_actors", "CHARLES BRONSON" ], [ "DEATH HUNT", "release_year", "1981" ], [ "DEATH HUNT", "starred_actors", "CHARLES BRONSON" ], [ "GHOST STORY", "release_year", "1981" ], [ "HAPPY BIRTHDAY TO ME", "directed_by", "J. LEE THOMPSON" ], [ "HAPPY BIRTHDAY TO ME", "release_year", "1981" ], [ "HOOD OF HORROR", "has_tags", "ANTHOLOGY" ], [ "KWAIDAN", "has_tags", "ANTHOLOGY" ], [ "KWAIDAN", "has_tags", "GHOST STORY" ], [ "LOLA", "release_year", "1981" ], [ "LOLA", "starred_actors", "CHARLES BRONSON" ], [ "MESSENGER OF DEATH", "directed_by", "J. LEE THOMPSON" ], [ "MESSENGER OF DEATH", "starred_actors", "CHARLES BRONSON" ], [ "MURPHY'S LAW", "directed_by", "J. LEE THOMPSON" ], [ "MURPHY'S LAW", "starred_actors", "CHARLES BRONSON" ], [ "ST. IVES", "directed_by", "J. LEE THOMPSON" ], [ "ST. IVES", "starred_actors", "CHARLES BRONSON" ], [ "THE EVIL THAT MEN DO", "directed_by", "J. LEE THOMPSON" ], [ "THE EVIL THAT MEN DO", "starred_actors", "CHARLES BRONSON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26513, EDMOND O'BRIEN 31783, ENGLISH 819, FIST OF THE NORTH STAR 15667, HUMPHREY BOGART 8239, KID GALAHAD 13889, MICHAEL CURTIZ 32167, SETON I. MILLER 7554, THE BAREFOOT CONTESSA 11265, THE SEA HAWK 11351, TONY RANDEL src, edge_attr, dst 819, directed_by, 11351 819, in_language, 31783 819, written_by, 11351 8239, directed_by, 13889 8239, has_tags, 13889 8239, starred_actors, 15667 8239, written_by, 32167 7554, starred_actors, 26513 7554, starred_actors, 15667 11265, directed_by, 13889 11265, has_tags, 13889 11265, in_language, 31783 11265, written_by, 32167 Question: In what context are EDMOND O'BRIEN, SETON I. MILLER, and TONY RANDEL connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EDMOND O'BRIEN", "SETON I. MILLER", "TONY RANDEL" ], "valid_edges": [ [ "FIST OF THE NORTH STAR", "directed_by", "TONY RANDEL" ], [ "FIST OF THE NORTH STAR", "in_language", "ENGLISH" ], [ "FIST OF THE NORTH STAR", "written_by", "TONY RANDEL" ], [ "KID GALAHAD", "directed_by", "MICHAEL CURTIZ" ], [ "KID GALAHAD", "has_tags", "MICHAEL CURTIZ" ], [ "KID GALAHAD", "starred_actors", "HUMPHREY BOGART" ], [ "KID GALAHAD", "written_by", "SETON I. MILLER" ], [ "THE BAREFOOT CONTESSA", "starred_actors", "EDMOND O'BRIEN" ], [ "THE BAREFOOT CONTESSA", "starred_actors", "HUMPHREY BOGART" ], [ "THE SEA HAWK", "directed_by", "MICHAEL CURTIZ" ], [ "THE SEA HAWK", "has_tags", "MICHAEL CURTIZ" ], [ "THE SEA HAWK", "in_language", "ENGLISH" ], [ "THE SEA HAWK", "written_by", "SETON I. MILLER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32082, 11-11-11 18132, 1938 658, 2012 30146, A CHRISTMAS CAROL 25735, ALAN MOWBRAY 6793, AND THEN THERE WERE NONE 10045, BD-R 38850, BILLIE BURKE 235, BRINGING UP BABY 38693, CHILD BRIDE 32610, CONSTANCE BENNETT 12161, DARREN LYNN BOUSMAN 24481, FRANCHISE 7289, HOLIDAY 5870, HORROR 14156, KING SOLOMON'S MINES 628, LEIGH WHANNELL 10284, LOVE FINDS ANDY HARDY 21045, MAX SCHRECK 3092, MERRILY WE LIVE 24593, MUSICAL 32891, NOSFERATU 33032, PORT OF SHADOWS 30416, REPO! THE GENETIC OPERA 27857, ROLAND YOUNG 6201, ROOM SERVICE 2561, SAW II 5812, SAW III 22536, SAW IV 13197, SHAWNEE SMITH 22336, TERRANCE ZDUNICH 8220, THAT HAMILTON WOMAN 3223, THE BARKLEYS OF BROADWAY 25250, THE BARRENS 7153, THE DEVIL'S CARNIVAL 4091, THE LADY VANISHES 5128, THERE GOES MY HEART 12105, TOBIN BELL 9800, TOPPER TAKES A TRIP 9050, WHAT PRICE HOLLYWOOD? src, edge_attr, dst 32082, directed_by, 12161 32082, has_genre, 5870 32082, written_by, 12161 30146, has_tags, 10045 30146, release_year, 18132 6793, has_tags, 10045 6793, starred_actors, 27857 235, has_tags, 10045 235, release_year, 18132 38693, has_tags, 10045 38693, release_year, 18132 7289, has_tags, 10045 7289, release_year, 18132 14156, has_tags, 10045 14156, starred_actors, 27857 10284, has_tags, 10045 10284, release_year, 18132 3092, has_tags, 10045 3092, release_year, 18132 3092, starred_actors, 25735 3092, starred_actors, 38850 3092, starred_actors, 32610 32891, has_genre, 5870 32891, has_tags, 10045 32891, starred_actors, 21045 33032, has_tags, 10045 33032, release_year, 18132 30416, directed_by, 12161 30416, has_genre, 5870 30416, has_genre, 24593 30416, has_tags, 24593 30416, written_by, 22336 6201, has_tags, 10045 6201, release_year, 18132 2561, directed_by, 12161 2561, has_genre, 5870 2561, has_tags, 12161 2561, has_tags, 24481 2561, has_tags, 5870 2561, starred_actors, 13197 2561, starred_actors, 12105 2561, written_by, 12161 2561, written_by, 628 5812, directed_by, 12161 5812, has_genre, 5870 5812, has_tags, 12161 5812, has_tags, 24481 5812, starred_actors, 13197 5812, starred_actors, 12105 5812, written_by, 628 22536, directed_by, 12161 22536, has_genre, 5870 22536, has_tags, 12161 22536, has_tags, 24481 22536, starred_actors, 12105 8220, has_tags, 10045 8220, starred_actors, 25735 3223, has_tags, 10045 3223, starred_actors, 38850 25250, directed_by, 12161 25250, has_genre, 5870 25250, release_year, 658 25250, written_by, 12161 7153, directed_by, 12161 7153, has_genre, 5870 7153, has_genre, 24593 7153, release_year, 658 7153, starred_actors, 22336 7153, written_by, 22336 4091, has_tags, 10045 4091, release_year, 18132 5128, has_tags, 10045 5128, release_year, 18132 9800, has_tags, 10045 9800, release_year, 18132 9800, starred_actors, 25735 9800, starred_actors, 38850 9800, starred_actors, 32610 9800, starred_actors, 27857 9050, has_tags, 10045 9050, starred_actors, 32610 Question: For what reason are DARREN LYNN BOUSMAN, MAX SCHRECK, and TOPPER TAKES A TRIP associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DARREN LYNN BOUSMAN", "MAX SCHRECK", "TOPPER TAKES A TRIP" ], "valid_edges": [ [ "11-11-11", "directed_by", "DARREN LYNN BOUSMAN" ], [ "11-11-11", "has_genre", "HORROR" ], [ "11-11-11", "written_by", "DARREN LYNN BOUSMAN" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "release_year", "1938" ], [ "AND THEN THERE WERE NONE", "has_tags", "BD-R" ], [ "AND THEN THERE WERE NONE", "starred_actors", "ROLAND YOUNG" ], [ "BRINGING UP BABY", "has_tags", "BD-R" ], [ "BRINGING UP BABY", "release_year", "1938" ], [ "CHILD BRIDE", "has_tags", "BD-R" ], [ "CHILD BRIDE", "release_year", "1938" ], [ "HOLIDAY", "has_tags", "BD-R" ], [ "HOLIDAY", "release_year", "1938" ], [ "KING SOLOMON'S MINES", "has_tags", "BD-R" ], [ "KING SOLOMON'S MINES", "starred_actors", "ROLAND YOUNG" ], [ "LOVE FINDS ANDY HARDY", "has_tags", "BD-R" ], [ "LOVE FINDS ANDY HARDY", "release_year", "1938" ], [ "MERRILY WE LIVE", "has_tags", "BD-R" ], [ "MERRILY WE LIVE", "release_year", "1938" ], [ "MERRILY WE LIVE", "starred_actors", "ALAN MOWBRAY" ], [ "MERRILY WE LIVE", "starred_actors", "BILLIE BURKE" ], [ "MERRILY WE LIVE", "starred_actors", "CONSTANCE BENNETT" ], [ "NOSFERATU", "has_genre", "HORROR" ], [ "NOSFERATU", "has_tags", "BD-R" ], [ "NOSFERATU", "starred_actors", "MAX SCHRECK" ], [ "PORT OF SHADOWS", "has_tags", "BD-R" ], [ "PORT OF SHADOWS", "release_year", "1938" ], [ "REPO! THE GENETIC OPERA", "directed_by", "DARREN LYNN BOUSMAN" ], [ "REPO! THE GENETIC OPERA", "has_genre", "HORROR" ], [ "REPO! THE GENETIC OPERA", "has_genre", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "has_tags", "MUSICAL" ], [ "REPO! THE GENETIC OPERA", "written_by", "TERRANCE ZDUNICH" ], [ "ROOM SERVICE", "has_tags", "BD-R" ], [ "ROOM SERVICE", "release_year", "1938" ], [ "SAW II", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW II", "has_genre", "HORROR" ], [ "SAW II", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW II", "has_tags", "FRANCHISE" ], [ "SAW II", "has_tags", "HORROR" ], [ "SAW II", "starred_actors", "SHAWNEE SMITH" ], [ "SAW II", "starred_actors", "TOBIN BELL" ], [ "SAW II", "written_by", "DARREN LYNN BOUSMAN" ], [ "SAW II", "written_by", "LEIGH WHANNELL" ], [ "SAW III", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW III", "has_genre", "HORROR" ], [ "SAW III", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW III", "has_tags", "FRANCHISE" ], [ "SAW III", "starred_actors", "SHAWNEE SMITH" ], [ "SAW III", "starred_actors", "TOBIN BELL" ], [ "SAW III", "written_by", "LEIGH WHANNELL" ], [ "SAW IV", "directed_by", "DARREN LYNN BOUSMAN" ], [ "SAW IV", "has_genre", "HORROR" ], [ "SAW IV", "has_tags", "DARREN LYNN BOUSMAN" ], [ "SAW IV", "has_tags", "FRANCHISE" ], [ "SAW IV", "starred_actors", "TOBIN BELL" ], [ "THAT HAMILTON WOMAN", "has_tags", "BD-R" ], [ "THAT HAMILTON WOMAN", "starred_actors", "ALAN MOWBRAY" ], [ "THE BARKLEYS OF BROADWAY", "has_tags", "BD-R" ], [ "THE BARKLEYS OF BROADWAY", "starred_actors", "BILLIE BURKE" ], [ "THE BARRENS", "directed_by", "DARREN LYNN BOUSMAN" ], [ "THE BARRENS", "has_genre", "HORROR" ], [ "THE BARRENS", "release_year", "2012" ], [ "THE BARRENS", "written_by", "DARREN LYNN BOUSMAN" ], [ "THE DEVIL'S CARNIVAL", "directed_by", "DARREN LYNN BOUSMAN" ], [ "THE DEVIL'S CARNIVAL", "has_genre", "HORROR" ], [ "THE DEVIL'S CARNIVAL", "has_genre", "MUSICAL" ], [ "THE DEVIL'S CARNIVAL", "release_year", "2012" ], [ "THE DEVIL'S CARNIVAL", "starred_actors", "TERRANCE ZDUNICH" ], [ "THE DEVIL'S CARNIVAL", "written_by", "TERRANCE ZDUNICH" ], [ "THE LADY VANISHES", "has_tags", "BD-R" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "THERE GOES MY HEART", "has_tags", "BD-R" ], [ "THERE GOES MY HEART", "release_year", "1938" ], [ "TOPPER TAKES A TRIP", "has_tags", "BD-R" ], [ "TOPPER TAKES A TRIP", "release_year", "1938" ], [ "TOPPER TAKES A TRIP", "starred_actors", "ALAN MOWBRAY" ], [ "TOPPER TAKES A TRIP", "starred_actors", "BILLIE BURKE" ], [ "TOPPER TAKES A TRIP", "starred_actors", "CONSTANCE BENNETT" ], [ "TOPPER TAKES A TRIP", "starred_actors", "ROLAND YOUNG" ], [ "WHAT PRICE HOLLYWOOD?", "has_tags", "BD-R" ], [ "WHAT PRICE HOLLYWOOD?", "starred_actors", "CONSTANCE BENNETT" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 38707, ASYLUM 36212, DRAMA 12367, HASSINA BURGAN 5870, HORROR 10128, JACOB'S LADDER 37353, NOEL 3100, PSYCHOLOGICAL HORROR 6696, SESSION 9 1195, THE PATIENCE STONE 22214, WAR src, edge_attr, dst 38707, has_genre, 36212 10128, has_genre, 5870 10128, has_tags, 3100 10128, has_tags, 22214 37353, has_genre, 36212 37353, has_tags, 36212 6696, has_genre, 5870 6696, has_tags, 38707 6696, has_tags, 5870 6696, has_tags, 3100 1195, has_genre, 36212 1195, has_genre, 22214 1195, starred_actors, 12367 Question: In what context are HASSINA BURGAN, NOEL, and PSYCHOLOGICAL HORROR connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HASSINA BURGAN", "NOEL", "PSYCHOLOGICAL HORROR" ], "valid_edges": [ [ "ASYLUM", "has_genre", "DRAMA" ], [ "JACOB'S LADDER", "has_genre", "HORROR" ], [ "JACOB'S LADDER", "has_tags", "PSYCHOLOGICAL HORROR" ], [ "JACOB'S LADDER", "has_tags", "WAR" ], [ "NOEL", "has_genre", "DRAMA" ], [ "NOEL", "has_tags", "DRAMA" ], [ "SESSION 9", "has_genre", "HORROR" ], [ "SESSION 9", "has_tags", "ASYLUM" ], [ "SESSION 9", "has_tags", "HORROR" ], [ "SESSION 9", "has_tags", "PSYCHOLOGICAL HORROR" ], [ "THE PATIENCE STONE", "has_genre", "DRAMA" ], [ "THE PATIENCE STONE", "has_genre", "WAR" ], [ "THE PATIENCE STONE", "starred_actors", "HASSINA BURGAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26762, 2008 39137, AS GOOD AS IT GETS 9340, BABY MAMA 10445, COLD PREY 2 24116, COLLEGE 2159, GHOST TOWN 31060, GIGANTIC 11565, GOOD 6608, GOOD DICK 28501, GOODBYE SOLO 18734, GREG KINNEAR 33476, PAUL LYNCH 24736, PROM NIGHT 19341, RACE 24467, SPEED RACER 13613, THE LAZARUS PROJECT 26588, THE SECRETS OF JONATHAN SPERRY 5465, WHAT DOESN'T KILL YOU src, edge_attr, dst 39137, has_imdb_rating, 11565 39137, has_tags, 18734 39137, starred_actors, 18734 9340, has_tags, 18734 9340, release_year, 26762 9340, starred_actors, 18734 10445, has_imdb_rating, 11565 10445, release_year, 26762 24116, has_imdb_rating, 11565 24116, release_year, 26762 2159, has_tags, 18734 2159, release_year, 26762 2159, starred_actors, 18734 31060, has_imdb_rating, 11565 31060, release_year, 26762 11565, has_imdb_rating, 11565 11565, release_year, 26762 6608, has_imdb_rating, 11565 6608, release_year, 26762 28501, has_imdb_rating, 11565 28501, release_year, 26762 24736, directed_by, 33476 24736, release_year, 26762 19341, has_imdb_rating, 11565 19341, release_year, 26762 24467, has_imdb_rating, 11565 24467, release_year, 26762 13613, has_imdb_rating, 11565 13613, release_year, 26762 26588, release_year, 26762 5465, has_imdb_rating, 11565 5465, release_year, 26762 Question: For what reason are AS GOOD AS IT GETS, PAUL LYNCH, and THE SECRETS OF JONATHAN SPERRY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AS GOOD AS IT GETS", "PAUL LYNCH", "THE SECRETS OF JONATHAN SPERRY" ], "valid_edges": [ [ "AS GOOD AS IT GETS", "has_imdb_rating", "GOOD" ], [ "AS GOOD AS IT GETS", "has_tags", "GREG KINNEAR" ], [ "AS GOOD AS IT GETS", "starred_actors", "GREG KINNEAR" ], [ "BABY MAMA", "has_tags", "GREG KINNEAR" ], [ "BABY MAMA", "release_year", "2008" ], [ "BABY MAMA", "starred_actors", "GREG KINNEAR" ], [ "COLD PREY 2", "has_imdb_rating", "GOOD" ], [ "COLD PREY 2", "release_year", "2008" ], [ "COLLEGE", "has_imdb_rating", "GOOD" ], [ "COLLEGE", "release_year", "2008" ], [ "GHOST TOWN", "has_tags", "GREG KINNEAR" ], [ "GHOST TOWN", "release_year", "2008" ], [ "GHOST TOWN", "starred_actors", "GREG KINNEAR" ], [ "GIGANTIC", "has_imdb_rating", "GOOD" ], [ "GIGANTIC", "release_year", "2008" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD", "release_year", "2008" ], [ "GOOD DICK", "has_imdb_rating", "GOOD" ], [ "GOOD DICK", "release_year", "2008" ], [ "GOODBYE SOLO", "has_imdb_rating", "GOOD" ], [ "GOODBYE SOLO", "release_year", "2008" ], [ "PROM NIGHT", "directed_by", "PAUL LYNCH" ], [ "PROM NIGHT", "release_year", "2008" ], [ "RACE", "has_imdb_rating", "GOOD" ], [ "RACE", "release_year", "2008" ], [ "SPEED RACER", "has_imdb_rating", "GOOD" ], [ "SPEED RACER", "release_year", "2008" ], [ "THE LAZARUS PROJECT", "has_imdb_rating", "GOOD" ], [ "THE LAZARUS PROJECT", "release_year", "2008" ], [ "THE SECRETS OF JONATHAN SPERRY", "release_year", "2008" ], [ "WHAT DOESN'T KILL YOU", "has_imdb_rating", "GOOD" ], [ "WHAT DOESN'T KILL YOU", "release_year", "2008" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 2133, 1998 25005, A MURDER OF CROWS 9719, AFTER LIFE 6395, BLUES HARP 36016, COUSIN BETTE 6943, FALLEN 21204, GEORGE CLOONEY 3553, GODZILLA 11565, GOOD 36874, JAPANESE 14797, O BROTHER, WHERE ART THOU? 31950, OCEAN WAVES 4235, OUT OF SIGHT 3297, PATCH ADAMS 27361, RIDING ALONE FOR THOUSANDS OF MILES 28, RING 32418, THE AMERICAN 38882, THE BIRD PEOPLE IN CHINA 4662, THE GOOD GERMAN 29181, THE MONUMENTS MEN 16029, THE TATTOOED WIDOW 30136, THE THIN RED LINE 9811, VEXILLE 38318, WHAT DREAMS MAY COME 19845, WITHOUT LIMITS 15808, YOU'VE GOT MAIL src, edge_attr, dst 25005, has_imdb_rating, 11565 25005, release_year, 2133 9719, in_language, 36874 9719, release_year, 2133 6395, in_language, 36874 6395, release_year, 2133 36016, has_imdb_rating, 11565 36016, release_year, 2133 6943, has_imdb_rating, 11565 6943, release_year, 2133 3553, in_language, 36874 3553, release_year, 2133 11565, has_imdb_rating, 11565 14797, has_imdb_rating, 11565 14797, has_tags, 21204 14797, starred_actors, 21204 31950, has_imdb_rating, 11565 31950, in_language, 36874 4235, has_tags, 21204 4235, release_year, 2133 4235, starred_actors, 21204 3297, has_imdb_rating, 11565 3297, release_year, 2133 27361, has_imdb_rating, 11565 27361, in_language, 36874 28, in_language, 36874 28, release_year, 2133 32418, has_tags, 21204 32418, starred_actors, 21204 38882, in_language, 36874 38882, release_year, 2133 4662, has_imdb_rating, 11565 4662, has_tags, 21204 4662, starred_actors, 21204 29181, directed_by, 21204 29181, has_imdb_rating, 11565 29181, has_tags, 21204 29181, starred_actors, 21204 29181, written_by, 21204 16029, has_imdb_rating, 11565 16029, release_year, 2133 30136, has_tags, 21204 30136, release_year, 2133 9811, in_language, 36874 38318, has_imdb_rating, 11565 38318, release_year, 2133 19845, has_imdb_rating, 11565 19845, release_year, 2133 15808, has_imdb_rating, 11565 15808, release_year, 2133 Question: For what reason are A MURDER OF CROWS, THE AMERICAN, and VEXILLE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A MURDER OF CROWS", "THE AMERICAN", "VEXILLE" ], "valid_edges": [ [ "A MURDER OF CROWS", "has_imdb_rating", "GOOD" ], [ "A MURDER OF CROWS", "release_year", "1998" ], [ "AFTER LIFE", "in_language", "JAPANESE" ], [ "AFTER LIFE", "release_year", "1998" ], [ "BLUES HARP", "in_language", "JAPANESE" ], [ "BLUES HARP", "release_year", "1998" ], [ "COUSIN BETTE", "has_imdb_rating", "GOOD" ], [ "COUSIN BETTE", "release_year", "1998" ], [ "FALLEN", "has_imdb_rating", "GOOD" ], [ "FALLEN", "release_year", "1998" ], [ "GODZILLA", "in_language", "JAPANESE" ], [ "GODZILLA", "release_year", "1998" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "GEORGE CLOONEY" ], [ "O BROTHER, WHERE ART THOU?", "starred_actors", "GEORGE CLOONEY" ], [ "OCEAN WAVES", "has_imdb_rating", "GOOD" ], [ "OCEAN WAVES", "in_language", "JAPANESE" ], [ "OUT OF SIGHT", "has_tags", "GEORGE CLOONEY" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "OUT OF SIGHT", "starred_actors", "GEORGE CLOONEY" ], [ "PATCH ADAMS", "has_imdb_rating", "GOOD" ], [ "PATCH ADAMS", "release_year", "1998" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "has_imdb_rating", "GOOD" ], [ "RIDING ALONE FOR THOUSANDS OF MILES", "in_language", "JAPANESE" ], [ "RING", "in_language", "JAPANESE" ], [ "RING", "release_year", "1998" ], [ "THE AMERICAN", "has_tags", "GEORGE CLOONEY" ], [ "THE AMERICAN", "starred_actors", "GEORGE CLOONEY" ], [ "THE BIRD PEOPLE IN CHINA", "in_language", "JAPANESE" ], [ "THE BIRD PEOPLE IN CHINA", "release_year", "1998" ], [ "THE GOOD GERMAN", "has_imdb_rating", "GOOD" ], [ "THE GOOD GERMAN", "has_tags", "GEORGE CLOONEY" ], [ "THE GOOD GERMAN", "starred_actors", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "directed_by", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "has_imdb_rating", "GOOD" ], [ "THE MONUMENTS MEN", "has_tags", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "starred_actors", "GEORGE CLOONEY" ], [ "THE MONUMENTS MEN", "written_by", "GEORGE CLOONEY" ], [ "THE TATTOOED WIDOW", "has_imdb_rating", "GOOD" ], [ "THE TATTOOED WIDOW", "release_year", "1998" ], [ "THE THIN RED LINE", "has_tags", "GEORGE CLOONEY" ], [ "THE THIN RED LINE", "release_year", "1998" ], [ "VEXILLE", "in_language", "JAPANESE" ], [ "WHAT DREAMS MAY COME", "has_imdb_rating", "GOOD" ], [ "WHAT DREAMS MAY COME", "release_year", "1998" ], [ "WITHOUT LIMITS", "has_imdb_rating", "GOOD" ], [ "WITHOUT LIMITS", "release_year", "1998" ], [ "YOU'VE GOT MAIL", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "release_year", "1998" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 15416, BOYFRIENDS AND GIRLFRIENDS 30463, COMEDY 20990, HOLY MATRIMONY 39920, OFFICE SPACE 5947, SOPHIE RENOIR src, edge_attr, dst 15416, has_genre, 30463 15416, starred_actors, 5947 20990, has_genre, 30463 39920, has_genre, 30463 39920, has_tags, 30463 Question: For what reason are HOLY MATRIMONY, OFFICE SPACE, and SOPHIE RENOIR associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HOLY MATRIMONY", "OFFICE SPACE", "SOPHIE RENOIR" ], "valid_edges": [ [ "BOYFRIENDS AND GIRLFRIENDS", "has_genre", "COMEDY" ], [ "BOYFRIENDS AND GIRLFRIENDS", "starred_actors", "SOPHIE RENOIR" ], [ "HOLY MATRIMONY", "has_genre", "COMEDY" ], [ "OFFICE SPACE", "has_genre", "COMEDY" ], [ "OFFICE SPACE", "has_tags", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 28210, ALAN ORMSBY 36853, ALTERED STATES 36593, BLACK CHRISTMAS 27791, BOB CLARK 37912, CAT PEOPLE 15226, CHILDREN SHOULDN'T PLAY WITH DEAD THINGS 25738, CHRISTMAS EVIL 13888, CITY OF THE LIVING DEAD 16813, CONTAMINATION 14128, D.J. COTRONA 9248, DEATH SHIP 22215, FRIDAY THE 13TH 1408, HE KNOWS YOU'RE ALONE 2600, HELL OF THE LIVING DEAD 5870, HORROR 24167, INFERNO 24437, MANIAC 30047, MOTEL HELL 19825, MOTHER'S DAY 8138, POPCORN 4604, PRIVATE BENJAMIN 24736, PROM NIGHT 5864, THE AWAKENING 34039, THE CHANGELING 27423, THE FOG 5592, THE HEARSE 19018, THE SHINING 14962, THE WATCHER IN THE WOODS 27274, VENOM 21887, WITHOUT WARNING src, edge_attr, dst 36853, has_genre, 5870 36853, release_year, 36268 36593, directed_by, 27791 36593, has_genre, 5870 36593, has_tags, 27791 36593, has_tags, 5870 37912, has_genre, 5870 37912, written_by, 28210 15226, directed_by, 27791 15226, has_genre, 5870 15226, starred_actors, 28210 15226, written_by, 28210 15226, written_by, 27791 25738, has_genre, 5870 25738, release_year, 36268 13888, has_genre, 5870 13888, has_tags, 5870 13888, release_year, 36268 16813, has_genre, 5870 16813, release_year, 36268 9248, has_genre, 5870 9248, release_year, 36268 22215, has_genre, 5870 22215, release_year, 36268 1408, has_genre, 5870 1408, release_year, 36268 2600, has_genre, 5870 2600, release_year, 36268 24167, has_genre, 5870 24167, release_year, 36268 24437, has_genre, 5870 24437, release_year, 36268 30047, has_genre, 5870 30047, release_year, 36268 19825, has_genre, 5870 19825, release_year, 36268 8138, directed_by, 28210 8138, has_genre, 5870 8138, written_by, 28210 4604, release_year, 36268 24736, has_genre, 5870 24736, release_year, 36268 5864, has_genre, 5870 5864, has_tags, 5870 5864, release_year, 36268 34039, has_genre, 5870 34039, release_year, 36268 27423, has_genre, 5870 27423, has_tags, 5870 27423, release_year, 36268 5592, has_genre, 5870 5592, release_year, 36268 19018, has_genre, 5870 19018, has_tags, 5870 19018, release_year, 36268 14962, has_genre, 5870 14962, release_year, 36268 27274, has_genre, 5870 27274, starred_actors, 14128 21887, has_genre, 5870 21887, release_year, 36268 Question: How are CHILDREN SHOULDN'T PLAY WITH DEAD THINGS, D.J. COTRONA, and PRIVATE BENJAMIN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "D.J. COTRONA", "PRIVATE BENJAMIN" ], "valid_edges": [ [ "ALTERED STATES", "has_genre", "HORROR" ], [ "ALTERED STATES", "release_year", "1980" ], [ "BLACK CHRISTMAS", "directed_by", "BOB CLARK" ], [ "BLACK CHRISTMAS", "has_genre", "HORROR" ], [ "BLACK CHRISTMAS", "has_tags", "BOB CLARK" ], [ "BLACK CHRISTMAS", "has_tags", "HORROR" ], [ "CAT PEOPLE", "has_genre", "HORROR" ], [ "CAT PEOPLE", "written_by", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "directed_by", "BOB CLARK" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "has_genre", "HORROR" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "starred_actors", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "written_by", "ALAN ORMSBY" ], [ "CHILDREN SHOULDN'T PLAY WITH DEAD THINGS", "written_by", "BOB CLARK" ], [ "CHRISTMAS EVIL", "has_genre", "HORROR" ], [ "CHRISTMAS EVIL", "release_year", "1980" ], [ "CITY OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "CITY OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "CITY OF THE LIVING DEAD", "release_year", "1980" ], [ "CONTAMINATION", "has_genre", "HORROR" ], [ "CONTAMINATION", "release_year", "1980" ], [ "DEATH SHIP", "has_genre", "HORROR" ], [ "DEATH SHIP", "release_year", "1980" ], [ "FRIDAY THE 13TH", "has_genre", "HORROR" ], [ "FRIDAY THE 13TH", "release_year", "1980" ], [ "HE KNOWS YOU'RE ALONE", "has_genre", "HORROR" ], [ "HE KNOWS YOU'RE ALONE", "release_year", "1980" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "INFERNO", "has_genre", "HORROR" ], [ "INFERNO", "release_year", "1980" ], [ "MANIAC", "has_genre", "HORROR" ], [ "MANIAC", "release_year", "1980" ], [ "MOTEL HELL", "has_genre", "HORROR" ], [ "MOTEL HELL", "release_year", "1980" ], [ "MOTHER'S DAY", "has_genre", "HORROR" ], [ "MOTHER'S DAY", "release_year", "1980" ], [ "POPCORN", "directed_by", "ALAN ORMSBY" ], [ "POPCORN", "has_genre", "HORROR" ], [ "POPCORN", "written_by", "ALAN ORMSBY" ], [ "PRIVATE BENJAMIN", "release_year", "1980" ], [ "PROM NIGHT", "has_genre", "HORROR" ], [ "PROM NIGHT", "release_year", "1980" ], [ "THE AWAKENING", "has_genre", "HORROR" ], [ "THE AWAKENING", "has_tags", "HORROR" ], [ "THE AWAKENING", "release_year", "1980" ], [ "THE CHANGELING", "has_genre", "HORROR" ], [ "THE CHANGELING", "release_year", "1980" ], [ "THE FOG", "has_genre", "HORROR" ], [ "THE FOG", "has_tags", "HORROR" ], [ "THE FOG", "release_year", "1980" ], [ "THE HEARSE", "has_genre", "HORROR" ], [ "THE HEARSE", "release_year", "1980" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "release_year", "1980" ], [ "THE WATCHER IN THE WOODS", "has_genre", "HORROR" ], [ "THE WATCHER IN THE WOODS", "release_year", "1980" ], [ "VENOM", "has_genre", "HORROR" ], [ "VENOM", "starred_actors", "D.J. COTRONA" ], [ "WITHOUT WARNING", "has_genre", "HORROR" ], [ "WITHOUT WARNING", "release_year", "1980" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6721, 1972 17315, 2007 37655, AL PACINO 2973, ALL THE COLORS OF THE DARK 9942, ANTHONY SHAFFER 15278, AVANTI! 13211, CALIBER 9 26346, DADDY'S LITTLE GIRLS 24214, DON'T TORTURE A DUCKLING 2848, FRENZY 31307, GODZILLA VS. GIGAN 33673, HEAT 11233, HIDEO YAMAMOTO 4215, ICHI THE KILLER 16200, ITALIAN 36874, JAPANESE 23374, LAST OF THE RED HOT LOVERS 31211, LUDWIG 1153, MICHAEL CAINE 15145, MYSTERY 37159, NEIL SIMON 37810, PULP 13081, R 28729, REMAKE 6119, SLEUTH 15568, THE CANTERBURY TALES 6524, THE GETAWAY 35551, THE GODFATHER 19595, THE HEARTBREAK KID 15202, THE LAST HOUSE ON THE LEFT 36168, THE MATTEI AFFAIR 8839, THE MECHANIC 34254, THEY ONLY KILL THEIR MASTERS 34730, TYLER PERRY 4117, UNDER THE FLAG OF THE RISING SUN 28211, WHAT HAVE YOU DONE TO SOLANGE? 6287, WHY DID I GET MARRIED? src, edge_attr, dst 2973, in_language, 16200 2973, release_year, 6721 15278, in_language, 16200 15278, release_year, 6721 13211, in_language, 16200 13211, release_year, 6721 26346, directed_by, 34730 26346, release_year, 17315 26346, written_by, 34730 24214, in_language, 16200 24214, release_year, 6721 2848, release_year, 6721 2848, written_by, 9942 31307, in_language, 36874 31307, release_year, 6721 33673, has_tags, 37655 33673, has_tags, 13081 33673, release_year, 6721 33673, starred_actors, 37655 4215, in_language, 36874 4215, written_by, 11233 23374, release_year, 6721 23374, written_by, 37159 31211, in_language, 16200 31211, release_year, 6721 37810, release_year, 6721 37810, starred_actors, 1153 6119, has_genre, 15145 6119, has_tags, 1153 6119, has_tags, 15145 6119, has_tags, 13081 6119, in_language, 16200 6119, release_year, 6721 6119, release_year, 17315 6119, starred_actors, 1153 6119, written_by, 9942 15568, in_language, 16200 15568, release_year, 6721 6524, has_tags, 28729 6524, release_year, 6721 35551, has_tags, 37655 35551, has_tags, 16200 35551, has_tags, 13081 35551, in_language, 16200 35551, release_year, 6721 35551, starred_actors, 37655 19595, has_tags, 37159 19595, has_tags, 13081 19595, has_tags, 28729 19595, release_year, 6721 19595, release_year, 17315 19595, written_by, 37159 15202, has_tags, 28729 15202, release_year, 6721 36168, in_language, 16200 36168, release_year, 6721 8839, has_tags, 28729 8839, release_year, 6721 34254, has_genre, 15145 34254, release_year, 6721 4117, in_language, 36874 4117, release_year, 6721 28211, has_genre, 15145 28211, in_language, 16200 28211, release_year, 6721 6287, directed_by, 34730 6287, has_tags, 34730 6287, release_year, 17315 6287, starred_actors, 34730 6287, written_by, 34730 Question: How are 1972, HIDEO YAMAMOTO, and WHY DID I GET MARRIED? related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1972", "HIDEO YAMAMOTO", "WHY DID I GET MARRIED?" ], "valid_edges": [ [ "ALL THE COLORS OF THE DARK", "in_language", "ITALIAN" ], [ "ALL THE COLORS OF THE DARK", "release_year", "1972" ], [ "AVANTI!", "in_language", "ITALIAN" ], [ "AVANTI!", "release_year", "1972" ], [ "CALIBER 9", "in_language", "ITALIAN" ], [ "CALIBER 9", "release_year", "1972" ], [ "DADDY'S LITTLE GIRLS", "directed_by", "TYLER PERRY" ], [ "DADDY'S LITTLE GIRLS", "release_year", "2007" ], [ "DADDY'S LITTLE GIRLS", "written_by", "TYLER PERRY" ], [ "DON'T TORTURE A DUCKLING", "in_language", "ITALIAN" ], [ "DON'T TORTURE A DUCKLING", "release_year", "1972" ], [ "FRENZY", "release_year", "1972" ], [ "FRENZY", "written_by", "ANTHONY SHAFFER" ], [ "GODZILLA VS. GIGAN", "in_language", "JAPANESE" ], [ "GODZILLA VS. GIGAN", "release_year", "1972" ], [ "HEAT", "has_tags", "AL PACINO" ], [ "HEAT", "has_tags", "R" ], [ "HEAT", "release_year", "1972" ], [ "HEAT", "starred_actors", "AL PACINO" ], [ "ICHI THE KILLER", "in_language", "JAPANESE" ], [ "ICHI THE KILLER", "written_by", "HIDEO YAMAMOTO" ], [ "LAST OF THE RED HOT LOVERS", "release_year", "1972" ], [ "LAST OF THE RED HOT LOVERS", "written_by", "NEIL SIMON" ], [ "LUDWIG", "in_language", "ITALIAN" ], [ "LUDWIG", "release_year", "1972" ], [ "PULP", "release_year", "1972" ], [ "PULP", "starred_actors", "MICHAEL CAINE" ], [ "SLEUTH", "has_genre", "MYSTERY" ], [ "SLEUTH", "has_tags", "MICHAEL CAINE" ], [ "SLEUTH", "has_tags", "MYSTERY" ], [ "SLEUTH", "has_tags", "R" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "SLEUTH", "release_year", "1972" ], [ "SLEUTH", "release_year", "2007" ], [ "SLEUTH", "starred_actors", "MICHAEL CAINE" ], [ "SLEUTH", "written_by", "ANTHONY SHAFFER" ], [ "THE CANTERBURY TALES", "in_language", "ITALIAN" ], [ "THE CANTERBURY TALES", "release_year", "1972" ], [ "THE GETAWAY", "has_tags", "REMAKE" ], [ "THE GETAWAY", "release_year", "1972" ], [ "THE GODFATHER", "has_tags", "AL PACINO" ], [ "THE GODFATHER", "has_tags", "ITALIAN" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "in_language", "ITALIAN" ], [ "THE GODFATHER", "release_year", "1972" ], [ "THE GODFATHER", "starred_actors", "AL PACINO" ], [ "THE HEARTBREAK KID", "has_tags", "NEIL SIMON" ], [ "THE HEARTBREAK KID", "has_tags", "R" ], [ "THE HEARTBREAK KID", "has_tags", "REMAKE" ], [ "THE HEARTBREAK KID", "release_year", "1972" ], [ "THE HEARTBREAK KID", "release_year", "2007" ], [ "THE HEARTBREAK KID", "written_by", "NEIL SIMON" ], [ "THE LAST HOUSE ON THE LEFT", "has_tags", "REMAKE" ], [ "THE LAST HOUSE ON THE LEFT", "release_year", "1972" ], [ "THE MATTEI AFFAIR", "in_language", "ITALIAN" ], [ "THE MATTEI AFFAIR", "release_year", "1972" ], [ "THE MECHANIC", "has_tags", "REMAKE" ], [ "THE MECHANIC", "release_year", "1972" ], [ "THEY ONLY KILL THEIR MASTERS", "has_genre", "MYSTERY" ], [ "THEY ONLY KILL THEIR MASTERS", "release_year", "1972" ], [ "UNDER THE FLAG OF THE RISING SUN", "in_language", "JAPANESE" ], [ "UNDER THE FLAG OF THE RISING SUN", "release_year", "1972" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "has_genre", "MYSTERY" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "in_language", "ITALIAN" ], [ "WHAT HAVE YOU DONE TO SOLANGE?", "release_year", "1972" ], [ "WHY DID I GET MARRIED?", "directed_by", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "has_tags", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "release_year", "2007" ], [ "WHY DID I GET MARRIED?", "starred_actors", "TYLER PERRY" ], [ "WHY DID I GET MARRIED?", "written_by", "TYLER PERRY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29561, 1943 29424, 2011 37908, AFRICAN CATS 37994, ANGEL DOG 39613, BEAUTY DAY 21372, BEVERLY HILLS CHIHUAHUA 2 26510, BORN TO BE WILD 29342, BULLY 17035, DEBTOCRACY 12841, DOCUMENTARY 3032, DOLPHIN TALE 1519, DREAMS OF A LIFE 10509, FAMILY 39366, HAPPY 20013, HAPPY FEET TWO 17345, HERE WITHOUT ME 23442, HOODWINKED TOO! HOOD VS. EVIL 21922, JANE EYRE 24247, LEONOR WATLING 19802, LOVE 28468, MAGIC TRIP 7839, MISS REPRESENTATION 12706, MR. POPPER'S PENGUINS 35524, ONE LIFE 2108, PEARL JAM TWENTY 29086, PINA 38002, RED DOG 10984, REVENGE OF THE ELECTRIC CAR 12599, SURVIVING PROGRESS 9972, TALK TO HER 2588, THE AMBASSADOR 24264, THE BATTLE OF RUSSIA 11259, THE BLACK POWER MIXTAPE 1967-1975 20837, THE CAPTAINS 20969, THE FLAT 39978, THE HUMAN COMEDY 30700, THE INTERRUPTERS 38461, THE LAST LIONS 27444, THE LAST MOUNTAIN 39587, THE OTHER F WORD 29052, THESE AMAZING SHADOWS 36765, THIS IS NOT A FILM 16214, UNLAWFUL KILLING 8957, WE BOUGHT A ZOO 4896, WHORES' GLORY 9056, YOU'VE BEEN TRUMPED src, edge_attr, dst 37908, has_genre, 12841 37908, release_year, 29424 37994, has_genre, 10509 37994, release_year, 29424 39613, has_genre, 12841 39613, release_year, 29424 21372, has_genre, 10509 21372, release_year, 29424 26510, has_genre, 12841 26510, release_year, 29424 29342, has_genre, 12841 29342, release_year, 29424 17035, has_genre, 12841 17035, release_year, 29424 3032, has_genre, 10509 3032, has_tags, 10509 3032, release_year, 29424 1519, has_genre, 12841 1519, release_year, 29424 39366, has_genre, 12841 39366, has_genre, 10509 39366, has_tags, 12841 39366, release_year, 29424 20013, has_genre, 10509 20013, release_year, 29424 17345, has_genre, 10509 17345, release_year, 29424 23442, has_genre, 10509 23442, release_year, 29424 21922, release_year, 29561 21922, release_year, 29424 19802, release_year, 29424 28468, has_genre, 12841 28468, release_year, 29424 7839, has_genre, 12841 7839, release_year, 29424 12706, has_genre, 10509 12706, release_year, 29424 35524, has_genre, 12841 35524, release_year, 29424 2108, has_genre, 12841 2108, release_year, 29424 29086, has_genre, 12841 29086, has_tags, 12841 29086, release_year, 29424 38002, has_genre, 10509 38002, release_year, 29424 10984, has_genre, 12841 10984, release_year, 29424 12599, has_genre, 12841 12599, has_tags, 12841 12599, release_year, 29424 9972, has_tags, 24247 9972, has_tags, 19802 9972, starred_actors, 24247 2588, has_genre, 12841 2588, release_year, 29424 24264, has_genre, 12841 24264, release_year, 29561 11259, has_genre, 12841 11259, release_year, 29424 20837, has_genre, 12841 20837, release_year, 29424 20969, has_genre, 12841 20969, release_year, 29424 39978, has_genre, 10509 39978, release_year, 29561 30700, has_genre, 12841 30700, release_year, 29424 38461, has_genre, 12841 38461, release_year, 29424 27444, has_genre, 12841 27444, release_year, 29424 39587, has_genre, 12841 39587, release_year, 29424 29052, has_genre, 12841 29052, release_year, 29424 36765, has_genre, 12841 36765, release_year, 29424 16214, has_genre, 12841 16214, release_year, 29424 8957, has_genre, 10509 8957, has_tags, 10509 8957, release_year, 29424 4896, has_genre, 12841 4896, has_tags, 12841 4896, release_year, 29424 9056, has_genre, 12841 9056, release_year, 29424 Question: How are DREAMS OF A LIFE, LEONOR WATLING, and THE HUMAN COMEDY related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DREAMS OF A LIFE", "LEONOR WATLING", "THE HUMAN COMEDY" ], "valid_edges": [ [ "AFRICAN CATS", "has_genre", "DOCUMENTARY" ], [ "AFRICAN CATS", "release_year", "2011" ], [ "ANGEL DOG", "has_genre", "FAMILY" ], [ "ANGEL DOG", "release_year", "2011" ], [ "BEAUTY DAY", "has_genre", "DOCUMENTARY" ], [ "BEAUTY DAY", "release_year", "2011" ], [ "BEVERLY HILLS CHIHUAHUA 2", "has_genre", "FAMILY" ], [ "BEVERLY HILLS CHIHUAHUA 2", "release_year", "2011" ], [ "BORN TO BE WILD", "has_genre", "DOCUMENTARY" ], [ "BORN TO BE WILD", "release_year", "2011" ], [ "BULLY", "has_genre", "DOCUMENTARY" ], [ "BULLY", "release_year", "2011" ], [ "DEBTOCRACY", "has_genre", "DOCUMENTARY" ], [ "DEBTOCRACY", "release_year", "2011" ], [ "DOLPHIN TALE", "has_genre", "FAMILY" ], [ "DOLPHIN TALE", "has_tags", "FAMILY" ], [ "DOLPHIN TALE", "release_year", "2011" ], [ "DREAMS OF A LIFE", "has_genre", "DOCUMENTARY" ], [ "DREAMS OF A LIFE", "release_year", "2011" ], [ "HAPPY", "has_genre", "DOCUMENTARY" ], [ "HAPPY", "has_genre", "FAMILY" ], [ "HAPPY", "has_tags", "DOCUMENTARY" ], [ "HAPPY", "release_year", "2011" ], [ "HAPPY FEET TWO", "has_genre", "FAMILY" ], [ "HAPPY FEET TWO", "release_year", "2011" ], [ "HERE WITHOUT ME", "has_genre", "FAMILY" ], [ "HERE WITHOUT ME", "release_year", "2011" ], [ "HOODWINKED TOO! HOOD VS. EVIL", "has_genre", "FAMILY" ], [ "HOODWINKED TOO! HOOD VS. EVIL", "release_year", "2011" ], [ "JANE EYRE", "release_year", "1943" ], [ "JANE EYRE", "release_year", "2011" ], [ "LOVE", "release_year", "2011" ], [ "MAGIC TRIP", "has_genre", "DOCUMENTARY" ], [ "MAGIC TRIP", "release_year", "2011" ], [ "MISS REPRESENTATION", "has_genre", "DOCUMENTARY" ], [ "MISS REPRESENTATION", "release_year", "2011" ], [ "MR. POPPER'S PENGUINS", "has_genre", "FAMILY" ], [ "MR. POPPER'S PENGUINS", "release_year", "2011" ], [ "ONE LIFE", "has_genre", "DOCUMENTARY" ], [ "ONE LIFE", "release_year", "2011" ], [ "PEARL JAM TWENTY", "has_genre", "DOCUMENTARY" ], [ "PEARL JAM TWENTY", "release_year", "2011" ], [ "PINA", "has_genre", "DOCUMENTARY" ], [ "PINA", "has_tags", "DOCUMENTARY" ], [ "PINA", "release_year", "2011" ], [ "RED DOG", "has_genre", "FAMILY" ], [ "RED DOG", "release_year", "2011" ], [ "REVENGE OF THE ELECTRIC CAR", "has_genre", "DOCUMENTARY" ], [ "REVENGE OF THE ELECTRIC CAR", "release_year", "2011" ], [ "SURVIVING PROGRESS", "has_genre", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "has_tags", "DOCUMENTARY" ], [ "SURVIVING PROGRESS", "release_year", "2011" ], [ "TALK TO HER", "has_tags", "LEONOR WATLING" ], [ "TALK TO HER", "has_tags", "LOVE" ], [ "TALK TO HER", "starred_actors", "LEONOR WATLING" ], [ "THE AMBASSADOR", "has_genre", "DOCUMENTARY" ], [ "THE AMBASSADOR", "release_year", "2011" ], [ "THE BATTLE OF RUSSIA", "has_genre", "DOCUMENTARY" ], [ "THE BATTLE OF RUSSIA", "release_year", "1943" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "has_genre", "DOCUMENTARY" ], [ "THE BLACK POWER MIXTAPE 1967-1975", "release_year", "2011" ], [ "THE CAPTAINS", "has_genre", "DOCUMENTARY" ], [ "THE CAPTAINS", "release_year", "2011" ], [ "THE FLAT", "has_genre", "DOCUMENTARY" ], [ "THE FLAT", "release_year", "2011" ], [ "THE HUMAN COMEDY", "has_genre", "FAMILY" ], [ "THE HUMAN COMEDY", "release_year", "1943" ], [ "THE INTERRUPTERS", "has_genre", "DOCUMENTARY" ], [ "THE INTERRUPTERS", "release_year", "2011" ], [ "THE LAST LIONS", "has_genre", "DOCUMENTARY" ], [ "THE LAST LIONS", "release_year", "2011" ], [ "THE LAST MOUNTAIN", "has_genre", "DOCUMENTARY" ], [ "THE LAST MOUNTAIN", "release_year", "2011" ], [ "THE OTHER F WORD", "has_genre", "DOCUMENTARY" ], [ "THE OTHER F WORD", "release_year", "2011" ], [ "THESE AMAZING SHADOWS", "has_genre", "DOCUMENTARY" ], [ "THESE AMAZING SHADOWS", "release_year", "2011" ], [ "THIS IS NOT A FILM", "has_genre", "DOCUMENTARY" ], [ "THIS IS NOT A FILM", "release_year", "2011" ], [ "UNLAWFUL KILLING", "has_genre", "DOCUMENTARY" ], [ "UNLAWFUL KILLING", "release_year", "2011" ], [ "WE BOUGHT A ZOO", "has_genre", "FAMILY" ], [ "WE BOUGHT A ZOO", "has_tags", "FAMILY" ], [ "WE BOUGHT A ZOO", "release_year", "2011" ], [ "WHORES' GLORY", "has_genre", "DOCUMENTARY" ], [ "WHORES' GLORY", "has_tags", "DOCUMENTARY" ], [ "WHORES' GLORY", "release_year", "2011" ], [ "YOU'VE BEEN TRUMPED", "has_genre", "DOCUMENTARY" ], [ "YOU'VE BEEN TRUMPED", "release_year", "2011" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35749, BRECKIN MEYER 1148, CONFESSIONS 8872, DANCER, TEXAS POP. 81 36212, DRAMA 4108, KANAE MINATO 12106, MATTHEW RHYS 27064, THE SCAPEGOAT src, edge_attr, dst 1148, has_genre, 36212 1148, written_by, 4108 8872, has_genre, 36212 8872, starred_actors, 35749 27064, has_genre, 36212 27064, starred_actors, 12106 Question: In what context are BRECKIN MEYER, KANAE MINATO, and MATTHEW RHYS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRECKIN MEYER", "KANAE MINATO", "MATTHEW RHYS" ], "valid_edges": [ [ "CONFESSIONS", "has_genre", "DRAMA" ], [ "CONFESSIONS", "written_by", "KANAE MINATO" ], [ "DANCER, TEXAS POP. 81", "has_genre", "DRAMA" ], [ "DANCER, TEXAS POP. 81", "starred_actors", "BRECKIN MEYER" ], [ "THE SCAPEGOAT", "has_genre", "DRAMA" ], [ "THE SCAPEGOAT", "starred_actors", "MATTHEW RHYS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13805, BRET ROBERTS 30463, COMEDY 5870, HORROR 13963, JOHNNY VEGAS 35018, KING COBRA 19020, NATIONAL LAMPOON PRESENTS DORM DAZE 34937, PATRICK CASEY 2327, SCOTT HILLENBRAND 39218, SEX LIVES OF THE POTATO MEN 8494, THE VIOLENT KIND 14057, TRANSYLMANIA src, edge_attr, dst 35018, directed_by, 2327 35018, has_genre, 5870 35018, starred_actors, 2327 35018, written_by, 2327 19020, directed_by, 2327 19020, has_genre, 30463 19020, written_by, 34937 39218, has_genre, 30463 39218, starred_actors, 13963 8494, has_genre, 5870 8494, starred_actors, 13805 14057, directed_by, 2327 14057, has_genre, 30463 14057, has_genre, 5870 14057, starred_actors, 34937 14057, written_by, 34937 Question: In what context are BRET ROBERTS, JOHNNY VEGAS, and SCOTT HILLENBRAND connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BRET ROBERTS", "JOHNNY VEGAS", "SCOTT HILLENBRAND" ], "valid_edges": [ [ "KING COBRA", "directed_by", "SCOTT HILLENBRAND" ], [ "KING COBRA", "has_genre", "HORROR" ], [ "KING COBRA", "starred_actors", "SCOTT HILLENBRAND" ], [ "KING COBRA", "written_by", "SCOTT HILLENBRAND" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "directed_by", "SCOTT HILLENBRAND" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "has_genre", "COMEDY" ], [ "NATIONAL LAMPOON PRESENTS DORM DAZE", "written_by", "PATRICK CASEY" ], [ "SEX LIVES OF THE POTATO MEN", "has_genre", "COMEDY" ], [ "SEX LIVES OF THE POTATO MEN", "starred_actors", "JOHNNY VEGAS" ], [ "THE VIOLENT KIND", "has_genre", "HORROR" ], [ "THE VIOLENT KIND", "starred_actors", "BRET ROBERTS" ], [ "TRANSYLMANIA", "directed_by", "SCOTT HILLENBRAND" ], [ "TRANSYLMANIA", "has_genre", "COMEDY" ], [ "TRANSYLMANIA", "has_genre", "HORROR" ], [ "TRANSYLMANIA", "starred_actors", "PATRICK CASEY" ], [ "TRANSYLMANIA", "written_by", "PATRICK CASEY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 20981, A WOMAN OF AFFAIRS 10340, ADRIFT 37608, AUSTRALIA 24556, DOWNSTAIRS 36212, DRAMA 29560, HE WHO GETS SLAPPED 5667, JOHN GILBERT 16469, LINH DAN PHAM 9235, MR. NOBODY 23155, WALKABOUT src, edge_attr, dst 20981, has_genre, 36212 20981, starred_actors, 5667 10340, has_genre, 36212 10340, release_year, 27261 10340, starred_actors, 16469 37608, has_genre, 36212 37608, has_tags, 37608 24556, has_genre, 36212 24556, starred_actors, 5667 24556, written_by, 5667 29560, has_genre, 36212 29560, starred_actors, 5667 9235, has_genre, 36212 9235, release_year, 27261 9235, starred_actors, 16469 23155, has_tags, 37608 Question: For what reason are JOHN GILBERT, LINH DAN PHAM, and WALKABOUT associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOHN GILBERT", "LINH DAN PHAM", "WALKABOUT" ], "valid_edges": [ [ "A WOMAN OF AFFAIRS", "has_genre", "DRAMA" ], [ "A WOMAN OF AFFAIRS", "starred_actors", "JOHN GILBERT" ], [ "ADRIFT", "has_genre", "DRAMA" ], [ "ADRIFT", "release_year", "2009" ], [ "ADRIFT", "starred_actors", "LINH DAN PHAM" ], [ "AUSTRALIA", "has_genre", "DRAMA" ], [ "AUSTRALIA", "has_tags", "AUSTRALIA" ], [ "DOWNSTAIRS", "has_genre", "DRAMA" ], [ "DOWNSTAIRS", "starred_actors", "JOHN GILBERT" ], [ "DOWNSTAIRS", "written_by", "JOHN GILBERT" ], [ "HE WHO GETS SLAPPED", "has_genre", "DRAMA" ], [ "HE WHO GETS SLAPPED", "starred_actors", "JOHN GILBERT" ], [ "MR. NOBODY", "has_genre", "DRAMA" ], [ "MR. NOBODY", "release_year", "2009" ], [ "MR. NOBODY", "starred_actors", "LINH DAN PHAM" ], [ "WALKABOUT", "has_tags", "AUSTRALIA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 12569, ACTS OF WORSHIP 29180, CHU CHIN CHOW 30463, COMEDY 14627, GEORGE ROBEY 30384, JUMP TOMORROW 28958, MICHAEL HYATT 19692, TUNDE ADEBIMPE src, edge_attr, dst 12569, release_year, 13408 12569, starred_actors, 28958 29180, has_genre, 30463 29180, starred_actors, 14627 30384, has_genre, 30463 30384, release_year, 13408 30384, starred_actors, 19692 Question: In what context are GEORGE ROBEY, MICHAEL HYATT, and TUNDE ADEBIMPE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GEORGE ROBEY", "MICHAEL HYATT", "TUNDE ADEBIMPE" ], "valid_edges": [ [ "ACTS OF WORSHIP", "release_year", "2001" ], [ "ACTS OF WORSHIP", "starred_actors", "MICHAEL HYATT" ], [ "CHU CHIN CHOW", "has_genre", "COMEDY" ], [ "CHU CHIN CHOW", "starred_actors", "GEORGE ROBEY" ], [ "JUMP TOMORROW", "has_genre", "COMEDY" ], [ "JUMP TOMORROW", "release_year", "2001" ], [ "JUMP TOMORROW", "starred_actors", "TUNDE ADEBIMPE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 27261, 2009 39750, ALIENS 4652, ANGELA SHELTON 23390, ARCADE 34587, BAD TASTE 23100, BODY BAGS 25126, BODY SNATCHERS 2747, CARNOSAUR 30463, COMEDY 29377, CRONOS 6692, DISTRICT 9 36212, DRAMA 5372, FORGOTTEN SILVER 28939, FRAN WALSH 17870, GHOST IN THE MACHINE 20214, HEAVENLY CREATURES 5870, HORROR 19098, KING KONG 32278, LEPRECHAUN 39670, MAN'S BEST FRIEND 9131, MEET THE FEEBLES 21188, MR. JONES 8519, MY BOYFRIEND'S BACK 25168, NEW ZEALAND 15793, NIGHT TERRORS 14075, PETER JACKSON 29013, PUPPET MASTER 4 23898, SUPERNATURAL 25979, THE DARK HALF 21684, THE FRIGHTENERS 26894, THE LOVELY BONES 13101, TUMBLEWEEDS src, edge_attr, dst 39750, has_tags, 5870 23390, has_genre, 5870 23390, release_year, 24438 34587, directed_by, 14075 34587, has_genre, 30463 34587, has_genre, 5870 34587, has_tags, 39750 34587, has_tags, 25168 34587, has_tags, 14075 34587, written_by, 14075 23100, has_genre, 5870 23100, release_year, 24438 25126, has_genre, 5870 25126, release_year, 24438 2747, has_genre, 5870 2747, release_year, 24438 29377, has_genre, 5870 29377, release_year, 24438 6692, has_tags, 14075 6692, release_year, 27261 5372, directed_by, 14075 5372, has_tags, 25168 5372, has_tags, 14075 5372, starred_actors, 14075 5372, written_by, 14075 17870, has_genre, 5870 17870, release_year, 24438 20214, directed_by, 14075 20214, has_genre, 36212 20214, has_tags, 25168 20214, has_tags, 14075 20214, written_by, 28939 20214, written_by, 14075 19098, directed_by, 14075 19098, has_tags, 19098 19098, has_tags, 14075 19098, written_by, 14075 32278, has_genre, 5870 32278, has_tags, 5870 32278, release_year, 24438 39670, has_genre, 5870 39670, release_year, 24438 9131, directed_by, 14075 9131, has_genre, 30463 9131, has_tags, 25168 9131, has_tags, 14075 9131, written_by, 28939 9131, written_by, 14075 21188, has_genre, 5870 21188, release_year, 24438 8519, has_genre, 5870 8519, release_year, 24438 15793, has_genre, 5870 15793, release_year, 24438 29013, has_genre, 5870 29013, release_year, 24438 25979, has_genre, 5870 25979, release_year, 24438 21684, directed_by, 14075 21684, has_genre, 30463 21684, has_genre, 5870 21684, has_tags, 14075 21684, has_tags, 23898 21684, written_by, 28939 21684, written_by, 14075 26894, directed_by, 14075 26894, has_genre, 36212 26894, has_tags, 14075 26894, has_tags, 23898 26894, release_year, 27261 26894, written_by, 14075 13101, has_genre, 30463 13101, has_genre, 36212 13101, written_by, 4652 Question: For what reason are ANGELA SHELTON, PETER JACKSON, and PUPPET MASTER 4 associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANGELA SHELTON", "PETER JACKSON", "PUPPET MASTER 4" ], "valid_edges": [ [ "ALIENS", "has_tags", "HORROR" ], [ "ARCADE", "has_genre", "HORROR" ], [ "ARCADE", "release_year", "1993" ], [ "BAD TASTE", "directed_by", "PETER JACKSON" ], [ "BAD TASTE", "has_genre", "COMEDY" ], [ "BAD TASTE", "has_genre", "HORROR" ], [ "BAD TASTE", "has_tags", "ALIENS" ], [ "BAD TASTE", "has_tags", "NEW ZEALAND" ], [ "BAD TASTE", "has_tags", "PETER JACKSON" ], [ "BAD TASTE", "written_by", "PETER JACKSON" ], [ "BODY BAGS", "has_genre", "HORROR" ], [ "BODY BAGS", "release_year", "1993" ], [ "BODY SNATCHERS", "has_genre", "HORROR" ], [ "BODY SNATCHERS", "release_year", "1993" ], [ "CARNOSAUR", "has_genre", "HORROR" ], [ "CARNOSAUR", "release_year", "1993" ], [ "CRONOS", "has_genre", "HORROR" ], [ "CRONOS", "release_year", "1993" ], [ "DISTRICT 9", "has_tags", "PETER JACKSON" ], [ "DISTRICT 9", "release_year", "2009" ], [ "FORGOTTEN SILVER", "directed_by", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "has_tags", "NEW ZEALAND" ], [ "FORGOTTEN SILVER", "has_tags", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "starred_actors", "PETER JACKSON" ], [ "FORGOTTEN SILVER", "written_by", "PETER JACKSON" ], [ "GHOST IN THE MACHINE", "has_genre", "HORROR" ], [ "GHOST IN THE MACHINE", "release_year", "1993" ], [ "HEAVENLY CREATURES", "directed_by", "PETER JACKSON" ], [ "HEAVENLY CREATURES", "has_genre", "DRAMA" ], [ "HEAVENLY CREATURES", "has_tags", "NEW ZEALAND" ], [ "HEAVENLY CREATURES", "has_tags", "PETER JACKSON" ], [ "HEAVENLY CREATURES", "written_by", "FRAN WALSH" ], [ "HEAVENLY CREATURES", "written_by", "PETER JACKSON" ], [ "KING KONG", "directed_by", "PETER JACKSON" ], [ "KING KONG", "has_tags", "KING KONG" ], [ "KING KONG", "has_tags", "PETER JACKSON" ], [ "KING KONG", "written_by", "PETER JACKSON" ], [ "LEPRECHAUN", "has_genre", "HORROR" ], [ "LEPRECHAUN", "has_tags", "HORROR" ], [ "LEPRECHAUN", "release_year", "1993" ], [ "MAN'S BEST FRIEND", "has_genre", "HORROR" ], [ "MAN'S BEST FRIEND", "release_year", "1993" ], [ "MEET THE FEEBLES", "directed_by", "PETER JACKSON" ], [ "MEET THE FEEBLES", "has_genre", "COMEDY" ], [ "MEET THE FEEBLES", "has_tags", "NEW ZEALAND" ], [ "MEET THE FEEBLES", "has_tags", "PETER JACKSON" ], [ "MEET THE FEEBLES", "written_by", "FRAN WALSH" ], [ "MEET THE FEEBLES", "written_by", "PETER JACKSON" ], [ "MR. JONES", "has_genre", "HORROR" ], [ "MR. JONES", "release_year", "1993" ], [ "MY BOYFRIEND'S BACK", "has_genre", "HORROR" ], [ "MY BOYFRIEND'S BACK", "release_year", "1993" ], [ "NIGHT TERRORS", "has_genre", "HORROR" ], [ "NIGHT TERRORS", "release_year", "1993" ], [ "PUPPET MASTER 4", "has_genre", "HORROR" ], [ "PUPPET MASTER 4", "release_year", "1993" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "release_year", "1993" ], [ "THE FRIGHTENERS", "directed_by", "PETER JACKSON" ], [ "THE FRIGHTENERS", "has_genre", "COMEDY" ], [ "THE FRIGHTENERS", "has_genre", "HORROR" ], [ "THE FRIGHTENERS", "has_tags", "PETER JACKSON" ], [ "THE FRIGHTENERS", "has_tags", "SUPERNATURAL" ], [ "THE FRIGHTENERS", "written_by", "FRAN WALSH" ], [ "THE FRIGHTENERS", "written_by", "PETER JACKSON" ], [ "THE LOVELY BONES", "directed_by", "PETER JACKSON" ], [ "THE LOVELY BONES", "has_genre", "DRAMA" ], [ "THE LOVELY BONES", "has_tags", "PETER JACKSON" ], [ "THE LOVELY BONES", "has_tags", "SUPERNATURAL" ], [ "THE LOVELY BONES", "release_year", "2009" ], [ "THE LOVELY BONES", "written_by", "PETER JACKSON" ], [ "TUMBLEWEEDS", "has_genre", "COMEDY" ], [ "TUMBLEWEEDS", "has_genre", "DRAMA" ], [ "TUMBLEWEEDS", "written_by", "ANGELA SHELTON" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29145, 10 ITEMS OR LESS 35845, 2006 18243, A SCANNER DARKLY 23754, AFTER THE WEDDING 6938, ALPHA DOG 8229, APOCALYPTO 24301, ART SCHOOL CONFIDENTIAL 18820, ASK THE DUST 24366, BABEL 36593, BLACK CHRISTMAS 16664, BLOOD DIAMOND 10531, BOBBY 867, BREAKING AND ENTERING 12724, BROKEN SKY 17899, BUG 33360, CANDY 22435, CHILDREN OF MEN 21625, CLERKS II 37750, CRANK 15115, CURSE OF THE GOLDEN FLOWER 3567, DAYS OF GLORY 24699, ELEGY 8262, FAMILY LAW 13766, FAST FOOD NATION 13893, FIDO 18217, FIND ME GUILTY 10315, FLAGS OF OUR FATHERS 39988, FRIENDS WITH MONEY 7879, HALF NELSON 26170, HOLLYWOODLAND 17120, INFAMOUS 19637, INLAND EMPIRE 7264, INSIDE MAN 18934, LETTERS FROM IWO JIMA 11277, LITTLE CHILDREN 24376, LITTLE MISS SUNSHINE 39673, LOS OLVIDADOS 33950, LUCKY NUMBER SLEVIN 38677, MIAMI VICE 3519, MY NAME IS JUANI 39852, PAN'S LABYRINTH 3451, PAPRIKA 24369, QUINCEAÑERA 13081, R 18480, RENAISSANCE 5766, RUNNING WITH SCISSORS 17383, SHERRYBABY 26930, SLITHER 12333, SMOKIN' ACES 7556, SPANISH 37498, TENACIOUS D IN THE PICK OF DESTINY 24057, THE BACKWOODS 11948, THE BLACK DAHLIA 31353, THE CONTRACT 1059, THE DA VINCI CODE 18997, THE DEPARTED 1723, THE FALL 4662, THE GOOD GERMAN 15862, THE GOOD SHEPHERD 32459, THE HAMMER 31309, THE HOAX 2467, THE LAST KING OF SCOTLAND 14315, THE LIVES OF OTHERS 22880, THE MACHINIST 17393, THE NIGHT LISTENER 1846, THE ONE PERCENT 956, THE ORPHANAGE 11383, THE SCIENCE OF SLEEP 37148, THE SECRET IN THEIR EYES 8334, TRANSSIBERIAN 25806, UNITED 93 23568, VANILLA SKY 36753, VENUS 35728, VOLVER src, edge_attr, dst 29145, has_tags, 13081 29145, release_year, 35845 18243, has_tags, 13081 18243, release_year, 35845 23754, has_tags, 13081 23754, release_year, 35845 6938, has_tags, 13081 6938, release_year, 35845 8229, has_tags, 13081 8229, release_year, 35845 24301, has_tags, 13081 24301, release_year, 35845 18820, has_tags, 13081 18820, release_year, 35845 24366, has_tags, 13081 24366, release_year, 35845 36593, has_tags, 13081 36593, release_year, 35845 16664, has_tags, 13081 16664, release_year, 35845 10531, has_tags, 13081 10531, release_year, 35845 867, has_tags, 13081 867, release_year, 35845 12724, in_language, 7556 12724, release_year, 35845 17899, has_tags, 13081 17899, release_year, 35845 33360, has_tags, 13081 33360, release_year, 35845 22435, has_tags, 13081 22435, release_year, 35845 21625, has_tags, 13081 21625, release_year, 35845 37750, has_tags, 13081 37750, release_year, 35845 15115, has_tags, 13081 15115, release_year, 35845 3567, has_tags, 13081 3567, release_year, 35845 24699, has_tags, 13081 24699, in_language, 7556 8262, in_language, 7556 8262, release_year, 35845 13766, has_tags, 13081 13766, release_year, 35845 13893, has_tags, 13081 13893, release_year, 35845 18217, has_tags, 13081 18217, release_year, 35845 10315, has_tags, 13081 10315, release_year, 35845 39988, has_tags, 13081 39988, release_year, 35845 7879, has_tags, 13081 7879, release_year, 35845 26170, has_tags, 13081 26170, release_year, 35845 17120, has_tags, 13081 17120, release_year, 35845 19637, has_tags, 13081 19637, release_year, 35845 7264, has_tags, 13081 7264, release_year, 35845 18934, has_tags, 13081 18934, release_year, 35845 11277, has_tags, 13081 11277, release_year, 35845 24376, has_tags, 13081 24376, release_year, 35845 39673, in_language, 7556 33950, has_tags, 13081 33950, release_year, 35845 38677, has_tags, 13081 38677, release_year, 35845 3519, in_language, 7556 3519, release_year, 35845 39852, has_tags, 13081 39852, has_tags, 7556 39852, in_language, 7556 39852, release_year, 35845 3451, has_tags, 13081 3451, release_year, 35845 24369, in_language, 7556 24369, release_year, 35845 18480, has_tags, 13081 18480, release_year, 35845 5766, has_tags, 13081 5766, release_year, 35845 17383, has_tags, 13081 17383, release_year, 35845 26930, has_tags, 13081 26930, release_year, 35845 12333, has_tags, 13081 12333, release_year, 35845 37498, has_tags, 13081 37498, release_year, 35845 24057, in_language, 7556 24057, release_year, 35845 11948, has_tags, 13081 11948, release_year, 35845 31353, has_tags, 13081 31353, release_year, 35845 1059, has_tags, 13081 1059, release_year, 35845 18997, has_tags, 13081 18997, release_year, 35845 1723, has_tags, 13081 1723, release_year, 35845 4662, has_tags, 13081 4662, release_year, 35845 15862, has_tags, 13081 15862, release_year, 35845 32459, has_tags, 13081 31309, has_tags, 13081 31309, release_year, 35845 2467, has_tags, 13081 2467, release_year, 35845 14315, has_tags, 13081 14315, release_year, 35845 22880, has_tags, 13081 22880, in_language, 7556 17393, has_tags, 13081 17393, release_year, 35845 1846, release_year, 35845 956, has_tags, 13081 956, has_tags, 7556 956, in_language, 7556 11383, has_tags, 13081 11383, release_year, 35845 37148, has_tags, 13081 37148, has_tags, 7556 37148, in_language, 7556 8334, has_tags, 13081 8334, in_language, 7556 25806, has_tags, 13081 25806, release_year, 35845 23568, has_tags, 13081 23568, in_language, 7556 36753, has_tags, 13081 36753, release_year, 35845 35728, has_tags, 13081 35728, has_tags, 7556 35728, in_language, 7556 35728, release_year, 35845 Question: How are LOS OLVIDADOS, THE HAMMER, and THE ONE PERCENT related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LOS OLVIDADOS", "THE HAMMER", "THE ONE PERCENT" ], "valid_edges": [ [ "10 ITEMS OR LESS", "has_tags", "R" ], [ "10 ITEMS OR LESS", "release_year", "2006" ], [ "A SCANNER DARKLY", "has_tags", "R" ], [ "A SCANNER DARKLY", "release_year", "2006" ], [ "AFTER THE WEDDING", "has_tags", "R" ], [ "AFTER THE WEDDING", "release_year", "2006" ], [ "ALPHA DOG", "has_tags", "R" ], [ "ALPHA DOG", "release_year", "2006" ], [ "APOCALYPTO", "has_tags", "R" ], [ "APOCALYPTO", "release_year", "2006" ], [ "ART SCHOOL CONFIDENTIAL", "has_tags", "R" ], [ "ART SCHOOL CONFIDENTIAL", "release_year", "2006" ], [ "ASK THE DUST", "has_tags", "R" ], [ "ASK THE DUST", "release_year", "2006" ], [ "BABEL", "has_tags", "R" ], [ "BABEL", "release_year", "2006" ], [ "BLACK CHRISTMAS", "has_tags", "R" ], [ "BLACK CHRISTMAS", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "R" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "BOBBY", "has_tags", "R" ], [ "BOBBY", "release_year", "2006" ], [ "BREAKING AND ENTERING", "has_tags", "R" ], [ "BREAKING AND ENTERING", "release_year", "2006" ], [ "BROKEN SKY", "in_language", "SPANISH" ], [ "BROKEN SKY", "release_year", "2006" ], [ "BUG", "has_tags", "R" ], [ "BUG", "release_year", "2006" ], [ "CANDY", "has_tags", "R" ], [ "CANDY", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "R" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "CLERKS II", "has_tags", "R" ], [ "CLERKS II", "release_year", "2006" ], [ "CRANK", "has_tags", "R" ], [ "CRANK", "release_year", "2006" ], [ "CURSE OF THE GOLDEN FLOWER", "has_tags", "R" ], [ "CURSE OF THE GOLDEN FLOWER", "release_year", "2006" ], [ "DAYS OF GLORY", "has_tags", "R" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "ELEGY", "has_tags", "R" ], [ "ELEGY", "in_language", "SPANISH" ], [ "FAMILY LAW", "in_language", "SPANISH" ], [ "FAMILY LAW", "release_year", "2006" ], [ "FAST FOOD NATION", "has_tags", "R" ], [ "FAST FOOD NATION", "release_year", "2006" ], [ "FIDO", "has_tags", "R" ], [ "FIDO", "release_year", "2006" ], [ "FIND ME GUILTY", "has_tags", "R" ], [ "FIND ME GUILTY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_tags", "R" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FRIENDS WITH MONEY", "has_tags", "R" ], [ "FRIENDS WITH MONEY", "release_year", "2006" ], [ "HALF NELSON", "has_tags", "R" ], [ "HALF NELSON", "release_year", "2006" ], [ "HOLLYWOODLAND", "has_tags", "R" ], [ "HOLLYWOODLAND", "release_year", "2006" ], [ "INFAMOUS", "has_tags", "R" ], [ "INFAMOUS", "release_year", "2006" ], [ "INLAND EMPIRE", "has_tags", "R" ], [ "INLAND EMPIRE", "release_year", "2006" ], [ "INSIDE MAN", "has_tags", "R" ], [ "INSIDE MAN", "release_year", "2006" ], [ "LETTERS FROM IWO JIMA", "has_tags", "R" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "LITTLE CHILDREN", "has_tags", "R" ], [ "LITTLE CHILDREN", "release_year", "2006" ], [ "LITTLE MISS SUNSHINE", "has_tags", "R" ], [ "LITTLE MISS SUNSHINE", "release_year", "2006" ], [ "LOS OLVIDADOS", "in_language", "SPANISH" ], [ "LUCKY NUMBER SLEVIN", "has_tags", "R" ], [ "LUCKY NUMBER SLEVIN", "release_year", "2006" ], [ "MIAMI VICE", "has_tags", "R" ], [ "MIAMI VICE", "release_year", "2006" ], [ "MY NAME IS JUANI", "in_language", "SPANISH" ], [ "MY NAME IS JUANI", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_tags", "R" ], [ "PAN'S LABYRINTH", "has_tags", "SPANISH" ], [ "PAN'S LABYRINTH", "in_language", "SPANISH" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PAPRIKA", "has_tags", "R" ], [ "PAPRIKA", "release_year", "2006" ], [ "QUINCEAÑERA", "in_language", "SPANISH" ], [ "QUINCEAÑERA", "release_year", "2006" ], [ "RENAISSANCE", "has_tags", "R" ], [ "RENAISSANCE", "release_year", "2006" ], [ "RUNNING WITH SCISSORS", "has_tags", "R" ], [ "RUNNING WITH SCISSORS", "release_year", "2006" ], [ "SHERRYBABY", "has_tags", "R" ], [ "SHERRYBABY", "release_year", "2006" ], [ "SLITHER", "has_tags", "R" ], [ "SLITHER", "release_year", "2006" ], [ "SMOKIN' ACES", "has_tags", "R" ], [ "SMOKIN' ACES", "release_year", "2006" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "has_tags", "R" ], [ "TENACIOUS D IN THE PICK OF DESTINY", "release_year", "2006" ], [ "THE BACKWOODS", "in_language", "SPANISH" ], [ "THE BACKWOODS", "release_year", "2006" ], [ "THE BLACK DAHLIA", "has_tags", "R" ], [ "THE BLACK DAHLIA", "release_year", "2006" ], [ "THE CONTRACT", "has_tags", "R" ], [ "THE CONTRACT", "release_year", "2006" ], [ "THE DA VINCI CODE", "has_tags", "R" ], [ "THE DA VINCI CODE", "release_year", "2006" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "release_year", "2006" ], [ "THE FALL", "has_tags", "R" ], [ "THE FALL", "release_year", "2006" ], [ "THE GOOD GERMAN", "has_tags", "R" ], [ "THE GOOD GERMAN", "release_year", "2006" ], [ "THE GOOD SHEPHERD", "has_tags", "R" ], [ "THE GOOD SHEPHERD", "release_year", "2006" ], [ "THE HAMMER", "has_tags", "R" ], [ "THE HOAX", "has_tags", "R" ], [ "THE HOAX", "release_year", "2006" ], [ "THE LAST KING OF SCOTLAND", "has_tags", "R" ], [ "THE LAST KING OF SCOTLAND", "release_year", "2006" ], [ "THE LIVES OF OTHERS", "has_tags", "R" ], [ "THE LIVES OF OTHERS", "release_year", "2006" ], [ "THE MACHINIST", "has_tags", "R" ], [ "THE MACHINIST", "in_language", "SPANISH" ], [ "THE NIGHT LISTENER", "has_tags", "R" ], [ "THE NIGHT LISTENER", "release_year", "2006" ], [ "THE ONE PERCENT", "release_year", "2006" ], [ "THE ORPHANAGE", "has_tags", "R" ], [ "THE ORPHANAGE", "has_tags", "SPANISH" ], [ "THE ORPHANAGE", "in_language", "SPANISH" ], [ "THE SCIENCE OF SLEEP", "has_tags", "R" ], [ "THE SCIENCE OF SLEEP", "release_year", "2006" ], [ "THE SECRET IN THEIR EYES", "has_tags", "R" ], [ "THE SECRET IN THEIR EYES", "has_tags", "SPANISH" ], [ "THE SECRET IN THEIR EYES", "in_language", "SPANISH" ], [ "TRANSSIBERIAN", "has_tags", "R" ], [ "TRANSSIBERIAN", "in_language", "SPANISH" ], [ "UNITED 93", "has_tags", "R" ], [ "UNITED 93", "release_year", "2006" ], [ "VANILLA SKY", "has_tags", "R" ], [ "VANILLA SKY", "in_language", "SPANISH" ], [ "VENUS", "has_tags", "R" ], [ "VENUS", "release_year", "2006" ], [ "VOLVER", "has_tags", "R" ], [ "VOLVER", "has_tags", "SPANISH" ], [ "VOLVER", "in_language", "SPANISH" ], [ "VOLVER", "release_year", "2006" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37224, 1990 19905, A TALE OF SPRINGTIME 28725, ANNE TEYSSÈDRE 1856, EUROPA EUROPA 22011, NIGHTBREED 10981, SERIAL KILLER src, edge_attr, dst 19905, release_year, 37224 19905, starred_actors, 28725 1856, release_year, 37224 22011, has_tags, 10981 22011, release_year, 37224 Question: For what reason are ANNE TEYSSÈDRE, EUROPA EUROPA, and SERIAL KILLER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANNE TEYSSÈDRE", "EUROPA EUROPA", "SERIAL KILLER" ], "valid_edges": [ [ "A TALE OF SPRINGTIME", "release_year", "1990" ], [ "A TALE OF SPRINGTIME", "starred_actors", "ANNE TEYSSÈDRE" ], [ "EUROPA EUROPA", "release_year", "1990" ], [ "NIGHTBREED", "has_tags", "SERIAL KILLER" ], [ "NIGHTBREED", "release_year", "1990" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 33645, BILL OBERST JR. 31778, BLACK SHEEP 29691, CHRIS FARLEY 5870, HORROR 9520, JODY LAMBERT 31312, PEOPLE LIKE US 24992, SCARY OR DIE src, edge_attr, dst 31778, has_genre, 5870 31778, has_tags, 29691 31778, starred_actors, 29691 31312, release_year, 658 31312, written_by, 9520 24992, has_genre, 5870 24992, release_year, 658 24992, starred_actors, 33645 Question: For what reason are BILL OBERST JR., CHRIS FARLEY, and JODY LAMBERT associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BILL OBERST JR.", "CHRIS FARLEY", "JODY LAMBERT" ], "valid_edges": [ [ "BLACK SHEEP", "has_genre", "HORROR" ], [ "BLACK SHEEP", "has_tags", "CHRIS FARLEY" ], [ "BLACK SHEEP", "starred_actors", "CHRIS FARLEY" ], [ "PEOPLE LIKE US", "release_year", "2012" ], [ "PEOPLE LIKE US", "written_by", "JODY LAMBERT" ], [ "SCARY OR DIE", "has_genre", "HORROR" ], [ "SCARY OR DIE", "release_year", "2012" ], [ "SCARY OR DIE", "starred_actors", "BILL OBERST JR." ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39641, ALONG CAME JONES 24276, CASANOVA BROWN 30463, COMEDY 29757, GARY COOPER 12557, HOW TO MARRY A MILLIONAIRE 34414, KARYN BOSNAK 35230, MICHAEL DUDIKOFF 11190, NUNNALLY JOHNSON 32766, RADIOACTIVE DREAMS 11290, TAKE HER, SHE'S MINE 29742, WHAT'S YOUR NUMBER? src, edge_attr, dst 39641, has_genre, 30463 39641, starred_actors, 29757 39641, written_by, 11190 24276, has_genre, 30463 24276, starred_actors, 29757 24276, written_by, 11190 12557, has_genre, 30463 12557, written_by, 11190 32766, has_genre, 30463 32766, starred_actors, 35230 11290, has_genre, 30463 11290, written_by, 11190 29742, has_genre, 30463 29742, written_by, 34414 Question: In what context are KARYN BOSNAK, MICHAEL DUDIKOFF, and NUNNALLY JOHNSON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KARYN BOSNAK", "MICHAEL DUDIKOFF", "NUNNALLY JOHNSON" ], "valid_edges": [ [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "starred_actors", "GARY COOPER" ], [ "ALONG CAME JONES", "written_by", "NUNNALLY JOHNSON" ], [ "CASANOVA BROWN", "has_genre", "COMEDY" ], [ "CASANOVA BROWN", "starred_actors", "GARY COOPER" ], [ "CASANOVA BROWN", "written_by", "NUNNALLY JOHNSON" ], [ "HOW TO MARRY A MILLIONAIRE", "has_genre", "COMEDY" ], [ "HOW TO MARRY A MILLIONAIRE", "written_by", "NUNNALLY JOHNSON" ], [ "RADIOACTIVE DREAMS", "has_genre", "COMEDY" ], [ "RADIOACTIVE DREAMS", "starred_actors", "MICHAEL DUDIKOFF" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "written_by", "NUNNALLY JOHNSON" ], [ "WHAT'S YOUR NUMBER?", "has_genre", "COMEDY" ], [ "WHAT'S YOUR NUMBER?", "written_by", "KARYN BOSNAK" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 658, 2012 22088, A BRIDGE TOO FAR 25987, A GUY NAMED JOE 23445, A MIDNIGHT CLEAR 27553, ACT OF VALOR 7663, ACTION IN THE NORTH ATLANTIC 22726, ANNE FRANK REMEMBERED 36876, ATTACK 32014, BALLAD OF A SOLDIER 34734, BATTLE OF THE BULGE 12185, BATTLEGROUND 6817, BENNO VIGNY 1912, BEYOND ALL BOUNDARIES 40074, BLACK BOOK 25285, COME AND SEE 10293, CONSPIRACY 4615, DARK BLUE WORLD 18972, DAS BOOT 11363, DEFIANCE 16353, EDGES OF THE LORD 26918, EMPEROR 22028, EMPIRE OF THE SUN 16930, ENEMY AT THE GATES 21289, ENTITY 27958, FIRES ON THE PLAIN 10315, FLAGS OF OUR FATHERS 13834, FLYING TIGERS 39145, FURY 30162, GUADALCANAL DIARY 15765, HAMSUN 33545, HART'S WAR 15343, IN DARKNESS 35518, IN HARM'S WAY 28700, INTO THE WHITE 38574, IT HAPPENED HERE 22012, IVAN'S CHILDHOOD 22167, KING RAT 9595, MEMPHIS BELLE 1422, MOROCCO 5127, MOTHER NIGHT 38294, MRS. MINIVER 20581, OPERATION PACIFIC 16806, PATTON 27373, RED DAWN 17742, RED TAILS 7978, RUROUNI KENSHIN 35586, SAHARA 23006, SANDS OF IWO JIMA 24365, SAVING PRIVATE RYAN 21196, STALAG 17 11124, STALINGRAD 37855, TEA WITH MUSSOLINI 38627, TEN TALL MEN 16103, THE AVENGERS 27210, THE BEST YEARS OF OUR LIVES 7710, THE BIG RED ONE 29788, THE BRIDGE AT REMAGEN 14436, THE BURMESE HARP 36692, THE CAINE MUTINY 828, THE ENEMY BELOW 30507, THE FIGHTING SEABEES 6424, THE GREAT ESCAPE 31393, THE GREAT RAID 405, THE HIDING PLACE 20299, THE HILL 27237, THE LONGEST DAY 30294, THE NIGHT OF THE GENERALS 1195, THE PATIENCE STONE 12614, THE PIANIST 32618, THE RAPE OF EUROPA 2739, THE SAPPHIRES 4962, THE SORROW AND THE PITY 21548, THE SUN 30136, THE THIN RED LINE 35911, THE TUSKEGEE AIRMEN 3123, THEY WERE EXPENDABLE 38352, TWELVE O'CLOCK HIGH 38730, TWO MEN WENT TO WAR 37253, U-571 39558, UNDERGROUND 33011, VALKYRIE 2175, VON RYAN'S EXPRESS 22214, WAR 9159, WAR COMES TO AMERICA 30056, WAR WITCH 5949, WHEN TRUMPETS FADE 23537, WHERE EAGLES DARE 24155, WORLD WAR II 15904, YANKS 16849, ZERO DARK THIRTY src, edge_attr, dst 22088, has_genre, 22214 22088, has_tags, 22214 22088, has_tags, 24155 25987, has_genre, 22214 25987, has_tags, 24155 23445, has_genre, 22214 23445, has_tags, 22214 23445, has_tags, 24155 27553, has_genre, 22214 27553, release_year, 658 7663, has_genre, 22214 7663, has_tags, 24155 22726, has_genre, 22214 22726, has_tags, 24155 36876, has_genre, 22214 36876, has_tags, 24155 32014, has_genre, 22214 32014, has_tags, 24155 34734, has_genre, 22214 34734, has_tags, 24155 12185, has_genre, 22214 12185, has_tags, 22214 12185, has_tags, 24155 1912, has_genre, 22214 1912, has_tags, 24155 40074, has_genre, 22214 40074, has_tags, 24155 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 4615, has_genre, 22214 4615, has_tags, 24155 18972, has_genre, 22214 18972, has_tags, 22214 18972, has_tags, 24155 11363, has_tags, 22214 11363, has_tags, 24155 16353, has_genre, 22214 16353, has_tags, 24155 26918, has_tags, 22214 26918, release_year, 658 22028, has_genre, 22214 22028, has_tags, 22214 22028, has_tags, 24155 16930, has_tags, 22214 16930, has_tags, 24155 21289, release_year, 658 27958, has_genre, 22214 27958, has_tags, 24155 10315, has_genre, 22214 10315, has_tags, 22214 10315, has_tags, 24155 13834, has_genre, 22214 13834, has_tags, 24155 39145, has_genre, 22214 39145, has_tags, 22214 39145, has_tags, 24155 30162, has_genre, 22214 30162, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 33545, has_genre, 22214 33545, has_tags, 24155 15343, has_genre, 22214 15343, has_tags, 22214 15343, has_tags, 24155 35518, has_genre, 22214 35518, has_tags, 24155 28700, has_genre, 22214 28700, release_year, 658 38574, has_genre, 22214 38574, has_tags, 24155 22012, has_genre, 22214 22012, has_tags, 22214 22012, has_tags, 24155 22167, has_genre, 22214 22167, has_tags, 24155 9595, has_genre, 22214 9595, has_tags, 24155 1422, written_by, 6817 5127, has_genre, 22214 5127, has_tags, 24155 38294, has_genre, 22214 38294, has_tags, 24155 20581, has_genre, 22214 20581, has_tags, 24155 16806, has_genre, 22214 16806, has_tags, 22214 16806, has_tags, 24155 27373, has_genre, 22214 27373, has_tags, 22214 27373, release_year, 658 17742, has_tags, 24155 17742, release_year, 658 7978, has_tags, 22214 7978, release_year, 658 35586, has_genre, 22214 35586, has_tags, 24155 23006, has_genre, 22214 23006, has_tags, 24155 24365, has_genre, 22214 24365, has_tags, 22214 24365, has_tags, 24155 21196, has_genre, 22214 21196, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 37855, has_genre, 22214 37855, has_tags, 24155 38627, has_genre, 22214 38627, has_tags, 1422 16103, has_tags, 22214 16103, release_year, 658 27210, has_genre, 22214 27210, has_tags, 24155 7710, has_genre, 22214 7710, has_tags, 24155 29788, has_genre, 22214 29788, has_tags, 24155 14436, has_genre, 22214 14436, has_tags, 24155 36692, has_genre, 22214 36692, has_tags, 24155 828, has_tags, 22214 828, has_tags, 24155 30507, has_genre, 22214 30507, has_tags, 24155 6424, has_tags, 22214 6424, has_tags, 24155 31393, has_genre, 22214 31393, has_tags, 24155 405, has_genre, 22214 405, has_tags, 24155 20299, has_genre, 22214 20299, has_tags, 24155 27237, has_tags, 22214 27237, has_tags, 24155 30294, has_tags, 22214 30294, has_tags, 24155 1195, has_genre, 22214 1195, release_year, 658 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 32618, has_genre, 22214 32618, has_tags, 24155 2739, has_tags, 22214 2739, release_year, 658 4962, has_genre, 22214 4962, has_tags, 24155 21548, has_tags, 22214 21548, has_tags, 24155 30136, has_genre, 22214 30136, has_tags, 22214 30136, has_tags, 24155 35911, has_genre, 22214 35911, has_tags, 24155 3123, has_genre, 22214 3123, has_tags, 24155 38352, has_genre, 22214 38352, has_tags, 24155 38730, has_genre, 22214 38730, has_tags, 24155 37253, has_genre, 22214 37253, has_tags, 22214 37253, has_tags, 24155 39558, has_genre, 22214 39558, has_tags, 24155 33011, has_genre, 22214 33011, has_tags, 24155 2175, has_genre, 22214 2175, has_tags, 24155 9159, has_genre, 22214 9159, has_tags, 24155 30056, has_genre, 22214 30056, release_year, 658 5949, has_genre, 22214 5949, has_tags, 24155 23537, has_genre, 22214 23537, has_tags, 24155 15904, has_genre, 22214 15904, has_tags, 24155 16849, has_tags, 22214 16849, release_year, 658 Question: In what context are BENNO VIGNY, ENTITY, and KING RAT connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BENNO VIGNY", "ENTITY", "KING RAT" ], "valid_edges": [ [ "A BRIDGE TOO FAR", "has_genre", "WAR" ], [ "A BRIDGE TOO FAR", "has_tags", "WAR" ], [ "A BRIDGE TOO FAR", "has_tags", "WORLD WAR II" ], [ "A GUY NAMED JOE", "has_genre", "WAR" ], [ "A GUY NAMED JOE", "has_tags", "WORLD WAR II" ], [ "A MIDNIGHT CLEAR", "has_genre", "WAR" ], [ "A MIDNIGHT CLEAR", "has_tags", "WAR" ], [ "A MIDNIGHT CLEAR", "has_tags", "WORLD WAR II" ], [ "ACT OF VALOR", "has_genre", "WAR" ], [ "ACT OF VALOR", "release_year", "2012" ], [ "ACTION IN THE NORTH ATLANTIC", "has_genre", "WAR" ], [ "ACTION IN THE NORTH ATLANTIC", "has_tags", "WORLD WAR II" ], [ "ANNE FRANK REMEMBERED", "has_genre", "WAR" ], [ "ANNE FRANK REMEMBERED", "has_tags", "WORLD WAR II" ], [ "ATTACK", "has_genre", "WAR" ], [ "ATTACK", "has_tags", "WORLD WAR II" ], [ "BALLAD OF A SOLDIER", "has_genre", "WAR" ], [ "BALLAD OF A SOLDIER", "has_tags", "WORLD WAR II" ], [ "BATTLE OF THE BULGE", "has_genre", "WAR" ], [ "BATTLE OF THE BULGE", "has_tags", "WORLD WAR II" ], [ "BATTLEGROUND", "has_genre", "WAR" ], [ "BATTLEGROUND", "has_tags", "WAR" ], [ "BATTLEGROUND", "has_tags", "WORLD WAR II" ], [ "BEYOND ALL BOUNDARIES", "has_genre", "WAR" ], [ "BEYOND ALL BOUNDARIES", "has_tags", "WORLD WAR II" ], [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "has_tags", "WORLD WAR II" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "DARK BLUE WORLD", "has_genre", "WAR" ], [ "DARK BLUE WORLD", "has_tags", "WORLD WAR II" ], [ "DAS BOOT", "has_genre", "WAR" ], [ "DAS BOOT", "has_tags", "WAR" ], [ "DAS BOOT", "has_tags", "WORLD WAR II" ], [ "DEFIANCE", "has_tags", "WAR" ], [ "DEFIANCE", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "has_genre", "WAR" ], [ "EDGES OF THE LORD", "has_tags", "WORLD WAR II" ], [ "EMPEROR", "has_tags", "WAR" ], [ "EMPEROR", "release_year", "2012" ], [ "EMPIRE OF THE SUN", "has_genre", "WAR" ], [ "EMPIRE OF THE SUN", "has_tags", "WAR" ], [ "EMPIRE OF THE SUN", "has_tags", "WORLD WAR II" ], [ "ENEMY AT THE GATES", "has_tags", "WAR" ], [ "ENEMY AT THE GATES", "has_tags", "WORLD WAR II" ], [ "ENTITY", "release_year", "2012" ], [ "FIRES ON THE PLAIN", "has_genre", "WAR" ], [ "FIRES ON THE PLAIN", "has_tags", "WORLD WAR II" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WORLD WAR II" ], [ "FLYING TIGERS", "has_genre", "WAR" ], [ "FLYING TIGERS", "has_tags", "WORLD WAR II" ], [ "FURY", "has_genre", "WAR" ], [ "FURY", "has_tags", "WAR" ], [ "FURY", "has_tags", "WORLD WAR II" ], [ "GUADALCANAL DIARY", "has_genre", "WAR" ], [ "GUADALCANAL DIARY", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HART'S WAR", "has_genre", "WAR" ], [ "HART'S WAR", "has_tags", "WORLD WAR II" ], [ "IN DARKNESS", "has_genre", "WAR" ], [ "IN DARKNESS", "has_tags", "WAR" ], [ "IN DARKNESS", "has_tags", "WORLD WAR II" ], [ "IN HARM'S WAY", "has_genre", "WAR" ], [ "IN HARM'S WAY", "has_tags", "WORLD WAR II" ], [ "INTO THE WHITE", "has_genre", "WAR" ], [ "INTO THE WHITE", "release_year", "2012" ], [ "IT HAPPENED HERE", "has_genre", "WAR" ], [ "IT HAPPENED HERE", "has_tags", "WORLD WAR II" ], [ "IVAN'S CHILDHOOD", "has_genre", "WAR" ], [ "IVAN'S CHILDHOOD", "has_tags", "WAR" ], [ "IVAN'S CHILDHOOD", "has_tags", "WORLD WAR II" ], [ "KING RAT", "has_genre", "WAR" ], [ "KING RAT", "has_tags", "WORLD WAR II" ], [ "MEMPHIS BELLE", "has_genre", "WAR" ], [ "MEMPHIS BELLE", "has_tags", "WORLD WAR II" ], [ "MOROCCO", "written_by", "BENNO VIGNY" ], [ "MOTHER NIGHT", "has_genre", "WAR" ], [ "MOTHER NIGHT", "has_tags", "WORLD WAR II" ], [ "MRS. MINIVER", "has_genre", "WAR" ], [ "MRS. MINIVER", "has_tags", "WORLD WAR II" ], [ "OPERATION PACIFIC", "has_genre", "WAR" ], [ "OPERATION PACIFIC", "has_tags", "WORLD WAR II" ], [ "PATTON", "has_genre", "WAR" ], [ "PATTON", "has_tags", "WAR" ], [ "PATTON", "has_tags", "WORLD WAR II" ], [ "RED DAWN", "has_genre", "WAR" ], [ "RED DAWN", "has_tags", "WAR" ], [ "RED DAWN", "release_year", "2012" ], [ "RED TAILS", "has_tags", "WORLD WAR II" ], [ "RED TAILS", "release_year", "2012" ], [ "RUROUNI KENSHIN", "has_tags", "WAR" ], [ "RUROUNI KENSHIN", "release_year", "2012" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "SANDS OF IWO JIMA", "has_genre", "WAR" ], [ "SANDS OF IWO JIMA", "has_tags", "WORLD WAR II" ], [ "SAVING PRIVATE RYAN", "has_genre", "WAR" ], [ "SAVING PRIVATE RYAN", "has_tags", "WAR" ], [ "SAVING PRIVATE RYAN", "has_tags", "WORLD WAR II" ], [ "STALAG 17", "has_genre", "WAR" ], [ "STALAG 17", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "TEA WITH MUSSOLINI", "has_genre", "WAR" ], [ "TEA WITH MUSSOLINI", "has_tags", "WORLD WAR II" ], [ "TEN TALL MEN", "has_genre", "WAR" ], [ "TEN TALL MEN", "has_tags", "MOROCCO" ], [ "THE AVENGERS", "has_tags", "WAR" ], [ "THE AVENGERS", "release_year", "2012" ], [ "THE BEST YEARS OF OUR LIVES", "has_genre", "WAR" ], [ "THE BEST YEARS OF OUR LIVES", "has_tags", "WORLD WAR II" ], [ "THE BIG RED ONE", "has_genre", "WAR" ], [ "THE BIG RED ONE", "has_tags", "WORLD WAR II" ], [ "THE BRIDGE AT REMAGEN", "has_genre", "WAR" ], [ "THE BRIDGE AT REMAGEN", "has_tags", "WORLD WAR II" ], [ "THE BURMESE HARP", "has_genre", "WAR" ], [ "THE BURMESE HARP", "has_tags", "WORLD WAR II" ], [ "THE CAINE MUTINY", "has_genre", "WAR" ], [ "THE CAINE MUTINY", "has_tags", "WORLD WAR II" ], [ "THE ENEMY BELOW", "has_tags", "WAR" ], [ "THE ENEMY BELOW", "has_tags", "WORLD WAR II" ], [ "THE FIGHTING SEABEES", "has_genre", "WAR" ], [ "THE FIGHTING SEABEES", "has_tags", "WORLD WAR II" ], [ "THE GREAT ESCAPE", "has_tags", "WAR" ], [ "THE GREAT ESCAPE", "has_tags", "WORLD WAR II" ], [ "THE GREAT RAID", "has_genre", "WAR" ], [ "THE GREAT RAID", "has_tags", "WORLD WAR II" ], [ "THE HIDING PLACE", "has_genre", "WAR" ], [ "THE HIDING PLACE", "has_tags", "WORLD WAR II" ], [ "THE HILL", "has_genre", "WAR" ], [ "THE HILL", "has_tags", "WORLD WAR II" ], [ "THE LONGEST DAY", "has_tags", "WAR" ], [ "THE LONGEST DAY", "has_tags", "WORLD WAR II" ], [ "THE NIGHT OF THE GENERALS", "has_tags", "WAR" ], [ "THE NIGHT OF THE GENERALS", "has_tags", "WORLD WAR II" ], [ "THE PATIENCE STONE", "has_genre", "WAR" ], [ "THE PATIENCE STONE", "release_year", "2012" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "THE RAPE OF EUROPA", "has_genre", "WAR" ], [ "THE RAPE OF EUROPA", "has_tags", "WORLD WAR II" ], [ "THE SAPPHIRES", "has_tags", "WAR" ], [ "THE SAPPHIRES", "release_year", "2012" ], [ "THE SORROW AND THE PITY", "has_genre", "WAR" ], [ "THE SORROW AND THE PITY", "has_tags", "WORLD WAR II" ], [ "THE SUN", "has_tags", "WAR" ], [ "THE SUN", "has_tags", "WORLD WAR II" ], [ "THE THIN RED LINE", "has_genre", "WAR" ], [ "THE THIN RED LINE", "has_tags", "WAR" ], [ "THE THIN RED LINE", "has_tags", "WORLD WAR II" ], [ "THE TUSKEGEE AIRMEN", "has_genre", "WAR" ], [ "THE TUSKEGEE AIRMEN", "has_tags", "WORLD WAR II" ], [ "THEY WERE EXPENDABLE", "has_genre", "WAR" ], [ "THEY WERE EXPENDABLE", "has_tags", "WORLD WAR II" ], [ "TWELVE O'CLOCK HIGH", "has_genre", "WAR" ], [ "TWELVE O'CLOCK HIGH", "has_tags", "WORLD WAR II" ], [ "TWO MEN WENT TO WAR", "has_genre", "WAR" ], [ "TWO MEN WENT TO WAR", "has_tags", "WORLD WAR II" ], [ "U-571", "has_genre", "WAR" ], [ "U-571", "has_tags", "WAR" ], [ "U-571", "has_tags", "WORLD WAR II" ], [ "UNDERGROUND", "has_genre", "WAR" ], [ "UNDERGROUND", "has_tags", "WORLD WAR II" ], [ "VALKYRIE", "has_genre", "WAR" ], [ "VALKYRIE", "has_tags", "WORLD WAR II" ], [ "VON RYAN'S EXPRESS", "has_genre", "WAR" ], [ "VON RYAN'S EXPRESS", "has_tags", "WORLD WAR II" ], [ "WAR COMES TO AMERICA", "has_genre", "WAR" ], [ "WAR COMES TO AMERICA", "has_tags", "WORLD WAR II" ], [ "WAR WITCH", "has_genre", "WAR" ], [ "WAR WITCH", "release_year", "2012" ], [ "WHEN TRUMPETS FADE", "has_genre", "WAR" ], [ "WHEN TRUMPETS FADE", "has_tags", "WORLD WAR II" ], [ "WHERE EAGLES DARE", "has_genre", "WAR" ], [ "WHERE EAGLES DARE", "has_tags", "WORLD WAR II" ], [ "YANKS", "has_genre", "WAR" ], [ "YANKS", "has_tags", "WORLD WAR II" ], [ "ZERO DARK THIRTY", "has_tags", "WAR" ], [ "ZERO DARK THIRTY", "release_year", "2012" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 33511, DRACULA UNTOLD 26691, FREEZER 4336, GARY SHORE 11593, JUSTIN LADER 11121, MIKAEL SALOMON 22108, THE ONE I LOVE src, edge_attr, dst 33511, directed_by, 4336 33511, release_year, 9377 26691, directed_by, 11121 26691, release_year, 9377 22108, release_year, 9377 22108, written_by, 11593 Question: In what context are GARY SHORE, JUSTIN LADER, and MIKAEL SALOMON connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GARY SHORE", "JUSTIN LADER", "MIKAEL SALOMON" ], "valid_edges": [ [ "DRACULA UNTOLD", "directed_by", "GARY SHORE" ], [ "DRACULA UNTOLD", "release_year", "2014" ], [ "FREEZER", "directed_by", "MIKAEL SALOMON" ], [ "FREEZER", "release_year", "2014" ], [ "THE ONE I LOVE", "release_year", "2014" ], [ "THE ONE I LOVE", "written_by", "JUSTIN LADER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3702, 1995 16785, HENRY KING 21518, HONEY, I SHRUNK THE KIDS 34716, JOAN CHEN 21580, KIDS 33783, KRISTINE SUTHERLAND 30583, THE GUNFIGHTER 3579, THE HUNTED 37284, THE SUN ALSO RISES src, edge_attr, dst 21518, has_tags, 21580 21518, starred_actors, 33783 21580, release_year, 3702 30583, directed_by, 16785 30583, has_tags, 16785 3579, release_year, 3702 3579, starred_actors, 34716 37284, directed_by, 16785 37284, starred_actors, 34716 Question: How are KRISTINE SUTHERLAND, THE GUNFIGHTER, and THE HUNTED related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "KRISTINE SUTHERLAND", "THE GUNFIGHTER", "THE HUNTED" ], "valid_edges": [ [ "HONEY, I SHRUNK THE KIDS", "has_tags", "KIDS" ], [ "HONEY, I SHRUNK THE KIDS", "starred_actors", "KRISTINE SUTHERLAND" ], [ "KIDS", "release_year", "1995" ], [ "THE GUNFIGHTER", "directed_by", "HENRY KING" ], [ "THE GUNFIGHTER", "has_tags", "HENRY KING" ], [ "THE HUNTED", "release_year", "1995" ], [ "THE HUNTED", "starred_actors", "JOAN CHEN" ], [ "THE SUN ALSO RISES", "directed_by", "HENRY KING" ], [ "THE SUN ALSO RISES", "starred_actors", "JOAN CHEN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 135, 1926 25395, AMERICAN GRAFFITI 10768, BACK TO THE FUTURE 9097, BLADE RUNNER 16240, HARRISON FORD 26458, LON CHANEY 12574, LONDON AFTER MIDNIGHT 36980, MARCELINE DAY 37497, NATIONAL FILM REGISTRY 29299, RAIDERS OF THE LOST ARK 32090, ROBERT ZEMECKIS 4689, SABRINA 34215, TELL IT TO THE MARINES 21989, THE BLACKBIRD 31204, THE CAMERAMAN 28677, THE CONVERSATION 31647, THE SON OF THE SHEIK 28744, THE UNHOLY THREE 19823, THE UNKNOWN 28747, TOD BROWNING 24209, WEST OF ZANZIBAR 1524, WHAT LIES BENEATH 9246, WHERE EAST IS EAST src, edge_attr, dst 25395, has_tags, 16240 25395, has_tags, 37497 10768, directed_by, 32090 10768, has_tags, 37497 10768, has_tags, 32090 10768, written_by, 32090 9097, has_tags, 16240 9097, has_tags, 37497 9097, starred_actors, 16240 12574, starred_actors, 26458 12574, starred_actors, 36980 12574, written_by, 28747 29299, has_tags, 16240 29299, has_tags, 37497 29299, starred_actors, 16240 4689, has_tags, 16240 4689, has_tags, 37497 4689, starred_actors, 16240 34215, release_year, 135 34215, starred_actors, 26458 21989, directed_by, 28747 21989, release_year, 135 21989, starred_actors, 26458 21989, written_by, 28747 31204, has_tags, 37497 31204, starred_actors, 36980 28677, has_tags, 16240 28677, has_tags, 37497 31647, has_tags, 37497 31647, release_year, 135 28744, directed_by, 28747 28744, starred_actors, 26458 19823, directed_by, 28747 19823, has_tags, 26458 19823, has_tags, 28747 19823, starred_actors, 26458 19823, written_by, 28747 24209, directed_by, 28747 24209, starred_actors, 26458 1524, directed_by, 32090 1524, has_tags, 16240 1524, has_tags, 32090 9246, directed_by, 28747 9246, starred_actors, 26458 9246, written_by, 28747 Question: How are LONDON AFTER MIDNIGHT, THE SON OF THE SHEIK, and WHAT LIES BENEATH related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LONDON AFTER MIDNIGHT", "THE SON OF THE SHEIK", "WHAT LIES BENEATH" ], "valid_edges": [ [ "AMERICAN GRAFFITI", "has_tags", "HARRISON FORD" ], [ "AMERICAN GRAFFITI", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BACK TO THE FUTURE", "directed_by", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BACK TO THE FUTURE", "has_tags", "ROBERT ZEMECKIS" ], [ "BACK TO THE FUTURE", "written_by", "ROBERT ZEMECKIS" ], [ "BLADE RUNNER", "has_tags", "HARRISON FORD" ], [ "BLADE RUNNER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "BLADE RUNNER", "starred_actors", "HARRISON FORD" ], [ "LONDON AFTER MIDNIGHT", "starred_actors", "LON CHANEY" ], [ "LONDON AFTER MIDNIGHT", "starred_actors", "MARCELINE DAY" ], [ "LONDON AFTER MIDNIGHT", "written_by", "TOD BROWNING" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "HARRISON FORD" ], [ "RAIDERS OF THE LOST ARK", "has_tags", "NATIONAL FILM REGISTRY" ], [ "RAIDERS OF THE LOST ARK", "starred_actors", "HARRISON FORD" ], [ "SABRINA", "has_tags", "HARRISON FORD" ], [ "SABRINA", "has_tags", "NATIONAL FILM REGISTRY" ], [ "SABRINA", "starred_actors", "HARRISON FORD" ], [ "TELL IT TO THE MARINES", "release_year", "1926" ], [ "TELL IT TO THE MARINES", "starred_actors", "LON CHANEY" ], [ "THE BLACKBIRD", "directed_by", "TOD BROWNING" ], [ "THE BLACKBIRD", "release_year", "1926" ], [ "THE BLACKBIRD", "starred_actors", "LON CHANEY" ], [ "THE BLACKBIRD", "written_by", "TOD BROWNING" ], [ "THE CAMERAMAN", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE CAMERAMAN", "starred_actors", "MARCELINE DAY" ], [ "THE CONVERSATION", "has_tags", "HARRISON FORD" ], [ "THE CONVERSATION", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SON OF THE SHEIK", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE SON OF THE SHEIK", "release_year", "1926" ], [ "THE UNHOLY THREE", "directed_by", "TOD BROWNING" ], [ "THE UNHOLY THREE", "starred_actors", "LON CHANEY" ], [ "THE UNKNOWN", "directed_by", "TOD BROWNING" ], [ "THE UNKNOWN", "has_tags", "LON CHANEY" ], [ "THE UNKNOWN", "has_tags", "TOD BROWNING" ], [ "THE UNKNOWN", "starred_actors", "LON CHANEY" ], [ "THE UNKNOWN", "written_by", "TOD BROWNING" ], [ "WEST OF ZANZIBAR", "directed_by", "TOD BROWNING" ], [ "WEST OF ZANZIBAR", "starred_actors", "LON CHANEY" ], [ "WHAT LIES BENEATH", "directed_by", "ROBERT ZEMECKIS" ], [ "WHAT LIES BENEATH", "has_tags", "HARRISON FORD" ], [ "WHAT LIES BENEATH", "has_tags", "ROBERT ZEMECKIS" ], [ "WHERE EAST IS EAST", "directed_by", "TOD BROWNING" ], [ "WHERE EAST IS EAST", "starred_actors", "LON CHANEY" ], [ "WHERE EAST IS EAST", "written_by", "TOD BROWNING" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4058, 16 YEARS OF ALCOHOL 1097, 2003 31345, 21 GRAMS 30643, ACROSS THE UNIVERSE 26501, ALILA 39500, ALL THE REAL GIRLS 16391, AMERICAN SPLENDOR 30281, ANA AND THE OTHERS 12144, BAD BOYS 33140, BAGHBAN 2419, BEYOND BORDERS 18822, BIG FISH 39878, BRIGHT FUTURE 22639, BRIGHT YOUNG THINGS 29448, CARANDIRU 19510, CLEOPATRA 4890, COLD MOUNTAIN 35932, DANA FUCHS 28659, DEAD END 28862, DOGVILLE 23182, DOPAMINE 36212, DRAMA 34486, EILA 14257, ELEPHANT 9048, EVIL 7866, FLYWHEEL 39946, GACY 3674, GAMES OF LOVE AND CHANCE 7599, GIRL WITH A PEARL EARRING 39494, HOLES 35319, HOPE SPRINGS 20309, HOUSE OF SAND AND FOG 19839, I ACCUSE 6684, I'LL SLEEP WHEN I'M DEAD 21437, IN THE CITY 31900, INCANTATO 39987, IT RUNS IN THE FAMILY 6425, IT'S ALL ABOUT LOVE 21614, JAPANESE STORY 8844, JONNY VANG 31245, KAL HO NAA HO 26853, LATTER DAYS 13296, LEVITY 15814, LOST IN TRANSLATION 35948, LOVE COMES SOFTLY 2088, MAIN PREM KI DIWANI HOON 11334, MASKED AND ANONYMOUS 18198, MATCHSTICK MEN 25936, MONA LISA SMILE 27827, MONSTER 12944, MY LIFE WITHOUT ME 9343, MYSTIC RIVER 37329, NATHALIE... 34705, NORMAL 21446, OFF THE MAP 10789, OPEN WATER 34120, OSAMA 23553, OUR TOWN 24769, OUT OF THE ASHES 23801, PARTY MONSTER 26350, PIECES OF APRIL 29357, RECONSTRUCTION 16708, ROADS TO KOKTEBEL 16356, ROBOT STORIES 5145, SAINTS AND SOLDIERS 3416, SARABAND 39821, SECONDHAND LIONS 4027, SHARA 38114, SHATTERED GLASS 5710, SOLDIER'S GIRL 19971, SPIN 6323, STRAYED 16954, SYLVIA 7985, SYMMETRY 11605, TAKE MY EYES 38965, THE BARBARIAN INVASIONS 38410, THE BATTLE OF SHAKER HEIGHTS 5144, THE BIG EMPTY 25461, THE COOLER 9758, THE CRAIGSLIST KILLER 21345, THE DREAMERS 12047, THE EVENT 20929, THE FIGHTING TEMPTATIONS 12447, THE HUMAN STAIN 32030, THE LOST PRINCE 24434, THE MUDGE BOY 28919, THE RETURN 30906, THE ROOM 38858, THE SHAPE OF THINGS 12883, THE SLEEPING DICTIONARY 2259, THE STATEMENT 38108, THE STATION AGENT 39036, THE STORY OF MARIE AND JULIEN 39883, THE STORY OF THE WEEPING CAMEL 22820, THE UNITED STATES OF LELAND 1411, THIRTEEN 10628, TIME OF THE WOLF 35264, TWO DAYS 11544, UNDER THE TUSCAN SUN 14956, VOICES OF A DISTANT STAR 39171, WHO KILLED BAMBI? 31862, WONDERLAND 27708, WUTHERING HEIGHTS 39834, YOUNG ADAM src, edge_attr, dst 4058, has_genre, 36212 4058, release_year, 1097 31345, has_genre, 36212 31345, has_tags, 36212 31345, release_year, 1097 30643, has_genre, 36212 30643, starred_actors, 35932 26501, has_genre, 36212 26501, release_year, 1097 39500, has_genre, 36212 39500, release_year, 1097 16391, has_genre, 36212 16391, release_year, 1097 30281, has_genre, 36212 30281, release_year, 1097 12144, has_genre, 36212 12144, release_year, 1097 33140, has_genre, 36212 33140, release_year, 1097 2419, has_genre, 36212 2419, release_year, 1097 18822, has_genre, 36212 18822, release_year, 1097 39878, has_genre, 36212 39878, release_year, 1097 22639, has_genre, 36212 22639, release_year, 1097 29448, has_genre, 36212 29448, release_year, 1097 19510, has_genre, 36212 19510, release_year, 1097 4890, has_genre, 36212 4890, has_tags, 36212 4890, release_year, 1097 28659, has_genre, 36212 28659, release_year, 1097 28862, has_genre, 36212 28862, has_tags, 36212 28862, release_year, 1097 23182, has_genre, 36212 23182, release_year, 1097 34486, has_genre, 36212 34486, release_year, 1097 14257, has_genre, 36212 14257, release_year, 1097 9048, has_genre, 36212 9048, release_year, 1097 7866, has_genre, 36212 7866, release_year, 1097 39946, has_genre, 36212 39946, release_year, 1097 3674, has_genre, 36212 3674, release_year, 1097 7599, has_genre, 36212 7599, has_tags, 36212 7599, release_year, 1097 39494, has_genre, 36212 39494, release_year, 1097 35319, has_genre, 36212 35319, release_year, 1097 20309, has_genre, 36212 20309, release_year, 1097 19839, has_genre, 36212 19839, release_year, 1097 6684, has_genre, 36212 6684, release_year, 1097 21437, has_genre, 36212 21437, release_year, 1097 31900, has_genre, 36212 31900, release_year, 1097 39987, has_genre, 36212 39987, release_year, 1097 6425, has_genre, 36212 6425, release_year, 1097 21614, has_genre, 36212 21614, release_year, 1097 8844, has_genre, 36212 8844, release_year, 1097 31245, has_genre, 36212 31245, release_year, 1097 26853, has_genre, 36212 26853, release_year, 1097 13296, has_genre, 36212 13296, release_year, 1097 15814, has_genre, 36212 15814, release_year, 1097 35948, has_genre, 36212 35948, release_year, 1097 2088, has_genre, 36212 2088, release_year, 1097 11334, has_genre, 36212 11334, release_year, 1097 18198, has_genre, 36212 18198, has_tags, 36212 18198, release_year, 1097 25936, has_genre, 36212 25936, release_year, 1097 27827, has_genre, 36212 27827, has_tags, 36212 27827, release_year, 1097 12944, has_genre, 36212 12944, release_year, 1097 9343, has_genre, 36212 9343, has_tags, 36212 9343, release_year, 1097 37329, has_genre, 36212 37329, release_year, 1097 34705, has_genre, 36212 34705, release_year, 1097 21446, has_genre, 36212 21446, has_tags, 36212 21446, release_year, 1097 10789, has_genre, 36212 10789, release_year, 1097 34120, has_genre, 36212 34120, release_year, 1097 23553, has_genre, 36212 23553, release_year, 1097 24769, has_genre, 36212 24769, release_year, 1097 23801, has_genre, 36212 23801, release_year, 1097 26350, has_genre, 36212 26350, release_year, 1097 29357, has_genre, 36212 29357, release_year, 1097 16708, has_genre, 36212 16708, release_year, 1097 16356, has_genre, 36212 16356, release_year, 1097 5145, has_genre, 36212 5145, release_year, 1097 3416, has_genre, 36212 3416, has_tags, 36212 3416, release_year, 1097 39821, has_genre, 36212 39821, release_year, 1097 4027, has_genre, 36212 4027, release_year, 1097 38114, has_genre, 36212 38114, release_year, 1097 5710, has_genre, 36212 5710, release_year, 1097 19971, has_genre, 36212 19971, release_year, 1097 6323, has_genre, 36212 6323, release_year, 1097 16954, has_genre, 36212 16954, release_year, 1097 7985, has_genre, 36212 7985, release_year, 1097 11605, has_genre, 36212 11605, release_year, 1097 38965, has_genre, 36212 38965, release_year, 1097 38410, has_genre, 36212 38410, release_year, 1097 5144, has_genre, 36212 5144, release_year, 1097 25461, has_genre, 36212 25461, release_year, 1097 9758, has_genre, 36212 21345, has_genre, 36212 21345, release_year, 1097 12047, has_genre, 36212 12047, release_year, 1097 20929, has_genre, 36212 20929, release_year, 1097 12447, has_genre, 36212 12447, release_year, 1097 32030, has_genre, 36212 32030, release_year, 1097 24434, has_genre, 36212 24434, release_year, 1097 28919, has_genre, 36212 28919, release_year, 1097 30906, has_genre, 36212 30906, release_year, 1097 38858, has_genre, 36212 38858, release_year, 1097 12883, has_genre, 36212 12883, release_year, 1097 2259, has_genre, 36212 2259, release_year, 1097 38108, has_genre, 36212 38108, release_year, 1097 39036, has_genre, 36212 39036, release_year, 1097 39883, has_genre, 36212 39883, release_year, 1097 22820, has_genre, 36212 22820, release_year, 1097 1411, has_genre, 36212 1411, has_tags, 36212 1411, release_year, 1097 10628, has_genre, 36212 10628, release_year, 1097 35264, has_genre, 36212 35264, release_year, 1097 11544, has_genre, 36212 11544, release_year, 1097 14956, has_genre, 36212 14956, release_year, 1097 39171, release_year, 1097 31862, has_genre, 36212 31862, release_year, 1097 27708, has_genre, 36212 27708, release_year, 1097 39834, has_genre, 36212 39834, release_year, 1097 Question: In what context are DANA FUCHS, THE CRAIGSLIST KILLER, and WHO KILLED BAMBI? connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DANA FUCHS", "THE CRAIGSLIST KILLER", "WHO KILLED BAMBI?" ], "valid_edges": [ [ "16 YEARS OF ALCOHOL", "has_genre", "DRAMA" ], [ "16 YEARS OF ALCOHOL", "release_year", "2003" ], [ "21 GRAMS", "has_genre", "DRAMA" ], [ "21 GRAMS", "has_tags", "DRAMA" ], [ "21 GRAMS", "release_year", "2003" ], [ "ACROSS THE UNIVERSE", "has_genre", "DRAMA" ], [ "ACROSS THE UNIVERSE", "starred_actors", "DANA FUCHS" ], [ "ALILA", "has_genre", "DRAMA" ], [ "ALILA", "release_year", "2003" ], [ "ALL THE REAL GIRLS", "has_genre", "DRAMA" ], [ "ALL THE REAL GIRLS", "release_year", "2003" ], [ "AMERICAN SPLENDOR", "has_genre", "DRAMA" ], [ "AMERICAN SPLENDOR", "release_year", "2003" ], [ "ANA AND THE OTHERS", "has_genre", "DRAMA" ], [ "ANA AND THE OTHERS", "release_year", "2003" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "release_year", "2003" ], [ "BAGHBAN", "has_genre", "DRAMA" ], [ "BAGHBAN", "release_year", "2003" ], [ "BEYOND BORDERS", "has_genre", "DRAMA" ], [ "BEYOND BORDERS", "release_year", "2003" ], [ "BIG FISH", "has_genre", "DRAMA" ], [ "BIG FISH", "release_year", "2003" ], [ "BRIGHT FUTURE", "has_genre", "DRAMA" ], [ "BRIGHT FUTURE", "release_year", "2003" ], [ "BRIGHT YOUNG THINGS", "has_genre", "DRAMA" ], [ "BRIGHT YOUNG THINGS", "release_year", "2003" ], [ "CARANDIRU", "has_genre", "DRAMA" ], [ "CARANDIRU", "release_year", "2003" ], [ "CLEOPATRA", "has_genre", "DRAMA" ], [ "CLEOPATRA", "release_year", "2003" ], [ "COLD MOUNTAIN", "has_genre", "DRAMA" ], [ "COLD MOUNTAIN", "has_tags", "DRAMA" ], [ "COLD MOUNTAIN", "release_year", "2003" ], [ "DEAD END", "has_genre", "DRAMA" ], [ "DEAD END", "release_year", "2003" ], [ "DOGVILLE", "has_genre", "DRAMA" ], [ "DOGVILLE", "has_tags", "DRAMA" ], [ "DOGVILLE", "release_year", "2003" ], [ "DOPAMINE", "has_genre", "DRAMA" ], [ "DOPAMINE", "release_year", "2003" ], [ "EILA", "has_genre", "DRAMA" ], [ "EILA", "release_year", "2003" ], [ "ELEPHANT", "has_genre", "DRAMA" ], [ "ELEPHANT", "release_year", "2003" ], [ "EVIL", "has_genre", "DRAMA" ], [ "EVIL", "release_year", "2003" ], [ "FLYWHEEL", "has_genre", "DRAMA" ], [ "FLYWHEEL", "release_year", "2003" ], [ "GACY", "has_genre", "DRAMA" ], [ "GACY", "release_year", "2003" ], [ "GAMES OF LOVE AND CHANCE", "has_genre", "DRAMA" ], [ "GAMES OF LOVE AND CHANCE", "release_year", "2003" ], [ "GIRL WITH A PEARL EARRING", "has_genre", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "has_tags", "DRAMA" ], [ "GIRL WITH A PEARL EARRING", "release_year", "2003" ], [ "HOLES", "has_genre", "DRAMA" ], [ "HOLES", "release_year", "2003" ], [ "HOPE SPRINGS", "has_genre", "DRAMA" ], [ "HOPE SPRINGS", "release_year", "2003" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "release_year", "2003" ], [ "I ACCUSE", "has_genre", "DRAMA" ], [ "I ACCUSE", "release_year", "2003" ], [ "I'LL SLEEP WHEN I'M DEAD", "has_genre", "DRAMA" ], [ "I'LL SLEEP WHEN I'M DEAD", "release_year", "2003" ], [ "IN THE CITY", "has_genre", "DRAMA" ], [ "IN THE CITY", "release_year", "2003" ], [ "INCANTATO", "has_genre", "DRAMA" ], [ "INCANTATO", "release_year", "2003" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "IT RUNS IN THE FAMILY", "release_year", "2003" ], [ "IT'S ALL ABOUT LOVE", "has_genre", "DRAMA" ], [ "IT'S ALL ABOUT LOVE", "release_year", "2003" ], [ "JAPANESE STORY", "has_genre", "DRAMA" ], [ "JAPANESE STORY", "release_year", "2003" ], [ "JONNY VANG", "has_genre", "DRAMA" ], [ "JONNY VANG", "release_year", "2003" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KAL HO NAA HO", "release_year", "2003" ], [ "LATTER DAYS", "has_genre", "DRAMA" ], [ "LATTER DAYS", "release_year", "2003" ], [ "LEVITY", "has_genre", "DRAMA" ], [ "LEVITY", "release_year", "2003" ], [ "LOST IN TRANSLATION", "has_genre", "DRAMA" ], [ "LOST IN TRANSLATION", "release_year", "2003" ], [ "LOVE COMES SOFTLY", "has_genre", "DRAMA" ], [ "LOVE COMES SOFTLY", "release_year", "2003" ], [ "MAIN PREM KI DIWANI HOON", "has_genre", "DRAMA" ], [ "MAIN PREM KI DIWANI HOON", "release_year", "2003" ], [ "MASKED AND ANONYMOUS", "has_genre", "DRAMA" ], [ "MASKED AND ANONYMOUS", "release_year", "2003" ], [ "MATCHSTICK MEN", "has_genre", "DRAMA" ], [ "MATCHSTICK MEN", "has_tags", "DRAMA" ], [ "MATCHSTICK MEN", "release_year", "2003" ], [ "MONA LISA SMILE", "has_genre", "DRAMA" ], [ "MONA LISA SMILE", "release_year", "2003" ], [ "MONSTER", "has_genre", "DRAMA" ], [ "MONSTER", "has_tags", "DRAMA" ], [ "MONSTER", "release_year", "2003" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "release_year", "2003" ], [ "MYSTIC RIVER", "has_genre", "DRAMA" ], [ "MYSTIC RIVER", "has_tags", "DRAMA" ], [ "MYSTIC RIVER", "release_year", "2003" ], [ "NATHALIE...", "has_genre", "DRAMA" ], [ "NATHALIE...", "release_year", "2003" ], [ "NORMAL", "has_genre", "DRAMA" ], [ "NORMAL", "release_year", "2003" ], [ "OFF THE MAP", "has_genre", "DRAMA" ], [ "OFF THE MAP", "has_tags", "DRAMA" ], [ "OFF THE MAP", "release_year", "2003" ], [ "OPEN WATER", "has_genre", "DRAMA" ], [ "OPEN WATER", "release_year", "2003" ], [ "OSAMA", "has_genre", "DRAMA" ], [ "OSAMA", "release_year", "2003" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "release_year", "2003" ], [ "OUT OF THE ASHES", "has_genre", "DRAMA" ], [ "OUT OF THE ASHES", "release_year", "2003" ], [ "PARTY MONSTER", "has_genre", "DRAMA" ], [ "PARTY MONSTER", "release_year", "2003" ], [ "PIECES OF APRIL", "has_genre", "DRAMA" ], [ "PIECES OF APRIL", "release_year", "2003" ], [ "RECONSTRUCTION", "has_genre", "DRAMA" ], [ "RECONSTRUCTION", "release_year", "2003" ], [ "ROADS TO KOKTEBEL", "has_genre", "DRAMA" ], [ "ROADS TO KOKTEBEL", "release_year", "2003" ], [ "ROBOT STORIES", "has_genre", "DRAMA" ], [ "ROBOT STORIES", "release_year", "2003" ], [ "SAINTS AND SOLDIERS", "has_genre", "DRAMA" ], [ "SAINTS AND SOLDIERS", "release_year", "2003" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "release_year", "2003" ], [ "SECONDHAND LIONS", "has_genre", "DRAMA" ], [ "SECONDHAND LIONS", "release_year", "2003" ], [ "SHARA", "has_genre", "DRAMA" ], [ "SHARA", "release_year", "2003" ], [ "SHATTERED GLASS", "has_genre", "DRAMA" ], [ "SHATTERED GLASS", "release_year", "2003" ], [ "SOLDIER'S GIRL", "has_genre", "DRAMA" ], [ "SOLDIER'S GIRL", "release_year", "2003" ], [ "SPIN", "has_genre", "DRAMA" ], [ "SPIN", "release_year", "2003" ], [ "STRAYED", "has_genre", "DRAMA" ], [ "STRAYED", "release_year", "2003" ], [ "SYLVIA", "has_genre", "DRAMA" ], [ "SYLVIA", "release_year", "2003" ], [ "SYMMETRY", "has_genre", "DRAMA" ], [ "SYMMETRY", "release_year", "2003" ], [ "TAKE MY EYES", "has_genre", "DRAMA" ], [ "TAKE MY EYES", "release_year", "2003" ], [ "THE BARBARIAN INVASIONS", "has_genre", "DRAMA" ], [ "THE BARBARIAN INVASIONS", "release_year", "2003" ], [ "THE BATTLE OF SHAKER HEIGHTS", "has_genre", "DRAMA" ], [ "THE BATTLE OF SHAKER HEIGHTS", "release_year", "2003" ], [ "THE BIG EMPTY", "has_genre", "DRAMA" ], [ "THE BIG EMPTY", "release_year", "2003" ], [ "THE COOLER", "has_genre", "DRAMA" ], [ "THE COOLER", "release_year", "2003" ], [ "THE CRAIGSLIST KILLER", "has_genre", "DRAMA" ], [ "THE DREAMERS", "has_genre", "DRAMA" ], [ "THE DREAMERS", "release_year", "2003" ], [ "THE EVENT", "has_genre", "DRAMA" ], [ "THE EVENT", "release_year", "2003" ], [ "THE FIGHTING TEMPTATIONS", "has_genre", "DRAMA" ], [ "THE FIGHTING TEMPTATIONS", "release_year", "2003" ], [ "THE HUMAN STAIN", "has_genre", "DRAMA" ], [ "THE HUMAN STAIN", "release_year", "2003" ], [ "THE LOST PRINCE", "has_genre", "DRAMA" ], [ "THE LOST PRINCE", "release_year", "2003" ], [ "THE MUDGE BOY", "has_genre", "DRAMA" ], [ "THE MUDGE BOY", "release_year", "2003" ], [ "THE RETURN", "has_genre", "DRAMA" ], [ "THE RETURN", "release_year", "2003" ], [ "THE ROOM", "has_genre", "DRAMA" ], [ "THE ROOM", "release_year", "2003" ], [ "THE SHAPE OF THINGS", "has_genre", "DRAMA" ], [ "THE SHAPE OF THINGS", "release_year", "2003" ], [ "THE SLEEPING DICTIONARY", "has_genre", "DRAMA" ], [ "THE SLEEPING DICTIONARY", "release_year", "2003" ], [ "THE STATEMENT", "has_genre", "DRAMA" ], [ "THE STATEMENT", "release_year", "2003" ], [ "THE STATION AGENT", "has_genre", "DRAMA" ], [ "THE STATION AGENT", "release_year", "2003" ], [ "THE STORY OF MARIE AND JULIEN", "has_genre", "DRAMA" ], [ "THE STORY OF MARIE AND JULIEN", "release_year", "2003" ], [ "THE STORY OF THE WEEPING CAMEL", "has_genre", "DRAMA" ], [ "THE STORY OF THE WEEPING CAMEL", "release_year", "2003" ], [ "THE UNITED STATES OF LELAND", "has_genre", "DRAMA" ], [ "THE UNITED STATES OF LELAND", "release_year", "2003" ], [ "THIRTEEN", "has_genre", "DRAMA" ], [ "THIRTEEN", "has_tags", "DRAMA" ], [ "THIRTEEN", "release_year", "2003" ], [ "TIME OF THE WOLF", "has_genre", "DRAMA" ], [ "TIME OF THE WOLF", "release_year", "2003" ], [ "TWO DAYS", "has_genre", "DRAMA" ], [ "TWO DAYS", "release_year", "2003" ], [ "UNDER THE TUSCAN SUN", "has_genre", "DRAMA" ], [ "UNDER THE TUSCAN SUN", "release_year", "2003" ], [ "VOICES OF A DISTANT STAR", "has_genre", "DRAMA" ], [ "VOICES OF A DISTANT STAR", "release_year", "2003" ], [ "WHO KILLED BAMBI?", "release_year", "2003" ], [ "WONDERLAND", "has_genre", "DRAMA" ], [ "WONDERLAND", "release_year", "2003" ], [ "WUTHERING HEIGHTS", "has_genre", "DRAMA" ], [ "WUTHERING HEIGHTS", "release_year", "2003" ], [ "YOUNG ADAM", "has_genre", "DRAMA" ], [ "YOUNG ADAM", "release_year", "2003" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 35046, FRANKLIN J. SCHAFFNER 28620, HIPPIES 13825, INSOMNIA 27037, NIKOLAJ FROBENIUS 27643, PLANET OF THE APES 26868, PSYCH-OUT 28729, REMAKE src, edge_attr, dst 13825, has_tags, 13825 13825, has_tags, 28729 13825, written_by, 27037 27643, directed_by, 35046 27643, has_tags, 35046 27643, has_tags, 28729 27643, release_year, 27810 26868, has_tags, 28620 26868, release_year, 27810 Question: For what reason are FRANKLIN J. SCHAFFNER, HIPPIES, and NIKOLAJ FROBENIUS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FRANKLIN J. SCHAFFNER", "HIPPIES", "NIKOLAJ FROBENIUS" ], "valid_edges": [ [ "INSOMNIA", "has_tags", "INSOMNIA" ], [ "INSOMNIA", "has_tags", "REMAKE" ], [ "INSOMNIA", "written_by", "NIKOLAJ FROBENIUS" ], [ "PLANET OF THE APES", "directed_by", "FRANKLIN J. SCHAFFNER" ], [ "PLANET OF THE APES", "has_tags", "FRANKLIN J. SCHAFFNER" ], [ "PLANET OF THE APES", "has_tags", "REMAKE" ], [ "PLANET OF THE APES", "release_year", "1968" ], [ "PSYCH-OUT", "has_tags", "HIPPIES" ], [ "PSYCH-OUT", "release_year", "1968" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29424, 2011 39964, 247°F 38344, A STREETCAR NAMED DESIRE 12981, ALL-STAR SUPERMAN 15253, COMIC BOOK 39571, DC COMICS 20538, DIANE LANE 24481, FRANCHISE 22361, JERRY SIEGEL 26324, JOHN ERMAN 9033, MAN OF STEEL 21474, MARLON BRANDO 2980, SUPERHERO 20948, SUPERMAN src, edge_attr, dst 39964, release_year, 29424 38344, directed_by, 26324 38344, has_tags, 21474 38344, starred_actors, 20538 38344, starred_actors, 21474 12981, has_tags, 20948 12981, release_year, 29424 9033, has_tags, 15253 9033, has_tags, 39571 9033, has_tags, 24481 9033, has_tags, 2980 9033, has_tags, 20948 9033, starred_actors, 20538 9033, written_by, 22361 20948, has_tags, 15253 20948, has_tags, 39571 20948, has_tags, 24481 20948, has_tags, 21474 20948, has_tags, 2980 20948, has_tags, 20948 20948, starred_actors, 21474 20948, written_by, 22361 Question: In what context are 247°F, JERRY SIEGEL, and JOHN ERMAN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "247°F", "JERRY SIEGEL", "JOHN ERMAN" ], "valid_edges": [ [ "247°F", "release_year", "2011" ], [ "A STREETCAR NAMED DESIRE", "directed_by", "JOHN ERMAN" ], [ "A STREETCAR NAMED DESIRE", "has_tags", "MARLON BRANDO" ], [ "A STREETCAR NAMED DESIRE", "starred_actors", "DIANE LANE" ], [ "A STREETCAR NAMED DESIRE", "starred_actors", "MARLON BRANDO" ], [ "ALL-STAR SUPERMAN", "has_tags", "SUPERMAN" ], [ "ALL-STAR SUPERMAN", "release_year", "2011" ], [ "MAN OF STEEL", "has_tags", "COMIC BOOK" ], [ "MAN OF STEEL", "has_tags", "DC COMICS" ], [ "MAN OF STEEL", "has_tags", "FRANCHISE" ], [ "MAN OF STEEL", "has_tags", "SUPERHERO" ], [ "MAN OF STEEL", "has_tags", "SUPERMAN" ], [ "MAN OF STEEL", "starred_actors", "DIANE LANE" ], [ "MAN OF STEEL", "written_by", "JERRY SIEGEL" ], [ "SUPERMAN", "has_tags", "COMIC BOOK" ], [ "SUPERMAN", "has_tags", "DC COMICS" ], [ "SUPERMAN", "has_tags", "FRANCHISE" ], [ "SUPERMAN", "has_tags", "MARLON BRANDO" ], [ "SUPERMAN", "has_tags", "SUPERHERO" ], [ "SUPERMAN", "has_tags", "SUPERMAN" ], [ "SUPERMAN", "starred_actors", "MARLON BRANDO" ], [ "SUPERMAN", "written_by", "JERRY SIEGEL" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1006, 1996 13408, 2001 39289, ACTION 32427, ALL THE QUEEN'S MEN 32015, BEHIND ENEMY LINES 28544, BLACK HAWK DOWN 23820, CARLA'S SONG 25285, COME AND SEE 10293, CONSPIRACY 4615, DARK BLUE WORLD 11363, DEFIANCE 16353, EDGES OF THE LORD 26690, ELLING 16930, ENEMY AT THE GATES 19194, ENIGMA 10315, FLAGS OF OUR FATHERS 15765, HAMSUN 33545, HART'S WAR 8842, INDEPENDENCE DAY 625, K-9 32792, LIBERTARIAS 5127, MOTHER NIGHT 16883, NORWEGIAN 17600, OFF LIMITS 234, PEARL HARBOR 34732, PLATOON 33042, PRISONER OF THE MOUNTAINS 17691, ROD DANIEL 35586, SAHARA 11124, STALINGRAD 10522, TAKING SIDES 13491, THE DEVIL'S BACKBONE 36390, THE ENGLISH PATIENT 27237, THE LONGEST DAY 23300, THE LOST BATTALION 16845, THE MAN WHO CAPTURED EICHMANN 3651, THE OTHER SIDE OF SUNDAY 12614, THE PIANIST 34479, TO END ALL WARS 3432, TRUE BLUE 6655, UPRISING 22214, WAR 23537, WHERE EAGLES DARE 11850, WILLEM DAFOE 24155, WORLD WAR II src, edge_attr, dst 32427, has_genre, 22214 32427, release_year, 13408 32015, has_genre, 22214 32015, has_tags, 22214 32015, release_year, 13408 28544, has_tags, 22214 28544, release_year, 13408 23820, has_genre, 22214 23820, release_year, 1006 25285, has_genre, 22214 25285, has_tags, 24155 10293, has_genre, 22214 10293, has_tags, 24155 10293, release_year, 13408 4615, has_genre, 22214 4615, has_tags, 24155 4615, release_year, 13408 11363, has_tags, 22214 11363, has_tags, 24155 16353, has_genre, 22214 16353, has_tags, 24155 16353, release_year, 13408 16353, starred_actors, 11850 26690, in_language, 16883 26690, release_year, 13408 16930, has_tags, 22214 16930, has_tags, 24155 16930, release_year, 13408 19194, has_tags, 24155 19194, release_year, 13408 10315, has_genre, 22214 10315, has_tags, 22214 10315, has_tags, 24155 15765, has_genre, 22214 15765, has_tags, 24155 15765, in_language, 16883 15765, release_year, 1006 33545, has_genre, 22214 33545, has_tags, 24155 8842, has_tags, 22214 8842, release_year, 1006 625, directed_by, 17691 625, has_genre, 39289 625, has_tags, 17691 32792, has_genre, 22214 32792, release_year, 1006 5127, has_genre, 22214 5127, has_tags, 24155 5127, release_year, 1006 17600, has_genre, 22214 17600, starred_actors, 11850 234, has_tags, 22214 234, release_year, 13408 34732, has_genre, 22214 34732, has_tags, 22214 34732, has_tags, 11850 34732, starred_actors, 11850 33042, has_genre, 22214 33042, release_year, 1006 35586, has_genre, 22214 35586, has_tags, 24155 11124, has_genre, 22214 11124, has_tags, 24155 10522, has_genre, 22214 10522, release_year, 13408 13491, has_tags, 22214 13491, release_year, 13408 36390, has_genre, 22214 36390, has_tags, 22214 36390, release_year, 1006 27237, has_tags, 22214 27237, has_tags, 24155 23300, has_genre, 22214 23300, release_year, 13408 16845, has_genre, 22214 16845, release_year, 1006 3651, in_language, 16883 3651, release_year, 1006 12614, has_genre, 22214 12614, has_tags, 22214 12614, has_tags, 24155 34479, has_genre, 22214 34479, has_tags, 22214 34479, release_year, 13408 3432, release_year, 1006 3432, release_year, 13408 6655, has_genre, 22214 6655, release_year, 13408 22214, has_genre, 39289 23537, has_genre, 22214 23537, has_tags, 24155 Question: For what reason are EDGES OF THE LORD, ROD DANIEL, and THE OTHER SIDE OF SUNDAY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EDGES OF THE LORD", "ROD DANIEL", "THE OTHER SIDE OF SUNDAY" ], "valid_edges": [ [ "ALL THE QUEEN'S MEN", "has_genre", "WAR" ], [ "ALL THE QUEEN'S MEN", "release_year", "2001" ], [ "BEHIND ENEMY LINES", "has_genre", "WAR" ], [ "BEHIND ENEMY LINES", "has_tags", "WAR" ], [ "BEHIND ENEMY LINES", "release_year", "2001" ], [ "BLACK HAWK DOWN", "has_tags", "WAR" ], [ "BLACK HAWK DOWN", "release_year", "2001" ], [ "CARLA'S SONG", "has_genre", "WAR" ], [ "CARLA'S SONG", "release_year", "1996" ], [ "COME AND SEE", "has_genre", "WAR" ], [ "COME AND SEE", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "has_genre", "WAR" ], [ "CONSPIRACY", "has_tags", "WORLD WAR II" ], [ "CONSPIRACY", "release_year", "2001" ], [ "DARK BLUE WORLD", "has_genre", "WAR" ], [ "DARK BLUE WORLD", "has_tags", "WORLD WAR II" ], [ "DARK BLUE WORLD", "release_year", "2001" ], [ "DEFIANCE", "has_tags", "WAR" ], [ "DEFIANCE", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "has_genre", "WAR" ], [ "EDGES OF THE LORD", "has_tags", "WORLD WAR II" ], [ "EDGES OF THE LORD", "release_year", "2001" ], [ "EDGES OF THE LORD", "starred_actors", "WILLEM DAFOE" ], [ "ELLING", "in_language", "NORWEGIAN" ], [ "ELLING", "release_year", "2001" ], [ "ENEMY AT THE GATES", "has_tags", "WAR" ], [ "ENEMY AT THE GATES", "has_tags", "WORLD WAR II" ], [ "ENEMY AT THE GATES", "release_year", "2001" ], [ "ENIGMA", "has_tags", "WORLD WAR II" ], [ "ENIGMA", "release_year", "2001" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "has_genre", "WAR" ], [ "HAMSUN", "has_tags", "WORLD WAR II" ], [ "HAMSUN", "in_language", "NORWEGIAN" ], [ "HAMSUN", "release_year", "1996" ], [ "HART'S WAR", "has_genre", "WAR" ], [ "HART'S WAR", "has_tags", "WORLD WAR II" ], [ "INDEPENDENCE DAY", "has_tags", "WAR" ], [ "INDEPENDENCE DAY", "release_year", "1996" ], [ "K-9", "directed_by", "ROD DANIEL" ], [ "K-9", "has_genre", "ACTION" ], [ "K-9", "has_tags", "ROD DANIEL" ], [ "LIBERTARIAS", "has_genre", "WAR" ], [ "LIBERTARIAS", "release_year", "1996" ], [ "MOTHER NIGHT", "has_genre", "WAR" ], [ "MOTHER NIGHT", "has_tags", "WORLD WAR II" ], [ "MOTHER NIGHT", "release_year", "1996" ], [ "OFF LIMITS", "has_genre", "WAR" ], [ "OFF LIMITS", "starred_actors", "WILLEM DAFOE" ], [ "PEARL HARBOR", "has_tags", "WAR" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PLATOON", "has_genre", "WAR" ], [ "PLATOON", "has_tags", "WAR" ], [ "PLATOON", "has_tags", "WILLEM DAFOE" ], [ "PLATOON", "starred_actors", "WILLEM DAFOE" ], [ "PRISONER OF THE MOUNTAINS", "has_genre", "WAR" ], [ "PRISONER OF THE MOUNTAINS", "release_year", "1996" ], [ "SAHARA", "has_genre", "WAR" ], [ "SAHARA", "has_tags", "WORLD WAR II" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "has_tags", "WORLD WAR II" ], [ "TAKING SIDES", "has_genre", "WAR" ], [ "TAKING SIDES", "release_year", "2001" ], [ "THE DEVIL'S BACKBONE", "has_tags", "WAR" ], [ "THE DEVIL'S BACKBONE", "release_year", "2001" ], [ "THE ENGLISH PATIENT", "has_genre", "WAR" ], [ "THE ENGLISH PATIENT", "has_tags", "WAR" ], [ "THE ENGLISH PATIENT", "release_year", "1996" ], [ "THE LONGEST DAY", "has_tags", "WAR" ], [ "THE LONGEST DAY", "has_tags", "WORLD WAR II" ], [ "THE LOST BATTALION", "has_genre", "WAR" ], [ "THE LOST BATTALION", "release_year", "2001" ], [ "THE MAN WHO CAPTURED EICHMANN", "has_genre", "WAR" ], [ "THE MAN WHO CAPTURED EICHMANN", "release_year", "1996" ], [ "THE OTHER SIDE OF SUNDAY", "in_language", "NORWEGIAN" ], [ "THE OTHER SIDE OF SUNDAY", "release_year", "1996" ], [ "THE PIANIST", "has_genre", "WAR" ], [ "THE PIANIST", "has_tags", "WAR" ], [ "THE PIANIST", "has_tags", "WORLD WAR II" ], [ "TO END ALL WARS", "has_genre", "WAR" ], [ "TO END ALL WARS", "has_tags", "WAR" ], [ "TO END ALL WARS", "release_year", "2001" ], [ "TRUE BLUE", "release_year", "1996" ], [ "TRUE BLUE", "release_year", "2001" ], [ "UPRISING", "has_genre", "WAR" ], [ "UPRISING", "release_year", "2001" ], [ "WAR", "has_genre", "ACTION" ], [ "WHERE EAGLES DARE", "has_genre", "WAR" ], [ "WHERE EAGLES DARE", "has_tags", "WORLD WAR II" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 32287, CARNIVAL OF SOULS 34298, CHARLES GEORGE HILDEBRANDT 28333, DAVID PROWSE 19365, FRANKENSTEIN AND THE MONSTER FROM HELL 5870, HORROR 9515, RING OF TERROR 26202, TALES OF TERROR 17361, THE BRAIN THAT WOULDN'T DIE 5773, THE DEADLY SPAWN 17058, THE HORRIBLE DR. HICHCOCK src, edge_attr, dst 32287, has_genre, 5870 32287, release_year, 3863 19365, has_genre, 5870 19365, starred_actors, 28333 9515, has_genre, 5870 9515, release_year, 3863 26202, has_genre, 5870 26202, release_year, 3863 17361, has_genre, 5870 17361, release_year, 3863 5773, has_genre, 5870 5773, starred_actors, 34298 17058, has_genre, 5870 17058, release_year, 3863 Question: How are 1962, CHARLES GEORGE HILDEBRANDT, and DAVID PROWSE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "1962", "CHARLES GEORGE HILDEBRANDT", "DAVID PROWSE" ], "valid_edges": [ [ "CARNIVAL OF SOULS", "has_genre", "HORROR" ], [ "CARNIVAL OF SOULS", "release_year", "1962" ], [ "FRANKENSTEIN AND THE MONSTER FROM HELL", "has_genre", "HORROR" ], [ "FRANKENSTEIN AND THE MONSTER FROM HELL", "starred_actors", "DAVID PROWSE" ], [ "RING OF TERROR", "has_genre", "HORROR" ], [ "RING OF TERROR", "release_year", "1962" ], [ "TALES OF TERROR", "has_genre", "HORROR" ], [ "TALES OF TERROR", "release_year", "1962" ], [ "THE BRAIN THAT WOULDN'T DIE", "has_genre", "HORROR" ], [ "THE BRAIN THAT WOULDN'T DIE", "release_year", "1962" ], [ "THE DEADLY SPAWN", "has_genre", "HORROR" ], [ "THE DEADLY SPAWN", "starred_actors", "CHARLES GEORGE HILDEBRANDT" ], [ "THE HORRIBLE DR. HICHCOCK", "has_genre", "HORROR" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24818, 1992 26277, A FEW GOOD MEN 15184, AARON SORKIN 25843, ALEX ZAMM 37558, ALICE MUNRO 21372, BEVERLY HILLS CHIHUAHUA 2 30463, COMEDY 4725, COURT 9192, COURTROOM 36212, DRAMA 26714, EDGE OF MADNESS 11565, GOOD 30221, LAW 33307, LAWYER 23580, LAWYERS 17559, LEGALLY BLONDE 28476, MURDER 21919, MY COUSIN VINNY 15607, THE LITTLE RASCALS SAVE THE DAY 5106, THE SOCIAL NETWORK src, edge_attr, dst 26277, has_genre, 36212 26277, has_imdb_rating, 11565 26277, has_tags, 15184 26277, has_tags, 4725 26277, has_tags, 9192 26277, has_tags, 36212 26277, has_tags, 30221 26277, has_tags, 33307 26277, has_tags, 23580 26277, has_tags, 28476 26277, release_year, 24818 26277, written_by, 15184 21372, directed_by, 25843 21372, has_genre, 30463 26714, has_genre, 36212 26714, written_by, 37558 17559, has_genre, 30463 17559, has_imdb_rating, 11565 17559, has_tags, 30463 17559, has_tags, 30221 17559, has_tags, 28476 21919, has_genre, 30463 21919, has_tags, 30463 21919, has_tags, 4725 21919, has_tags, 9192 21919, has_tags, 30221 21919, has_tags, 33307 21919, has_tags, 23580 21919, has_tags, 28476 21919, release_year, 24818 15607, directed_by, 25843 15607, has_genre, 30463 15607, written_by, 25843 5106, has_genre, 36212 5106, has_tags, 15184 5106, has_tags, 30221 5106, written_by, 15184 Question: In what context are ALEX ZAMM, ALICE MUNRO, and LAW connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ALEX ZAMM", "ALICE MUNRO", "LAW" ], "valid_edges": [ [ "A FEW GOOD MEN", "has_genre", "DRAMA" ], [ "A FEW GOOD MEN", "has_imdb_rating", "GOOD" ], [ "A FEW GOOD MEN", "has_tags", "AARON SORKIN" ], [ "A FEW GOOD MEN", "has_tags", "COURT" ], [ "A FEW GOOD MEN", "has_tags", "COURTROOM" ], [ "A FEW GOOD MEN", "has_tags", "DRAMA" ], [ "A FEW GOOD MEN", "has_tags", "LAW" ], [ "A FEW GOOD MEN", "has_tags", "LAWYER" ], [ "A FEW GOOD MEN", "has_tags", "LAWYERS" ], [ "A FEW GOOD MEN", "has_tags", "MURDER" ], [ "A FEW GOOD MEN", "release_year", "1992" ], [ "A FEW GOOD MEN", "written_by", "AARON SORKIN" ], [ "BEVERLY HILLS CHIHUAHUA 2", "directed_by", "ALEX ZAMM" ], [ "BEVERLY HILLS CHIHUAHUA 2", "has_genre", "COMEDY" ], [ "EDGE OF MADNESS", "has_genre", "DRAMA" ], [ "EDGE OF MADNESS", "written_by", "ALICE MUNRO" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEGALLY BLONDE", "has_tags", "LAW" ], [ "LEGALLY BLONDE", "has_tags", "MURDER" ], [ "MY COUSIN VINNY", "has_genre", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COMEDY" ], [ "MY COUSIN VINNY", "has_tags", "COURT" ], [ "MY COUSIN VINNY", "has_tags", "COURTROOM" ], [ "MY COUSIN VINNY", "has_tags", "LAW" ], [ "MY COUSIN VINNY", "has_tags", "LAWYER" ], [ "MY COUSIN VINNY", "has_tags", "LAWYERS" ], [ "MY COUSIN VINNY", "has_tags", "MURDER" ], [ "MY COUSIN VINNY", "release_year", "1992" ], [ "THE LITTLE RASCALS SAVE THE DAY", "directed_by", "ALEX ZAMM" ], [ "THE LITTLE RASCALS SAVE THE DAY", "has_genre", "COMEDY" ], [ "THE LITTLE RASCALS SAVE THE DAY", "written_by", "ALEX ZAMM" ], [ "THE SOCIAL NETWORK", "has_genre", "DRAMA" ], [ "THE SOCIAL NETWORK", "has_tags", "AARON SORKIN" ], [ "THE SOCIAL NETWORK", "has_tags", "LAW" ], [ "THE SOCIAL NETWORK", "written_by", "AARON SORKIN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35845, 2006 11079, BORDERTOWN 8432, CONCUSSION 36212, DRAMA 18716, JULIA DEVILLERS 13401, READ IT AND WEEP 34632, STACIE PASSON 15289, WALLACE SMITH src, edge_attr, dst 11079, has_genre, 36212 11079, release_year, 35845 11079, written_by, 15289 8432, directed_by, 34632 8432, has_genre, 36212 8432, written_by, 34632 13401, release_year, 35845 13401, written_by, 18716 Question: In what context are JULIA DEVILLERS, STACIE PASSON, and WALLACE SMITH connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JULIA DEVILLERS", "STACIE PASSON", "WALLACE SMITH" ], "valid_edges": [ [ "BORDERTOWN", "has_genre", "DRAMA" ], [ "BORDERTOWN", "release_year", "2006" ], [ "BORDERTOWN", "written_by", "WALLACE SMITH" ], [ "CONCUSSION", "directed_by", "STACIE PASSON" ], [ "CONCUSSION", "has_genre", "DRAMA" ], [ "CONCUSSION", "written_by", "STACIE PASSON" ], [ "READ IT AND WEEP", "release_year", "2006" ], [ "READ IT AND WEEP", "written_by", "JULIA DEVILLERS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 9538, DON SIEGEL 30217, HELL IS FOR HEROES 35995, MAXIMILIAN SCHELL 18454, MY GEISHA 33101, SHIRLEY MACLAINE 18670, THE CHOSEN 17058, THE HORRIBLE DR. HICHCOCK 13523, THE RELUCTANT SAINT 7843, TWO FOR THE SEESAW 37550, TWO MULES FOR SISTER SARA src, edge_attr, dst 30217, directed_by, 9538 30217, has_tags, 9538 30217, release_year, 3863 18454, release_year, 3863 18454, starred_actors, 33101 18670, starred_actors, 35995 17058, release_year, 3863 13523, has_tags, 35995 13523, release_year, 3863 13523, starred_actors, 35995 7843, has_tags, 33101 7843, release_year, 3863 7843, starred_actors, 33101 37550, directed_by, 9538 37550, has_tags, 9538 37550, starred_actors, 33101 Question: For what reason are THE CHOSEN, THE HORRIBLE DR. HICHCOCK, and TWO MULES FOR SISTER SARA associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "THE CHOSEN", "THE HORRIBLE DR. HICHCOCK", "TWO MULES FOR SISTER SARA" ], "valid_edges": [ [ "HELL IS FOR HEROES", "directed_by", "DON SIEGEL" ], [ "HELL IS FOR HEROES", "has_tags", "DON SIEGEL" ], [ "HELL IS FOR HEROES", "release_year", "1962" ], [ "MY GEISHA", "release_year", "1962" ], [ "MY GEISHA", "starred_actors", "SHIRLEY MACLAINE" ], [ "THE CHOSEN", "starred_actors", "MAXIMILIAN SCHELL" ], [ "THE HORRIBLE DR. HICHCOCK", "release_year", "1962" ], [ "THE RELUCTANT SAINT", "has_tags", "MAXIMILIAN SCHELL" ], [ "THE RELUCTANT SAINT", "release_year", "1962" ], [ "THE RELUCTANT SAINT", "starred_actors", "MAXIMILIAN SCHELL" ], [ "TWO FOR THE SEESAW", "has_tags", "SHIRLEY MACLAINE" ], [ "TWO FOR THE SEESAW", "release_year", "1962" ], [ "TWO FOR THE SEESAW", "starred_actors", "SHIRLEY MACLAINE" ], [ "TWO MULES FOR SISTER SARA", "directed_by", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "has_tags", "DON SIEGEL" ], [ "TWO MULES FOR SISTER SARA", "starred_actors", "SHIRLEY MACLAINE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35798, 2010 30463, COMEDY 36212, DRAMA 4838, EAT PRAY LOVE 4090, LOUIS C.K 35134, MERCEDES MCNAB 5766, RUNNING WITH SCISSORS 31492, RYAN MURPHY 35470, THE NORMAL HEART 33138, THIRST 8012, TOMORROW NIGHT src, edge_attr, dst 4838, directed_by, 31492 4838, has_genre, 36212 4838, release_year, 35798 4838, written_by, 31492 5766, directed_by, 31492 5766, has_genre, 30463 5766, has_genre, 36212 5766, written_by, 31492 35470, directed_by, 31492 35470, has_genre, 36212 33138, has_genre, 36212 33138, release_year, 35798 33138, starred_actors, 35134 8012, has_genre, 30463 8012, has_tags, 30463 8012, has_tags, 4090 Question: For what reason are LOUIS C.K, MERCEDES MCNAB, and RYAN MURPHY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LOUIS C.K", "MERCEDES MCNAB", "RYAN MURPHY" ], "valid_edges": [ [ "EAT PRAY LOVE", "directed_by", "RYAN MURPHY" ], [ "EAT PRAY LOVE", "has_genre", "DRAMA" ], [ "EAT PRAY LOVE", "release_year", "2010" ], [ "EAT PRAY LOVE", "written_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "directed_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "has_genre", "COMEDY" ], [ "RUNNING WITH SCISSORS", "has_genre", "DRAMA" ], [ "RUNNING WITH SCISSORS", "written_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "directed_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "has_genre", "DRAMA" ], [ "THIRST", "has_genre", "DRAMA" ], [ "THIRST", "release_year", "2010" ], [ "THIRST", "starred_actors", "MERCEDES MCNAB" ], [ "TOMORROW NIGHT", "has_genre", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "COMEDY" ], [ "TOMORROW NIGHT", "has_tags", "LOUIS C.K" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 23439, +1 1421, 2013 35522, A COMMON MAN 18644, A RESURRECTION 20629, A SINGLE SHOT 36431, ASSAULT ON WALL STREET 21421, BIG BAD WOLVES 16664, BLOOD DIAMOND 7483, BLOOD TIES 11338, BLUE RUIN 39346, BORGMAN 38211, BROKEN CITY 39398, CAPTAIN PHILLIPS 25216, COHERENCE 25131, COLD COMES THE NIGHT 38680, COMPULSION 40079, CONTRACTED 22349, CRAWLSPACE 9647, D-DAY 33372, DARK SKIES 9641, DIRTY PRETTY THINGS 8823, DRISHYAM 3047, ENEMY 8491, ESCAPE PLAN 2577, EVIDENCE 40134, FELONY 5287, FROZEN 22832, GETAWAY 35657, GLORIA 12776, GRAND PIANO 31326, GRAVITY 14366, HAUNTER 33891, HORNS 33776, HOURS 13177, HOUSE HUNTING 571, IN SECRET 32370, JOY BRYANT 378, JOY RIDE 17358, LAST PASSENGER 17319, LONDON 26190, MAGIC MAGIC 33165, MISCHIEF NIGHT 11517, MISSIONARY 21188, MR. JONES 25264, NOTES ON A SCANDAL 26943, NOW YOU SEE ME 12443, ODD THOMAS 32954, OLDBOY 536, OUT OF THE FURNACE 8352, PARANOIA 32279, PARKER 38966, PAUL WALKER 29074, PENTHOUSE NORTH 4066, PIONEER 13471, PRISONERS 10085, R. LANCE HILL 22512, RUNNER RUNNER 6745, SCENIC ROUTE 38583, SHIFTY 2404, SIDE EFFECTS 27160, SOLO 33956, SOUTH AFRICA 2485, SPARKS 26621, STAY 30357, STOKER 16450, STRANGER BY THE LAKE 34509, SWEETWATER 28652, TABLE NO. 21 16900, THE CALL 29799, THE CANYONS 31128, THE COUNSELOR 38107, THE EAST 2878, THE EVIL THAT MEN DO 35937, THE FIFTH ESTATE 36893, THE GIRL ON THE TRAIN 13613, THE LAZARUS PROJECT 8137, THE MACHINE 31276, THE NUMBERS STATION 27098, THE PRESTIGE 6427, THE PURGE 13106, THE SACRAMENT 32390, THE SKULLS 24811, THRILLER 38582, TOM AT THE FARM 27476, TORMENT 15230, TRANCE 5603, VEHICLE 19 26489, WELCOME TO THE PUNCH 32403, WHITE HOUSE DOWN src, edge_attr, dst 23439, has_genre, 24811 23439, release_year, 1421 35522, has_genre, 24811 35522, release_year, 1421 18644, has_genre, 24811 18644, release_year, 1421 20629, has_genre, 24811 20629, release_year, 1421 36431, has_genre, 24811 36431, release_year, 1421 21421, has_genre, 24811 21421, release_year, 1421 16664, has_genre, 24811 16664, has_tags, 33956 7483, has_genre, 24811 7483, release_year, 1421 11338, has_genre, 24811 11338, release_year, 1421 39346, has_genre, 24811 39346, release_year, 1421 38211, has_genre, 24811 38211, release_year, 1421 39398, has_genre, 24811 39398, release_year, 1421 25216, has_genre, 24811 25216, release_year, 1421 25131, has_genre, 24811 25131, release_year, 1421 38680, has_genre, 24811 38680, release_year, 1421 40079, has_genre, 24811 40079, release_year, 1421 22349, has_genre, 24811 22349, release_year, 1421 9647, has_genre, 24811 9647, release_year, 1421 33372, has_genre, 24811 33372, release_year, 1421 9641, has_genre, 24811 9641, has_tags, 17319 8823, has_genre, 24811 8823, release_year, 1421 3047, has_genre, 24811 3047, release_year, 1421 8491, has_genre, 24811 8491, release_year, 1421 2577, has_genre, 24811 2577, release_year, 1421 40134, has_genre, 24811 40134, release_year, 1421 5287, has_genre, 24811 5287, release_year, 1421 22832, has_genre, 24811 22832, release_year, 1421 35657, has_genre, 24811 35657, release_year, 1421 12776, has_genre, 24811 12776, release_year, 1421 31326, has_genre, 24811 31326, release_year, 1421 14366, has_genre, 24811 14366, release_year, 1421 33891, has_genre, 24811 33891, release_year, 1421 33776, has_genre, 24811 33776, release_year, 1421 33776, starred_actors, 38966 13177, has_genre, 24811 13177, release_year, 1421 571, has_genre, 24811 571, release_year, 1421 378, has_genre, 24811 378, has_tags, 38966 378, starred_actors, 38966 17358, has_genre, 24811 17358, release_year, 1421 17319, starred_actors, 32370 26190, has_genre, 24811 26190, release_year, 1421 33165, has_genre, 24811 33165, release_year, 1421 11517, has_genre, 24811 11517, release_year, 1421 21188, has_genre, 24811 21188, release_year, 1421 25264, has_genre, 24811 25264, has_tags, 17319 26943, has_genre, 24811 26943, release_year, 1421 12443, has_genre, 24811 12443, release_year, 1421 32954, has_genre, 24811 32954, release_year, 1421 536, has_genre, 24811 536, release_year, 1421 8352, has_genre, 24811 8352, release_year, 1421 32279, has_genre, 24811 32279, release_year, 1421 29074, has_genre, 24811 29074, release_year, 1421 4066, has_genre, 24811 4066, release_year, 1421 13471, has_tags, 24811 13471, release_year, 1421 22512, has_genre, 24811 22512, has_tags, 24811 22512, release_year, 1421 6745, has_genre, 24811 6745, release_year, 1421 38583, has_genre, 24811 38583, has_tags, 17319 2404, has_genre, 24811 2404, release_year, 1421 27160, has_genre, 24811 27160, release_year, 1421 2485, has_genre, 24811 2485, release_year, 1421 26621, has_genre, 24811 26621, release_year, 1421 30357, has_genre, 24811 30357, has_tags, 24811 30357, release_year, 1421 16450, has_genre, 24811 16450, release_year, 1421 34509, has_genre, 24811 34509, release_year, 1421 28652, has_genre, 24811 28652, release_year, 1421 16900, has_genre, 24811 16900, release_year, 1421 29799, has_genre, 24811 29799, release_year, 1421 31128, has_genre, 24811 31128, release_year, 1421 38107, has_genre, 24811 38107, release_year, 1421 2878, has_genre, 24811 2878, written_by, 10085 35937, has_genre, 24811 35937, release_year, 1421 36893, has_genre, 24811 36893, release_year, 1421 13613, has_genre, 24811 13613, starred_actors, 38966 8137, has_genre, 24811 8137, release_year, 1421 31276, has_genre, 24811 31276, release_year, 1421 27098, has_genre, 24811 27098, has_tags, 17319 27098, has_tags, 24811 6427, has_genre, 24811 6427, release_year, 1421 13106, has_genre, 24811 13106, release_year, 1421 32390, has_genre, 24811 32390, starred_actors, 38966 38582, has_genre, 24811 38582, release_year, 1421 27476, has_genre, 24811 27476, release_year, 1421 15230, has_tags, 24811 15230, release_year, 1421 5603, has_genre, 24811 5603, has_tags, 33956 5603, release_year, 1421 5603, starred_actors, 38966 26489, has_genre, 24811 26489, release_year, 1421 32403, has_genre, 24811 32403, has_tags, 24811 32403, release_year, 1421 Question: How are JOY BRYANT, R. LANCE HILL, and VEHICLE 19 related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOY BRYANT", "R. LANCE HILL", "VEHICLE 19" ], "valid_edges": [ [ "+1", "has_genre", "THRILLER" ], [ "+1", "release_year", "2013" ], [ "A COMMON MAN", "has_genre", "THRILLER" ], [ "A COMMON MAN", "release_year", "2013" ], [ "A RESURRECTION", "has_genre", "THRILLER" ], [ "A RESURRECTION", "release_year", "2013" ], [ "A SINGLE SHOT", "has_genre", "THRILLER" ], [ "A SINGLE SHOT", "release_year", "2013" ], [ "ASSAULT ON WALL STREET", "has_genre", "THRILLER" ], [ "ASSAULT ON WALL STREET", "release_year", "2013" ], [ "BIG BAD WOLVES", "has_genre", "THRILLER" ], [ "BIG BAD WOLVES", "release_year", "2013" ], [ "BLOOD DIAMOND", "has_genre", "THRILLER" ], [ "BLOOD DIAMOND", "has_tags", "SOUTH AFRICA" ], [ "BLOOD TIES", "has_genre", "THRILLER" ], [ "BLOOD TIES", "release_year", "2013" ], [ "BLUE RUIN", "has_genre", "THRILLER" ], [ "BLUE RUIN", "release_year", "2013" ], [ "BORGMAN", "has_genre", "THRILLER" ], [ "BORGMAN", "release_year", "2013" ], [ "BROKEN CITY", "has_genre", "THRILLER" ], [ "BROKEN CITY", "release_year", "2013" ], [ "CAPTAIN PHILLIPS", "has_genre", "THRILLER" ], [ "CAPTAIN PHILLIPS", "release_year", "2013" ], [ "COHERENCE", "has_genre", "THRILLER" ], [ "COHERENCE", "release_year", "2013" ], [ "COLD COMES THE NIGHT", "has_genre", "THRILLER" ], [ "COLD COMES THE NIGHT", "release_year", "2013" ], [ "COMPULSION", "has_genre", "THRILLER" ], [ "COMPULSION", "release_year", "2013" ], [ "CONTRACTED", "has_genre", "THRILLER" ], [ "CONTRACTED", "release_year", "2013" ], [ "CRAWLSPACE", "has_genre", "THRILLER" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "D-DAY", "has_genre", "THRILLER" ], [ "D-DAY", "release_year", "2013" ], [ "DARK SKIES", "has_genre", "THRILLER" ], [ "DARK SKIES", "release_year", "2013" ], [ "DIRTY PRETTY THINGS", "has_genre", "THRILLER" ], [ "DIRTY PRETTY THINGS", "has_tags", "LONDON" ], [ "DRISHYAM", "has_genre", "THRILLER" ], [ "DRISHYAM", "release_year", "2013" ], [ "ENEMY", "has_genre", "THRILLER" ], [ "ENEMY", "release_year", "2013" ], [ "ESCAPE PLAN", "has_genre", "THRILLER" ], [ "ESCAPE PLAN", "release_year", "2013" ], [ "EVIDENCE", "has_genre", "THRILLER" ], [ "EVIDENCE", "release_year", "2013" ], [ "FELONY", "has_genre", "THRILLER" ], [ "FELONY", "release_year", "2013" ], [ "FROZEN", "has_genre", "THRILLER" ], [ "FROZEN", "release_year", "2013" ], [ "GETAWAY", "has_genre", "THRILLER" ], [ "GETAWAY", "release_year", "2013" ], [ "GLORIA", "has_genre", "THRILLER" ], [ "GLORIA", "release_year", "2013" ], [ "GRAND PIANO", "has_genre", "THRILLER" ], [ "GRAND PIANO", "release_year", "2013" ], [ "GRAVITY", "has_genre", "THRILLER" ], [ "GRAVITY", "release_year", "2013" ], [ "HAUNTER", "has_genre", "THRILLER" ], [ "HAUNTER", "release_year", "2013" ], [ "HORNS", "has_genre", "THRILLER" ], [ "HORNS", "release_year", "2013" ], [ "HOURS", "has_genre", "THRILLER" ], [ "HOURS", "release_year", "2013" ], [ "HOURS", "starred_actors", "PAUL WALKER" ], [ "HOUSE HUNTING", "has_genre", "THRILLER" ], [ "HOUSE HUNTING", "release_year", "2013" ], [ "IN SECRET", "has_genre", "THRILLER" ], [ "IN SECRET", "release_year", "2013" ], [ "JOY RIDE", "has_genre", "THRILLER" ], [ "JOY RIDE", "has_tags", "PAUL WALKER" ], [ "JOY RIDE", "starred_actors", "PAUL WALKER" ], [ "LAST PASSENGER", "has_genre", "THRILLER" ], [ "LAST PASSENGER", "release_year", "2013" ], [ "LONDON", "starred_actors", "JOY BRYANT" ], [ "MAGIC MAGIC", "has_genre", "THRILLER" ], [ "MAGIC MAGIC", "release_year", "2013" ], [ "MISCHIEF NIGHT", "has_genre", "THRILLER" ], [ "MISCHIEF NIGHT", "release_year", "2013" ], [ "MISSIONARY", "has_genre", "THRILLER" ], [ "MISSIONARY", "release_year", "2013" ], [ "MR. JONES", "has_genre", "THRILLER" ], [ "MR. JONES", "release_year", "2013" ], [ "NOTES ON A SCANDAL", "has_genre", "THRILLER" ], [ "NOTES ON A SCANDAL", "has_tags", "LONDON" ], [ "NOW YOU SEE ME", "has_genre", "THRILLER" ], [ "NOW YOU SEE ME", "release_year", "2013" ], [ "ODD THOMAS", "has_genre", "THRILLER" ], [ "ODD THOMAS", "release_year", "2013" ], [ "OLDBOY", "has_genre", "THRILLER" ], [ "OLDBOY", "release_year", "2013" ], [ "OUT OF THE FURNACE", "has_genre", "THRILLER" ], [ "OUT OF THE FURNACE", "release_year", "2013" ], [ "PARANOIA", "has_genre", "THRILLER" ], [ "PARANOIA", "release_year", "2013" ], [ "PARKER", "has_genre", "THRILLER" ], [ "PARKER", "release_year", "2013" ], [ "PENTHOUSE NORTH", "has_genre", "THRILLER" ], [ "PENTHOUSE NORTH", "release_year", "2013" ], [ "PIONEER", "has_genre", "THRILLER" ], [ "PIONEER", "release_year", "2013" ], [ "PRISONERS", "has_tags", "THRILLER" ], [ "PRISONERS", "release_year", "2013" ], [ "RUNNER RUNNER", "has_genre", "THRILLER" ], [ "RUNNER RUNNER", "has_tags", "THRILLER" ], [ "RUNNER RUNNER", "release_year", "2013" ], [ "SCENIC ROUTE", "has_genre", "THRILLER" ], [ "SCENIC ROUTE", "release_year", "2013" ], [ "SHIFTY", "has_genre", "THRILLER" ], [ "SHIFTY", "has_tags", "LONDON" ], [ "SIDE EFFECTS", "has_genre", "THRILLER" ], [ "SIDE EFFECTS", "release_year", "2013" ], [ "SOLO", "has_genre", "THRILLER" ], [ "SOLO", "release_year", "2013" ], [ "SPARKS", "has_genre", "THRILLER" ], [ "SPARKS", "release_year", "2013" ], [ "STAY", "has_genre", "THRILLER" ], [ "STAY", "release_year", "2013" ], [ "STOKER", "has_genre", "THRILLER" ], [ "STOKER", "has_tags", "THRILLER" ], [ "STOKER", "release_year", "2013" ], [ "STRANGER BY THE LAKE", "has_genre", "THRILLER" ], [ "STRANGER BY THE LAKE", "release_year", "2013" ], [ "SWEETWATER", "has_genre", "THRILLER" ], [ "SWEETWATER", "release_year", "2013" ], [ "TABLE NO. 21", "has_genre", "THRILLER" ], [ "TABLE NO. 21", "release_year", "2013" ], [ "THE CALL", "has_genre", "THRILLER" ], [ "THE CALL", "release_year", "2013" ], [ "THE CANYONS", "has_genre", "THRILLER" ], [ "THE CANYONS", "release_year", "2013" ], [ "THE COUNSELOR", "has_genre", "THRILLER" ], [ "THE COUNSELOR", "release_year", "2013" ], [ "THE EAST", "has_genre", "THRILLER" ], [ "THE EAST", "release_year", "2013" ], [ "THE EVIL THAT MEN DO", "has_genre", "THRILLER" ], [ "THE EVIL THAT MEN DO", "written_by", "R. LANCE HILL" ], [ "THE FIFTH ESTATE", "has_genre", "THRILLER" ], [ "THE FIFTH ESTATE", "release_year", "2013" ], [ "THE GIRL ON THE TRAIN", "has_genre", "THRILLER" ], [ "THE GIRL ON THE TRAIN", "release_year", "2013" ], [ "THE LAZARUS PROJECT", "has_genre", "THRILLER" ], [ "THE LAZARUS PROJECT", "starred_actors", "PAUL WALKER" ], [ "THE MACHINE", "has_genre", "THRILLER" ], [ "THE MACHINE", "release_year", "2013" ], [ "THE NUMBERS STATION", "has_genre", "THRILLER" ], [ "THE NUMBERS STATION", "release_year", "2013" ], [ "THE PRESTIGE", "has_genre", "THRILLER" ], [ "THE PRESTIGE", "has_tags", "LONDON" ], [ "THE PRESTIGE", "has_tags", "THRILLER" ], [ "THE PURGE", "has_genre", "THRILLER" ], [ "THE PURGE", "release_year", "2013" ], [ "THE SACRAMENT", "has_genre", "THRILLER" ], [ "THE SACRAMENT", "release_year", "2013" ], [ "THE SKULLS", "has_genre", "THRILLER" ], [ "THE SKULLS", "starred_actors", "PAUL WALKER" ], [ "TOM AT THE FARM", "has_genre", "THRILLER" ], [ "TOM AT THE FARM", "release_year", "2013" ], [ "TORMENT", "has_genre", "THRILLER" ], [ "TORMENT", "release_year", "2013" ], [ "TRANCE", "has_tags", "THRILLER" ], [ "TRANCE", "release_year", "2013" ], [ "VEHICLE 19", "has_genre", "THRILLER" ], [ "VEHICLE 19", "has_tags", "SOUTH AFRICA" ], [ "VEHICLE 19", "release_year", "2013" ], [ "VEHICLE 19", "starred_actors", "PAUL WALKER" ], [ "WELCOME TO THE PUNCH", "has_genre", "THRILLER" ], [ "WELCOME TO THE PUNCH", "release_year", "2013" ], [ "WHITE HOUSE DOWN", "has_genre", "THRILLER" ], [ "WHITE HOUSE DOWN", "has_tags", "THRILLER" ], [ "WHITE HOUSE DOWN", "release_year", "2013" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 33387, CITY OF GOD 32183, DOUGLAS SILVA 15436, EPIC 11565, GOOD 26124, GOOD NEIGHBOR SAM 12502, GOODBYE CHARLIE 37848, MURDER MOST FOUL 23364, RENÉ PETER 34860, THIS IS THE NIGHT src, edge_attr, dst 33387, has_tags, 15436 33387, starred_actors, 32183 15436, has_imdb_rating, 11565 11565, has_imdb_rating, 11565 26124, has_imdb_rating, 11565 26124, release_year, 30172 12502, has_imdb_rating, 11565 12502, release_year, 30172 37848, has_imdb_rating, 11565 37848, release_year, 30172 34860, has_imdb_rating, 11565 34860, written_by, 23364 Question: For what reason are DOUGLAS SILVA, GOODBYE CHARLIE, and RENÉ PETER associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DOUGLAS SILVA", "GOODBYE CHARLIE", "RENÉ PETER" ], "valid_edges": [ [ "CITY OF GOD", "has_tags", "EPIC" ], [ "CITY OF GOD", "starred_actors", "DOUGLAS SILVA" ], [ "EPIC", "has_imdb_rating", "GOOD" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "release_year", "1964" ], [ "GOODBYE CHARLIE", "has_imdb_rating", "GOOD" ], [ "GOODBYE CHARLIE", "release_year", "1964" ], [ "MURDER MOST FOUL", "has_imdb_rating", "GOOD" ], [ "MURDER MOST FOUL", "release_year", "1964" ], [ "THIS IS THE NIGHT", "has_imdb_rating", "GOOD" ], [ "THIS IS THE NIGHT", "written_by", "RENÉ PETER" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32539, BREAKFAST WITH SCOT 30463, COMEDY 36690, COMRADE X 9353, LAURIE LYND 3459, LONESOME JIM src, edge_attr, dst 32539, directed_by, 9353 32539, has_genre, 30463 36690, has_genre, 30463 3459, has_genre, 30463 Question: How are COMRADE X, LAURIE LYND, and LONESOME JIM related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "COMRADE X", "LAURIE LYND", "LONESOME JIM" ], "valid_edges": [ [ "BREAKFAST WITH SCOT", "directed_by", "LAURIE LYND" ], [ "BREAKFAST WITH SCOT", "has_genre", "COMEDY" ], [ "COMRADE X", "has_genre", "COMEDY" ], [ "LONESOME JIM", "has_genre", "COMEDY" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39397, AIMEE MOLLOY 20757, CLOUDS OF SILS MARIA 36212, DRAMA 7480, EDEN 6480, GERMAN 15765, HAMSUN 16788, INBETWEEN WORLDS 39284, POSSESSION 30919, PRISON 3126, ROSEWATER 3416, SARABAND 23194, STATIONS OF THE CROSS 2227, THE GIRL IN THE PARK 9406, THE IMITATION GAME 14874, THE SCARLET LETTER src, edge_attr, dst 20757, has_genre, 36212 20757, in_language, 6480 7480, has_genre, 36212 7480, in_language, 6480 15765, has_genre, 36212 15765, in_language, 6480 16788, has_genre, 36212 16788, in_language, 6480 39284, has_genre, 36212 39284, in_language, 6480 30919, has_genre, 36212 3126, has_genre, 36212 3126, has_tags, 30919 3126, written_by, 39397 3416, has_genre, 36212 3416, has_tags, 36212 3416, in_language, 6480 23194, has_genre, 36212 23194, in_language, 6480 2227, has_genre, 36212 9406, has_genre, 36212 9406, in_language, 6480 14874, has_genre, 36212 14874, in_language, 6480 Question: In what context are AIMEE MOLLOY, THE GIRL IN THE PARK, and THE SCARLET LETTER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "AIMEE MOLLOY", "THE GIRL IN THE PARK", "THE SCARLET LETTER" ], "valid_edges": [ [ "CLOUDS OF SILS MARIA", "has_genre", "DRAMA" ], [ "CLOUDS OF SILS MARIA", "in_language", "GERMAN" ], [ "EDEN", "has_genre", "DRAMA" ], [ "EDEN", "in_language", "GERMAN" ], [ "HAMSUN", "has_genre", "DRAMA" ], [ "HAMSUN", "in_language", "GERMAN" ], [ "INBETWEEN WORLDS", "has_genre", "DRAMA" ], [ "INBETWEEN WORLDS", "in_language", "GERMAN" ], [ "POSSESSION", "has_genre", "DRAMA" ], [ "POSSESSION", "in_language", "GERMAN" ], [ "PRISON", "has_genre", "DRAMA" ], [ "ROSEWATER", "has_genre", "DRAMA" ], [ "ROSEWATER", "has_tags", "PRISON" ], [ "ROSEWATER", "written_by", "AIMEE MOLLOY" ], [ "SARABAND", "has_genre", "DRAMA" ], [ "SARABAND", "has_tags", "DRAMA" ], [ "SARABAND", "in_language", "GERMAN" ], [ "STATIONS OF THE CROSS", "has_genre", "DRAMA" ], [ "STATIONS OF THE CROSS", "in_language", "GERMAN" ], [ "THE GIRL IN THE PARK", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "in_language", "GERMAN" ], [ "THE SCARLET LETTER", "has_genre", "DRAMA" ], [ "THE SCARLET LETTER", "in_language", "GERMAN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 22229, CLAIRE OF THE MOON 30463, COMEDY 2890, DESERT HEARTS 36212, DRAMA 35150, FRIED GREEN TOMATOES 35421, GO FISH 8635, LESBIAN 7221, LOVE SICK 10378, MAURY YESTON 17860, NINE 8280, PARIAH 22661, RAISE THE RED LANTERN 24853, SPIDER LILIES 27200, SU TONG 20210, THE WOMEN src, edge_attr, dst 22229, has_genre, 36212 22229, has_tags, 8635 2890, has_genre, 36212 2890, has_tags, 8635 35150, has_genre, 30463 35150, has_genre, 36212 35150, has_tags, 36212 35150, has_tags, 8635 35150, release_year, 10702 35421, has_genre, 36212 35421, has_tags, 8635 7221, has_genre, 36212 7221, has_tags, 8635 17860, has_genre, 36212 17860, written_by, 10378 8280, has_genre, 36212 8280, has_tags, 8635 22661, release_year, 10702 22661, written_by, 27200 24853, has_genre, 36212 24853, has_tags, 36212 24853, has_tags, 8635 20210, has_genre, 30463 20210, has_genre, 36212 20210, has_tags, 8635 Question: In what context are LESBIAN, MAURY YESTON, and SU TONG connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "LESBIAN", "MAURY YESTON", "SU TONG" ], "valid_edges": [ [ "CLAIRE OF THE MOON", "has_genre", "DRAMA" ], [ "CLAIRE OF THE MOON", "has_tags", "LESBIAN" ], [ "DESERT HEARTS", "has_genre", "DRAMA" ], [ "DESERT HEARTS", "has_tags", "LESBIAN" ], [ "FRIED GREEN TOMATOES", "has_genre", "COMEDY" ], [ "FRIED GREEN TOMATOES", "has_genre", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "DRAMA" ], [ "FRIED GREEN TOMATOES", "has_tags", "LESBIAN" ], [ "FRIED GREEN TOMATOES", "release_year", "1991" ], [ "GO FISH", "has_genre", "DRAMA" ], [ "GO FISH", "has_tags", "LESBIAN" ], [ "LOVE SICK", "has_genre", "DRAMA" ], [ "LOVE SICK", "has_tags", "LESBIAN" ], [ "NINE", "has_genre", "DRAMA" ], [ "NINE", "written_by", "MAURY YESTON" ], [ "PARIAH", "has_genre", "DRAMA" ], [ "PARIAH", "has_tags", "LESBIAN" ], [ "RAISE THE RED LANTERN", "release_year", "1991" ], [ "RAISE THE RED LANTERN", "written_by", "SU TONG" ], [ "SPIDER LILIES", "has_genre", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "DRAMA" ], [ "SPIDER LILIES", "has_tags", "LESBIAN" ], [ "THE WOMEN", "has_genre", "COMEDY" ], [ "THE WOMEN", "has_genre", "DRAMA" ], [ "THE WOMEN", "has_tags", "LESBIAN" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17315, 2007 10597, BECOMING JANE 30501, BEOWULF 21275, BROKEN ENGLISH 1424, CALIFORNIA DREAMIN' 3928, CHEENI KUM 30463, COMEDY 928, CONTROL 31783, ENGLISH 9003, FUNNY GAMES 26968, HOT FUZZ 12821, JAB WE MET 29792, JOY DIVISION 14878, KABHI HAAN KABHI NAA 33888, LOVE IN THE TIME OF CHOLERA 28622, MY BLUEBERRY NIGHTS 20348, PATHFINDER 12825, PERSUASION 1643, RISE OF THE FOOTSOLDIER 17447, SON OF RAMBOW 28002, SUKIYAKI WESTERN DJANGO 25270, THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT 30090, THE AIR UP THERE 8201, THE BAND'S VISIT 25509, THE DEBT 1589, THE FLOCK 32459, THE HAMMER 10331, THE KITE RUNNER 8712, THE LORD OF THE RINGS 21696, THE MAN FROM LONDON 11046, UNDER THE SAME MOON 9265, YOLANDA VAZQUEZ src, edge_attr, dst 10597, in_language, 31783 10597, release_year, 17315 30501, in_language, 31783 30501, release_year, 17315 21275, in_language, 31783 21275, release_year, 17315 1424, in_language, 31783 1424, release_year, 17315 3928, in_language, 31783 3928, release_year, 17315 928, in_language, 31783 928, release_year, 17315 9003, in_language, 31783 9003, release_year, 17315 26968, has_genre, 30463 26968, has_tags, 30463 26968, in_language, 31783 26968, release_year, 17315 12821, has_genre, 30463 12821, in_language, 31783 12821, release_year, 17315 29792, in_language, 31783 29792, release_year, 17315 14878, has_genre, 30463 14878, in_language, 31783 33888, in_language, 31783 33888, release_year, 17315 28622, in_language, 31783 28622, release_year, 17315 20348, in_language, 31783 20348, release_year, 17315 12825, in_language, 31783 12825, release_year, 17315 1643, in_language, 31783 1643, release_year, 17315 17447, has_genre, 30463 17447, in_language, 31783 17447, release_year, 17315 28002, in_language, 31783 28002, release_year, 17315 25270, has_genre, 30463 25270, in_language, 31783 30090, has_genre, 30463 30090, has_tags, 30463 30090, starred_actors, 9265 8201, in_language, 31783 8201, release_year, 17315 25509, in_language, 31783 25509, release_year, 17315 1589, in_language, 31783 1589, release_year, 17315 32459, has_genre, 30463 32459, release_year, 17315 10331, in_language, 31783 10331, release_year, 17315 8712, in_language, 31783 21696, in_language, 31783 21696, release_year, 17315 11046, in_language, 31783 11046, release_year, 17315 Question: For what reason are THE HAMMER, THE LORD OF THE RINGS, and YOLANDA VAZQUEZ associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "THE HAMMER", "THE LORD OF THE RINGS", "YOLANDA VAZQUEZ" ], "valid_edges": [ [ "BECOMING JANE", "in_language", "ENGLISH" ], [ "BECOMING JANE", "release_year", "2007" ], [ "BEOWULF", "in_language", "ENGLISH" ], [ "BEOWULF", "release_year", "2007" ], [ "BROKEN ENGLISH", "in_language", "ENGLISH" ], [ "BROKEN ENGLISH", "release_year", "2007" ], [ "CALIFORNIA DREAMIN'", "in_language", "ENGLISH" ], [ "CALIFORNIA DREAMIN'", "release_year", "2007" ], [ "CHEENI KUM", "in_language", "ENGLISH" ], [ "CHEENI KUM", "release_year", "2007" ], [ "CONTROL", "in_language", "ENGLISH" ], [ "CONTROL", "release_year", "2007" ], [ "FUNNY GAMES", "in_language", "ENGLISH" ], [ "FUNNY GAMES", "release_year", "2007" ], [ "HOT FUZZ", "has_genre", "COMEDY" ], [ "HOT FUZZ", "has_tags", "COMEDY" ], [ "HOT FUZZ", "in_language", "ENGLISH" ], [ "HOT FUZZ", "release_year", "2007" ], [ "JAB WE MET", "has_genre", "COMEDY" ], [ "JAB WE MET", "in_language", "ENGLISH" ], [ "JAB WE MET", "release_year", "2007" ], [ "JOY DIVISION", "in_language", "ENGLISH" ], [ "JOY DIVISION", "release_year", "2007" ], [ "KABHI HAAN KABHI NAA", "has_genre", "COMEDY" ], [ "KABHI HAAN KABHI NAA", "in_language", "ENGLISH" ], [ "LOVE IN THE TIME OF CHOLERA", "in_language", "ENGLISH" ], [ "LOVE IN THE TIME OF CHOLERA", "release_year", "2007" ], [ "MY BLUEBERRY NIGHTS", "in_language", "ENGLISH" ], [ "MY BLUEBERRY NIGHTS", "release_year", "2007" ], [ "PATHFINDER", "in_language", "ENGLISH" ], [ "PATHFINDER", "release_year", "2007" ], [ "PERSUASION", "in_language", "ENGLISH" ], [ "PERSUASION", "release_year", "2007" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "RISE OF THE FOOTSOLDIER", "release_year", "2007" ], [ "SON OF RAMBOW", "has_genre", "COMEDY" ], [ "SON OF RAMBOW", "in_language", "ENGLISH" ], [ "SON OF RAMBOW", "release_year", "2007" ], [ "SUKIYAKI WESTERN DJANGO", "in_language", "ENGLISH" ], [ "SUKIYAKI WESTERN DJANGO", "release_year", "2007" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PRISCILLA, QUEEN OF THE DESERT", "in_language", "ENGLISH" ], [ "THE AIR UP THERE", "has_genre", "COMEDY" ], [ "THE AIR UP THERE", "has_tags", "COMEDY" ], [ "THE AIR UP THERE", "starred_actors", "YOLANDA VAZQUEZ" ], [ "THE BAND'S VISIT", "in_language", "ENGLISH" ], [ "THE BAND'S VISIT", "release_year", "2007" ], [ "THE DEBT", "in_language", "ENGLISH" ], [ "THE DEBT", "release_year", "2007" ], [ "THE FLOCK", "in_language", "ENGLISH" ], [ "THE FLOCK", "release_year", "2007" ], [ "THE HAMMER", "has_genre", "COMEDY" ], [ "THE HAMMER", "release_year", "2007" ], [ "THE KITE RUNNER", "in_language", "ENGLISH" ], [ "THE KITE RUNNER", "release_year", "2007" ], [ "THE LORD OF THE RINGS", "in_language", "ENGLISH" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MAN FROM LONDON", "release_year", "2007" ], [ "UNDER THE SAME MOON", "in_language", "ENGLISH" ], [ "UNDER THE SAME MOON", "release_year", "2007" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1892, 1932 6216, 1952 15374, 2005 38588, 5 FINGERS 33955, EMPIRE OF THE WOLVES 7498, FLIGHTPLAN 6480, GERMAN 34073, HELL 6047, HÔTEL DES INVALIDES 38312, MOUTH TO MOUTH 36899, SHORT 3008, SUMMER IN BERLIN 12267, THE BLUE LIGHT 3354, THE BROTHERS GRIMM 10661, THE MUSIC BOX 6575, THE WAVE 38370, VAMPYR 39544, WE FEED THE WORLD src, edge_attr, dst 38588, in_language, 6480 38588, release_year, 6216 33955, release_year, 15374 7498, in_language, 6480 7498, release_year, 15374 34073, in_language, 6480 34073, release_year, 15374 6047, has_genre, 36899 6047, release_year, 6216 38312, in_language, 6480 38312, release_year, 15374 3008, in_language, 6480 3008, release_year, 15374 12267, in_language, 6480 12267, release_year, 1892 3354, in_language, 6480 3354, release_year, 15374 10661, has_genre, 36899 10661, has_tags, 36899 10661, release_year, 1892 6575, has_genre, 36899 6575, in_language, 6480 38370, in_language, 6480 38370, release_year, 1892 39544, in_language, 6480 39544, release_year, 15374 Question: For what reason are EMPIRE OF THE WOLVES, HÔTEL DES INVALIDES, and VAMPYR associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EMPIRE OF THE WOLVES", "HÔTEL DES INVALIDES", "VAMPYR" ], "valid_edges": [ [ "5 FINGERS", "in_language", "GERMAN" ], [ "5 FINGERS", "release_year", "1952" ], [ "EMPIRE OF THE WOLVES", "release_year", "2005" ], [ "FLIGHTPLAN", "in_language", "GERMAN" ], [ "FLIGHTPLAN", "release_year", "2005" ], [ "HELL", "in_language", "GERMAN" ], [ "HELL", "release_year", "2005" ], [ "HÔTEL DES INVALIDES", "has_genre", "SHORT" ], [ "HÔTEL DES INVALIDES", "release_year", "1952" ], [ "MOUTH TO MOUTH", "in_language", "GERMAN" ], [ "MOUTH TO MOUTH", "release_year", "2005" ], [ "SUMMER IN BERLIN", "in_language", "GERMAN" ], [ "SUMMER IN BERLIN", "release_year", "2005" ], [ "THE BLUE LIGHT", "in_language", "GERMAN" ], [ "THE BLUE LIGHT", "release_year", "1932" ], [ "THE BROTHERS GRIMM", "in_language", "GERMAN" ], [ "THE BROTHERS GRIMM", "release_year", "2005" ], [ "THE MUSIC BOX", "has_genre", "SHORT" ], [ "THE MUSIC BOX", "has_tags", "SHORT" ], [ "THE MUSIC BOX", "release_year", "1932" ], [ "THE WAVE", "has_genre", "SHORT" ], [ "THE WAVE", "in_language", "GERMAN" ], [ "VAMPYR", "in_language", "GERMAN" ], [ "VAMPYR", "release_year", "1932" ], [ "WE FEED THE WORLD", "in_language", "GERMAN" ], [ "WE FEED THE WORLD", "release_year", "2005" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 4763, ADVENTURE 27192, DON PAUL 36212, DRAMA 36153, LAWRENCE B. MARCUS 15525, PETULIA 1400, RICHARD BRIERS 23530, THE ROAD TO EL DORADO 25311, WATERSHIP DOWN src, edge_attr, dst 15525, has_genre, 36212 15525, written_by, 36153 23530, directed_by, 27192 23530, has_genre, 4763 25311, has_genre, 4763 25311, has_genre, 36212 25311, starred_actors, 1400 Question: For what reason are DON PAUL, LAWRENCE B. MARCUS, and RICHARD BRIERS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DON PAUL", "LAWRENCE B. MARCUS", "RICHARD BRIERS" ], "valid_edges": [ [ "PETULIA", "has_genre", "DRAMA" ], [ "PETULIA", "written_by", "LAWRENCE B. MARCUS" ], [ "THE ROAD TO EL DORADO", "directed_by", "DON PAUL" ], [ "THE ROAD TO EL DORADO", "has_genre", "ADVENTURE" ], [ "WATERSHIP DOWN", "has_genre", "ADVENTURE" ], [ "WATERSHIP DOWN", "has_genre", "DRAMA" ], [ "WATERSHIP DOWN", "starred_actors", "RICHARD BRIERS" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1006, 1996 36448, DEADLY VOYAGE 9445, JANET GUNN 63, MICHAEL JORDAN 3288, SPACE JAM 12863, THE QUEST src, edge_attr, dst 36448, release_year, 1006 3288, release_year, 1006 3288, starred_actors, 63 12863, release_year, 1006 12863, starred_actors, 9445 Question: For what reason are DEADLY VOYAGE, JANET GUNN, and MICHAEL JORDAN associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DEADLY VOYAGE", "JANET GUNN", "MICHAEL JORDAN" ], "valid_edges": [ [ "DEADLY VOYAGE", "release_year", "1996" ], [ "SPACE JAM", "release_year", "1996" ], [ "SPACE JAM", "starred_actors", "MICHAEL JORDAN" ], [ "THE QUEST", "release_year", "1996" ], [ "THE QUEST", "starred_actors", "JANET GUNN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 7158, 1958 25221, 1981 33215, A NIGHT TO REMEMBER 21806, AUNTIE MAME 19992, BIG DEAL ON MADONNA STREET 30463, COMEDY 27772, GIANTS AND TOYS 5527, GIGI 14193, HOUSEBOAT 9712, INDISCREET 22253, JUDIT POGÁNY 9198, MALIBU'S MOST WANTED 8610, ME AND THE COLONEL 31657, MON ONCLE 24842, NO TIME FOR SERGEANTS 15070, ONIONHEAD 15988, PARTY GIRL 12895, TEACHER'S PET 7973, THE HIDDEN FORTRESS 22174, THE LITTLE FOX 6857, THE MATCHMAKER 36072, THE RELUCTANT DEBUTANTE 15546, THE TUNNEL OF LOVE src, edge_attr, dst 25221, has_genre, 30463 33215, has_genre, 30463 33215, release_year, 7158 21806, has_genre, 30463 21806, release_year, 7158 19992, has_genre, 30463 19992, release_year, 7158 27772, has_genre, 30463 27772, release_year, 7158 5527, has_genre, 30463 5527, release_year, 7158 14193, has_genre, 30463 14193, release_year, 7158 9712, has_genre, 30463 9712, release_year, 7158 9198, has_genre, 30463 8610, has_genre, 30463 8610, release_year, 7158 31657, has_genre, 30463 31657, release_year, 7158 24842, has_genre, 30463 24842, release_year, 7158 15070, has_genre, 30463 15070, release_year, 7158 15988, has_genre, 30463 15988, release_year, 7158 12895, has_genre, 30463 12895, release_year, 7158 7973, release_year, 7158 22174, release_year, 25221 22174, starred_actors, 22253 6857, has_genre, 30463 6857, release_year, 7158 36072, has_genre, 30463 36072, release_year, 7158 15546, has_genre, 30463 15546, release_year, 7158 Question: In what context are JUDIT POGÁNY, MALIBU'S MOST WANTED, and THE HIDDEN FORTRESS connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JUDIT POGÁNY", "MALIBU'S MOST WANTED", "THE HIDDEN FORTRESS" ], "valid_edges": [ [ "1981", "has_genre", "COMEDY" ], [ "A NIGHT TO REMEMBER", "has_genre", "COMEDY" ], [ "A NIGHT TO REMEMBER", "release_year", "1958" ], [ "AUNTIE MAME", "has_genre", "COMEDY" ], [ "AUNTIE MAME", "release_year", "1958" ], [ "BIG DEAL ON MADONNA STREET", "has_genre", "COMEDY" ], [ "BIG DEAL ON MADONNA STREET", "release_year", "1958" ], [ "GIANTS AND TOYS", "has_genre", "COMEDY" ], [ "GIANTS AND TOYS", "release_year", "1958" ], [ "GIGI", "has_genre", "COMEDY" ], [ "GIGI", "release_year", "1958" ], [ "HOUSEBOAT", "has_genre", "COMEDY" ], [ "HOUSEBOAT", "release_year", "1958" ], [ "INDISCREET", "has_genre", "COMEDY" ], [ "INDISCREET", "release_year", "1958" ], [ "MALIBU'S MOST WANTED", "has_genre", "COMEDY" ], [ "ME AND THE COLONEL", "has_genre", "COMEDY" ], [ "ME AND THE COLONEL", "release_year", "1958" ], [ "MON ONCLE", "has_genre", "COMEDY" ], [ "MON ONCLE", "release_year", "1958" ], [ "NO TIME FOR SERGEANTS", "has_genre", "COMEDY" ], [ "NO TIME FOR SERGEANTS", "release_year", "1958" ], [ "ONIONHEAD", "has_genre", "COMEDY" ], [ "ONIONHEAD", "release_year", "1958" ], [ "PARTY GIRL", "has_genre", "COMEDY" ], [ "PARTY GIRL", "release_year", "1958" ], [ "TEACHER'S PET", "has_genre", "COMEDY" ], [ "TEACHER'S PET", "release_year", "1958" ], [ "THE HIDDEN FORTRESS", "release_year", "1958" ], [ "THE LITTLE FOX", "release_year", "1981" ], [ "THE LITTLE FOX", "starred_actors", "JUDIT POGÁNY" ], [ "THE MATCHMAKER", "has_genre", "COMEDY" ], [ "THE MATCHMAKER", "release_year", "1958" ], [ "THE RELUCTANT DEBUTANTE", "has_genre", "COMEDY" ], [ "THE RELUCTANT DEBUTANTE", "release_year", "1958" ], [ "THE TUNNEL OF LOVE", "has_genre", "COMEDY" ], [ "THE TUNNEL OF LOVE", "release_year", "1958" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 17978, AMERICAN VIOLET 13792, DON JON 36212, DRAMA 7585, TEXAS 2555, THE RARE BREED 11614, TIM DISNEY 25313, TONY DANZA 36026, WESTERN src, edge_attr, dst 17978, directed_by, 11614 17978, has_genre, 36212 17978, has_tags, 7585 13792, has_genre, 36212 13792, starred_actors, 25313 7585, has_genre, 36026 2555, has_genre, 36026 Question: For what reason are THE RARE BREED, TIM DISNEY, and TONY DANZA associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "THE RARE BREED", "TIM DISNEY", "TONY DANZA" ], "valid_edges": [ [ "AMERICAN VIOLET", "directed_by", "TIM DISNEY" ], [ "AMERICAN VIOLET", "has_genre", "DRAMA" ], [ "AMERICAN VIOLET", "has_tags", "TEXAS" ], [ "DON JON", "has_genre", "DRAMA" ], [ "DON JON", "starred_actors", "TONY DANZA" ], [ "TEXAS", "has_genre", "WESTERN" ], [ "THE RARE BREED", "has_genre", "WESTERN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26048, AMERICAN HUSTLE 11079, BORDERTOWN 29517, CARROLL GRAHAM 6871, COP LAND 14724, CRIME 36212, DRAMA 21640, GARDEN STATE 4246, JERSEY BOYS 22845, MUSIC 25511, NEW JERSEY 10275, ROBERT VERNAY 19351, THE COUNT OF MONTE CRISTO src, edge_attr, dst 26048, has_genre, 14724 26048, has_genre, 36212 26048, has_tags, 25511 11079, has_genre, 36212 11079, written_by, 29517 6871, has_genre, 14724 6871, has_genre, 36212 6871, has_tags, 14724 6871, has_tags, 36212 6871, has_tags, 25511 21640, has_genre, 36212 21640, has_tags, 22845 21640, has_tags, 25511 4246, has_genre, 36212 4246, has_genre, 22845 4246, has_tags, 22845 4246, has_tags, 25511 19351, directed_by, 10275 19351, has_genre, 36212 19351, written_by, 10275 Question: In what context are CARROLL GRAHAM, NEW JERSEY, and ROBERT VERNAY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CARROLL GRAHAM", "NEW JERSEY", "ROBERT VERNAY" ], "valid_edges": [ [ "AMERICAN HUSTLE", "has_genre", "CRIME" ], [ "AMERICAN HUSTLE", "has_genre", "DRAMA" ], [ "AMERICAN HUSTLE", "has_tags", "NEW JERSEY" ], [ "BORDERTOWN", "has_genre", "DRAMA" ], [ "BORDERTOWN", "written_by", "CARROLL GRAHAM" ], [ "COP LAND", "has_genre", "CRIME" ], [ "COP LAND", "has_genre", "DRAMA" ], [ "COP LAND", "has_tags", "CRIME" ], [ "COP LAND", "has_tags", "DRAMA" ], [ "COP LAND", "has_tags", "NEW JERSEY" ], [ "GARDEN STATE", "has_genre", "DRAMA" ], [ "GARDEN STATE", "has_tags", "MUSIC" ], [ "GARDEN STATE", "has_tags", "NEW JERSEY" ], [ "JERSEY BOYS", "has_genre", "DRAMA" ], [ "JERSEY BOYS", "has_genre", "MUSIC" ], [ "JERSEY BOYS", "has_tags", "MUSIC" ], [ "JERSEY BOYS", "has_tags", "NEW JERSEY" ], [ "THE COUNT OF MONTE CRISTO", "directed_by", "ROBERT VERNAY" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "written_by", "ROBERT VERNAY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 25717, 1953 1567, 1954 2355, 3 RING CIRCUS 35934, A LADY TAKES A CHANCE 18914, A LESSON IN LOVE 9152, A STAR IS BORN 21802, ABBOTT AND COSTELLO GO TO MARS 15922, ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE 22569, ALL ABOUT THE BENJAMINS 39641, ALONG CAME JONES 33952, ATHENA 38657, BEAT THE DEVIL 4698, BETTY GRABLE 10218, BLACK WIDOW 29294, BREAD, LOVE AND DREAMS 26642, BUS STOP 8430, CALL ME MADAM 24276, CASANOVA BROWN 16795, CASANOVA'S BIG NIGHT 30463, COMEDY 5865, DAVID WAYNE 27558, DESIGNING WOMAN 36492, DIAMONDS 1480, DREAM WIFE 36249, GENEVIEVE 38125, HIS PRIVATE SECRETARY 20400, HOBSON'S CHOICE 12557, HOW TO MARRY A MILLIONAIRE 17344, I VITELLONI 14341, IT COULD HAPPEN TO YOU 30470, IT SHOULD HAPPEN TO YOU 12435, JOHN WAYNE 6956, KNOCK ON WOOD 31519, LAUREN BACALL 10267, LET'S MAKE LOVE 432, LOTTERY 27297, MAGIC TOWN 21143, MARILYN MONROE 7495, MCLINTOCK! 13717, MONKEY BUSINESS 18524, MY BLUE HEAVEN 1436, NIGHT PEOPLE 30968, NOTHING SACRED 11190, NUNNALLY JOHNSON 39193, PHFFFT 13096, ROMAN HOLIDAY 20954, ROXIE HART 4689, SABRINA 7941, SEX AND THE SINGLE GIRL 26840, SOME LIKE IT HOT 39543, SUSAN SLEPT HERE 11290, TAKE HER, SHE'S MINE 22407, THE ACTRESS 32851, THE BAND WAGON 18855, THE CADDY 18055, THE CAPTAIN'S PARADISE 23631, THE HIGH AND THE MIGHTY 17527, THE MIRROR HAS TWO FACES 12672, THE MOON IS BLUE 16199, THE QUIET MAN 11310, THE REFORMER AND THE REDHEAD 3848, THE RETURN OF DON CAMILLO 25574, THE SEVEN YEAR ITCH 31357, THE SHOOTIST 10991, THE SUN SHINES BRIGHT 23294, THE TENDER TRAP 8289, THE TITFIELD THUNDERBOLT 15263, THE TWONKY 17209, THERE'S NO BUSINESS LIKE SHOW BUSINESS 27872, TRACK OF THE CAT 31364, WE'RE NOT MARRIED! 36409, WELCOME MR. MARSHALL! 24706, WILLIAM A. WELLMAN src, edge_attr, dst 2355, has_genre, 30463 2355, release_year, 1567 35934, has_genre, 30463 35934, starred_actors, 12435 18914, has_genre, 30463 18914, release_year, 1567 9152, directed_by, 24706 9152, has_tags, 24706 9152, release_year, 1567 9152, written_by, 24706 21802, has_genre, 30463 21802, release_year, 25717 15922, has_genre, 30463 15922, release_year, 25717 22569, has_genre, 30463 22569, has_tags, 30463 22569, has_tags, 432 39641, has_genre, 30463 39641, written_by, 11190 33952, has_genre, 30463 33952, release_year, 1567 38657, has_genre, 30463 38657, release_year, 25717 10218, directed_by, 11190 10218, release_year, 1567 10218, written_by, 11190 29294, has_genre, 30463 29294, release_year, 25717 26642, has_genre, 30463 26642, has_tags, 21143 26642, starred_actors, 21143 8430, has_genre, 30463 8430, release_year, 25717 24276, has_genre, 30463 24276, written_by, 11190 16795, has_genre, 30463 16795, release_year, 1567 27558, has_genre, 30463 27558, starred_actors, 31519 36492, has_genre, 30463 36492, starred_actors, 31519 1480, has_genre, 30463 1480, release_year, 25717 36249, has_genre, 30463 36249, release_year, 25717 38125, has_genre, 30463 38125, starred_actors, 12435 20400, has_genre, 30463 20400, release_year, 1567 12557, has_genre, 30463 12557, has_tags, 31519 12557, has_tags, 21143 12557, release_year, 25717 12557, starred_actors, 4698 12557, starred_actors, 5865 12557, starred_actors, 31519 12557, starred_actors, 21143 12557, written_by, 11190 17344, has_genre, 30463 17344, release_year, 25717 14341, has_genre, 30463 14341, has_tags, 30463 14341, has_tags, 432 30470, has_genre, 30463 30470, release_year, 1567 6956, has_genre, 30463 6956, release_year, 1567 10267, has_genre, 30463 10267, starred_actors, 21143 27297, directed_by, 24706 27297, has_genre, 30463 7495, has_genre, 30463 7495, has_tags, 12435 7495, starred_actors, 12435 13717, has_genre, 30463 13717, has_tags, 30463 13717, starred_actors, 21143 18524, has_genre, 30463 18524, starred_actors, 4698 1436, directed_by, 11190 1436, release_year, 1567 1436, written_by, 11190 30968, directed_by, 24706 30968, has_genre, 30463 30968, has_tags, 24706 39193, has_genre, 30463 39193, release_year, 1567 13096, has_genre, 30463 13096, has_tags, 30463 13096, release_year, 25717 20954, directed_by, 24706 20954, has_genre, 30463 20954, has_tags, 24706 4689, has_genre, 30463 4689, release_year, 1567 7941, has_genre, 30463 7941, starred_actors, 31519 26840, has_genre, 30463 26840, has_tags, 30463 26840, has_tags, 21143 26840, starred_actors, 21143 39543, has_genre, 30463 39543, release_year, 1567 11290, has_genre, 30463 11290, written_by, 11190 22407, has_genre, 30463 22407, release_year, 25717 32851, has_genre, 30463 32851, release_year, 25717 18855, has_genre, 30463 18855, release_year, 25717 18055, has_genre, 30463 18055, release_year, 25717 23631, directed_by, 24706 23631, has_tags, 24706 23631, release_year, 1567 23631, starred_actors, 12435 17527, has_genre, 30463 17527, starred_actors, 31519 12672, has_genre, 30463 12672, release_year, 25717 16199, has_genre, 30463 16199, has_tags, 12435 16199, starred_actors, 12435 11310, has_genre, 30463 11310, starred_actors, 5865 3848, has_genre, 30463 3848, release_year, 25717 25574, has_genre, 30463 25574, has_tags, 21143 25574, starred_actors, 21143 31357, has_tags, 12435 31357, starred_actors, 12435 31357, starred_actors, 31519 10991, has_genre, 30463 10991, release_year, 25717 23294, has_genre, 30463 23294, starred_actors, 5865 8289, has_genre, 30463 8289, release_year, 25717 15263, has_genre, 30463 15263, release_year, 25717 17209, has_genre, 30463 17209, release_year, 1567 17209, starred_actors, 21143 27872, directed_by, 24706 27872, release_year, 1567 31364, has_genre, 30463 31364, starred_actors, 21143 36409, has_genre, 30463 36409, release_year, 25717 Question: In what context are HOW TO MARRY A MILLIONAIRE, LOTTERY, and THE HIGH AND THE MIGHTY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HOW TO MARRY A MILLIONAIRE", "LOTTERY", "THE HIGH AND THE MIGHTY" ], "valid_edges": [ [ "3 RING CIRCUS", "has_genre", "COMEDY" ], [ "3 RING CIRCUS", "release_year", "1954" ], [ "A LADY TAKES A CHANCE", "has_genre", "COMEDY" ], [ "A LADY TAKES A CHANCE", "starred_actors", "JOHN WAYNE" ], [ "A LESSON IN LOVE", "has_genre", "COMEDY" ], [ "A LESSON IN LOVE", "release_year", "1954" ], [ "A STAR IS BORN", "directed_by", "WILLIAM A. WELLMAN" ], [ "A STAR IS BORN", "has_tags", "WILLIAM A. WELLMAN" ], [ "A STAR IS BORN", "release_year", "1954" ], [ "A STAR IS BORN", "written_by", "WILLIAM A. WELLMAN" ], [ "ABBOTT AND COSTELLO GO TO MARS", "has_genre", "COMEDY" ], [ "ABBOTT AND COSTELLO GO TO MARS", "release_year", "1953" ], [ "ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE", "has_genre", "COMEDY" ], [ "ABBOTT AND COSTELLO MEET DR. JEKYLL AND MR. HYDE", "release_year", "1953" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "LOTTERY" ], [ "ALONG CAME JONES", "has_genre", "COMEDY" ], [ "ALONG CAME JONES", "written_by", "NUNNALLY JOHNSON" ], [ "ATHENA", "has_genre", "COMEDY" ], [ "ATHENA", "release_year", "1954" ], [ "BEAT THE DEVIL", "has_genre", "COMEDY" ], [ "BEAT THE DEVIL", "release_year", "1953" ], [ "BLACK WIDOW", "directed_by", "NUNNALLY JOHNSON" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BLACK WIDOW", "written_by", "NUNNALLY JOHNSON" ], [ "BREAD, LOVE AND DREAMS", "has_genre", "COMEDY" ], [ "BREAD, LOVE AND DREAMS", "release_year", "1953" ], [ "BUS STOP", "has_genre", "COMEDY" ], [ "BUS STOP", "has_tags", "MARILYN MONROE" ], [ "BUS STOP", "starred_actors", "MARILYN MONROE" ], [ "CALL ME MADAM", "has_genre", "COMEDY" ], [ "CALL ME MADAM", "release_year", "1953" ], [ "CASANOVA BROWN", "has_genre", "COMEDY" ], [ "CASANOVA BROWN", "written_by", "NUNNALLY JOHNSON" ], [ "CASANOVA'S BIG NIGHT", "has_genre", "COMEDY" ], [ "CASANOVA'S BIG NIGHT", "release_year", "1954" ], [ "DESIGNING WOMAN", "has_genre", "COMEDY" ], [ "DESIGNING WOMAN", "starred_actors", "LAUREN BACALL" ], [ "DIAMONDS", "has_genre", "COMEDY" ], [ "DIAMONDS", "starred_actors", "LAUREN BACALL" ], [ "DREAM WIFE", "has_genre", "COMEDY" ], [ "DREAM WIFE", "release_year", "1953" ], [ "GENEVIEVE", "has_genre", "COMEDY" ], [ "GENEVIEVE", "release_year", "1953" ], [ "HIS PRIVATE SECRETARY", "has_genre", "COMEDY" ], [ "HIS PRIVATE SECRETARY", "starred_actors", "JOHN WAYNE" ], [ "HOBSON'S CHOICE", "has_genre", "COMEDY" ], [ "HOBSON'S CHOICE", "release_year", "1954" ], [ "HOW TO MARRY A MILLIONAIRE", "has_genre", "COMEDY" ], [ "HOW TO MARRY A MILLIONAIRE", "has_tags", "LAUREN BACALL" ], [ "HOW TO MARRY A MILLIONAIRE", "has_tags", "MARILYN MONROE" ], [ "HOW TO MARRY A MILLIONAIRE", "release_year", "1953" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "BETTY GRABLE" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "DAVID WAYNE" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "LAUREN BACALL" ], [ "HOW TO MARRY A MILLIONAIRE", "starred_actors", "MARILYN MONROE" ], [ "HOW TO MARRY A MILLIONAIRE", "written_by", "NUNNALLY JOHNSON" ], [ "I VITELLONI", "has_genre", "COMEDY" ], [ "I VITELLONI", "release_year", "1953" ], [ "IT COULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "COMEDY" ], [ "IT COULD HAPPEN TO YOU", "has_tags", "LOTTERY" ], [ "IT SHOULD HAPPEN TO YOU", "has_genre", "COMEDY" ], [ "IT SHOULD HAPPEN TO YOU", "release_year", "1954" ], [ "KNOCK ON WOOD", "has_genre", "COMEDY" ], [ "KNOCK ON WOOD", "release_year", "1954" ], [ "LET'S MAKE LOVE", "has_genre", "COMEDY" ], [ "LET'S MAKE LOVE", "starred_actors", "MARILYN MONROE" ], [ "MAGIC TOWN", "directed_by", "WILLIAM A. WELLMAN" ], [ "MAGIC TOWN", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_genre", "COMEDY" ], [ "MCLINTOCK!", "has_tags", "JOHN WAYNE" ], [ "MCLINTOCK!", "starred_actors", "JOHN WAYNE" ], [ "MONKEY BUSINESS", "has_genre", "COMEDY" ], [ "MONKEY BUSINESS", "has_tags", "COMEDY" ], [ "MONKEY BUSINESS", "starred_actors", "MARILYN MONROE" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "starred_actors", "BETTY GRABLE" ], [ "NIGHT PEOPLE", "directed_by", "NUNNALLY JOHNSON" ], [ "NIGHT PEOPLE", "release_year", "1954" ], [ "NIGHT PEOPLE", "written_by", "NUNNALLY JOHNSON" ], [ "NOTHING SACRED", "directed_by", "WILLIAM A. WELLMAN" ], [ "NOTHING SACRED", "has_genre", "COMEDY" ], [ "NOTHING SACRED", "has_tags", "WILLIAM A. WELLMAN" ], [ "PHFFFT", "has_genre", "COMEDY" ], [ "PHFFFT", "release_year", "1954" ], [ "ROMAN HOLIDAY", "has_genre", "COMEDY" ], [ "ROMAN HOLIDAY", "has_tags", "COMEDY" ], [ "ROMAN HOLIDAY", "release_year", "1953" ], [ "ROXIE HART", "directed_by", "WILLIAM A. WELLMAN" ], [ "ROXIE HART", "has_genre", "COMEDY" ], [ "ROXIE HART", "has_tags", "WILLIAM A. WELLMAN" ], [ "SABRINA", "has_genre", "COMEDY" ], [ "SABRINA", "release_year", "1954" ], [ "SEX AND THE SINGLE GIRL", "has_genre", "COMEDY" ], [ "SEX AND THE SINGLE GIRL", "starred_actors", "LAUREN BACALL" ], [ "SOME LIKE IT HOT", "has_genre", "COMEDY" ], [ "SOME LIKE IT HOT", "has_tags", "COMEDY" ], [ "SOME LIKE IT HOT", "has_tags", "MARILYN MONROE" ], [ "SOME LIKE IT HOT", "starred_actors", "MARILYN MONROE" ], [ "SUSAN SLEPT HERE", "has_genre", "COMEDY" ], [ "SUSAN SLEPT HERE", "release_year", "1954" ], [ "TAKE HER, SHE'S MINE", "has_genre", "COMEDY" ], [ "TAKE HER, SHE'S MINE", "written_by", "NUNNALLY JOHNSON" ], [ "THE ACTRESS", "has_genre", "COMEDY" ], [ "THE ACTRESS", "release_year", "1953" ], [ "THE BAND WAGON", "has_genre", "COMEDY" ], [ "THE BAND WAGON", "release_year", "1953" ], [ "THE CADDY", "has_genre", "COMEDY" ], [ "THE CADDY", "release_year", "1953" ], [ "THE CAPTAIN'S PARADISE", "has_genre", "COMEDY" ], [ "THE CAPTAIN'S PARADISE", "release_year", "1953" ], [ "THE HIGH AND THE MIGHTY", "directed_by", "WILLIAM A. WELLMAN" ], [ "THE HIGH AND THE MIGHTY", "has_tags", "WILLIAM A. WELLMAN" ], [ "THE HIGH AND THE MIGHTY", "release_year", "1954" ], [ "THE HIGH AND THE MIGHTY", "starred_actors", "JOHN WAYNE" ], [ "THE MIRROR HAS TWO FACES", "has_genre", "COMEDY" ], [ "THE MIRROR HAS TWO FACES", "starred_actors", "LAUREN BACALL" ], [ "THE MOON IS BLUE", "has_genre", "COMEDY" ], [ "THE MOON IS BLUE", "release_year", "1953" ], [ "THE QUIET MAN", "has_genre", "COMEDY" ], [ "THE QUIET MAN", "has_tags", "JOHN WAYNE" ], [ "THE QUIET MAN", "starred_actors", "JOHN WAYNE" ], [ "THE REFORMER AND THE REDHEAD", "has_genre", "COMEDY" ], [ "THE REFORMER AND THE REDHEAD", "starred_actors", "DAVID WAYNE" ], [ "THE RETURN OF DON CAMILLO", "has_genre", "COMEDY" ], [ "THE RETURN OF DON CAMILLO", "release_year", "1953" ], [ "THE SEVEN YEAR ITCH", "has_genre", "COMEDY" ], [ "THE SEVEN YEAR ITCH", "has_tags", "MARILYN MONROE" ], [ "THE SEVEN YEAR ITCH", "starred_actors", "MARILYN MONROE" ], [ "THE SHOOTIST", "has_tags", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "JOHN WAYNE" ], [ "THE SHOOTIST", "starred_actors", "LAUREN BACALL" ], [ "THE SUN SHINES BRIGHT", "has_genre", "COMEDY" ], [ "THE SUN SHINES BRIGHT", "release_year", "1953" ], [ "THE TENDER TRAP", "has_genre", "COMEDY" ], [ "THE TENDER TRAP", "starred_actors", "DAVID WAYNE" ], [ "THE TITFIELD THUNDERBOLT", "has_genre", "COMEDY" ], [ "THE TITFIELD THUNDERBOLT", "release_year", "1953" ], [ "THE TWONKY", "has_genre", "COMEDY" ], [ "THE TWONKY", "release_year", "1953" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "has_genre", "COMEDY" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "release_year", "1954" ], [ "THERE'S NO BUSINESS LIKE SHOW BUSINESS", "starred_actors", "MARILYN MONROE" ], [ "TRACK OF THE CAT", "directed_by", "WILLIAM A. WELLMAN" ], [ "TRACK OF THE CAT", "release_year", "1954" ], [ "WE'RE NOT MARRIED!", "has_genre", "COMEDY" ], [ "WE'RE NOT MARRIED!", "starred_actors", "MARILYN MONROE" ], [ "WELCOME MR. MARSHALL!", "has_genre", "COMEDY" ], [ "WELCOME MR. MARSHALL!", "release_year", "1953" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10045, BD-R 235, BRINGING UP BABY 30463, COMEDY 23299, GET CARTER 22984, HAGAR WILDE 13163, I LOVE TROUBLE 8097, S. SYLVAN SIMON 4088, STEPHEN KAY src, edge_attr, dst 235, has_genre, 30463 235, has_tags, 10045 235, has_tags, 30463 235, written_by, 22984 23299, directed_by, 4088 23299, has_tags, 10045 13163, directed_by, 8097 13163, has_genre, 30463 Question: In what context are HAGAR WILDE, S. SYLVAN SIMON, and STEPHEN KAY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HAGAR WILDE", "S. SYLVAN SIMON", "STEPHEN KAY" ], "valid_edges": [ [ "BRINGING UP BABY", "has_genre", "COMEDY" ], [ "BRINGING UP BABY", "has_tags", "BD-R" ], [ "BRINGING UP BABY", "has_tags", "COMEDY" ], [ "BRINGING UP BABY", "written_by", "HAGAR WILDE" ], [ "GET CARTER", "directed_by", "STEPHEN KAY" ], [ "GET CARTER", "has_tags", "BD-R" ], [ "I LOVE TROUBLE", "directed_by", "S. SYLVAN SIMON" ], [ "I LOVE TROUBLE", "has_genre", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 23257, AN UNFORGETTABLE SUMMER 2537, ANDRE DUBUS III 36212, DRAMA 18266, ERICSON CORE 20309, HOUSE OF SAND AND FOG 23380, INVINCIBLE 22155, LUCIAN PINTILIE 27464, ROMANIAN 25792, THE OAK src, edge_attr, dst 23257, directed_by, 22155 23257, has_genre, 36212 23257, in_language, 27464 23257, written_by, 22155 20309, has_genre, 36212 20309, written_by, 2537 23380, directed_by, 18266 23380, has_genre, 36212 25792, directed_by, 22155 25792, has_genre, 36212 25792, in_language, 27464 25792, written_by, 22155 Question: For what reason are ANDRE DUBUS III, ERICSON CORE, and LUCIAN PINTILIE associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANDRE DUBUS III", "ERICSON CORE", "LUCIAN PINTILIE" ], "valid_edges": [ [ "AN UNFORGETTABLE SUMMER", "directed_by", "LUCIAN PINTILIE" ], [ "AN UNFORGETTABLE SUMMER", "has_genre", "DRAMA" ], [ "AN UNFORGETTABLE SUMMER", "in_language", "ROMANIAN" ], [ "AN UNFORGETTABLE SUMMER", "written_by", "LUCIAN PINTILIE" ], [ "HOUSE OF SAND AND FOG", "has_genre", "DRAMA" ], [ "HOUSE OF SAND AND FOG", "written_by", "ANDRE DUBUS III" ], [ "INVINCIBLE", "directed_by", "ERICSON CORE" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "THE OAK", "directed_by", "LUCIAN PINTILIE" ], [ "THE OAK", "has_genre", "DRAMA" ], [ "THE OAK", "in_language", "ROMANIAN" ], [ "THE OAK", "written_by", "LUCIAN PINTILIE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 1543, 61* 30721, A BEAUTIFUL MIND 30146, A CHRISTMAS CAROL 19865, A.I. ARTIFICIAL INTELLIGENCE 1538, ALIAS BETTY 4141, AN AMERICAN RHAPSODY 22873, ANGEL EYES 462, AUTUMN SPRING 1156, AVALON 5593, BABY BOY 6309, BABY TAKE A BOW 23952, BANDITS 13418, BARTLEBY 28835, BIG BULLY 11298, BOLIVIA 20912, BRIDE OF THE WIND 7461, BROTHERHOOD OF THE WOLF 17892, CAMOUFLAGE 29794, CHARLOTTE GRAY 18016, CLICK 30463, COMEDY 10272, CONFESSIONS OF A TEENAGE DRAMA QUEEN 10293, CONSPIRACY 23979, CRAZY/BEAUTIFUL 656, CRUSH 6935, DIANE BAKER 1915, DIL CHAHTA HAI 7281, DON'S PLUM 22255, DONNIE DARKO 36212, DRAMA 27747, DRIVEN 10941, DRIVING MISS DAISY 17266, DUST 19194, ENIGMA 24686, FATE 6915, FOCUS 12664, GHOST WORLD 38300, GLITTER 15389, GYPSY 83 1937, HANNAH AND HER SISTERS 29107, HARLEM NIGHTS 21060, HARVARD MAN 19139, HEARTS IN ATLANTIS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 35625, HUMAN NATURE 10714, I AM SAM 20430, IN THE BEDROOM 23380, INVINCIBLE 39987, IT RUNS IN THE FAMILY 23526, JACKPOT 12610, JOE SOMEBODY 31226, JULIE JOHNSON 6206, KABHI KHUSHI KABHIE GHAM... 7699, KINGDOM COME 7888, L.I.E. 19121, LAST ORDERS 39962, LIFE AS A HOUSE 29734, LITTLE SECRETS 22386, LOST AND DELIRIOUS 17728, MAD LOVE 30062, MANIC 33714, MEAN MACHINE 14565, MONSTER'S BALL 24616, MOSTLY MARTHA 10824, O 32514, ONE 2 KA 4 32186, ONE MAN UP 5023, PARENTHOOD 28044, PAULINE AND PAULETTE 234, PEARL HARBOR 29748, PISTOL OPERA 28106, PROZAC NATION 8367, RAIN 28182, RARE BIRDS 38381, ROCK STAR 29441, SEX AND LUCIA 2407, SON OF THE BRIDE 7175, STOLEN KISSES 7949, STORYTELLING 27762, SWEET NOVEMBER 15887, TAPE 13270, TEXAS RANGERS 2582, THE AFFAIR OF THE NECKLACE 15795, THE ANNIVERSARY PARTY 33436, THE BANK 267, THE BELIEVER 25674, THE BROTHERS 4789, THE BROTHERS MCMULLEN 30854, THE CAT'S MEOW 4946, THE CAVEMAN'S VALENTINE 28948, THE FAMILY STONE 27328, THE HORSE IN THE GRAY FLANNEL SUIT 39978, THE HUMAN COMEDY 14993, THE INVISIBLE CIRCUS 23268, THE JIMMY SHOW 4143, THE LAST CASTLE 28107, THE LAST KISS 12566, THE MAJESTIC 23940, THE MAN FROM ELYSIAN FIELDS 22538, THE OTHER SIDE OF HEAVEN 27573, THE OTHERS 39469, THE PORNOGRAPHER 18649, THE RIVER 20728, THE ROYAL TENENBAUMS 23798, THE SHIPPING NEWS 27910, THE UNSAID 2839, THE WIZARD OF BAGHDAD 38275, THIRTEEN CONVERSATIONS ABOUT ONE THING 25783, TIME OUT 27854, TO THE LEFT OF THE FATHER 35988, TORTILLA SOUP 8974, TREED MURRAY 17093, UNFAIR COMPETITION 6655, UPRISING 35443, VIZONTELE 18892, WAKING LIFE 8957, WE BOUGHT A ZOO 19679, WIDE AWAKE 19926, WORLD TRAVELER 25391, Y TU MAMÁ TAMBIÉN src, edge_attr, dst 13747, has_genre, 30463 13747, has_genre, 36212 13747, release_year, 13408 1543, has_genre, 36212 1543, release_year, 13408 30721, has_genre, 36212 30721, has_tags, 36212 30721, release_year, 13408 30146, has_genre, 30463 30146, has_genre, 36212 19865, has_genre, 36212 19865, release_year, 13408 1538, has_genre, 36212 1538, release_year, 13408 4141, has_genre, 36212 4141, release_year, 13408 22873, has_genre, 36212 22873, release_year, 13408 462, has_genre, 36212 462, release_year, 13408 1156, has_genre, 36212 1156, release_year, 13408 5593, has_genre, 30463 5593, has_genre, 36212 5593, release_year, 13408 6309, has_genre, 30463 6309, has_genre, 36212 23952, has_genre, 30463 23952, has_genre, 36212 23952, release_year, 13408 13418, has_genre, 30463 13418, has_genre, 36212 13418, release_year, 13408 28835, has_genre, 30463 28835, has_genre, 36212 11298, has_genre, 36212 11298, release_year, 13408 20912, has_genre, 36212 20912, release_year, 13408 7461, has_genre, 36212 7461, release_year, 13408 17892, has_genre, 30463 17892, has_genre, 36212 17892, release_year, 13408 29794, has_genre, 36212 29794, release_year, 13408 18016, has_genre, 30463 18016, has_genre, 36212 18016, has_tags, 30463 10272, has_genre, 30463 10272, has_tags, 30463 10272, has_tags, 36212 10293, has_genre, 36212 10293, release_year, 13408 23979, has_genre, 36212 23979, release_year, 13408 656, has_genre, 36212 656, release_year, 13408 1915, has_genre, 30463 1915, has_genre, 36212 1915, has_tags, 30463 1915, release_year, 13408 7281, has_genre, 36212 7281, release_year, 13408 22255, has_genre, 36212 22255, release_year, 13408 27747, has_genre, 36212 27747, release_year, 13408 10941, has_genre, 30463 10941, has_genre, 36212 10941, has_tags, 36212 17266, has_genre, 36212 17266, release_year, 13408 19194, has_genre, 36212 19194, release_year, 13408 24686, has_genre, 36212 24686, release_year, 13408 6915, has_genre, 30463 6915, has_genre, 36212 6915, release_year, 13408 12664, has_genre, 30463 12664, has_genre, 36212 12664, release_year, 13408 38300, has_genre, 36212 38300, release_year, 13408 15389, has_genre, 36212 15389, release_year, 13408 1937, has_genre, 30463 1937, has_genre, 36212 1937, has_tags, 30463 29107, has_genre, 30463 29107, has_genre, 36212 21060, has_genre, 30463 21060, has_genre, 36212 21060, release_year, 13408 19139, has_genre, 36212 19139, release_year, 13408 1292, has_genre, 30463 1292, has_genre, 36212 1292, release_year, 13408 38901, has_genre, 30463 38901, has_genre, 36212 38901, release_year, 13408 35625, has_genre, 30463 35625, has_genre, 36212 35625, release_year, 13408 10714, has_genre, 36212 10714, release_year, 13408 20430, has_genre, 36212 20430, has_tags, 36212 20430, release_year, 13408 23380, has_genre, 36212 23380, release_year, 13408 39987, has_genre, 30463 39987, has_genre, 36212 23526, has_genre, 30463 23526, has_genre, 36212 23526, release_year, 13408 12610, has_genre, 30463 12610, has_genre, 36212 12610, release_year, 13408 31226, has_genre, 36212 31226, release_year, 13408 6206, has_genre, 36212 6206, release_year, 13408 7699, has_genre, 30463 7699, has_genre, 36212 7699, release_year, 13408 7888, has_genre, 36212 7888, release_year, 13408 19121, has_genre, 36212 19121, release_year, 13408 39962, has_genre, 36212 39962, release_year, 13408 29734, has_genre, 30463 29734, has_genre, 36212 29734, release_year, 13408 22386, has_genre, 36212 22386, release_year, 13408 17728, has_genre, 36212 17728, release_year, 13408 30062, has_genre, 36212 30062, release_year, 13408 33714, has_genre, 30463 33714, has_genre, 36212 33714, release_year, 13408 14565, has_genre, 36212 14565, release_year, 13408 24616, has_genre, 30463 24616, has_genre, 36212 24616, release_year, 13408 10824, has_genre, 36212 10824, release_year, 13408 32514, has_genre, 36212 32514, release_year, 13408 32186, has_genre, 30463 32186, has_genre, 36212 32186, release_year, 13408 5023, has_genre, 30463 5023, has_genre, 36212 5023, has_tags, 30463 28044, has_genre, 30463 28044, has_genre, 36212 28044, release_year, 13408 234, has_genre, 36212 234, has_tags, 36212 234, release_year, 13408 29748, release_year, 13408 28106, has_genre, 36212 28106, release_year, 13408 8367, has_genre, 36212 8367, release_year, 13408 28182, has_genre, 30463 28182, has_genre, 36212 28182, release_year, 13408 38381, has_genre, 30463 38381, has_genre, 36212 38381, release_year, 13408 29441, has_genre, 36212 29441, release_year, 13408 2407, has_genre, 30463 2407, has_genre, 36212 2407, release_year, 13408 7175, has_genre, 30463 7175, has_genre, 36212 7949, has_genre, 30463 7949, has_genre, 36212 7949, release_year, 13408 27762, has_genre, 30463 27762, has_genre, 36212 27762, release_year, 13408 15887, has_genre, 36212 15887, release_year, 13408 13270, has_genre, 36212 13270, release_year, 13408 2582, has_genre, 36212 2582, release_year, 13408 15795, has_genre, 30463 15795, has_genre, 36212 15795, release_year, 13408 33436, has_genre, 36212 33436, release_year, 13408 267, has_genre, 36212 267, release_year, 13408 25674, has_genre, 30463 25674, has_genre, 36212 25674, release_year, 13408 4789, has_genre, 30463 4789, has_genre, 36212 30854, has_genre, 36212 30854, release_year, 13408 4946, has_genre, 36212 4946, release_year, 13408 28948, has_genre, 30463 28948, has_genre, 36212 28948, has_tags, 30463 28948, has_tags, 36212 27328, has_genre, 30463 27328, starred_actors, 6935 39978, has_genre, 30463 39978, has_genre, 36212 14993, has_genre, 36212 14993, release_year, 13408 23268, has_genre, 36212 23268, release_year, 13408 4143, has_genre, 36212 4143, release_year, 13408 28107, has_genre, 30463 28107, has_genre, 36212 28107, release_year, 13408 12566, has_genre, 36212 12566, release_year, 13408 23940, has_genre, 36212 23940, release_year, 13408 22538, has_genre, 36212 22538, release_year, 13408 27573, has_tags, 36212 27573, release_year, 13408 39469, has_genre, 36212 39469, release_year, 13408 18649, has_genre, 36212 18649, release_year, 13408 20728, has_genre, 30463 20728, has_genre, 36212 20728, has_tags, 30463 20728, release_year, 13408 23798, has_genre, 36212 23798, release_year, 13408 27910, has_genre, 36212 27910, release_year, 13408 2839, has_genre, 30463 2839, starred_actors, 6935 38275, has_genre, 36212 38275, release_year, 13408 25783, has_genre, 36212 25783, release_year, 13408 27854, has_genre, 36212 27854, release_year, 13408 35988, has_genre, 30463 35988, has_genre, 36212 35988, release_year, 13408 8974, has_genre, 36212 8974, release_year, 13408 17093, has_genre, 36212 17093, release_year, 13408 6655, has_genre, 36212 6655, release_year, 13408 35443, has_genre, 30463 35443, has_genre, 36212 35443, has_tags, 30463 35443, release_year, 13408 18892, has_genre, 36212 18892, release_year, 13408 8957, has_genre, 30463 8957, has_genre, 36212 19679, has_genre, 30463 19679, has_genre, 36212 19926, has_genre, 36212 19926, release_year, 13408 25391, has_genre, 36212 25391, has_tags, 36212 25391, release_year, 13408 Question: In what context are DIANE BAKER, HARLEM NIGHTS, and PISTOL OPERA connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DIANE BAKER", "HARLEM NIGHTS", "PISTOL OPERA" ], "valid_edges": [ [ "25 WATTS", "has_genre", "COMEDY" ], [ "25 WATTS", "has_genre", "DRAMA" ], [ "25 WATTS", "release_year", "2001" ], [ "61*", "has_genre", "DRAMA" ], [ "61*", "release_year", "2001" ], [ "A BEAUTIFUL MIND", "has_genre", "DRAMA" ], [ "A BEAUTIFUL MIND", "has_tags", "DRAMA" ], [ "A BEAUTIFUL MIND", "release_year", "2001" ], [ "A CHRISTMAS CAROL", "has_genre", "COMEDY" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "has_genre", "DRAMA" ], [ "A.I. ARTIFICIAL INTELLIGENCE", "release_year", "2001" ], [ "ALIAS BETTY", "has_genre", "DRAMA" ], [ "ALIAS BETTY", "release_year", "2001" ], [ "AN AMERICAN RHAPSODY", "has_genre", "DRAMA" ], [ "AN AMERICAN RHAPSODY", "release_year", "2001" ], [ "ANGEL EYES", "has_genre", "DRAMA" ], [ "ANGEL EYES", "release_year", "2001" ], [ "AUTUMN SPRING", "has_genre", "DRAMA" ], [ "AUTUMN SPRING", "release_year", "2001" ], [ "AVALON", "has_genre", "DRAMA" ], [ "AVALON", "release_year", "2001" ], [ "BABY BOY", "has_genre", "COMEDY" ], [ "BABY BOY", "has_genre", "DRAMA" ], [ "BABY BOY", "release_year", "2001" ], [ "BABY TAKE A BOW", "has_genre", "COMEDY" ], [ "BABY TAKE A BOW", "has_genre", "DRAMA" ], [ "BANDITS", "has_genre", "COMEDY" ], [ "BANDITS", "has_genre", "DRAMA" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "COMEDY" ], [ "BARTLEBY", "has_genre", "DRAMA" ], [ "BARTLEBY", "release_year", "2001" ], [ "BIG BULLY", "has_genre", "COMEDY" ], [ "BIG BULLY", "has_genre", "DRAMA" ], [ "BOLIVIA", "has_genre", "DRAMA" ], [ "BOLIVIA", "release_year", "2001" ], [ "BRIDE OF THE WIND", "has_genre", "DRAMA" ], [ "BRIDE OF THE WIND", "release_year", "2001" ], [ "BROTHERHOOD OF THE WOLF", "has_genre", "DRAMA" ], [ "BROTHERHOOD OF THE WOLF", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "COMEDY" ], [ "CAMOUFLAGE", "has_genre", "DRAMA" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CHARLOTTE GRAY", "has_genre", "DRAMA" ], [ "CHARLOTTE GRAY", "release_year", "2001" ], [ "CLICK", "has_genre", "COMEDY" ], [ "CLICK", "has_genre", "DRAMA" ], [ "CLICK", "has_tags", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_genre", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "COMEDY" ], [ "CONFESSIONS OF A TEENAGE DRAMA QUEEN", "has_tags", "DRAMA" ], [ "CONSPIRACY", "has_genre", "DRAMA" ], [ "CONSPIRACY", "release_year", "2001" ], [ "CRAZY/BEAUTIFUL", "has_genre", "DRAMA" ], [ "CRAZY/BEAUTIFUL", "release_year", "2001" ], [ "CRUSH", "has_genre", "DRAMA" ], [ "CRUSH", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "COMEDY" ], [ "DIL CHAHTA HAI", "has_genre", "DRAMA" ], [ "DIL CHAHTA HAI", "has_tags", "COMEDY" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'S PLUM", "has_genre", "DRAMA" ], [ "DON'S PLUM", "release_year", "2001" ], [ "DONNIE DARKO", "has_genre", "DRAMA" ], [ "DONNIE DARKO", "release_year", "2001" ], [ "DRIVEN", "has_genre", "DRAMA" ], [ "DRIVEN", "release_year", "2001" ], [ "DRIVING MISS DAISY", "has_genre", "COMEDY" ], [ "DRIVING MISS DAISY", "has_genre", "DRAMA" ], [ "DRIVING MISS DAISY", "has_tags", "DRAMA" ], [ "DUST", "has_genre", "DRAMA" ], [ "DUST", "release_year", "2001" ], [ "ENIGMA", "has_genre", "DRAMA" ], [ "ENIGMA", "release_year", "2001" ], [ "FATE", "has_genre", "DRAMA" ], [ "FATE", "release_year", "2001" ], [ "FOCUS", "has_genre", "COMEDY" ], [ "FOCUS", "has_genre", "DRAMA" ], [ "FOCUS", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "COMEDY" ], [ "GHOST WORLD", "has_genre", "DRAMA" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GLITTER", "has_genre", "DRAMA" ], [ "GLITTER", "release_year", "2001" ], [ "GYPSY 83", "has_genre", "DRAMA" ], [ "GYPSY 83", "release_year", "2001" ], [ "HANNAH AND HER SISTERS", "has_genre", "COMEDY" ], [ "HANNAH AND HER SISTERS", "has_genre", "DRAMA" ], [ "HANNAH AND HER SISTERS", "has_tags", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "COMEDY" ], [ "HARLEM NIGHTS", "has_genre", "DRAMA" ], [ "HARVARD MAN", "has_genre", "COMEDY" ], [ "HARVARD MAN", "has_genre", "DRAMA" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HEARTS IN ATLANTIS", "has_genre", "DRAMA" ], [ "HEARTS IN ATLANTIS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "COMEDY" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "DRAMA" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "has_genre", "DRAMA" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "I AM SAM", "has_genre", "DRAMA" ], [ "I AM SAM", "release_year", "2001" ], [ "IN THE BEDROOM", "has_genre", "DRAMA" ], [ "IN THE BEDROOM", "has_tags", "DRAMA" ], [ "IN THE BEDROOM", "release_year", "2001" ], [ "INVINCIBLE", "has_genre", "DRAMA" ], [ "INVINCIBLE", "release_year", "2001" ], [ "IT RUNS IN THE FAMILY", "has_genre", "COMEDY" ], [ "IT RUNS IN THE FAMILY", "has_genre", "DRAMA" ], [ "JACKPOT", "has_genre", "COMEDY" ], [ "JACKPOT", "has_genre", "DRAMA" ], [ "JACKPOT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "COMEDY" ], [ "JOE SOMEBODY", "has_genre", "DRAMA" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JULIE JOHNSON", "has_genre", "DRAMA" ], [ "JULIE JOHNSON", "release_year", "2001" ], [ "KABHI KHUSHI KABHIE GHAM...", "has_genre", "DRAMA" ], [ "KABHI KHUSHI KABHIE GHAM...", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "COMEDY" ], [ "KINGDOM COME", "has_genre", "DRAMA" ], [ "KINGDOM COME", "release_year", "2001" ], [ "L.I.E.", "has_genre", "DRAMA" ], [ "L.I.E.", "release_year", "2001" ], [ "LAST ORDERS", "has_genre", "DRAMA" ], [ "LAST ORDERS", "release_year", "2001" ], [ "LIFE AS A HOUSE", "has_genre", "DRAMA" ], [ "LIFE AS A HOUSE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "COMEDY" ], [ "LITTLE SECRETS", "has_genre", "DRAMA" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LOST AND DELIRIOUS", "has_genre", "DRAMA" ], [ "LOST AND DELIRIOUS", "release_year", "2001" ], [ "MAD LOVE", "has_genre", "DRAMA" ], [ "MAD LOVE", "release_year", "2001" ], [ "MANIC", "has_genre", "DRAMA" ], [ "MANIC", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "COMEDY" ], [ "MEAN MACHINE", "has_genre", "DRAMA" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONSTER'S BALL", "has_genre", "DRAMA" ], [ "MONSTER'S BALL", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "COMEDY" ], [ "MOSTLY MARTHA", "has_genre", "DRAMA" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "O", "has_genre", "DRAMA" ], [ "O", "release_year", "2001" ], [ "ONE 2 KA 4", "has_genre", "DRAMA" ], [ "ONE 2 KA 4", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "COMEDY" ], [ "ONE MAN UP", "has_genre", "DRAMA" ], [ "ONE MAN UP", "release_year", "2001" ], [ "PARENTHOOD", "has_genre", "COMEDY" ], [ "PARENTHOOD", "has_genre", "DRAMA" ], [ "PARENTHOOD", "has_tags", "COMEDY" ], [ "PAULINE AND PAULETTE", "has_genre", "COMEDY" ], [ "PAULINE AND PAULETTE", "has_genre", "DRAMA" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PEARL HARBOR", "has_genre", "DRAMA" ], [ "PEARL HARBOR", "has_tags", "DRAMA" ], [ "PEARL HARBOR", "release_year", "2001" ], [ "PISTOL OPERA", "release_year", "2001" ], [ "PROZAC NATION", "has_genre", "DRAMA" ], [ "PROZAC NATION", "release_year", "2001" ], [ "RAIN", "has_genre", "DRAMA" ], [ "RAIN", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "COMEDY" ], [ "RARE BIRDS", "has_genre", "DRAMA" ], [ "RARE BIRDS", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "has_genre", "DRAMA" ], [ "ROCK STAR", "release_year", "2001" ], [ "SEX AND LUCIA", "has_genre", "DRAMA" ], [ "SEX AND LUCIA", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "COMEDY" ], [ "SON OF THE BRIDE", "has_genre", "DRAMA" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "STOLEN KISSES", "has_genre", "COMEDY" ], [ "STOLEN KISSES", "has_genre", "DRAMA" ], [ "STORYTELLING", "has_genre", "COMEDY" ], [ "STORYTELLING", "has_genre", "DRAMA" ], [ "STORYTELLING", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "COMEDY" ], [ "SWEET NOVEMBER", "has_genre", "DRAMA" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TAPE", "has_genre", "DRAMA" ], [ "TAPE", "release_year", "2001" ], [ "TEXAS RANGERS", "has_genre", "DRAMA" ], [ "TEXAS RANGERS", "release_year", "2001" ], [ "THE AFFAIR OF THE NECKLACE", "has_genre", "DRAMA" ], [ "THE AFFAIR OF THE NECKLACE", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "COMEDY" ], [ "THE ANNIVERSARY PARTY", "has_genre", "DRAMA" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BANK", "has_genre", "DRAMA" ], [ "THE BANK", "release_year", "2001" ], [ "THE BELIEVER", "has_genre", "DRAMA" ], [ "THE BELIEVER", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "COMEDY" ], [ "THE BROTHERS", "has_genre", "DRAMA" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE BROTHERS MCMULLEN", "has_genre", "COMEDY" ], [ "THE BROTHERS MCMULLEN", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "has_genre", "DRAMA" ], [ "THE CAT'S MEOW", "release_year", "2001" ], [ "THE CAVEMAN'S VALENTINE", "has_genre", "DRAMA" ], [ "THE CAVEMAN'S VALENTINE", "release_year", "2001" ], [ "THE FAMILY STONE", "has_genre", "COMEDY" ], [ "THE FAMILY STONE", "has_genre", "DRAMA" ], [ "THE FAMILY STONE", "has_tags", "COMEDY" ], [ "THE FAMILY STONE", "has_tags", "DRAMA" ], [ "THE HORSE IN THE GRAY FLANNEL SUIT", "has_genre", "COMEDY" ], [ "THE HORSE IN THE GRAY FLANNEL SUIT", "starred_actors", "DIANE BAKER" ], [ "THE HUMAN COMEDY", "has_genre", "COMEDY" ], [ "THE HUMAN COMEDY", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "has_genre", "DRAMA" ], [ "THE INVISIBLE CIRCUS", "release_year", "2001" ], [ "THE JIMMY SHOW", "has_genre", "DRAMA" ], [ "THE JIMMY SHOW", "release_year", "2001" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "has_genre", "DRAMA" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAJESTIC", "has_genre", "DRAMA" ], [ "THE MAJESTIC", "release_year", "2001" ], [ "THE MAN FROM ELYSIAN FIELDS", "has_genre", "DRAMA" ], [ "THE MAN FROM ELYSIAN FIELDS", "release_year", "2001" ], [ "THE OTHER SIDE OF HEAVEN", "has_genre", "DRAMA" ], [ "THE OTHER SIDE OF HEAVEN", "release_year", "2001" ], [ "THE OTHERS", "has_tags", "DRAMA" ], [ "THE OTHERS", "release_year", "2001" ], [ "THE PORNOGRAPHER", "has_genre", "DRAMA" ], [ "THE PORNOGRAPHER", "release_year", "2001" ], [ "THE RIVER", "has_genre", "DRAMA" ], [ "THE RIVER", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "has_genre", "DRAMA" ], [ "THE ROYAL TENENBAUMS", "has_tags", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHIPPING NEWS", "has_genre", "DRAMA" ], [ "THE SHIPPING NEWS", "release_year", "2001" ], [ "THE UNSAID", "has_genre", "DRAMA" ], [ "THE UNSAID", "release_year", "2001" ], [ "THE WIZARD OF BAGHDAD", "has_genre", "COMEDY" ], [ "THE WIZARD OF BAGHDAD", "starred_actors", "DIANE BAKER" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "has_genre", "DRAMA" ], [ "THIRTEEN CONVERSATIONS ABOUT ONE THING", "release_year", "2001" ], [ "TIME OUT", "has_genre", "DRAMA" ], [ "TIME OUT", "release_year", "2001" ], [ "TO THE LEFT OF THE FATHER", "has_genre", "DRAMA" ], [ "TO THE LEFT OF THE FATHER", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "COMEDY" ], [ "TORTILLA SOUP", "has_genre", "DRAMA" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TREED MURRAY", "has_genre", "DRAMA" ], [ "TREED MURRAY", "release_year", "2001" ], [ "UNFAIR COMPETITION", "has_genre", "DRAMA" ], [ "UNFAIR COMPETITION", "release_year", "2001" ], [ "UPRISING", "has_genre", "DRAMA" ], [ "UPRISING", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "COMEDY" ], [ "VIZONTELE", "has_genre", "DRAMA" ], [ "VIZONTELE", "has_tags", "COMEDY" ], [ "VIZONTELE", "release_year", "2001" ], [ "WAKING LIFE", "has_genre", "DRAMA" ], [ "WAKING LIFE", "release_year", "2001" ], [ "WE BOUGHT A ZOO", "has_genre", "COMEDY" ], [ "WE BOUGHT A ZOO", "has_genre", "DRAMA" ], [ "WIDE AWAKE", "has_genre", "COMEDY" ], [ "WIDE AWAKE", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "has_genre", "DRAMA" ], [ "WORLD TRAVELER", "release_year", "2001" ], [ "Y TU MAMÁ TAMBIÉN", "has_genre", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "has_tags", "DRAMA" ], [ "Y TU MAMÁ TAMBIÉN", "release_year", "2001" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 32015, BEHIND ENEMY LINES 30463, COMEDY 21587, HOW I WON THE WAR 15503, JENÉE LAMARQUE 24297, MARK CARLTON 34811, PATRICK RYAN 4335, THE PRETTY ONE 22214, WAR src, edge_attr, dst 32015, has_genre, 22214 32015, has_tags, 22214 32015, starred_actors, 24297 21587, has_genre, 30463 21587, has_genre, 22214 21587, written_by, 34811 4335, directed_by, 15503 4335, has_genre, 30463 4335, written_by, 15503 Question: In what context are JENÉE LAMARQUE, MARK CARLTON, and PATRICK RYAN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JENÉE LAMARQUE", "MARK CARLTON", "PATRICK RYAN" ], "valid_edges": [ [ "BEHIND ENEMY LINES", "has_genre", "WAR" ], [ "BEHIND ENEMY LINES", "has_tags", "WAR" ], [ "BEHIND ENEMY LINES", "starred_actors", "MARK CARLTON" ], [ "HOW I WON THE WAR", "has_genre", "COMEDY" ], [ "HOW I WON THE WAR", "has_genre", "WAR" ], [ "HOW I WON THE WAR", "written_by", "PATRICK RYAN" ], [ "THE PRETTY ONE", "directed_by", "JENÉE LAMARQUE" ], [ "THE PRETTY ONE", "has_genre", "COMEDY" ], [ "THE PRETTY ONE", "written_by", "JENÉE LAMARQUE" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11112, 1939 26633, 1989 33875, A GRAND DAY OUT 24177, ANIMATION 39085, BILLY ELLIOT 16654, BRITISH 32706, FIRST LOVE 17440, GULLIVER'S TRAVELS 17118, HENRY V 24241, LEE HALL 15198, THE HUNCHBACK OF NOTRE DAME 31303, THE LITTLE MERMAID src, edge_attr, dst 33875, has_genre, 24177 33875, has_tags, 16654 33875, release_year, 26633 39085, has_tags, 16654 39085, written_by, 24241 32706, release_year, 11112 17440, has_genre, 24177 17440, release_year, 11112 17118, has_tags, 16654 17118, release_year, 26633 15198, has_genre, 24177 15198, release_year, 11112 31303, has_genre, 24177 31303, has_tags, 24177 31303, release_year, 26633 Question: For what reason are A GRAND DAY OUT, FIRST LOVE, and LEE HALL associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A GRAND DAY OUT", "FIRST LOVE", "LEE HALL" ], "valid_edges": [ [ "A GRAND DAY OUT", "has_genre", "ANIMATION" ], [ "A GRAND DAY OUT", "has_tags", "BRITISH" ], [ "A GRAND DAY OUT", "release_year", "1989" ], [ "BILLY ELLIOT", "has_tags", "BRITISH" ], [ "BILLY ELLIOT", "written_by", "LEE HALL" ], [ "FIRST LOVE", "release_year", "1939" ], [ "GULLIVER'S TRAVELS", "has_genre", "ANIMATION" ], [ "GULLIVER'S TRAVELS", "release_year", "1939" ], [ "HENRY V", "has_tags", "BRITISH" ], [ "HENRY V", "release_year", "1989" ], [ "THE HUNCHBACK OF NOTRE DAME", "has_genre", "ANIMATION" ], [ "THE HUNCHBACK OF NOTRE DAME", "release_year", "1939" ], [ "THE LITTLE MERMAID", "has_genre", "ANIMATION" ], [ "THE LITTLE MERMAID", "has_tags", "ANIMATION" ], [ "THE LITTLE MERMAID", "release_year", "1989" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21931, 1941 7841, 1987 10149, A HUNGARIAN FAIRY TALE 36420, A TAXING WOMAN 23612, DOLLS 22028, EMPIRE OF THE SUN 36874, JAPANESE 21030, NANA 7585, TEXAS 735, THE REVISIONARIES 8589, WICKED CITY src, edge_attr, dst 21931, in_language, 36874 10149, release_year, 7841 36420, in_language, 36874 36420, release_year, 7841 23612, in_language, 36874 23612, release_year, 7841 22028, in_language, 36874 22028, release_year, 7841 21030, in_language, 36874 7585, release_year, 21931 735, has_tags, 7585 8589, in_language, 36874 8589, release_year, 7841 Question: For what reason are A HUNGARIAN FAIRY TALE, NANA, and THE REVISIONARIES associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A HUNGARIAN FAIRY TALE", "NANA", "THE REVISIONARIES" ], "valid_edges": [ [ "1941", "in_language", "JAPANESE" ], [ "A HUNGARIAN FAIRY TALE", "release_year", "1987" ], [ "A TAXING WOMAN", "in_language", "JAPANESE" ], [ "A TAXING WOMAN", "release_year", "1987" ], [ "DOLLS", "in_language", "JAPANESE" ], [ "DOLLS", "release_year", "1987" ], [ "EMPIRE OF THE SUN", "in_language", "JAPANESE" ], [ "EMPIRE OF THE SUN", "release_year", "1987" ], [ "NANA", "in_language", "JAPANESE" ], [ "TEXAS", "release_year", "1941" ], [ "THE REVISIONARIES", "has_tags", "TEXAS" ], [ "WICKED CITY", "in_language", "JAPANESE" ], [ "WICKED CITY", "release_year", "1987" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 36268, 1980 24525, 1984 38097, 1985 37484, 2004 32087, BARBARA CUPISTI 26883, CEMETERY MAN 9243, CHARLES GRODIN 30463, COMEDY 21942, DAWN OF THE DEAD 6095, DAY OF THE DEAD 18708, DEADHEADS 5963, GEORGE A. ROMERO 2600, HELL OF THE LIVING DEAD 36859, HELLO AGAIN 5870, HORROR 16200, ITALIAN 7548, JUDITH IVEY 25134, LAND OF THE DEAD 2072, MICHELE SOAVI 32988, NIGHT OF THE LIVING DEAD 25714, NIGHTMARE CITY 13081, R 28729, REMAKE 25673, ROMERO 29855, SHAUN OF THE DEAD 10334, THE CHURCH 36990, THE LONELY GUY 16017, THE RETURN OF THE LIVING DEAD 20553, THE WOMAN IN RED 9639, UNDEAD 14902, ZOMBIE 21798, ZOMBIE HOLOCAUST 33616, ZOMBIE LAKE 39354, ZOMBIES src, edge_attr, dst 26883, directed_by, 2072 26883, has_genre, 30463 26883, has_genre, 5870 26883, has_tags, 14902 26883, has_tags, 39354 26883, in_language, 16200 21942, directed_by, 5963 21942, has_genre, 5870 21942, has_tags, 5963 21942, has_tags, 5870 21942, has_tags, 13081 21942, has_tags, 28729 21942, has_tags, 25673 21942, has_tags, 14902 21942, has_tags, 39354 21942, release_year, 37484 21942, written_by, 5963 6095, directed_by, 5963 6095, has_genre, 5870 6095, has_tags, 5963 6095, has_tags, 5870 6095, has_tags, 14902 6095, release_year, 38097 6095, written_by, 5963 18708, has_genre, 30463 18708, has_tags, 30463 18708, has_tags, 14902 2600, has_genre, 5870 2600, has_tags, 14902 2600, has_tags, 39354 2600, in_language, 16200 2600, release_year, 36268 36859, has_genre, 30463 36859, starred_actors, 7548 25134, directed_by, 5963 25134, has_genre, 5870 25134, has_tags, 5963 25134, has_tags, 25673 25134, has_tags, 14902 25134, written_by, 5963 32988, directed_by, 5963 32988, has_genre, 5870 32988, has_tags, 5963 32988, has_tags, 5870 32988, has_tags, 28729 32988, has_tags, 14902 32988, has_tags, 39354 32988, written_by, 5963 25714, has_tags, 14902 25714, has_tags, 39354 25714, in_language, 16200 25714, release_year, 36268 29855, has_genre, 30463 29855, has_tags, 30463 29855, has_tags, 13081 29855, has_tags, 14902 29855, has_tags, 39354 29855, release_year, 37484 10334, directed_by, 2072 10334, has_genre, 5870 10334, in_language, 16200 10334, starred_actors, 32087 10334, written_by, 2072 36990, has_genre, 30463 36990, release_year, 24525 36990, starred_actors, 9243 36990, starred_actors, 7548 16017, has_genre, 30463 16017, has_genre, 5870 16017, has_tags, 14902 16017, has_tags, 39354 16017, release_year, 38097 20553, has_genre, 30463 20553, release_year, 24525 20553, starred_actors, 9243 20553, starred_actors, 7548 9639, has_genre, 30463 9639, has_genre, 5870 9639, has_tags, 14902 21798, has_tags, 14902 21798, in_language, 16200 33616, has_genre, 5870 33616, has_tags, 14902 33616, has_tags, 39354 Question: In what context are BARBARA CUPISTI, JUDITH IVEY, and ZOMBIE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BARBARA CUPISTI", "JUDITH IVEY", "ZOMBIE" ], "valid_edges": [ [ "CEMETERY MAN", "directed_by", "MICHELE SOAVI" ], [ "CEMETERY MAN", "has_genre", "COMEDY" ], [ "CEMETERY MAN", "has_genre", "HORROR" ], [ "CEMETERY MAN", "has_tags", "ZOMBIE" ], [ "CEMETERY MAN", "has_tags", "ZOMBIES" ], [ "CEMETERY MAN", "in_language", "ITALIAN" ], [ "DAWN OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "DAWN OF THE DEAD", "has_genre", "HORROR" ], [ "DAWN OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "DAWN OF THE DEAD", "has_tags", "HORROR" ], [ "DAWN OF THE DEAD", "has_tags", "R" ], [ "DAWN OF THE DEAD", "has_tags", "REMAKE" ], [ "DAWN OF THE DEAD", "has_tags", "ROMERO" ], [ "DAWN OF THE DEAD", "has_tags", "ZOMBIE" ], [ "DAWN OF THE DEAD", "has_tags", "ZOMBIES" ], [ "DAWN OF THE DEAD", "release_year", "2004" ], [ "DAWN OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "has_genre", "HORROR" ], [ "DAY OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "DAY OF THE DEAD", "has_tags", "HORROR" ], [ "DAY OF THE DEAD", "has_tags", "ZOMBIE" ], [ "DAY OF THE DEAD", "release_year", "1985" ], [ "DAY OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "DEADHEADS", "has_genre", "COMEDY" ], [ "DEADHEADS", "has_tags", "COMEDY" ], [ "DEADHEADS", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "HELL OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "HELL OF THE LIVING DEAD", "in_language", "ITALIAN" ], [ "HELL OF THE LIVING DEAD", "release_year", "1980" ], [ "HELLO AGAIN", "has_genre", "COMEDY" ], [ "HELLO AGAIN", "starred_actors", "JUDITH IVEY" ], [ "LAND OF THE DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "LAND OF THE DEAD", "has_genre", "HORROR" ], [ "LAND OF THE DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "LAND OF THE DEAD", "has_tags", "ROMERO" ], [ "LAND OF THE DEAD", "has_tags", "ZOMBIE" ], [ "LAND OF THE DEAD", "written_by", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "directed_by", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "GEORGE A. ROMERO" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "HORROR" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "REMAKE" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "NIGHT OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "NIGHT OF THE LIVING DEAD", "written_by", "GEORGE A. ROMERO" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIE" ], [ "NIGHTMARE CITY", "has_tags", "ZOMBIES" ], [ "NIGHTMARE CITY", "in_language", "ITALIAN" ], [ "NIGHTMARE CITY", "release_year", "1980" ], [ "SHAUN OF THE DEAD", "has_genre", "COMEDY" ], [ "SHAUN OF THE DEAD", "has_tags", "COMEDY" ], [ "SHAUN OF THE DEAD", "has_tags", "R" ], [ "SHAUN OF THE DEAD", "has_tags", "ZOMBIE" ], [ "SHAUN OF THE DEAD", "has_tags", "ZOMBIES" ], [ "SHAUN OF THE DEAD", "release_year", "2004" ], [ "THE CHURCH", "directed_by", "MICHELE SOAVI" ], [ "THE CHURCH", "has_genre", "HORROR" ], [ "THE CHURCH", "in_language", "ITALIAN" ], [ "THE CHURCH", "starred_actors", "BARBARA CUPISTI" ], [ "THE CHURCH", "written_by", "MICHELE SOAVI" ], [ "THE LONELY GUY", "has_genre", "COMEDY" ], [ "THE LONELY GUY", "release_year", "1984" ], [ "THE LONELY GUY", "starred_actors", "CHARLES GRODIN" ], [ "THE LONELY GUY", "starred_actors", "JUDITH IVEY" ], [ "THE RETURN OF THE LIVING DEAD", "has_genre", "COMEDY" ], [ "THE RETURN OF THE LIVING DEAD", "has_genre", "HORROR" ], [ "THE RETURN OF THE LIVING DEAD", "has_tags", "ZOMBIE" ], [ "THE RETURN OF THE LIVING DEAD", "has_tags", "ZOMBIES" ], [ "THE RETURN OF THE LIVING DEAD", "release_year", "1985" ], [ "THE WOMAN IN RED", "has_genre", "COMEDY" ], [ "THE WOMAN IN RED", "release_year", "1984" ], [ "THE WOMAN IN RED", "starred_actors", "CHARLES GRODIN" ], [ "THE WOMAN IN RED", "starred_actors", "JUDITH IVEY" ], [ "UNDEAD", "has_genre", "COMEDY" ], [ "UNDEAD", "has_genre", "HORROR" ], [ "UNDEAD", "has_tags", "ZOMBIE" ], [ "ZOMBIE HOLOCAUST", "has_tags", "ZOMBIE" ], [ "ZOMBIE HOLOCAUST", "in_language", "ITALIAN" ], [ "ZOMBIE LAKE", "has_genre", "HORROR" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIE" ], [ "ZOMBIE LAKE", "has_tags", "ZOMBIES" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18132, 1938 35798, 2010 10768, BACK TO THE FUTURE 23299, GET CARTER 23544, INCEPTION 978, INFERNAL AFFAIRS 13825, INSOMNIA 29071, MEMENTO 28347, NICK WHITFIELD 32954, OLDBOY 32533, SCIENCE FICTION 11568, SKELETONS 16219, STORY 19102, SUPER 8 34042, THE CITADEL 4091, THE LADY VANISHES 24811, THRILLER 23568, VANILLA SKY src, edge_attr, dst 35798, has_tags, 32533 10768, has_tags, 32533 10768, has_tags, 16219 23299, has_genre, 24811 23299, has_tags, 16219 23544, has_tags, 32533 23544, has_tags, 24811 978, has_genre, 24811 978, has_tags, 16219 978, has_tags, 24811 13825, has_genre, 24811 13825, has_tags, 16219 29071, has_genre, 24811 29071, has_tags, 16219 32954, has_genre, 24811 32954, has_tags, 16219 11568, directed_by, 28347 11568, release_year, 35798 11568, written_by, 28347 19102, has_genre, 24811 19102, has_tags, 32533 19102, has_tags, 16219 34042, release_year, 18132 4091, has_genre, 24811 4091, release_year, 18132 23568, has_tags, 32533 23568, has_tags, 24811 Question: In what context are NICK WHITFIELD, SUPER 8, and THE CITADEL connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "NICK WHITFIELD", "SUPER 8", "THE CITADEL" ], "valid_edges": [ [ "2010", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE", "has_tags", "SCIENCE FICTION" ], [ "BACK TO THE FUTURE", "has_tags", "STORY" ], [ "GET CARTER", "has_genre", "THRILLER" ], [ "GET CARTER", "has_tags", "STORY" ], [ "INCEPTION", "has_tags", "SCIENCE FICTION" ], [ "INCEPTION", "has_tags", "THRILLER" ], [ "INFERNAL AFFAIRS", "has_genre", "THRILLER" ], [ "INFERNAL AFFAIRS", "has_tags", "STORY" ], [ "INFERNAL AFFAIRS", "has_tags", "THRILLER" ], [ "INSOMNIA", "has_genre", "THRILLER" ], [ "INSOMNIA", "has_tags", "STORY" ], [ "MEMENTO", "has_genre", "THRILLER" ], [ "MEMENTO", "has_tags", "STORY" ], [ "OLDBOY", "has_genre", "THRILLER" ], [ "OLDBOY", "has_tags", "STORY" ], [ "SKELETONS", "directed_by", "NICK WHITFIELD" ], [ "SKELETONS", "release_year", "2010" ], [ "SKELETONS", "written_by", "NICK WHITFIELD" ], [ "SUPER 8", "has_genre", "THRILLER" ], [ "SUPER 8", "has_tags", "SCIENCE FICTION" ], [ "SUPER 8", "has_tags", "STORY" ], [ "THE CITADEL", "release_year", "1938" ], [ "THE LADY VANISHES", "has_genre", "THRILLER" ], [ "THE LADY VANISHES", "release_year", "1938" ], [ "VANILLA SKY", "has_tags", "SCIENCE FICTION" ], [ "VANILLA SKY", "has_tags", "THRILLER" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27810, 1968 35845, 2006 3209, A NEW WAVE 33360, CANDY 22824, ICELANDIC 31412, JAR CITY 17302, OF HORSES AND MEN 15582, THE SHOES OF THE FISHERMAN src, edge_attr, dst 3209, release_year, 35845 33360, release_year, 27810 33360, release_year, 35845 31412, in_language, 22824 31412, release_year, 35845 17302, in_language, 22824 15582, release_year, 27810 Question: In what context are A NEW WAVE, OF HORSES AND MEN, and THE SHOES OF THE FISHERMAN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A NEW WAVE", "OF HORSES AND MEN", "THE SHOES OF THE FISHERMAN" ], "valid_edges": [ [ "A NEW WAVE", "release_year", "2006" ], [ "CANDY", "release_year", "1968" ], [ "CANDY", "release_year", "2006" ], [ "JAR CITY", "in_language", "ICELANDIC" ], [ "JAR CITY", "release_year", "2006" ], [ "OF HORSES AND MEN", "in_language", "ICELANDIC" ], [ "THE SHOES OF THE FISHERMAN", "release_year", "1968" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 30172, 1964 35935, 2002 27059, CATCH ME IF YOU CAN 14724, CRIME 39881, DAVID MCLEAN 17400, GANGS OF NEW YORK 17272, LEONARDO DICAPRIO 23963, MARIKO KAGA 5586, MARTIN SCORSESE 25658, PALE FLOWER 13081, R 18997, THE DEPARTED 29752, THE STRANGLER src, edge_attr, dst 27059, has_genre, 14724 27059, has_tags, 14724 27059, has_tags, 17272 27059, release_year, 35935 27059, starred_actors, 17272 17400, directed_by, 5586 17400, has_genre, 14724 17400, has_tags, 17272 17400, has_tags, 5586 17400, has_tags, 13081 17400, release_year, 35935 17400, starred_actors, 17272 25658, has_genre, 14724 25658, release_year, 30172 25658, starred_actors, 23963 18997, directed_by, 5586 18997, has_genre, 14724 18997, has_tags, 14724 18997, has_tags, 17272 18997, has_tags, 5586 18997, has_tags, 13081 18997, starred_actors, 17272 29752, release_year, 30172 29752, starred_actors, 39881 Question: For what reason are DAVID MCLEAN, LEONARDO DICAPRIO, and MARIKO KAGA associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DAVID MCLEAN", "LEONARDO DICAPRIO", "MARIKO KAGA" ], "valid_edges": [ [ "CATCH ME IF YOU CAN", "has_genre", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "CRIME" ], [ "CATCH ME IF YOU CAN", "has_tags", "LEONARDO DICAPRIO" ], [ "CATCH ME IF YOU CAN", "release_year", "2002" ], [ "CATCH ME IF YOU CAN", "starred_actors", "LEONARDO DICAPRIO" ], [ "GANGS OF NEW YORK", "directed_by", "MARTIN SCORSESE" ], [ "GANGS OF NEW YORK", "has_genre", "CRIME" ], [ "GANGS OF NEW YORK", "has_tags", "LEONARDO DICAPRIO" ], [ "GANGS OF NEW YORK", "has_tags", "MARTIN SCORSESE" ], [ "GANGS OF NEW YORK", "has_tags", "R" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "GANGS OF NEW YORK", "starred_actors", "LEONARDO DICAPRIO" ], [ "PALE FLOWER", "has_genre", "CRIME" ], [ "PALE FLOWER", "release_year", "1964" ], [ "PALE FLOWER", "starred_actors", "MARIKO KAGA" ], [ "THE DEPARTED", "directed_by", "MARTIN SCORSESE" ], [ "THE DEPARTED", "has_genre", "CRIME" ], [ "THE DEPARTED", "has_tags", "CRIME" ], [ "THE DEPARTED", "has_tags", "LEONARDO DICAPRIO" ], [ "THE DEPARTED", "has_tags", "MARTIN SCORSESE" ], [ "THE DEPARTED", "has_tags", "R" ], [ "THE DEPARTED", "starred_actors", "LEONARDO DICAPRIO" ], [ "THE STRANGLER", "release_year", "1964" ], [ "THE STRANGLER", "starred_actors", "DAVID MCLEAN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39813, 1971 37484, 2004 20228, A GOOD OLD FASHIONED ORGY 24039, A GOOD YEAR 39801, A NEW LEAF 26525, ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY 1698, ALFIE 21398, AMERICAN PIE 1546, AN AMERICAN WEREWOLF IN LONDON 36172, AND NOW FOR SOMETHING COMPLETELY DIFFERENT 38136, ARACHNOPHOBIA 39137, AS GOOD AS IT GETS 17133, AS YOU LIKE IT 5658, BAD BOY BUBBY 27816, BANANAS 10045, BD-R 26356, BEAUTY IN TROUBLE 36479, BORN TO DANCE 16452, BORN TO WIN 37616, BORN YESTERDAY 34243, BRIGHT EYES 10361, BYE BYE BIRDIE 19950, CHASING LIBERTY 15721, CIAO, PROFESSORE! 34828, COLD TURKEY 24116, COLLEGE 39887, COME BLOW YOUR HORN 30463, COMEDY 36016, COUSIN BETTE 30433, DELUSIONS OF GRANDEUR 20574, DICK VAN DYKE 21079, DIRTY DEEDS 20474, DIVORCE AMERICAN STYLE 33382, DOM HEMINGWAY 22983, DONA FLOR AND HER TWO HUSBANDS 27563, DOUBLE WEDDING 36212, DRAMA 38250, FATHER OF THE BRIDE 31060, GIGANTIC 11565, GOOD 10113, GOOD ADVICE 26282, GOOD HAIR 21763, GOOD MORNING, VIETNAM 26124, GOOD NEIGHBOR SAM 12502, GOODBYE CHARLIE 17652, GOODBYE, COLUMBUS 6388, HAROLD AND MAUDE 11014, HE'S JUST NOT THAT INTO YOU 35856, HEARTS OF THE WEST 10411, HOW TASTY WAS MY LITTLE FRENCHMAN 141, I HEART HUCKABEES 38304, IN GOOD COMPANY 7575, INTIMATE RELATIONS 25290, JERRY MAGUIRE 6099, JOHNNY DANGEROUSLY 1029, JUDE LAW 17397, KISS ME GOODBYE 19232, KOTCH 21091, LADY LIBERTY 22957, LEAP YEAR 17559, LEGALLY BLONDE 35898, LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS 11903, LET IT RIDE 16121, LITTLE MURDERS 3459, LONESOME JIM 32973, LT. ROBIN CRUSOE, U.S.N. 39913, MATINEE 26718, MEET THE PARENTS 27936, MONSTERS UNIVERSITY 12668, MRS. POLLIFAX-SPY 9435, MURDER AT THE GALLOP 112, MUSIC FROM ANOTHER ROOM 18524, MY BLUE HEAVEN 3027, NIGHT AT THE MUSEUM 1271, NO TIME FOR LOVE 15316, NORMAN LEAR 14797, O BROTHER, WHERE ART THOU? 8935, ONE NIGHT AT MCCOOL'S 10734, ORPHANS 36867, PAPER LION 35289, PARANORMAN 3297, PATCH ADAMS 5958, PERCHED ON A TREE 7053, PLATINUM BLONDE 10026, PLAZA SUITE 21040, PRETTY MAIDS ALL IN A ROW 21462, RAISING ARIZONA 32180, RAT RACE 35122, REVENGE OF THE NERDS 10066, ROMANTIC COMEDY 11370, RUSTLERS' RHAPSODY 21512, SHERLOCK HOLMES 6468, SKIN GAME 8456, SPLASH 3350, SUCH GOOD FRIENDS 29113, SUMMER OF '42 23720, TAKING OFF 6667, THE BIG CHILL 5299, THE BIG STORE 39463, THE BOY FRIEND 26573, THE GOLD RUSH 30181, THE GOOD FAIRY 914, THE GOOD GIRL 14807, THE GOODBYE GIRL 26955, THE HOLIDAY 31283, THE HOUND OF THE BASKERVILLES 27062, THE MILLION DOLLAR DUCK 14272, THE NIGHT THEY RAIDED MINSKY'S 15015, THE OPPOSITE SEX 16236, THE SURE THING 29643, THE TAO OF STEVE 33932, THE WHEELER DEALERS 34860, THIS IS THE NIGHT 6839, TOM MURRAY 17536, TRAFIC 832, TRUE STORIES 31620, UUNO TURHAPURO ARMEIJAN LEIVISSÄ 31, WELL KNOWN 26622, WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME? 36996, WHY BE GOOD? 22756, WINDOW TO PARIS 8184, YOU CAN'T TAKE IT WITH YOU 38863, YOU'LL NEVER GET RICH 5178, YOU'RE A GOOD MAN, CHARLIE BROWN 15808, YOU'VE GOT MAIL src, edge_attr, dst 20228, has_genre, 30463 20228, has_imdb_rating, 11565 24039, has_genre, 30463 24039, has_imdb_rating, 11565 39801, has_genre, 30463 39801, release_year, 39813 26525, has_genre, 30463 26525, has_imdb_rating, 11565 1698, has_genre, 30463 1698, has_genre, 36212 1698, has_tags, 10045 1698, has_tags, 1029 1698, release_year, 37484 1698, starred_actors, 1029 21398, has_genre, 30463 21398, has_imdb_rating, 11565 21398, has_tags, 30463 1546, has_genre, 30463 1546, has_imdb_rating, 11565 36172, has_genre, 30463 36172, has_tags, 30463 36172, release_year, 39813 38136, has_genre, 30463 38136, has_imdb_rating, 11565 38136, has_tags, 30463 39137, has_genre, 30463 39137, has_imdb_rating, 11565 39137, has_tags, 30463 17133, has_genre, 30463 17133, has_imdb_rating, 11565 5658, has_genre, 30463 5658, has_imdb_rating, 11565 27816, has_genre, 30463 27816, has_tags, 30463 27816, release_year, 39813 26356, has_genre, 30463 26356, has_imdb_rating, 11565 36479, has_genre, 30463 36479, has_imdb_rating, 11565 16452, has_genre, 30463 16452, release_year, 39813 37616, has_genre, 30463 37616, has_imdb_rating, 11565 34243, has_genre, 30463 34243, has_imdb_rating, 11565 10361, has_genre, 30463 10361, starred_actors, 20574 19950, has_genre, 30463 19950, has_imdb_rating, 11565 15721, has_genre, 30463 15721, has_imdb_rating, 11565 34828, directed_by, 15316 34828, has_genre, 30463 34828, has_imdb_rating, 11565 34828, has_imdb_votes, 31 34828, release_year, 39813 34828, starred_actors, 20574 34828, written_by, 15316 24116, has_genre, 30463 24116, has_imdb_rating, 11565 39887, has_genre, 30463 39887, written_by, 15316 36016, has_genre, 30463 36016, has_imdb_rating, 11565 30433, has_genre, 30463 30433, release_year, 39813 21079, has_genre, 30463 21079, has_imdb_rating, 11565 21079, has_tags, 30463 20474, has_genre, 30463 20474, starred_actors, 20574 20474, written_by, 15316 33382, has_genre, 30463 33382, has_genre, 36212 33382, starred_actors, 1029 22983, has_genre, 30463 22983, has_imdb_rating, 11565 27563, has_genre, 30463 27563, has_imdb_rating, 11565 38250, has_genre, 30463 38250, has_imdb_rating, 11565 38250, has_tags, 30463 31060, has_genre, 30463 31060, has_imdb_rating, 11565 11565, has_imdb_rating, 11565 10113, has_genre, 30463 10113, has_imdb_rating, 11565 26282, has_genre, 30463 26282, has_imdb_rating, 11565 21763, has_genre, 30463 21763, has_imdb_rating, 11565 26124, has_genre, 30463 26124, has_imdb_rating, 11565 12502, has_genre, 30463 12502, has_imdb_rating, 11565 17652, has_genre, 30463 17652, has_imdb_rating, 11565 6388, has_genre, 30463 6388, release_year, 39813 11014, has_genre, 30463 11014, has_imdb_rating, 11565 35856, has_genre, 30463 35856, has_imdb_rating, 11565 10411, has_genre, 30463 10411, release_year, 39813 141, has_genre, 30463 141, has_tags, 30463 141, has_tags, 1029 141, release_year, 37484 38304, has_genre, 30463 38304, has_imdb_rating, 11565 7575, has_genre, 30463 7575, has_imdb_rating, 11565 25290, has_genre, 30463 25290, has_imdb_rating, 11565 25290, has_tags, 30463 6099, has_genre, 30463 6099, has_imdb_rating, 11565 17397, has_genre, 30463 17397, has_imdb_rating, 11565 19232, has_genre, 30463 19232, release_year, 39813 21091, has_genre, 30463 21091, release_year, 39813 22957, has_genre, 30463 22957, has_imdb_rating, 11565 17559, has_genre, 30463 17559, has_imdb_rating, 11565 17559, has_tags, 30463 35898, has_genre, 30463 35898, has_tags, 1029 35898, has_tags, 10734 35898, release_year, 37484 11903, has_genre, 30463 11903, has_imdb_rating, 11565 16121, has_genre, 30463 16121, release_year, 39813 3459, has_genre, 30463 3459, has_imdb_rating, 11565 32973, has_genre, 30463 32973, has_tags, 20574 32973, starred_actors, 20574 39913, has_genre, 30463 39913, has_imdb_rating, 11565 26718, has_genre, 30463 26718, has_imdb_rating, 11565 26718, has_tags, 30463 27936, has_genre, 30463 27936, has_imdb_rating, 11565 27936, has_tags, 30463 12668, has_genre, 30463 12668, release_year, 39813 9435, has_genre, 30463 9435, has_imdb_rating, 11565 112, has_genre, 30463 112, has_genre, 36212 112, has_tags, 1029 112, starred_actors, 1029 18524, has_genre, 30463 18524, has_imdb_rating, 11565 3027, has_genre, 30463 3027, has_tags, 20574 3027, starred_actors, 20574 1271, has_genre, 30463 1271, has_imdb_rating, 11565 14797, has_genre, 30463 14797, has_imdb_rating, 11565 14797, has_tags, 30463 8935, has_genre, 30463 8935, has_imdb_rating, 11565 10734, has_genre, 30463 36867, has_genre, 30463 36867, has_imdb_rating, 11565 35289, has_genre, 30463 35289, has_imdb_rating, 11565 3297, has_genre, 30463 3297, has_imdb_rating, 11565 5958, has_genre, 30463 5958, release_year, 39813 7053, has_genre, 30463 7053, has_imdb_votes, 31 10026, has_genre, 30463 10026, release_year, 39813 21040, has_genre, 30463 21040, release_year, 39813 21462, has_genre, 30463 21462, has_imdb_rating, 11565 21462, has_tags, 30463 32180, has_genre, 30463 32180, has_imdb_rating, 11565 32180, has_tags, 30463 35122, has_genre, 30463 35122, has_imdb_rating, 11565 10066, has_genre, 30463 11370, has_genre, 30463 11370, has_imdb_rating, 11565 21512, has_tags, 30463 21512, has_tags, 1029 21512, has_tags, 21512 21512, starred_actors, 1029 6468, has_genre, 30463 6468, release_year, 39813 8456, has_genre, 30463 8456, has_imdb_rating, 11565 3350, has_genre, 30463 3350, has_imdb_rating, 11565 3350, release_year, 39813 29113, has_genre, 30463 29113, release_year, 39813 23720, has_genre, 30463 23720, release_year, 39813 6667, has_genre, 30463 6667, has_imdb_rating, 11565 5299, has_genre, 30463 5299, has_imdb_rating, 11565 39463, has_genre, 30463 39463, release_year, 39813 26573, has_genre, 30463 26573, has_tags, 30463 26573, starred_actors, 6839 30181, has_genre, 30463 30181, has_imdb_rating, 11565 914, has_genre, 30463 914, has_imdb_rating, 11565 14807, has_genre, 30463 14807, has_imdb_rating, 11565 26955, has_genre, 30463 26955, has_tags, 10045 26955, has_tags, 1029 26955, has_tags, 10066 26955, starred_actors, 1029 31283, has_genre, 30463 31283, has_tags, 21512 27062, has_genre, 30463 27062, release_year, 39813 14272, has_genre, 30463 14272, written_by, 15316 15015, has_genre, 30463 15015, has_imdb_rating, 11565 16236, has_genre, 30463 16236, has_imdb_rating, 11565 29643, has_genre, 30463 29643, has_imdb_rating, 11565 33932, has_genre, 30463 33932, has_imdb_rating, 11565 34860, has_genre, 30463 34860, has_imdb_rating, 11565 17536, has_genre, 30463 17536, has_imdb_rating, 11565 17536, release_year, 39813 832, has_genre, 30463 832, has_imdb_rating, 11565 31620, has_genre, 30463 31620, has_imdb_votes, 31 26622, has_genre, 30463 26622, release_year, 39813 36996, has_genre, 30463 36996, has_imdb_rating, 11565 22756, has_genre, 30463 22756, has_imdb_rating, 11565 8184, has_genre, 30463 8184, has_imdb_rating, 11565 38863, has_genre, 30463 38863, has_imdb_rating, 11565 5178, has_genre, 30463 5178, has_imdb_rating, 11565 15808, has_genre, 30463 15808, has_imdb_rating, 11565 15808, has_tags, 30463 Question: In what context are COLD TURKEY, JUDE LAW, and TOM MURRAY connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "COLD TURKEY", "JUDE LAW", "TOM MURRAY" ], "valid_edges": [ [ "A GOOD OLD FASHIONED ORGY", "has_genre", "COMEDY" ], [ "A GOOD OLD FASHIONED ORGY", "has_imdb_rating", "GOOD" ], [ "A GOOD YEAR", "has_genre", "COMEDY" ], [ "A GOOD YEAR", "has_imdb_rating", "GOOD" ], [ "A NEW LEAF", "has_genre", "COMEDY" ], [ "A NEW LEAF", "release_year", "1971" ], [ "ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY", "has_genre", "COMEDY" ], [ "ALEXANDER AND THE TERRIBLE, HORRIBLE, NO GOOD, VERY BAD DAY", "has_imdb_rating", "GOOD" ], [ "ALFIE", "has_genre", "COMEDY" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "has_tags", "BD-R" ], [ "ALFIE", "has_tags", "JUDE LAW" ], [ "ALFIE", "release_year", "2004" ], [ "ALFIE", "starred_actors", "JUDE LAW" ], [ "AMERICAN PIE", "has_genre", "COMEDY" ], [ "AMERICAN PIE", "has_imdb_rating", "GOOD" ], [ "AMERICAN PIE", "has_tags", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_genre", "COMEDY" ], [ "AN AMERICAN WEREWOLF IN LONDON", "has_imdb_rating", "GOOD" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "has_genre", "COMEDY" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "has_tags", "COMEDY" ], [ "AND NOW FOR SOMETHING COMPLETELY DIFFERENT", "release_year", "1971" ], [ "ARACHNOPHOBIA", "has_genre", "COMEDY" ], [ "ARACHNOPHOBIA", "has_imdb_rating", "GOOD" ], [ "ARACHNOPHOBIA", "has_tags", "COMEDY" ], [ "AS GOOD AS IT GETS", "has_genre", "COMEDY" ], [ "AS GOOD AS IT GETS", "has_imdb_rating", "GOOD" ], [ "AS GOOD AS IT GETS", "has_tags", "COMEDY" ], [ "AS YOU LIKE IT", "has_genre", "COMEDY" ], [ "AS YOU LIKE IT", "has_imdb_rating", "GOOD" ], [ "BAD BOY BUBBY", "has_genre", "COMEDY" ], [ "BAD BOY BUBBY", "has_imdb_rating", "GOOD" ], [ "BANANAS", "has_genre", "COMEDY" ], [ "BANANAS", "has_tags", "COMEDY" ], [ "BANANAS", "release_year", "1971" ], [ "BEAUTY IN TROUBLE", "has_genre", "COMEDY" ], [ "BEAUTY IN TROUBLE", "has_imdb_rating", "GOOD" ], [ "BORN TO DANCE", "has_genre", "COMEDY" ], [ "BORN TO DANCE", "has_imdb_rating", "GOOD" ], [ "BORN TO WIN", "has_genre", "COMEDY" ], [ "BORN TO WIN", "release_year", "1971" ], [ "BORN YESTERDAY", "has_genre", "COMEDY" ], [ "BORN YESTERDAY", "has_imdb_rating", "GOOD" ], [ "BRIGHT EYES", "has_genre", "COMEDY" ], [ "BRIGHT EYES", "has_imdb_rating", "GOOD" ], [ "BYE BYE BIRDIE", "has_genre", "COMEDY" ], [ "BYE BYE BIRDIE", "starred_actors", "DICK VAN DYKE" ], [ "CHASING LIBERTY", "has_genre", "COMEDY" ], [ "CHASING LIBERTY", "has_imdb_rating", "GOOD" ], [ "CIAO, PROFESSORE!", "has_genre", "COMEDY" ], [ "CIAO, PROFESSORE!", "has_imdb_rating", "GOOD" ], [ "COLD TURKEY", "directed_by", "NORMAN LEAR" ], [ "COLD TURKEY", "has_genre", "COMEDY" ], [ "COLD TURKEY", "has_imdb_rating", "GOOD" ], [ "COLD TURKEY", "has_imdb_votes", "WELL KNOWN" ], [ "COLD TURKEY", "release_year", "1971" ], [ "COLD TURKEY", "starred_actors", "DICK VAN DYKE" ], [ "COLD TURKEY", "written_by", "NORMAN LEAR" ], [ "COLLEGE", "has_genre", "COMEDY" ], [ "COLLEGE", "has_imdb_rating", "GOOD" ], [ "COME BLOW YOUR HORN", "has_genre", "COMEDY" ], [ "COME BLOW YOUR HORN", "written_by", "NORMAN LEAR" ], [ "COUSIN BETTE", "has_genre", "COMEDY" ], [ "COUSIN BETTE", "has_imdb_rating", "GOOD" ], [ "DELUSIONS OF GRANDEUR", "has_genre", "COMEDY" ], [ "DELUSIONS OF GRANDEUR", "release_year", "1971" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_imdb_rating", "GOOD" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIVORCE AMERICAN STYLE", "has_genre", "COMEDY" ], [ "DIVORCE AMERICAN STYLE", "starred_actors", "DICK VAN DYKE" ], [ "DIVORCE AMERICAN STYLE", "written_by", "NORMAN LEAR" ], [ "DOM HEMINGWAY", "has_genre", "COMEDY" ], [ "DOM HEMINGWAY", "has_genre", "DRAMA" ], [ "DOM HEMINGWAY", "starred_actors", "JUDE LAW" ], [ "DONA FLOR AND HER TWO HUSBANDS", "has_genre", "COMEDY" ], [ "DONA FLOR AND HER TWO HUSBANDS", "has_imdb_rating", "GOOD" ], [ "DOUBLE WEDDING", "has_genre", "COMEDY" ], [ "DOUBLE WEDDING", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_genre", "COMEDY" ], [ "FATHER OF THE BRIDE", "has_imdb_rating", "GOOD" ], [ "FATHER OF THE BRIDE", "has_tags", "COMEDY" ], [ "GIGANTIC", "has_genre", "COMEDY" ], [ "GIGANTIC", "has_imdb_rating", "GOOD" ], [ "GOOD", "has_imdb_rating", "GOOD" ], [ "GOOD ADVICE", "has_genre", "COMEDY" ], [ "GOOD ADVICE", "has_imdb_rating", "GOOD" ], [ "GOOD HAIR", "has_genre", "COMEDY" ], [ "GOOD HAIR", "has_imdb_rating", "GOOD" ], [ "GOOD MORNING, VIETNAM", "has_genre", "COMEDY" ], [ "GOOD MORNING, VIETNAM", "has_imdb_rating", "GOOD" ], [ "GOOD NEIGHBOR SAM", "has_genre", "COMEDY" ], [ "GOOD NEIGHBOR SAM", "has_imdb_rating", "GOOD" ], [ "GOODBYE CHARLIE", "has_genre", "COMEDY" ], [ "GOODBYE CHARLIE", "has_imdb_rating", "GOOD" ], [ "GOODBYE, COLUMBUS", "has_genre", "COMEDY" ], [ "GOODBYE, COLUMBUS", "has_imdb_rating", "GOOD" ], [ "HAROLD AND MAUDE", "has_genre", "COMEDY" ], [ "HAROLD AND MAUDE", "release_year", "1971" ], [ "HE'S JUST NOT THAT INTO YOU", "has_genre", "COMEDY" ], [ "HE'S JUST NOT THAT INTO YOU", "has_imdb_rating", "GOOD" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_imdb_rating", "GOOD" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "has_genre", "COMEDY" ], [ "HOW TASTY WAS MY LITTLE FRENCHMAN", "release_year", "1971" ], [ "I HEART HUCKABEES", "has_genre", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "COMEDY" ], [ "I HEART HUCKABEES", "has_tags", "JUDE LAW" ], [ "I HEART HUCKABEES", "release_year", "2004" ], [ "IN GOOD COMPANY", "has_genre", "COMEDY" ], [ "IN GOOD COMPANY", "has_imdb_rating", "GOOD" ], [ "INTIMATE RELATIONS", "has_genre", "COMEDY" ], [ "INTIMATE RELATIONS", "has_imdb_rating", "GOOD" ], [ "JERRY MAGUIRE", "has_genre", "COMEDY" ], [ "JERRY MAGUIRE", "has_imdb_rating", "GOOD" ], [ "JERRY MAGUIRE", "has_tags", "COMEDY" ], [ "JOHNNY DANGEROUSLY", "has_genre", "COMEDY" ], [ "JOHNNY DANGEROUSLY", "has_imdb_rating", "GOOD" ], [ "KISS ME GOODBYE", "has_genre", "COMEDY" ], [ "KISS ME GOODBYE", "has_imdb_rating", "GOOD" ], [ "KOTCH", "has_genre", "COMEDY" ], [ "KOTCH", "release_year", "1971" ], [ "LADY LIBERTY", "has_genre", "COMEDY" ], [ "LADY LIBERTY", "release_year", "1971" ], [ "LEAP YEAR", "has_genre", "COMEDY" ], [ "LEAP YEAR", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_imdb_rating", "GOOD" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_genre", "COMEDY" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_tags", "JUDE LAW" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "has_tags", "ORPHANS" ], [ "LEMONY SNICKET'S A SERIES OF UNFORTUNATE EVENTS", "release_year", "2004" ], [ "LET IT RIDE", "has_genre", "COMEDY" ], [ "LET IT RIDE", "has_imdb_rating", "GOOD" ], [ "LITTLE MURDERS", "has_genre", "COMEDY" ], [ "LITTLE MURDERS", "release_year", "1971" ], [ "LONESOME JIM", "has_genre", "COMEDY" ], [ "LONESOME JIM", "has_imdb_rating", "GOOD" ], [ "LT. ROBIN CRUSOE, U.S.N.", "has_genre", "COMEDY" ], [ "LT. ROBIN CRUSOE, U.S.N.", "has_tags", "DICK VAN DYKE" ], [ "LT. ROBIN CRUSOE, U.S.N.", "starred_actors", "DICK VAN DYKE" ], [ "MATINEE", "has_genre", "COMEDY" ], [ "MATINEE", "has_imdb_rating", "GOOD" ], [ "MEET THE PARENTS", "has_genre", "COMEDY" ], [ "MEET THE PARENTS", "has_imdb_rating", "GOOD" ], [ "MEET THE PARENTS", "has_tags", "COMEDY" ], [ "MONSTERS UNIVERSITY", "has_genre", "COMEDY" ], [ "MONSTERS UNIVERSITY", "has_imdb_rating", "GOOD" ], [ "MONSTERS UNIVERSITY", "has_tags", "COMEDY" ], [ "MRS. POLLIFAX-SPY", "has_genre", "COMEDY" ], [ "MRS. POLLIFAX-SPY", "release_year", "1971" ], [ "MURDER AT THE GALLOP", "has_genre", "COMEDY" ], [ "MURDER AT THE GALLOP", "has_imdb_rating", "GOOD" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "COMEDY" ], [ "MUSIC FROM ANOTHER ROOM", "has_genre", "DRAMA" ], [ "MUSIC FROM ANOTHER ROOM", "has_tags", "JUDE LAW" ], [ "MUSIC FROM ANOTHER ROOM", "starred_actors", "JUDE LAW" ], [ "MY BLUE HEAVEN", "has_genre", "COMEDY" ], [ "MY BLUE HEAVEN", "has_imdb_rating", "GOOD" ], [ "NIGHT AT THE MUSEUM", "has_genre", "COMEDY" ], [ "NIGHT AT THE MUSEUM", "has_tags", "DICK VAN DYKE" ], [ "NIGHT AT THE MUSEUM", "starred_actors", "DICK VAN DYKE" ], [ "NO TIME FOR LOVE", "has_genre", "COMEDY" ], [ "NO TIME FOR LOVE", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_imdb_rating", "GOOD" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "has_genre", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "has_imdb_rating", "GOOD" ], [ "ORPHANS", "has_genre", "COMEDY" ], [ "PAPER LION", "has_genre", "COMEDY" ], [ "PAPER LION", "has_imdb_rating", "GOOD" ], [ "PARANORMAN", "has_genre", "COMEDY" ], [ "PARANORMAN", "has_imdb_rating", "GOOD" ], [ "PATCH ADAMS", "has_genre", "COMEDY" ], [ "PATCH ADAMS", "has_imdb_rating", "GOOD" ], [ "PERCHED ON A TREE", "has_genre", "COMEDY" ], [ "PERCHED ON A TREE", "release_year", "1971" ], [ "PLATINUM BLONDE", "has_genre", "COMEDY" ], [ "PLATINUM BLONDE", "has_imdb_votes", "WELL KNOWN" ], [ "PLAZA SUITE", "has_genre", "COMEDY" ], [ "PLAZA SUITE", "release_year", "1971" ], [ "PRETTY MAIDS ALL IN A ROW", "has_genre", "COMEDY" ], [ "PRETTY MAIDS ALL IN A ROW", "release_year", "1971" ], [ "RAISING ARIZONA", "has_genre", "COMEDY" ], [ "RAISING ARIZONA", "has_imdb_rating", "GOOD" ], [ "RAISING ARIZONA", "has_tags", "COMEDY" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_imdb_rating", "GOOD" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "REVENGE OF THE NERDS", "has_genre", "COMEDY" ], [ "REVENGE OF THE NERDS", "has_imdb_rating", "GOOD" ], [ "ROMANTIC COMEDY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_genre", "COMEDY" ], [ "RUSTLERS' RHAPSODY", "has_imdb_rating", "GOOD" ], [ "SHERLOCK HOLMES", "has_tags", "COMEDY" ], [ "SHERLOCK HOLMES", "has_tags", "JUDE LAW" ], [ "SHERLOCK HOLMES", "has_tags", "SHERLOCK HOLMES" ], [ "SHERLOCK HOLMES", "starred_actors", "JUDE LAW" ], [ "SKIN GAME", "has_genre", "COMEDY" ], [ "SKIN GAME", "release_year", "1971" ], [ "SPLASH", "has_genre", "COMEDY" ], [ "SPLASH", "has_imdb_rating", "GOOD" ], [ "SUCH GOOD FRIENDS", "has_genre", "COMEDY" ], [ "SUCH GOOD FRIENDS", "has_imdb_rating", "GOOD" ], [ "SUCH GOOD FRIENDS", "release_year", "1971" ], [ "SUMMER OF '42", "has_genre", "COMEDY" ], [ "SUMMER OF '42", "release_year", "1971" ], [ "TAKING OFF", "has_genre", "COMEDY" ], [ "TAKING OFF", "release_year", "1971" ], [ "THE BIG CHILL", "has_genre", "COMEDY" ], [ "THE BIG CHILL", "has_imdb_rating", "GOOD" ], [ "THE BIG STORE", "has_genre", "COMEDY" ], [ "THE BIG STORE", "has_imdb_rating", "GOOD" ], [ "THE BOY FRIEND", "has_genre", "COMEDY" ], [ "THE BOY FRIEND", "release_year", "1971" ], [ "THE GOLD RUSH", "has_genre", "COMEDY" ], [ "THE GOLD RUSH", "has_tags", "COMEDY" ], [ "THE GOLD RUSH", "starred_actors", "TOM MURRAY" ], [ "THE GOOD FAIRY", "has_genre", "COMEDY" ], [ "THE GOOD FAIRY", "has_imdb_rating", "GOOD" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "has_imdb_rating", "GOOD" ], [ "THE GOODBYE GIRL", "has_genre", "COMEDY" ], [ "THE GOODBYE GIRL", "has_imdb_rating", "GOOD" ], [ "THE HOLIDAY", "has_genre", "COMEDY" ], [ "THE HOLIDAY", "has_tags", "BD-R" ], [ "THE HOLIDAY", "has_tags", "JUDE LAW" ], [ "THE HOLIDAY", "has_tags", "ROMANTIC COMEDY" ], [ "THE HOLIDAY", "starred_actors", "JUDE LAW" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "COMEDY" ], [ "THE HOUND OF THE BASKERVILLES", "has_tags", "SHERLOCK HOLMES" ], [ "THE MILLION DOLLAR DUCK", "has_genre", "COMEDY" ], [ "THE MILLION DOLLAR DUCK", "release_year", "1971" ], [ "THE NIGHT THEY RAIDED MINSKY'S", "has_genre", "COMEDY" ], [ "THE NIGHT THEY RAIDED MINSKY'S", "written_by", "NORMAN LEAR" ], [ "THE OPPOSITE SEX", "has_genre", "COMEDY" ], [ "THE OPPOSITE SEX", "has_imdb_rating", "GOOD" ], [ "THE SURE THING", "has_genre", "COMEDY" ], [ "THE SURE THING", "has_imdb_rating", "GOOD" ], [ "THE TAO OF STEVE", "has_genre", "COMEDY" ], [ "THE TAO OF STEVE", "has_imdb_rating", "GOOD" ], [ "THE WHEELER DEALERS", "has_genre", "COMEDY" ], [ "THE WHEELER DEALERS", "has_imdb_rating", "GOOD" ], [ "THIS IS THE NIGHT", "has_genre", "COMEDY" ], [ "THIS IS THE NIGHT", "has_imdb_rating", "GOOD" ], [ "TRAFIC", "has_genre", "COMEDY" ], [ "TRAFIC", "has_imdb_rating", "GOOD" ], [ "TRAFIC", "release_year", "1971" ], [ "TRUE STORIES", "has_genre", "COMEDY" ], [ "TRUE STORIES", "has_imdb_rating", "GOOD" ], [ "UUNO TURHAPURO ARMEIJAN LEIVISSÄ", "has_genre", "COMEDY" ], [ "UUNO TURHAPURO ARMEIJAN LEIVISSÄ", "has_imdb_votes", "WELL KNOWN" ], [ "WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME?", "has_genre", "COMEDY" ], [ "WHO IS HARRY KELLERMAN AND WHY IS HE SAYING THOSE TERRIBLE THINGS ABOUT ME?", "release_year", "1971" ], [ "WHY BE GOOD?", "has_genre", "COMEDY" ], [ "WHY BE GOOD?", "has_imdb_rating", "GOOD" ], [ "WINDOW TO PARIS", "has_genre", "COMEDY" ], [ "WINDOW TO PARIS", "has_imdb_rating", "GOOD" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_genre", "COMEDY" ], [ "YOU CAN'T TAKE IT WITH YOU", "has_imdb_rating", "GOOD" ], [ "YOU'LL NEVER GET RICH", "has_genre", "COMEDY" ], [ "YOU'LL NEVER GET RICH", "has_imdb_rating", "GOOD" ], [ "YOU'RE A GOOD MAN, CHARLIE BROWN", "has_genre", "COMEDY" ], [ "YOU'RE A GOOD MAN, CHARLIE BROWN", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "has_genre", "COMEDY" ], [ "YOU'VE GOT MAIL", "has_imdb_rating", "GOOD" ], [ "YOU'VE GOT MAIL", "has_tags", "COMEDY" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35187, 1948 3863, 1962 40009, A FOREIGN AFFAIR 16566, A MONKEY IN WINTER 18595, HENRI VERNEUIL 25397, I AS IN ICARUS 12473, PITFALL 17361, THE BRAIN THAT WOULDN'T DIE src, edge_attr, dst 40009, release_year, 35187 16566, directed_by, 18595 16566, has_tags, 18595 16566, release_year, 3863 25397, directed_by, 18595 25397, written_by, 18595 12473, release_year, 35187 12473, release_year, 3863 17361, release_year, 3863 Question: In what context are A FOREIGN AFFAIR, I AS IN ICARUS, and THE BRAIN THAT WOULDN'T DIE connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A FOREIGN AFFAIR", "I AS IN ICARUS", "THE BRAIN THAT WOULDN'T DIE" ], "valid_edges": [ [ "A FOREIGN AFFAIR", "release_year", "1948" ], [ "A MONKEY IN WINTER", "directed_by", "HENRI VERNEUIL" ], [ "A MONKEY IN WINTER", "has_tags", "HENRI VERNEUIL" ], [ "A MONKEY IN WINTER", "release_year", "1962" ], [ "I AS IN ICARUS", "directed_by", "HENRI VERNEUIL" ], [ "I AS IN ICARUS", "written_by", "HENRI VERNEUIL" ], [ "PITFALL", "release_year", "1948" ], [ "PITFALL", "release_year", "1962" ], [ "THE BRAIN THAT WOULDN'T DIE", "release_year", "1962" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35935, 2002 4310, 24 HOUR PARTY PEOPLE 9408, 40 DAYS AND 40 NIGHTS 36647, 8 WOMEN 11957, 9 DEAD GAY GUYS 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 68, ADMISSION 33534, AFTERNOON DELIGHT 17111, ALI G INDAHOUSE 22569, ALL ABOUT THE BENJAMINS 28458, ALL IS BRIGHT 16113, ANALYZE THAT 32612, ANNA ODELL 7302, AS COOL AS I AM 35314, AUSTIN POWERS IN GOLDMEMBER 29535, AVENGING ANGELO 23899, BAD COMPANY 36819, BARBERSHOP 15433, BEND IT LIKE BECKHAM 39619, BIG FAT LIAR 8732, BIG TROUBLE 27128, BOAT TRIP 32620, BUBBA HO-TEP 14572, BUYING THE COW 27929, CABIN FEVER 23286, CARNAGE 20073, CHERISH 10349, CHICAGO 32644, CHINESE ODYSSEY 2002 1267, CLOSER TO THE MOON 30463, COMEDY 21391, CRACKERJACK 30019, CROSSROADS 21730, DAY OF THE WACKO 19179, DEATH TO SMOOCHY 29309, DELIVERY MAN 21079, DIRTY DEEDS 33382, DOM HEMINGWAY 13792, DON JON 36212, DRAMA 25651, DUMMY 26815, EIGHT CRAZY NIGHTS 38543, EIGHT LEGGED FREAKS 28256, FILTH 27539, FRANK MCKLUSKY, C.I. 29241, FRIDAY AFTER NEXT 5287, FROZEN 21415, GREGORY GO BOOM 10990, HEARTLANDS 3829, HERO 15629, HOME ALONE 4 21886, HOME ROOM 22069, I SPY 27919, I'M WITH LUCY 16371, ICE AGE 17197, IGBY GOES DOWN 15909, INSTRUCTIONS NOT INCLUDED 33001, JUST A KISS 2204, JUWANNA MANN 31245, KAL HO NAA HO 32010, KISS THE BRIDE 12137, LIFE OR SOMETHING LIKE IT 28832, LIFE WITHOUT DICK 16155, LOVE LIZA 9812, MAID IN MANHATTAN 4270, MEN WITH BROOMS 36083, MIRANDA 20803, MR. DEEDS 22064, MY BIG FAT GREEK WEDDING 4887, MY LEFT EYE SEES GHOSTS 35262, MY MOTHER LIKES WOMEN 35794, NOVO 1493, NOW YOU KNOW 2721, OCCIDENT 4582, ONCE UPON A TIME IN THE MIDLANDS 39121, ONE CHANCE 37178, ORANGE COUNTY 25824, PARADISE 27117, PASSIONADA 9976, PIPE DREAM 7136, PRINCE AVALANCHE 3688, PUMPKIN 34602, PUNCH-DRUNK LOVE 21890, R.S.V.P. 25769, ROGER DODGER 25243, SAVING MR. BANKS 12987, SCOOBY-DOO 15252, SCREWED IN TALLINN 19244, SERVING SARA 6603, SEX IS COMEDY 26261, SHOWTIME 15043, SLACKERS 25151, SNOW DOGS 24961, SORORITY BOYS 35843, SPUN 5170, STEALING HARVARD 15100, SUPER SUCKER 9276, SWEET HOME ALABAMA 26790, SWEPT AWAY 36316, THE ADVENTURES OF PLUTO NASH 3961, THE AMAZING CATFISH 2316, THE ANARCHIST COOKBOOK 304, THE BANGER SISTERS 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 914, THE GOOD GIRL 26531, THE GURU 24302, THE HOT CHICK 13534, THE IMPORTANCE OF BEING EARNEST 2147, THE MAN WITHOUT A PAST 6908, THE MASTER OF DISGUISE 295, THE NEW GUY 1192, THE ONE AND ONLY 4335, THE PRETTY ONE 39078, THE REUNION 31401, THE RULES OF ATTRACTION 30746, THE SECRET LIFE OF WALTER MITTY 32975, THE SPECTACULAR NOW 7052, THE SWEETEST THING 34172, THE TUXEDO 34916, THE WAY WAY BACK 22625, TOGETHER 10720, TRIGGERMEN 26275, TRUST ME 9612, TWO WEEKS NOTICE 13214, UNCONDITIONAL LOVE 16991, UNDERCOVER BROTHER 21576, WAKING UP IN RENO 37568, WELCOME TO COLLINWOOD 39802, WHEN IN ROME src, edge_attr, dst 4310, has_genre, 30463 4310, has_genre, 36212 4310, release_year, 35935 9408, has_genre, 30463 9408, has_tags, 30463 9408, release_year, 35935 36647, has_genre, 30463 36647, release_year, 35935 11957, has_genre, 30463 11957, release_year, 35935 6008, has_genre, 30463 6008, has_genre, 36212 6008, has_tags, 30463 6008, has_tags, 36212 6008, release_year, 35935 37599, has_genre, 30463 37599, has_genre, 36212 37599, has_tags, 30463 37599, has_tags, 36212 37599, release_year, 35935 68, has_genre, 30463 68, has_genre, 36212 68, has_tags, 30463 33534, has_genre, 30463 33534, has_genre, 36212 17111, has_genre, 30463 17111, release_year, 35935 22569, has_genre, 30463 22569, has_tags, 30463 22569, release_year, 35935 28458, has_genre, 30463 28458, has_genre, 36212 16113, has_genre, 30463 16113, has_tags, 30463 16113, release_year, 35935 7302, has_genre, 30463 7302, has_genre, 36212 35314, has_genre, 30463 35314, has_tags, 30463 35314, release_year, 35935 29535, has_genre, 30463 29535, release_year, 35935 23899, has_genre, 30463 23899, release_year, 35935 36819, has_genre, 30463 36819, release_year, 35935 15433, has_genre, 30463 15433, has_genre, 36212 15433, release_year, 35935 39619, has_genre, 30463 39619, release_year, 35935 8732, has_genre, 30463 8732, release_year, 35935 27128, has_genre, 30463 27128, release_year, 35935 32620, has_genre, 30463 32620, has_tags, 30463 32620, release_year, 35935 14572, has_genre, 30463 14572, release_year, 35935 27929, has_genre, 30463 27929, release_year, 35935 23286, has_genre, 30463 23286, has_genre, 36212 23286, release_year, 35935 20073, has_genre, 30463 20073, has_genre, 36212 20073, release_year, 35935 10349, has_genre, 30463 10349, has_genre, 36212 10349, release_year, 35935 32644, has_genre, 30463 32644, release_year, 35935 1267, has_genre, 30463 1267, has_genre, 36212 1267, has_tags, 30463 21391, has_genre, 30463 21391, release_year, 35935 30019, has_genre, 30463 30019, has_genre, 36212 30019, release_year, 35935 21730, has_genre, 30463 21730, has_genre, 36212 21730, release_year, 35935 19179, has_genre, 30463 19179, release_year, 35935 29309, has_genre, 30463 29309, has_genre, 36212 29309, has_tags, 36212 21079, has_genre, 30463 21079, has_tags, 30463 21079, release_year, 35935 33382, has_genre, 30463 33382, has_genre, 36212 13792, has_genre, 30463 13792, has_genre, 36212 25651, has_genre, 30463 25651, has_genre, 36212 25651, release_year, 35935 26815, has_genre, 30463 26815, release_year, 35935 38543, has_genre, 30463 38543, release_year, 35935 28256, has_genre, 30463 28256, has_genre, 36212 27539, has_genre, 30463 27539, release_year, 35935 29241, has_genre, 30463 29241, release_year, 35935 5287, has_genre, 30463 5287, has_genre, 36212 21415, has_genre, 30463 21415, has_genre, 36212 10990, has_genre, 30463 10990, has_genre, 36212 10990, release_year, 35935 3829, has_genre, 30463 3829, has_genre, 36212 3829, release_year, 35935 15629, has_genre, 30463 15629, release_year, 35935 21886, release_year, 35935 22069, has_genre, 30463 22069, has_tags, 30463 22069, release_year, 35935 27919, has_genre, 30463 27919, release_year, 35935 16371, has_genre, 30463 16371, has_tags, 30463 16371, release_year, 35935 17197, has_genre, 30463 17197, has_genre, 36212 17197, release_year, 35935 15909, has_genre, 30463 15909, has_genre, 36212 33001, has_genre, 30463 33001, release_year, 35935 2204, has_genre, 30463 2204, release_year, 35935 31245, has_genre, 30463 31245, has_genre, 36212 32010, has_genre, 30463 32010, release_year, 35935 12137, has_genre, 30463 12137, release_year, 35935 28832, has_genre, 30463 28832, release_year, 35935 16155, has_genre, 30463 16155, release_year, 35935 9812, has_genre, 30463 9812, release_year, 35935 4270, has_genre, 30463 4270, release_year, 35935 36083, has_genre, 30463 36083, release_year, 35935 20803, has_genre, 30463 20803, release_year, 35935 22064, has_genre, 30463 22064, has_tags, 30463 22064, release_year, 35935 4887, has_genre, 30463 4887, release_year, 35935 35262, has_genre, 30463 35262, release_year, 35935 35794, has_genre, 30463 35794, release_year, 35935 1493, has_genre, 30463 1493, release_year, 35935 2721, has_genre, 30463 2721, release_year, 35935 4582, has_genre, 30463 4582, release_year, 35935 39121, has_genre, 30463 39121, has_genre, 36212 37178, has_genre, 30463 37178, release_year, 35935 25824, has_genre, 30463 25824, has_genre, 36212 27117, has_genre, 30463 27117, release_year, 35935 9976, has_genre, 30463 9976, release_year, 35935 7136, has_genre, 30463 7136, has_genre, 36212 3688, has_genre, 30463 3688, release_year, 35935 34602, has_genre, 30463 34602, has_genre, 36212 34602, has_tags, 30463 34602, release_year, 35935 21890, has_genre, 30463 21890, release_year, 35935 25769, has_genre, 30463 25769, has_genre, 36212 25769, release_year, 35935 25243, has_genre, 30463 25243, has_genre, 36212 12987, has_genre, 30463 12987, release_year, 35935 15252, has_genre, 30463 15252, has_genre, 36212 19244, has_genre, 30463 19244, release_year, 35935 6603, has_genre, 30463 6603, release_year, 35935 26261, has_genre, 30463 26261, release_year, 35935 15043, has_genre, 30463 15043, release_year, 35935 25151, has_genre, 30463 25151, release_year, 35935 24961, has_genre, 30463 24961, release_year, 35935 35843, has_genre, 30463 35843, has_genre, 36212 35843, release_year, 35935 5170, has_genre, 30463 5170, release_year, 35935 15100, has_genre, 30463 15100, release_year, 35935 9276, has_genre, 30463 9276, release_year, 35935 26790, has_genre, 30463 26790, has_genre, 36212 26790, release_year, 35935 36316, has_genre, 30463 36316, release_year, 35935 3961, has_genre, 30463 3961, has_genre, 36212 2316, has_genre, 30463 2316, has_genre, 36212 2316, release_year, 35935 304, has_genre, 30463 304, release_year, 35935 11696, has_genre, 30463 11696, has_genre, 36212 11696, release_year, 35935 3324, has_genre, 30463 3324, has_genre, 36212 3324, release_year, 35935 914, has_genre, 30463 914, release_year, 35935 26531, has_genre, 30463 26531, release_year, 35935 24302, has_genre, 30463 24302, has_tags, 30463 24302, release_year, 35935 13534, has_genre, 30463 13534, has_genre, 36212 13534, release_year, 35935 2147, has_genre, 30463 2147, has_genre, 36212 2147, has_tags, 36212 2147, release_year, 35935 6908, has_genre, 30463 6908, release_year, 35935 295, has_genre, 30463 295, release_year, 35935 1192, has_genre, 30463 1192, release_year, 35935 4335, has_genre, 30463 4335, has_genre, 36212 39078, directed_by, 32612 39078, has_genre, 36212 39078, written_by, 32612 31401, has_genre, 30463 31401, has_genre, 36212 31401, release_year, 35935 30746, has_genre, 30463 30746, has_genre, 36212 32975, has_genre, 30463 32975, has_genre, 36212 7052, has_genre, 30463 7052, has_tags, 30463 7052, release_year, 35935 34172, has_genre, 30463 34172, has_tags, 30463 34172, release_year, 35935 34916, has_genre, 30463 34916, has_genre, 36212 34916, has_tags, 36212 22625, has_genre, 30463 22625, has_genre, 36212 10720, has_genre, 30463 10720, release_year, 35935 26275, has_genre, 30463 26275, has_genre, 36212 9612, has_genre, 30463 9612, release_year, 35935 13214, has_genre, 30463 13214, release_year, 35935 16991, has_genre, 30463 16991, release_year, 35935 21576, has_genre, 30463 21576, release_year, 35935 37568, has_genre, 30463 37568, has_tags, 30463 37568, release_year, 35935 39802, has_genre, 30463 39802, release_year, 35935 Question: In what context are ANNA ODELL, HOME ROOM, and KAL HO NAA HO connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANNA ODELL", "HOME ROOM", "KAL HO NAA HO" ], "valid_edges": [ [ "24 HOUR PARTY PEOPLE", "has_genre", "COMEDY" ], [ "24 HOUR PARTY PEOPLE", "has_genre", "DRAMA" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "40 DAYS AND 40 NIGHTS", "has_genre", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "has_tags", "COMEDY" ], [ "40 DAYS AND 40 NIGHTS", "release_year", "2002" ], [ "8 WOMEN", "has_genre", "COMEDY" ], [ "8 WOMEN", "release_year", "2002" ], [ "9 DEAD GAY GUYS", "has_genre", "COMEDY" ], [ "9 DEAD GAY GUYS", "release_year", "2002" ], [ "ABOUT A BOY", "has_genre", "COMEDY" ], [ "ABOUT A BOY", "has_genre", "DRAMA" ], [ "ABOUT A BOY", "has_tags", "COMEDY" ], [ "ABOUT A BOY", "has_tags", "DRAMA" ], [ "ABOUT A BOY", "release_year", "2002" ], [ "ABOUT SCHMIDT", "has_genre", "COMEDY" ], [ "ABOUT SCHMIDT", "has_genre", "DRAMA" ], [ "ABOUT SCHMIDT", "has_tags", "COMEDY" ], [ "ABOUT SCHMIDT", "has_tags", "DRAMA" ], [ "ABOUT SCHMIDT", "release_year", "2002" ], [ "ADMISSION", "has_genre", "COMEDY" ], [ "ADMISSION", "has_genre", "DRAMA" ], [ "ADMISSION", "has_tags", "COMEDY" ], [ "AFTERNOON DELIGHT", "has_genre", "COMEDY" ], [ "AFTERNOON DELIGHT", "has_genre", "DRAMA" ], [ "ALI G INDAHOUSE", "has_genre", "COMEDY" ], [ "ALI G INDAHOUSE", "release_year", "2002" ], [ "ALL ABOUT THE BENJAMINS", "has_genre", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "has_tags", "COMEDY" ], [ "ALL ABOUT THE BENJAMINS", "release_year", "2002" ], [ "ALL IS BRIGHT", "has_genre", "COMEDY" ], [ "ALL IS BRIGHT", "has_genre", "DRAMA" ], [ "ANALYZE THAT", "has_genre", "COMEDY" ], [ "ANALYZE THAT", "has_tags", "COMEDY" ], [ "ANALYZE THAT", "release_year", "2002" ], [ "AS COOL AS I AM", "has_genre", "COMEDY" ], [ "AS COOL AS I AM", "has_genre", "DRAMA" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_genre", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "has_tags", "COMEDY" ], [ "AUSTIN POWERS IN GOLDMEMBER", "release_year", "2002" ], [ "AVENGING ANGELO", "has_genre", "COMEDY" ], [ "AVENGING ANGELO", "release_year", "2002" ], [ "BAD COMPANY", "has_genre", "COMEDY" ], [ "BAD COMPANY", "release_year", "2002" ], [ "BARBERSHOP", "has_genre", "COMEDY" ], [ "BARBERSHOP", "release_year", "2002" ], [ "BEND IT LIKE BECKHAM", "has_genre", "COMEDY" ], [ "BEND IT LIKE BECKHAM", "has_genre", "DRAMA" ], [ "BEND IT LIKE BECKHAM", "release_year", "2002" ], [ "BIG FAT LIAR", "has_genre", "COMEDY" ], [ "BIG FAT LIAR", "release_year", "2002" ], [ "BIG TROUBLE", "has_genre", "COMEDY" ], [ "BIG TROUBLE", "release_year", "2002" ], [ "BOAT TRIP", "has_genre", "COMEDY" ], [ "BOAT TRIP", "release_year", "2002" ], [ "BUBBA HO-TEP", "has_genre", "COMEDY" ], [ "BUBBA HO-TEP", "has_tags", "COMEDY" ], [ "BUBBA HO-TEP", "release_year", "2002" ], [ "BUYING THE COW", "has_genre", "COMEDY" ], [ "BUYING THE COW", "release_year", "2002" ], [ "CABIN FEVER", "has_genre", "COMEDY" ], [ "CABIN FEVER", "release_year", "2002" ], [ "CARNAGE", "has_genre", "COMEDY" ], [ "CARNAGE", "has_genre", "DRAMA" ], [ "CARNAGE", "release_year", "2002" ], [ "CHERISH", "has_genre", "COMEDY" ], [ "CHERISH", "has_genre", "DRAMA" ], [ "CHERISH", "release_year", "2002" ], [ "CHICAGO", "has_genre", "COMEDY" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CHICAGO", "release_year", "2002" ], [ "CHINESE ODYSSEY 2002", "has_genre", "COMEDY" ], [ "CHINESE ODYSSEY 2002", "release_year", "2002" ], [ "CLOSER TO THE MOON", "has_genre", "COMEDY" ], [ "CLOSER TO THE MOON", "has_genre", "DRAMA" ], [ "CLOSER TO THE MOON", "has_tags", "COMEDY" ], [ "CRACKERJACK", "has_genre", "COMEDY" ], [ "CRACKERJACK", "release_year", "2002" ], [ "CROSSROADS", "has_genre", "COMEDY" ], [ "CROSSROADS", "has_genre", "DRAMA" ], [ "CROSSROADS", "release_year", "2002" ], [ "DAY OF THE WACKO", "has_genre", "COMEDY" ], [ "DAY OF THE WACKO", "has_genre", "DRAMA" ], [ "DAY OF THE WACKO", "release_year", "2002" ], [ "DEATH TO SMOOCHY", "has_genre", "COMEDY" ], [ "DEATH TO SMOOCHY", "release_year", "2002" ], [ "DELIVERY MAN", "has_genre", "COMEDY" ], [ "DELIVERY MAN", "has_genre", "DRAMA" ], [ "DELIVERY MAN", "has_tags", "DRAMA" ], [ "DIRTY DEEDS", "has_genre", "COMEDY" ], [ "DIRTY DEEDS", "has_tags", "COMEDY" ], [ "DIRTY DEEDS", "release_year", "2002" ], [ "DOM HEMINGWAY", "has_genre", "COMEDY" ], [ "DOM HEMINGWAY", "has_genre", "DRAMA" ], [ "DON JON", "has_genre", "COMEDY" ], [ "DON JON", "has_genre", "DRAMA" ], [ "DUMMY", "has_genre", "COMEDY" ], [ "DUMMY", "has_genre", "DRAMA" ], [ "DUMMY", "release_year", "2002" ], [ "EIGHT CRAZY NIGHTS", "has_genre", "COMEDY" ], [ "EIGHT CRAZY NIGHTS", "release_year", "2002" ], [ "EIGHT LEGGED FREAKS", "has_genre", "COMEDY" ], [ "EIGHT LEGGED FREAKS", "release_year", "2002" ], [ "FILTH", "has_genre", "COMEDY" ], [ "FILTH", "has_genre", "DRAMA" ], [ "FRANK MCKLUSKY, C.I.", "has_genre", "COMEDY" ], [ "FRANK MCKLUSKY, C.I.", "release_year", "2002" ], [ "FRIDAY AFTER NEXT", "has_genre", "COMEDY" ], [ "FRIDAY AFTER NEXT", "release_year", "2002" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "GREGORY GO BOOM", "has_genre", "COMEDY" ], [ "GREGORY GO BOOM", "has_genre", "DRAMA" ], [ "HEARTLANDS", "has_genre", "COMEDY" ], [ "HEARTLANDS", "has_genre", "DRAMA" ], [ "HEARTLANDS", "release_year", "2002" ], [ "HERO", "has_genre", "COMEDY" ], [ "HERO", "has_genre", "DRAMA" ], [ "HERO", "release_year", "2002" ], [ "HOME ALONE 4", "has_genre", "COMEDY" ], [ "HOME ALONE 4", "release_year", "2002" ], [ "HOME ROOM", "release_year", "2002" ], [ "I SPY", "has_genre", "COMEDY" ], [ "I SPY", "has_tags", "COMEDY" ], [ "I SPY", "release_year", "2002" ], [ "I'M WITH LUCY", "has_genre", "COMEDY" ], [ "I'M WITH LUCY", "release_year", "2002" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "release_year", "2002" ], [ "IGBY GOES DOWN", "has_genre", "COMEDY" ], [ "IGBY GOES DOWN", "has_genre", "DRAMA" ], [ "IGBY GOES DOWN", "release_year", "2002" ], [ "INSTRUCTIONS NOT INCLUDED", "has_genre", "COMEDY" ], [ "INSTRUCTIONS NOT INCLUDED", "has_genre", "DRAMA" ], [ "JUST A KISS", "has_genre", "COMEDY" ], [ "JUST A KISS", "release_year", "2002" ], [ "JUWANNA MANN", "has_genre", "COMEDY" ], [ "JUWANNA MANN", "release_year", "2002" ], [ "KAL HO NAA HO", "has_genre", "COMEDY" ], [ "KAL HO NAA HO", "has_genre", "DRAMA" ], [ "KISS THE BRIDE", "has_genre", "COMEDY" ], [ "KISS THE BRIDE", "release_year", "2002" ], [ "LIFE OR SOMETHING LIKE IT", "has_genre", "COMEDY" ], [ "LIFE OR SOMETHING LIKE IT", "release_year", "2002" ], [ "LIFE WITHOUT DICK", "has_genre", "COMEDY" ], [ "LIFE WITHOUT DICK", "release_year", "2002" ], [ "LOVE LIZA", "has_genre", "COMEDY" ], [ "LOVE LIZA", "release_year", "2002" ], [ "MAID IN MANHATTAN", "has_genre", "COMEDY" ], [ "MAID IN MANHATTAN", "release_year", "2002" ], [ "MEN WITH BROOMS", "has_genre", "COMEDY" ], [ "MEN WITH BROOMS", "release_year", "2002" ], [ "MIRANDA", "has_genre", "COMEDY" ], [ "MIRANDA", "release_year", "2002" ], [ "MR. DEEDS", "has_genre", "COMEDY" ], [ "MR. DEEDS", "release_year", "2002" ], [ "MY BIG FAT GREEK WEDDING", "has_genre", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "has_tags", "COMEDY" ], [ "MY BIG FAT GREEK WEDDING", "release_year", "2002" ], [ "MY LEFT EYE SEES GHOSTS", "has_genre", "COMEDY" ], [ "MY LEFT EYE SEES GHOSTS", "release_year", "2002" ], [ "MY MOTHER LIKES WOMEN", "has_genre", "COMEDY" ], [ "MY MOTHER LIKES WOMEN", "release_year", "2002" ], [ "NOVO", "has_genre", "COMEDY" ], [ "NOVO", "release_year", "2002" ], [ "NOW YOU KNOW", "has_genre", "COMEDY" ], [ "NOW YOU KNOW", "release_year", "2002" ], [ "OCCIDENT", "has_genre", "COMEDY" ], [ "OCCIDENT", "release_year", "2002" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "has_genre", "COMEDY" ], [ "ONCE UPON A TIME IN THE MIDLANDS", "release_year", "2002" ], [ "ONE CHANCE", "has_genre", "COMEDY" ], [ "ONE CHANCE", "has_genre", "DRAMA" ], [ "ORANGE COUNTY", "has_genre", "COMEDY" ], [ "ORANGE COUNTY", "release_year", "2002" ], [ "PARADISE", "has_genre", "COMEDY" ], [ "PARADISE", "has_genre", "DRAMA" ], [ "PASSIONADA", "has_genre", "COMEDY" ], [ "PASSIONADA", "release_year", "2002" ], [ "PIPE DREAM", "has_genre", "COMEDY" ], [ "PIPE DREAM", "release_year", "2002" ], [ "PRINCE AVALANCHE", "has_genre", "COMEDY" ], [ "PRINCE AVALANCHE", "has_genre", "DRAMA" ], [ "PUMPKIN", "has_genre", "COMEDY" ], [ "PUMPKIN", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "has_genre", "DRAMA" ], [ "PUNCH-DRUNK LOVE", "has_tags", "COMEDY" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "R.S.V.P.", "has_genre", "COMEDY" ], [ "R.S.V.P.", "release_year", "2002" ], [ "ROGER DODGER", "has_genre", "COMEDY" ], [ "ROGER DODGER", "has_genre", "DRAMA" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SAVING MR. BANKS", "has_genre", "COMEDY" ], [ "SAVING MR. BANKS", "has_genre", "DRAMA" ], [ "SCOOBY-DOO", "has_genre", "COMEDY" ], [ "SCOOBY-DOO", "release_year", "2002" ], [ "SCREWED IN TALLINN", "has_genre", "COMEDY" ], [ "SCREWED IN TALLINN", "has_genre", "DRAMA" ], [ "SERVING SARA", "has_genre", "COMEDY" ], [ "SERVING SARA", "release_year", "2002" ], [ "SEX IS COMEDY", "has_genre", "COMEDY" ], [ "SEX IS COMEDY", "release_year", "2002" ], [ "SHOWTIME", "has_genre", "COMEDY" ], [ "SHOWTIME", "release_year", "2002" ], [ "SLACKERS", "has_genre", "COMEDY" ], [ "SLACKERS", "release_year", "2002" ], [ "SNOW DOGS", "has_genre", "COMEDY" ], [ "SNOW DOGS", "release_year", "2002" ], [ "SORORITY BOYS", "has_genre", "COMEDY" ], [ "SORORITY BOYS", "release_year", "2002" ], [ "SPUN", "has_genre", "COMEDY" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "release_year", "2002" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "release_year", "2002" ], [ "SUPER SUCKER", "has_genre", "COMEDY" ], [ "SUPER SUCKER", "release_year", "2002" ], [ "SWEET HOME ALABAMA", "has_genre", "COMEDY" ], [ "SWEET HOME ALABAMA", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "COMEDY" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "THE ADVENTURES OF PLUTO NASH", "has_genre", "COMEDY" ], [ "THE ADVENTURES OF PLUTO NASH", "release_year", "2002" ], [ "THE AMAZING CATFISH", "has_genre", "COMEDY" ], [ "THE AMAZING CATFISH", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "COMEDY" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BANGER SISTERS", "has_genre", "COMEDY" ], [ "THE BANGER SISTERS", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "COMEDY" ], [ "THE CUCKOO", "has_genre", "DRAMA" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "COMEDY" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "DRAMA" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE GOOD GIRL", "has_genre", "COMEDY" ], [ "THE GOOD GIRL", "release_year", "2002" ], [ "THE GURU", "has_genre", "COMEDY" ], [ "THE GURU", "release_year", "2002" ], [ "THE HOT CHICK", "has_genre", "COMEDY" ], [ "THE HOT CHICK", "has_tags", "COMEDY" ], [ "THE HOT CHICK", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "COMEDY" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "DRAMA" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE MAN WITHOUT A PAST", "has_genre", "COMEDY" ], [ "THE MAN WITHOUT A PAST", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE MASTER OF DISGUISE", "has_genre", "COMEDY" ], [ "THE MASTER OF DISGUISE", "release_year", "2002" ], [ "THE NEW GUY", "has_genre", "COMEDY" ], [ "THE NEW GUY", "release_year", "2002" ], [ "THE ONE AND ONLY", "has_genre", "COMEDY" ], [ "THE ONE AND ONLY", "release_year", "2002" ], [ "THE PRETTY ONE", "has_genre", "COMEDY" ], [ "THE PRETTY ONE", "has_genre", "DRAMA" ], [ "THE REUNION", "directed_by", "ANNA ODELL" ], [ "THE REUNION", "has_genre", "DRAMA" ], [ "THE REUNION", "written_by", "ANNA ODELL" ], [ "THE RULES OF ATTRACTION", "has_genre", "COMEDY" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "COMEDY" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SPECTACULAR NOW", "has_genre", "COMEDY" ], [ "THE SPECTACULAR NOW", "has_genre", "DRAMA" ], [ "THE SWEETEST THING", "has_genre", "COMEDY" ], [ "THE SWEETEST THING", "has_tags", "COMEDY" ], [ "THE SWEETEST THING", "release_year", "2002" ], [ "THE TUXEDO", "has_genre", "COMEDY" ], [ "THE TUXEDO", "has_tags", "COMEDY" ], [ "THE TUXEDO", "release_year", "2002" ], [ "THE WAY WAY BACK", "has_genre", "COMEDY" ], [ "THE WAY WAY BACK", "has_genre", "DRAMA" ], [ "THE WAY WAY BACK", "has_tags", "DRAMA" ], [ "TOGETHER", "has_genre", "COMEDY" ], [ "TOGETHER", "has_genre", "DRAMA" ], [ "TRIGGERMEN", "has_genre", "COMEDY" ], [ "TRIGGERMEN", "release_year", "2002" ], [ "TRUST ME", "has_genre", "COMEDY" ], [ "TRUST ME", "has_genre", "DRAMA" ], [ "TWO WEEKS NOTICE", "has_genre", "COMEDY" ], [ "TWO WEEKS NOTICE", "release_year", "2002" ], [ "UNCONDITIONAL LOVE", "has_genre", "COMEDY" ], [ "UNCONDITIONAL LOVE", "release_year", "2002" ], [ "UNDERCOVER BROTHER", "has_genre", "COMEDY" ], [ "UNDERCOVER BROTHER", "release_year", "2002" ], [ "WAKING UP IN RENO", "has_genre", "COMEDY" ], [ "WAKING UP IN RENO", "release_year", "2002" ], [ "WELCOME TO COLLINWOOD", "has_genre", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "has_tags", "COMEDY" ], [ "WELCOME TO COLLINWOOD", "release_year", "2002" ], [ "WHEN IN ROME", "has_genre", "COMEDY" ], [ "WHEN IN ROME", "release_year", "2002" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 10702, 1991 10830, JÖRG BUTTGEREIT 14714, K2 38235, NEKROMANTIK 2 24916, PATRICK MEYERS 36578, THE PEOPLE UNDER THE STAIRS src, edge_attr, dst 14714, release_year, 10702 14714, written_by, 24916 38235, directed_by, 10830 38235, release_year, 10702 38235, starred_actors, 10830 38235, written_by, 10830 36578, release_year, 10702 Question: For what reason are JÖRG BUTTGEREIT, PATRICK MEYERS, and THE PEOPLE UNDER THE STAIRS associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JÖRG BUTTGEREIT", "PATRICK MEYERS", "THE PEOPLE UNDER THE STAIRS" ], "valid_edges": [ [ "K2", "release_year", "1991" ], [ "K2", "written_by", "PATRICK MEYERS" ], [ "NEKROMANTIK 2", "directed_by", "JÖRG BUTTGEREIT" ], [ "NEKROMANTIK 2", "release_year", "1991" ], [ "NEKROMANTIK 2", "starred_actors", "JÖRG BUTTGEREIT" ], [ "NEKROMANTIK 2", "written_by", "JÖRG BUTTGEREIT" ], [ "THE PEOPLE UNDER THE STAIRS", "release_year", "1991" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37168, 15TH CENTURY 6925, 1966 39094, ANDREI RUBLEV 30330, CLEAVANT DERRICKS 38118, MOSCOW ON THE HUDSON 30659, PATRICK WYMARK 16206, RUSSIAN 37079, THE PSYCHOPATH src, edge_attr, dst 39094, has_tags, 37168 39094, has_tags, 16206 39094, in_language, 16206 39094, release_year, 6925 38118, in_language, 16206 38118, starred_actors, 30330 37079, release_year, 6925 37079, starred_actors, 30659 Question: For what reason are 15TH CENTURY, CLEAVANT DERRICKS, and PATRICK WYMARK associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "15TH CENTURY", "CLEAVANT DERRICKS", "PATRICK WYMARK" ], "valid_edges": [ [ "ANDREI RUBLEV", "has_tags", "15TH CENTURY" ], [ "ANDREI RUBLEV", "has_tags", "RUSSIAN" ], [ "ANDREI RUBLEV", "in_language", "RUSSIAN" ], [ "ANDREI RUBLEV", "release_year", "1966" ], [ "MOSCOW ON THE HUDSON", "in_language", "RUSSIAN" ], [ "MOSCOW ON THE HUDSON", "starred_actors", "CLEAVANT DERRICKS" ], [ "THE PSYCHOPATH", "release_year", "1966" ], [ "THE PSYCHOPATH", "starred_actors", "PATRICK WYMARK" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 35747, 1408 6216, 1952 35063, 1976 1421, 2013 33779, A HAUNTED HOUSE 36766, A HAUNTING AT SILVER FALLS 18644, A RESURRECTION 7327, ALL CHEERLEADERS DIE 36810, AN AMERICAN HAUNTING 9782, BANSHEE CHAPTER 34701, BENEATH 24456, BLOOD GLACIER 8065, BRIAN DE PALMA 5851, BURNT OFFERINGS 24454, CARRIE 32401, CAST A DEADLY SPELL 28328, CAT'S EYE 9241, CHASTITY BITES 5741, CHILDREN OF THE CORN 35713, CHLOË GRACE MORETZ 24443, CHRISTINE 40079, CONTRACTED 22349, CRAWLSPACE 30260, CREEPSHOW 19984, CREEPSHOW 2 25956, CUJO 4964, CURSE OF CHUCKY 33372, DARK SKIES 31257, DARK TOUCH 3093, DEAD IN TOMBSTONE 25528, DEVIL'S PASS 39647, DON PORTER 30262, DRACULA 35978, DREAMCATCHER 35855, ESCAPE FROM TOMORROW 23129, EVIL DEAD 10355, FRANKENSTEIN'S ARMY 23822, GOD TOLD ME TO 33104, HAUNT 14366, HAUNTER 798, HELL BABY 5870, HORROR 10147, HOUSE 32245, I SPIT ON YOUR GRAVE 2 39172, IN FEAR 39767, JUG FACE 14429, JULIANNE MOORE 2687, LAURENCE OLIVIER 29987, LET ME IN 24015, LORD OF TEARS 29898, MAMA 3129, MAXIMUM OVERDRIVE 33165, MISCHIEF NIGHT 7625, MISERY 21188, MR. JONES 13716, NOTHING LEFT TO FEAR 13530, NURSE 3D 848, OCULUS 28917, PET SEMATARY 19296, PROXY 3322, QUICKSILVER HIGHWAY 32894, RIDING THE BULLET 23082, RIGOR MORTIS 19611, SHE-WOLF OF LONDON 30671, SILVER BULLET 29168, SISSY SPACEK 19479, SISTERS 16247, SLEEPWALKERS 16551, SQUIRM 23284, STEPHEN KING 29841, THE BIRDS 16442, THE COLLECTOR 21288, THE COLONY 7853, THE CONJURING 25979, THE DARK HALF 26351, THE DEAD ZONE 28279, THE HUMAN RACE 17331, THE LAST DAYS ON MARS 12833, THE LAST EXORCISM PART II 10379, THE LAWNMOWER MAN 26566, THE MANGLER 33919, THE MIST 21784, THE MONKEY'S PAW 40021, THE NIGHT FLIER 17910, THE OMEN 6427, THE PURGE 13106, THE SACRAMENT 19018, THE SHINING 30502, THE WHITE REINDEER 10423, THE WITCH WHO CAME FROM THE SEA 7808, THINNER 1657, TIPPI HEDREN 20875, TO THE DEVIL A DAUGHTER 27476, TORMENT 17409, TRICK OR TREAT 34305, V/H/S/2 18049, WE ARE WHAT WE ARE 5553, WELCOME TO THE JUNGLE 26506, WER 24046, WEREWOLF WOMAN 22737, WICKED LITTLE THINGS 10486, WILLIAM KATT 29732, WILLIAM WYLER 33045, WOLF CREEK 2 20105, WORLD WAR Z src, edge_attr, dst 35747, has_genre, 5870 35747, has_tags, 5870 35747, has_tags, 23284 35747, written_by, 23284 33779, has_genre, 5870 33779, release_year, 1421 36766, has_genre, 5870 36766, release_year, 1421 18644, has_genre, 5870 18644, release_year, 1421 7327, has_genre, 5870 7327, release_year, 1421 36810, has_genre, 5870 36810, starred_actors, 29168 9782, has_genre, 5870 9782, release_year, 1421 34701, has_genre, 5870 34701, release_year, 1421 24456, has_genre, 5870 24456, release_year, 1421 5851, has_genre, 5870 5851, release_year, 35063 24454, directed_by, 8065 24454, directed_by, 29732 24454, has_genre, 5870 24454, has_tags, 8065 24454, has_tags, 5870 24454, has_tags, 29168 24454, has_tags, 23284 24454, has_tags, 29732 24454, release_year, 6216 24454, release_year, 35063 24454, release_year, 1421 24454, starred_actors, 35713 24454, starred_actors, 14429 24454, starred_actors, 2687 24454, starred_actors, 29168 24454, starred_actors, 10486 24454, written_by, 23284 32401, has_genre, 5870 32401, starred_actors, 14429 28328, has_genre, 5870 28328, has_tags, 23284 28328, written_by, 23284 9241, has_genre, 5870 9241, release_year, 1421 5741, has_genre, 5870 5741, has_tags, 23284 5741, written_by, 23284 24443, has_genre, 5870 24443, has_tags, 23284 24443, written_by, 23284 40079, has_genre, 5870 40079, release_year, 1421 22349, has_genre, 5870 22349, release_year, 1421 30260, has_genre, 5870 30260, written_by, 23284 19984, has_genre, 5870 19984, has_tags, 23284 19984, written_by, 23284 25956, has_genre, 5870 25956, has_tags, 23284 25956, written_by, 23284 4964, has_genre, 5870 4964, has_tags, 5870 4964, release_year, 1421 33372, has_genre, 5870 33372, release_year, 1421 31257, has_genre, 5870 31257, release_year, 1421 3093, has_genre, 5870 3093, release_year, 1421 25528, has_genre, 5870 25528, release_year, 1421 30262, has_genre, 5870 30262, has_tags, 5870 30262, starred_actors, 2687 35978, has_genre, 5870 35978, has_tags, 23284 35978, written_by, 23284 35855, has_genre, 5870 35855, release_year, 1421 23129, has_genre, 5870 23129, has_tags, 5870 23129, release_year, 1421 10355, has_genre, 5870 10355, release_year, 1421 23822, has_genre, 5870 23822, release_year, 35063 33104, has_genre, 5870 33104, release_year, 1421 14366, has_genre, 5870 14366, release_year, 1421 798, has_genre, 5870 798, has_tags, 5870 798, release_year, 1421 10147, has_genre, 5870 10147, starred_actors, 10486 32245, has_genre, 5870 32245, release_year, 1421 39172, has_genre, 5870 39172, release_year, 1421 39767, has_genre, 5870 39767, release_year, 1421 29987, has_genre, 5870 29987, has_tags, 5870 29987, starred_actors, 35713 24015, has_genre, 5870 24015, release_year, 1421 29898, has_genre, 5870 29898, has_tags, 5870 29898, release_year, 1421 3129, directed_by, 23284 3129, has_genre, 5870 3129, has_tags, 23284 3129, written_by, 23284 33165, has_genre, 5870 33165, release_year, 1421 7625, has_tags, 5870 7625, has_tags, 23284 7625, written_by, 23284 21188, has_genre, 5870 21188, release_year, 1421 13716, has_genre, 5870 13716, release_year, 1421 13530, has_genre, 5870 13530, release_year, 1421 848, has_genre, 5870 848, release_year, 1421 28917, has_genre, 5870 28917, has_tags, 5870 28917, has_tags, 23284 28917, written_by, 23284 19296, has_genre, 5870 19296, release_year, 1421 3322, has_genre, 5870 3322, written_by, 23284 32894, has_genre, 5870 32894, has_tags, 23284 32894, written_by, 23284 23082, has_genre, 5870 23082, release_year, 1421 19611, has_genre, 5870 19611, starred_actors, 39647 30671, has_genre, 5870 30671, has_tags, 23284 30671, written_by, 23284 19479, directed_by, 8065 19479, has_genre, 5870 19479, has_tags, 8065 19479, written_by, 8065 16247, has_genre, 5870 16247, has_tags, 5870 16247, has_tags, 23284 16247, written_by, 23284 16551, has_genre, 5870 16551, release_year, 35063 29841, has_genre, 5870 29841, has_tags, 5870 29841, has_tags, 1657 29841, starred_actors, 1657 16442, directed_by, 29732 16442, has_genre, 5870 16442, has_tags, 29732 21288, has_genre, 5870 21288, release_year, 1421 7853, has_genre, 5870 7853, has_tags, 5870 7853, release_year, 1421 25979, has_genre, 5870 25979, has_tags, 23284 25979, written_by, 23284 26351, has_genre, 5870 26351, has_tags, 23284 26351, written_by, 23284 28279, has_genre, 5870 28279, release_year, 1421 17331, has_genre, 5870 17331, release_year, 1421 12833, has_genre, 5870 12833, release_year, 1421 10379, has_genre, 5870 10379, written_by, 23284 26566, has_genre, 5870 26566, has_tags, 5870 26566, has_tags, 23284 26566, written_by, 23284 33919, has_genre, 5870 33919, has_tags, 23284 33919, written_by, 23284 21784, has_genre, 5870 21784, release_year, 1421 40021, has_genre, 5870 40021, written_by, 23284 17910, has_genre, 5870 17910, has_tags, 5870 17910, release_year, 35063 6427, has_genre, 5870 6427, release_year, 1421 13106, has_genre, 5870 13106, has_tags, 5870 13106, release_year, 1421 19018, has_genre, 5870 19018, has_tags, 5870 19018, has_tags, 23284 19018, written_by, 23284 30502, has_genre, 5870 30502, release_year, 6216 10423, has_genre, 5870 10423, release_year, 35063 7808, has_genre, 5870 7808, has_tags, 23284 7808, written_by, 23284 20875, has_genre, 5870 20875, release_year, 35063 27476, has_genre, 5870 27476, release_year, 1421 17409, has_genre, 5870 17409, release_year, 6216 34305, has_genre, 5870 34305, has_tags, 5870 34305, release_year, 1421 18049, has_genre, 5870 18049, has_tags, 5870 18049, release_year, 1421 5553, has_genre, 5870 5553, release_year, 1421 26506, has_genre, 5870 26506, release_year, 1421 24046, has_genre, 5870 24046, release_year, 35063 22737, has_genre, 5870 22737, starred_actors, 35713 33045, has_genre, 5870 33045, release_year, 1421 20105, has_genre, 5870 20105, release_year, 1421 Question: In what context are CARRIE, DON PORTER, and TIPPI HEDREN connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CARRIE", "DON PORTER", "TIPPI HEDREN" ], "valid_edges": [ [ "1408", "has_genre", "HORROR" ], [ "1408", "has_tags", "HORROR" ], [ "1408", "has_tags", "STEPHEN KING" ], [ "1408", "written_by", "STEPHEN KING" ], [ "A HAUNTED HOUSE", "has_genre", "HORROR" ], [ "A HAUNTED HOUSE", "release_year", "2013" ], [ "A HAUNTING AT SILVER FALLS", "has_genre", "HORROR" ], [ "A HAUNTING AT SILVER FALLS", "release_year", "2013" ], [ "A RESURRECTION", "has_genre", "HORROR" ], [ "A RESURRECTION", "release_year", "2013" ], [ "ALL CHEERLEADERS DIE", "has_genre", "HORROR" ], [ "ALL CHEERLEADERS DIE", "release_year", "2013" ], [ "AN AMERICAN HAUNTING", "has_genre", "HORROR" ], [ "AN AMERICAN HAUNTING", "starred_actors", "SISSY SPACEK" ], [ "BANSHEE CHAPTER", "has_genre", "HORROR" ], [ "BANSHEE CHAPTER", "release_year", "2013" ], [ "BENEATH", "has_genre", "HORROR" ], [ "BENEATH", "release_year", "2013" ], [ "BLOOD GLACIER", "has_genre", "HORROR" ], [ "BLOOD GLACIER", "release_year", "2013" ], [ "BURNT OFFERINGS", "has_genre", "HORROR" ], [ "BURNT OFFERINGS", "release_year", "1976" ], [ "CARRIE", "directed_by", "BRIAN DE PALMA" ], [ "CARRIE", "directed_by", "WILLIAM WYLER" ], [ "CARRIE", "has_genre", "HORROR" ], [ "CARRIE", "has_tags", "BRIAN DE PALMA" ], [ "CARRIE", "has_tags", "HORROR" ], [ "CARRIE", "has_tags", "SISSY SPACEK" ], [ "CARRIE", "has_tags", "STEPHEN KING" ], [ "CARRIE", "has_tags", "WILLIAM WYLER" ], [ "CARRIE", "release_year", "1952" ], [ "CARRIE", "release_year", "1976" ], [ "CARRIE", "release_year", "2013" ], [ "CARRIE", "starred_actors", "CHLOË GRACE MORETZ" ], [ "CARRIE", "starred_actors", "JULIANNE MOORE" ], [ "CARRIE", "starred_actors", "LAURENCE OLIVIER" ], [ "CARRIE", "starred_actors", "SISSY SPACEK" ], [ "CARRIE", "starred_actors", "WILLIAM KATT" ], [ "CARRIE", "written_by", "STEPHEN KING" ], [ "CAST A DEADLY SPELL", "has_genre", "HORROR" ], [ "CAST A DEADLY SPELL", "starred_actors", "JULIANNE MOORE" ], [ "CAT'S EYE", "has_genre", "HORROR" ], [ "CAT'S EYE", "has_tags", "STEPHEN KING" ], [ "CAT'S EYE", "written_by", "STEPHEN KING" ], [ "CHASTITY BITES", "has_genre", "HORROR" ], [ "CHASTITY BITES", "release_year", "2013" ], [ "CHILDREN OF THE CORN", "has_genre", "HORROR" ], [ "CHILDREN OF THE CORN", "has_tags", "STEPHEN KING" ], [ "CHILDREN OF THE CORN", "written_by", "STEPHEN KING" ], [ "CHRISTINE", "has_genre", "HORROR" ], [ "CHRISTINE", "has_tags", "STEPHEN KING" ], [ "CHRISTINE", "written_by", "STEPHEN KING" ], [ "CONTRACTED", "has_genre", "HORROR" ], [ "CONTRACTED", "release_year", "2013" ], [ "CRAWLSPACE", "has_genre", "HORROR" ], [ "CRAWLSPACE", "release_year", "2013" ], [ "CREEPSHOW", "has_genre", "HORROR" ], [ "CREEPSHOW", "written_by", "STEPHEN KING" ], [ "CREEPSHOW 2", "has_genre", "HORROR" ], [ "CREEPSHOW 2", "has_tags", "STEPHEN KING" ], [ "CREEPSHOW 2", "written_by", "STEPHEN KING" ], [ "CUJO", "has_genre", "HORROR" ], [ "CUJO", "has_tags", "STEPHEN KING" ], [ "CUJO", "written_by", "STEPHEN KING" ], [ "CURSE OF CHUCKY", "has_genre", "HORROR" ], [ "CURSE OF CHUCKY", "has_tags", "HORROR" ], [ "CURSE OF CHUCKY", "release_year", "2013" ], [ "DARK SKIES", "has_genre", "HORROR" ], [ "DARK SKIES", "release_year", "2013" ], [ "DARK TOUCH", "has_genre", "HORROR" ], [ "DARK TOUCH", "release_year", "2013" ], [ "DEAD IN TOMBSTONE", "has_genre", "HORROR" ], [ "DEAD IN TOMBSTONE", "release_year", "2013" ], [ "DEVIL'S PASS", "has_genre", "HORROR" ], [ "DEVIL'S PASS", "release_year", "2013" ], [ "DRACULA", "has_genre", "HORROR" ], [ "DRACULA", "has_tags", "HORROR" ], [ "DRACULA", "starred_actors", "LAURENCE OLIVIER" ], [ "DREAMCATCHER", "has_genre", "HORROR" ], [ "DREAMCATCHER", "has_tags", "STEPHEN KING" ], [ "DREAMCATCHER", "written_by", "STEPHEN KING" ], [ "ESCAPE FROM TOMORROW", "has_genre", "HORROR" ], [ "ESCAPE FROM TOMORROW", "release_year", "2013" ], [ "EVIL DEAD", "has_genre", "HORROR" ], [ "EVIL DEAD", "has_tags", "HORROR" ], [ "EVIL DEAD", "release_year", "2013" ], [ "FRANKENSTEIN'S ARMY", "has_genre", "HORROR" ], [ "FRANKENSTEIN'S ARMY", "release_year", "2013" ], [ "GOD TOLD ME TO", "has_genre", "HORROR" ], [ "GOD TOLD ME TO", "release_year", "1976" ], [ "HAUNT", "has_genre", "HORROR" ], [ "HAUNT", "release_year", "2013" ], [ "HAUNTER", "has_genre", "HORROR" ], [ "HAUNTER", "release_year", "2013" ], [ "HELL BABY", "has_genre", "HORROR" ], [ "HELL BABY", "has_tags", "HORROR" ], [ "HELL BABY", "release_year", "2013" ], [ "HOUSE", "has_genre", "HORROR" ], [ "HOUSE", "starred_actors", "WILLIAM KATT" ], [ "I SPIT ON YOUR GRAVE 2", "has_genre", "HORROR" ], [ "I SPIT ON YOUR GRAVE 2", "release_year", "2013" ], [ "IN FEAR", "has_genre", "HORROR" ], [ "IN FEAR", "release_year", "2013" ], [ "JUG FACE", "has_genre", "HORROR" ], [ "JUG FACE", "release_year", "2013" ], [ "LET ME IN", "has_genre", "HORROR" ], [ "LET ME IN", "has_tags", "HORROR" ], [ "LET ME IN", "starred_actors", "CHLOË GRACE MORETZ" ], [ "LORD OF TEARS", "has_genre", "HORROR" ], [ "LORD OF TEARS", "release_year", "2013" ], [ "MAMA", "has_genre", "HORROR" ], [ "MAMA", "has_tags", "HORROR" ], [ "MAMA", "release_year", "2013" ], [ "MAXIMUM OVERDRIVE", "directed_by", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "has_genre", "HORROR" ], [ "MAXIMUM OVERDRIVE", "has_tags", "STEPHEN KING" ], [ "MAXIMUM OVERDRIVE", "written_by", "STEPHEN KING" ], [ "MISCHIEF NIGHT", "has_genre", "HORROR" ], [ "MISCHIEF NIGHT", "release_year", "2013" ], [ "MISERY", "has_tags", "HORROR" ], [ "MISERY", "has_tags", "STEPHEN KING" ], [ "MISERY", "written_by", "STEPHEN KING" ], [ "MR. JONES", "has_genre", "HORROR" ], [ "MR. JONES", "release_year", "2013" ], [ "NOTHING LEFT TO FEAR", "has_genre", "HORROR" ], [ "NOTHING LEFT TO FEAR", "release_year", "2013" ], [ "NURSE 3D", "has_genre", "HORROR" ], [ "NURSE 3D", "release_year", "2013" ], [ "OCULUS", "has_genre", "HORROR" ], [ "OCULUS", "release_year", "2013" ], [ "PET SEMATARY", "has_genre", "HORROR" ], [ "PET SEMATARY", "has_tags", "HORROR" ], [ "PET SEMATARY", "has_tags", "STEPHEN KING" ], [ "PET SEMATARY", "written_by", "STEPHEN KING" ], [ "PROXY", "has_genre", "HORROR" ], [ "PROXY", "release_year", "2013" ], [ "QUICKSILVER HIGHWAY", "has_genre", "HORROR" ], [ "QUICKSILVER HIGHWAY", "written_by", "STEPHEN KING" ], [ "RIDING THE BULLET", "has_genre", "HORROR" ], [ "RIDING THE BULLET", "has_tags", "STEPHEN KING" ], [ "RIDING THE BULLET", "written_by", "STEPHEN KING" ], [ "RIGOR MORTIS", "has_genre", "HORROR" ], [ "RIGOR MORTIS", "release_year", "2013" ], [ "SHE-WOLF OF LONDON", "has_genre", "HORROR" ], [ "SHE-WOLF OF LONDON", "starred_actors", "DON PORTER" ], [ "SILVER BULLET", "has_genre", "HORROR" ], [ "SILVER BULLET", "has_tags", "STEPHEN KING" ], [ "SILVER BULLET", "written_by", "STEPHEN KING" ], [ "SISTERS", "directed_by", "BRIAN DE PALMA" ], [ "SISTERS", "has_genre", "HORROR" ], [ "SISTERS", "has_tags", "BRIAN DE PALMA" ], [ "SISTERS", "written_by", "BRIAN DE PALMA" ], [ "SLEEPWALKERS", "has_genre", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "HORROR" ], [ "SLEEPWALKERS", "has_tags", "STEPHEN KING" ], [ "SLEEPWALKERS", "written_by", "STEPHEN KING" ], [ "SQUIRM", "has_genre", "HORROR" ], [ "SQUIRM", "release_year", "1976" ], [ "THE BIRDS", "has_genre", "HORROR" ], [ "THE BIRDS", "has_tags", "HORROR" ], [ "THE BIRDS", "has_tags", "TIPPI HEDREN" ], [ "THE BIRDS", "starred_actors", "TIPPI HEDREN" ], [ "THE COLLECTOR", "directed_by", "WILLIAM WYLER" ], [ "THE COLLECTOR", "has_genre", "HORROR" ], [ "THE COLLECTOR", "has_tags", "WILLIAM WYLER" ], [ "THE COLONY", "has_genre", "HORROR" ], [ "THE COLONY", "release_year", "2013" ], [ "THE CONJURING", "has_genre", "HORROR" ], [ "THE CONJURING", "has_tags", "HORROR" ], [ "THE CONJURING", "release_year", "2013" ], [ "THE DARK HALF", "has_genre", "HORROR" ], [ "THE DARK HALF", "has_tags", "STEPHEN KING" ], [ "THE DARK HALF", "written_by", "STEPHEN KING" ], [ "THE DEAD ZONE", "has_genre", "HORROR" ], [ "THE DEAD ZONE", "has_tags", "STEPHEN KING" ], [ "THE DEAD ZONE", "written_by", "STEPHEN KING" ], [ "THE HUMAN RACE", "has_genre", "HORROR" ], [ "THE HUMAN RACE", "release_year", "2013" ], [ "THE LAST DAYS ON MARS", "has_genre", "HORROR" ], [ "THE LAST DAYS ON MARS", "release_year", "2013" ], [ "THE LAST EXORCISM PART II", "has_genre", "HORROR" ], [ "THE LAST EXORCISM PART II", "release_year", "2013" ], [ "THE LAWNMOWER MAN", "has_genre", "HORROR" ], [ "THE LAWNMOWER MAN", "written_by", "STEPHEN KING" ], [ "THE MANGLER", "has_genre", "HORROR" ], [ "THE MANGLER", "has_tags", "HORROR" ], [ "THE MANGLER", "has_tags", "STEPHEN KING" ], [ "THE MANGLER", "written_by", "STEPHEN KING" ], [ "THE MIST", "has_genre", "HORROR" ], [ "THE MIST", "has_tags", "STEPHEN KING" ], [ "THE MIST", "written_by", "STEPHEN KING" ], [ "THE MONKEY'S PAW", "has_genre", "HORROR" ], [ "THE MONKEY'S PAW", "release_year", "2013" ], [ "THE NIGHT FLIER", "has_genre", "HORROR" ], [ "THE NIGHT FLIER", "written_by", "STEPHEN KING" ], [ "THE OMEN", "has_genre", "HORROR" ], [ "THE OMEN", "has_tags", "HORROR" ], [ "THE OMEN", "release_year", "1976" ], [ "THE PURGE", "has_genre", "HORROR" ], [ "THE PURGE", "release_year", "2013" ], [ "THE SACRAMENT", "has_genre", "HORROR" ], [ "THE SACRAMENT", "has_tags", "HORROR" ], [ "THE SACRAMENT", "release_year", "2013" ], [ "THE SHINING", "has_genre", "HORROR" ], [ "THE SHINING", "has_tags", "HORROR" ], [ "THE SHINING", "has_tags", "STEPHEN KING" ], [ "THE SHINING", "written_by", "STEPHEN KING" ], [ "THE WHITE REINDEER", "has_genre", "HORROR" ], [ "THE WHITE REINDEER", "release_year", "1952" ], [ "THE WITCH WHO CAME FROM THE SEA", "has_genre", "HORROR" ], [ "THE WITCH WHO CAME FROM THE SEA", "release_year", "1976" ], [ "THINNER", "has_genre", "HORROR" ], [ "THINNER", "has_tags", "STEPHEN KING" ], [ "THINNER", "written_by", "STEPHEN KING" ], [ "TO THE DEVIL A DAUGHTER", "has_genre", "HORROR" ], [ "TO THE DEVIL A DAUGHTER", "release_year", "1976" ], [ "TORMENT", "has_genre", "HORROR" ], [ "TORMENT", "release_year", "2013" ], [ "TRICK OR TREAT", "has_genre", "HORROR" ], [ "TRICK OR TREAT", "release_year", "1952" ], [ "V/H/S/2", "has_genre", "HORROR" ], [ "V/H/S/2", "has_tags", "HORROR" ], [ "V/H/S/2", "release_year", "2013" ], [ "WE ARE WHAT WE ARE", "has_genre", "HORROR" ], [ "WE ARE WHAT WE ARE", "has_tags", "HORROR" ], [ "WE ARE WHAT WE ARE", "release_year", "2013" ], [ "WELCOME TO THE JUNGLE", "has_genre", "HORROR" ], [ "WELCOME TO THE JUNGLE", "release_year", "2013" ], [ "WER", "has_genre", "HORROR" ], [ "WER", "release_year", "2013" ], [ "WEREWOLF WOMAN", "has_genre", "HORROR" ], [ "WEREWOLF WOMAN", "release_year", "1976" ], [ "WICKED LITTLE THINGS", "has_genre", "HORROR" ], [ "WICKED LITTLE THINGS", "starred_actors", "CHLOË GRACE MORETZ" ], [ "WOLF CREEK 2", "has_genre", "HORROR" ], [ "WOLF CREEK 2", "release_year", "2013" ], [ "WORLD WAR Z", "has_genre", "HORROR" ], [ "WORLD WAR Z", "release_year", "2013" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 1567, 1954 2133, 1998 6094, A CLOCKWORK ORANGE 19635, A TRUE MOB STORY 39208, APPOINTMENT WITH DEATH 30204, BAFFLED! 19633, BIRTHDAY GIRL 10218, BLACK WIDOW 6469, BODY COUNT 40039, BRAVE NEW WORLD 26884, BROWN'S REQUIEM 8313, CAUGHT UP 36568, CLAY PIGEONS 14724, CRIME 19328, CRIME WAVE 31527, DAD SAVAGE 34528, DARK CITY 23396, DIAL M FOR MURDER 20848, EARL CAMERON 8026, END OF THE GAME 31783, ENGLISH 19728, EVILENKO 6943, FALLEN 16516, FIFTY DEAD MEN WALKING 1033, FRACTURE 13308, FREEDOMLAND 3553, GODZILLA 31603, GORILLA AT LARGE 8046, GOSFORD PARK 38953, HIDEOUS KINKY 22006, I WANT YOU 28169, IN THE CUT 978, INFERNAL AFFAIRS 20264, JAIL BAIT 27661, JOHNNY SKIDMARKS 38160, JOURNEY TO ITALY 3743, JUDAS KISS 34878, LADY ON A TRAIN 14601, LES MISÉRABLES 38721, LOCK, STOCK AND TWO SMOKING BARRELS 34362, LULU ON THE BRIDGE 22792, MICHAEL WINTERBOTTOM 1454, MICKEY BLUE EYES 3487, MINORITY REPORT 10883, MONTANA 6137, MONUMENT AVE. 23695, MULAN 11311, MURDER ON THE ORIENT EXPRESS 15145, MYSTERY 35498, MYSTERY OF THE 13TH GUEST 7925, MYSTERY ROAD 30629, NIGHT NURSE 35865, ON THE WATERFRONT 15481, ONE TOUGH COP 4235, OUT OF SIGHT 8509, PASSION 19622, PHOENIX 39462, POOL OF LONDON 28091, PSYCHO 38043, PUSHER 1643, RISE OF THE FOOTSOLDIER 38195, ROBINSON CRUSOE 5362, ROUNDERS 32607, RUSH HOUR 8020, SAFE MEN 32487, SAPPHIRE 8436, SPIRITS OF THE DEAD 33414, SWEET SIXTEEN 32730, TALK OF ANGELS 14696, THE BIG LEBOWSKI 38918, THE FAMILY 4068, THE GENERAL 31283, THE HOUND OF THE BASKERVILLES 6870, THE KILLER INSIDE ME 28177, THE KRAYS 4091, THE LADY VANISHES 13050, THE LEGEND OF 1900 21696, THE MAN FROM LONDON 12887, THE MIRROR CRACK'D 30294, THE NIGHT OF THE GENERALS 37490, THE PERFECT MURDER 40086, THE PLACE BEYOND THE PINES 30014, THE RAID 2 8660, THE RECKONING 3275, THE REPLACEMENT KILLERS 19255, THE VALACHI PAPERS 14962, THE WATCHER IN THE WOODS 33585, THURSDAY 6485, TRIXIE 308, TRUE CRIME 10238, UNDERWORLD 10133, UNKNOWN 4736, WHERE'S MARLOWE? 8390, WHISTLING IN DIXIE 24960, WILD THINGS 31862, WONDERLAND 37210, ZODIAC 17777, ZULU src, edge_attr, dst 6094, has_genre, 14724 6094, in_language, 31783 19635, has_genre, 14724 19635, release_year, 2133 39208, has_genre, 14724 39208, has_genre, 15145 30204, has_genre, 15145 30204, in_language, 31783 19633, has_genre, 14724 19633, in_language, 31783 10218, has_genre, 14724 10218, has_genre, 15145 10218, has_tags, 14724 10218, release_year, 1567 6469, has_genre, 14724 6469, release_year, 2133 40039, in_language, 31783 40039, release_year, 2133 26884, has_genre, 14724 26884, release_year, 2133 8313, has_genre, 14724 8313, release_year, 2133 36568, has_genre, 14724 36568, release_year, 2133 19328, has_genre, 14724 19328, release_year, 1567 31527, in_language, 31783 31527, release_year, 2133 34528, has_genre, 15145 34528, release_year, 2133 23396, has_genre, 14724 23396, in_language, 31783 23396, release_year, 1567 8026, has_genre, 14724 8026, in_language, 31783 19728, has_genre, 14724 19728, in_language, 31783 6943, has_genre, 14724 6943, release_year, 2133 16516, has_tags, 14724 16516, in_language, 31783 1033, has_genre, 14724 1033, has_genre, 15145 13308, has_genre, 14724 13308, has_genre, 15145 3553, release_year, 1567 3553, release_year, 2133 31603, has_genre, 15145 31603, release_year, 1567 8046, has_genre, 15145 8046, in_language, 31783 38953, in_language, 31783 38953, release_year, 2133 22006, directed_by, 22792 22006, has_genre, 14724 22006, in_language, 31783 22006, release_year, 2133 28169, has_genre, 15145 28169, in_language, 31783 978, has_genre, 14724 978, in_language, 31783 20264, has_genre, 14724 20264, release_year, 1567 27661, has_genre, 15145 27661, release_year, 2133 38160, in_language, 31783 38160, release_year, 1567 3743, has_genre, 14724 3743, release_year, 2133 34878, has_genre, 14724 34878, has_genre, 15145 14601, in_language, 31783 14601, release_year, 2133 38721, has_genre, 14724 38721, has_tags, 14724 38721, release_year, 2133 34362, has_genre, 15145 34362, release_year, 2133 1454, has_genre, 14724 1454, in_language, 31783 3487, has_genre, 15145 3487, has_tags, 14724 3487, has_tags, 15145 10883, has_genre, 14724 10883, release_year, 2133 6137, has_genre, 14724 6137, release_year, 2133 23695, in_language, 31783 23695, release_year, 2133 11311, has_genre, 14724 11311, has_genre, 15145 11311, has_tags, 15145 35498, has_genre, 14724 35498, has_genre, 15145 7925, has_genre, 14724 7925, has_genre, 15145 30629, has_genre, 14724 30629, has_genre, 15145 35865, has_genre, 14724 35865, release_year, 1567 15481, has_genre, 14724 15481, release_year, 2133 4235, has_genre, 14724 4235, release_year, 2133 8509, has_genre, 14724 8509, in_language, 31783 19622, has_genre, 14724 19622, release_year, 2133 39462, has_genre, 14724 39462, starred_actors, 20848 28091, has_genre, 15145 28091, has_tags, 15145 28091, release_year, 2133 38043, has_genre, 14724 38043, in_language, 31783 1643, has_genre, 14724 1643, has_tags, 14724 1643, in_language, 31783 38195, in_language, 31783 38195, release_year, 1567 5362, has_genre, 14724 5362, release_year, 2133 32607, has_tags, 14724 32607, release_year, 2133 8020, has_genre, 14724 8020, release_year, 2133 32487, has_genre, 14724 32487, has_genre, 15145 32487, in_language, 31783 8436, has_genre, 15145 8436, in_language, 31783 33414, has_genre, 14724 33414, in_language, 31783 32730, in_language, 31783 32730, release_year, 2133 14696, has_genre, 14724 14696, has_tags, 14724 14696, release_year, 2133 38918, has_genre, 14724 38918, in_language, 31783 4068, has_genre, 14724 4068, release_year, 2133 31283, has_genre, 14724 31283, has_genre, 15145 6870, directed_by, 22792 6870, has_genre, 14724 6870, has_tags, 22792 28177, has_genre, 14724 28177, in_language, 31783 4091, has_genre, 15145 4091, in_language, 31783 13050, in_language, 31783 13050, release_year, 2133 21696, has_genre, 14724 21696, in_language, 31783 12887, has_genre, 14724 12887, has_genre, 15145 30294, has_genre, 14724 30294, has_genre, 15145 37490, has_tags, 14724 37490, in_language, 31783 40086, has_genre, 14724 40086, in_language, 31783 30014, has_genre, 14724 30014, in_language, 31783 8660, has_genre, 14724 8660, has_genre, 15145 3275, has_genre, 14724 3275, release_year, 2133 19255, has_genre, 14724 19255, in_language, 31783 14962, has_genre, 15145 14962, in_language, 31783 33585, has_genre, 14724 33585, release_year, 2133 6485, has_genre, 14724 6485, has_genre, 15145 308, has_genre, 14724 308, has_genre, 15145 10238, has_genre, 14724 10238, in_language, 31783 10133, has_genre, 14724 10133, in_language, 31783 4736, has_genre, 15145 4736, release_year, 2133 8390, has_genre, 14724 8390, has_genre, 15145 24960, has_genre, 14724 24960, release_year, 2133 31862, directed_by, 22792 31862, has_genre, 14724 31862, has_tags, 22792 37210, has_genre, 14724 37210, has_genre, 15145 37210, has_tags, 14724 17777, has_genre, 14724 17777, in_language, 31783 Question: In what context are EARL CAMERON, GORILLA AT LARGE, and I WANT YOU connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "EARL CAMERON", "GORILLA AT LARGE", "I WANT YOU" ], "valid_edges": [ [ "A CLOCKWORK ORANGE", "has_genre", "CRIME" ], [ "A CLOCKWORK ORANGE", "in_language", "ENGLISH" ], [ "A TRUE MOB STORY", "has_genre", "CRIME" ], [ "A TRUE MOB STORY", "release_year", "1998" ], [ "APPOINTMENT WITH DEATH", "has_genre", "CRIME" ], [ "APPOINTMENT WITH DEATH", "has_genre", "MYSTERY" ], [ "BAFFLED!", "has_genre", "MYSTERY" ], [ "BAFFLED!", "in_language", "ENGLISH" ], [ "BIRTHDAY GIRL", "has_genre", "CRIME" ], [ "BIRTHDAY GIRL", "in_language", "ENGLISH" ], [ "BLACK WIDOW", "has_genre", "CRIME" ], [ "BLACK WIDOW", "has_genre", "MYSTERY" ], [ "BLACK WIDOW", "has_tags", "CRIME" ], [ "BLACK WIDOW", "release_year", "1954" ], [ "BODY COUNT", "has_genre", "CRIME" ], [ "BODY COUNT", "release_year", "1998" ], [ "BRAVE NEW WORLD", "in_language", "ENGLISH" ], [ "BRAVE NEW WORLD", "release_year", "1998" ], [ "BROWN'S REQUIEM", "has_genre", "CRIME" ], [ "BROWN'S REQUIEM", "release_year", "1998" ], [ "CAUGHT UP", "has_genre", "CRIME" ], [ "CAUGHT UP", "release_year", "1998" ], [ "CLAY PIGEONS", "has_genre", "CRIME" ], [ "CLAY PIGEONS", "release_year", "1998" ], [ "CRIME WAVE", "has_genre", "CRIME" ], [ "CRIME WAVE", "release_year", "1954" ], [ "DAD SAVAGE", "in_language", "ENGLISH" ], [ "DAD SAVAGE", "release_year", "1998" ], [ "DARK CITY", "has_genre", "MYSTERY" ], [ "DARK CITY", "release_year", "1998" ], [ "DIAL M FOR MURDER", "has_genre", "CRIME" ], [ "DIAL M FOR MURDER", "in_language", "ENGLISH" ], [ "DIAL M FOR MURDER", "release_year", "1954" ], [ "END OF THE GAME", "has_genre", "CRIME" ], [ "END OF THE GAME", "in_language", "ENGLISH" ], [ "EVILENKO", "has_genre", "CRIME" ], [ "EVILENKO", "in_language", "ENGLISH" ], [ "FALLEN", "has_genre", "CRIME" ], [ "FALLEN", "release_year", "1998" ], [ "FIFTY DEAD MEN WALKING", "has_tags", "CRIME" ], [ "FIFTY DEAD MEN WALKING", "in_language", "ENGLISH" ], [ "FRACTURE", "has_genre", "CRIME" ], [ "FRACTURE", "has_genre", "MYSTERY" ], [ "FREEDOMLAND", "has_genre", "CRIME" ], [ "FREEDOMLAND", "has_genre", "MYSTERY" ], [ "GODZILLA", "release_year", "1954" ], [ "GODZILLA", "release_year", "1998" ], [ "GORILLA AT LARGE", "has_genre", "MYSTERY" ], [ "GORILLA AT LARGE", "release_year", "1954" ], [ "GOSFORD PARK", "has_genre", "MYSTERY" ], [ "GOSFORD PARK", "in_language", "ENGLISH" ], [ "HIDEOUS KINKY", "in_language", "ENGLISH" ], [ "HIDEOUS KINKY", "release_year", "1998" ], [ "I WANT YOU", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "I WANT YOU", "has_genre", "CRIME" ], [ "I WANT YOU", "in_language", "ENGLISH" ], [ "I WANT YOU", "release_year", "1998" ], [ "IN THE CUT", "has_genre", "MYSTERY" ], [ "IN THE CUT", "in_language", "ENGLISH" ], [ "INFERNAL AFFAIRS", "has_genre", "CRIME" ], [ "INFERNAL AFFAIRS", "in_language", "ENGLISH" ], [ "JAIL BAIT", "has_genre", "CRIME" ], [ "JAIL BAIT", "release_year", "1954" ], [ "JOHNNY SKIDMARKS", "has_genre", "MYSTERY" ], [ "JOHNNY SKIDMARKS", "release_year", "1998" ], [ "JOURNEY TO ITALY", "in_language", "ENGLISH" ], [ "JOURNEY TO ITALY", "release_year", "1954" ], [ "JUDAS KISS", "has_genre", "CRIME" ], [ "JUDAS KISS", "release_year", "1998" ], [ "LADY ON A TRAIN", "has_genre", "CRIME" ], [ "LADY ON A TRAIN", "has_genre", "MYSTERY" ], [ "LES MISÉRABLES", "in_language", "ENGLISH" ], [ "LES MISÉRABLES", "release_year", "1998" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_genre", "CRIME" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "has_tags", "CRIME" ], [ "LOCK, STOCK AND TWO SMOKING BARRELS", "release_year", "1998" ], [ "LULU ON THE BRIDGE", "has_genre", "MYSTERY" ], [ "LULU ON THE BRIDGE", "release_year", "1998" ], [ "MICKEY BLUE EYES", "has_genre", "CRIME" ], [ "MICKEY BLUE EYES", "in_language", "ENGLISH" ], [ "MINORITY REPORT", "has_genre", "MYSTERY" ], [ "MINORITY REPORT", "has_tags", "CRIME" ], [ "MINORITY REPORT", "has_tags", "MYSTERY" ], [ "MONTANA", "has_genre", "CRIME" ], [ "MONTANA", "release_year", "1998" ], [ "MONUMENT AVE.", "has_genre", "CRIME" ], [ "MONUMENT AVE.", "release_year", "1998" ], [ "MULAN", "in_language", "ENGLISH" ], [ "MULAN", "release_year", "1998" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "CRIME" ], [ "MURDER ON THE ORIENT EXPRESS", "has_genre", "MYSTERY" ], [ "MURDER ON THE ORIENT EXPRESS", "has_tags", "MYSTERY" ], [ "MYSTERY OF THE 13TH GUEST", "has_genre", "CRIME" ], [ "MYSTERY OF THE 13TH GUEST", "has_genre", "MYSTERY" ], [ "MYSTERY ROAD", "has_genre", "CRIME" ], [ "MYSTERY ROAD", "has_genre", "MYSTERY" ], [ "NIGHT NURSE", "has_genre", "CRIME" ], [ "NIGHT NURSE", "has_genre", "MYSTERY" ], [ "ON THE WATERFRONT", "has_genre", "CRIME" ], [ "ON THE WATERFRONT", "release_year", "1954" ], [ "ONE TOUGH COP", "has_genre", "CRIME" ], [ "ONE TOUGH COP", "release_year", "1998" ], [ "OUT OF SIGHT", "has_genre", "CRIME" ], [ "OUT OF SIGHT", "release_year", "1998" ], [ "PASSION", "has_genre", "CRIME" ], [ "PASSION", "in_language", "ENGLISH" ], [ "PHOENIX", "has_genre", "CRIME" ], [ "PHOENIX", "release_year", "1998" ], [ "POOL OF LONDON", "has_genre", "CRIME" ], [ "POOL OF LONDON", "starred_actors", "EARL CAMERON" ], [ "PSYCHO", "has_genre", "MYSTERY" ], [ "PSYCHO", "has_tags", "MYSTERY" ], [ "PSYCHO", "release_year", "1998" ], [ "PUSHER", "has_genre", "CRIME" ], [ "PUSHER", "in_language", "ENGLISH" ], [ "RISE OF THE FOOTSOLDIER", "has_genre", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "has_tags", "CRIME" ], [ "RISE OF THE FOOTSOLDIER", "in_language", "ENGLISH" ], [ "ROBINSON CRUSOE", "in_language", "ENGLISH" ], [ "ROBINSON CRUSOE", "release_year", "1954" ], [ "ROUNDERS", "has_genre", "CRIME" ], [ "ROUNDERS", "release_year", "1998" ], [ "RUSH HOUR", "has_tags", "CRIME" ], [ "RUSH HOUR", "release_year", "1998" ], [ "SAFE MEN", "has_genre", "CRIME" ], [ "SAFE MEN", "release_year", "1998" ], [ "SAPPHIRE", "has_genre", "CRIME" ], [ "SAPPHIRE", "has_genre", "MYSTERY" ], [ "SAPPHIRE", "in_language", "ENGLISH" ], [ "SPIRITS OF THE DEAD", "has_genre", "MYSTERY" ], [ "SPIRITS OF THE DEAD", "in_language", "ENGLISH" ], [ "SWEET SIXTEEN", "has_genre", "CRIME" ], [ "SWEET SIXTEEN", "in_language", "ENGLISH" ], [ "TALK OF ANGELS", "in_language", "ENGLISH" ], [ "TALK OF ANGELS", "release_year", "1998" ], [ "THE BIG LEBOWSKI", "has_genre", "CRIME" ], [ "THE BIG LEBOWSKI", "has_tags", "CRIME" ], [ "THE BIG LEBOWSKI", "release_year", "1998" ], [ "THE FAMILY", "has_genre", "CRIME" ], [ "THE FAMILY", "in_language", "ENGLISH" ], [ "THE GENERAL", "has_genre", "CRIME" ], [ "THE GENERAL", "release_year", "1998" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "CRIME" ], [ "THE HOUND OF THE BASKERVILLES", "has_genre", "MYSTERY" ], [ "THE KILLER INSIDE ME", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "THE KILLER INSIDE ME", "has_genre", "CRIME" ], [ "THE KILLER INSIDE ME", "has_tags", "MICHAEL WINTERBOTTOM" ], [ "THE KRAYS", "has_genre", "CRIME" ], [ "THE KRAYS", "in_language", "ENGLISH" ], [ "THE LADY VANISHES", "has_genre", "MYSTERY" ], [ "THE LADY VANISHES", "in_language", "ENGLISH" ], [ "THE LEGEND OF 1900", "in_language", "ENGLISH" ], [ "THE LEGEND OF 1900", "release_year", "1998" ], [ "THE MAN FROM LONDON", "has_genre", "CRIME" ], [ "THE MAN FROM LONDON", "in_language", "ENGLISH" ], [ "THE MIRROR CRACK'D", "has_genre", "CRIME" ], [ "THE MIRROR CRACK'D", "has_genre", "MYSTERY" ], [ "THE NIGHT OF THE GENERALS", "has_genre", "CRIME" ], [ "THE NIGHT OF THE GENERALS", "has_genre", "MYSTERY" ], [ "THE PERFECT MURDER", "has_tags", "CRIME" ], [ "THE PERFECT MURDER", "in_language", "ENGLISH" ], [ "THE PLACE BEYOND THE PINES", "has_genre", "CRIME" ], [ "THE PLACE BEYOND THE PINES", "in_language", "ENGLISH" ], [ "THE RAID 2", "has_genre", "CRIME" ], [ "THE RAID 2", "in_language", "ENGLISH" ], [ "THE RECKONING", "has_genre", "CRIME" ], [ "THE RECKONING", "has_genre", "MYSTERY" ], [ "THE REPLACEMENT KILLERS", "has_genre", "CRIME" ], [ "THE REPLACEMENT KILLERS", "release_year", "1998" ], [ "THE VALACHI PAPERS", "has_genre", "CRIME" ], [ "THE VALACHI PAPERS", "in_language", "ENGLISH" ], [ "THE WATCHER IN THE WOODS", "has_genre", "MYSTERY" ], [ "THE WATCHER IN THE WOODS", "in_language", "ENGLISH" ], [ "THURSDAY", "has_genre", "CRIME" ], [ "THURSDAY", "release_year", "1998" ], [ "TRIXIE", "has_genre", "CRIME" ], [ "TRIXIE", "has_genre", "MYSTERY" ], [ "TRUE CRIME", "has_genre", "CRIME" ], [ "TRUE CRIME", "has_genre", "MYSTERY" ], [ "UNDERWORLD", "has_genre", "CRIME" ], [ "UNDERWORLD", "in_language", "ENGLISH" ], [ "UNKNOWN", "has_genre", "CRIME" ], [ "UNKNOWN", "in_language", "ENGLISH" ], [ "WHERE'S MARLOWE?", "has_genre", "MYSTERY" ], [ "WHERE'S MARLOWE?", "release_year", "1998" ], [ "WHISTLING IN DIXIE", "has_genre", "CRIME" ], [ "WHISTLING IN DIXIE", "has_genre", "MYSTERY" ], [ "WILD THINGS", "has_genre", "CRIME" ], [ "WILD THINGS", "release_year", "1998" ], [ "WONDERLAND", "directed_by", "MICHAEL WINTERBOTTOM" ], [ "WONDERLAND", "has_genre", "CRIME" ], [ "WONDERLAND", "has_tags", "MICHAEL WINTERBOTTOM" ], [ "ZODIAC", "has_genre", "CRIME" ], [ "ZODIAC", "has_genre", "MYSTERY" ], [ "ZODIAC", "has_tags", "CRIME" ], [ "ZULU", "has_genre", "CRIME" ], [ "ZULU", "in_language", "ENGLISH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 26257, 1994 1006, 1996 35798, 2010 7698, ANIMATED 24177, ANIMATION 14271, BEETHOVEN 19826, BLACK DEATH 15757, BRIAN LEVANT 722, CHARACTERS 14728, CLASSIC 20883, DEATH 37059, DEATH AT A FUNERAL 10509, FAMILY 22958, FAMOUS 36066, FANTASY 18521, FLY AWAY HOME 15959, FRANK OZ 11565, GOOD 28307, HARRY AND THE HENDERSONS 34869, HOTEL TRANSYLVANIA 16200, ITALIAN 4798, JINGLE ALL THE WAY 7690, JOHN LITHGOW 26784, LITTLE WOMEN 4011, LOST IN SPACE 3764, MARMADUKE 19691, MAUDE T. HOWELL 15413, MONSTERS 37497, NATIONAL FILM REGISTRY 14026, PINOCCHIO 13081, R 32533, SCIENCE FICTION 24467, SPEED RACER 30812, THE DARK CRYSTAL 26726, THE DIARY OF ANNE FRANK 17956, THE FLINTSTONES 35551, THE GODFATHER 37999, THE MAN WHO PLAYED GOD 18537, THE SPY NEXT DOOR 12162, YOU CAN COUNT ON ME src, edge_attr, dst 35798, has_tags, 7690 35798, has_tags, 32533 35798, starred_actors, 7690 14271, directed_by, 15757 14271, has_genre, 10509 14271, has_tags, 15757 14271, has_tags, 10509 19826, release_year, 35798 37059, directed_by, 15959 37059, has_tags, 20883 37059, has_tags, 10509 37059, has_tags, 15959 37059, has_tags, 13081 37059, release_year, 35798 18521, has_genre, 10509 18521, has_tags, 20883 18521, release_year, 1006 28307, has_genre, 10509 28307, has_genre, 36066 28307, has_tags, 10509 28307, has_tags, 7690 28307, starred_actors, 7690 34869, has_genre, 24177 34869, has_genre, 10509 34869, has_imdb_votes, 22958 34869, has_tags, 7698 34869, has_tags, 24177 34869, has_tags, 15413 4798, directed_by, 15757 4798, has_genre, 10509 4798, has_tags, 15757 4798, release_year, 1006 26784, has_genre, 10509 26784, has_imdb_rating, 11565 26784, has_tags, 722 26784, has_tags, 14728 26784, release_year, 26257 4011, has_genre, 10509 4011, has_tags, 32533 3764, has_genre, 10509 3764, release_year, 35798 15413, release_year, 35798 14026, has_genre, 24177 14026, has_genre, 10509 14026, has_genre, 36066 14026, has_imdb_rating, 11565 14026, has_tags, 7698 14026, has_tags, 24177 14026, has_tags, 722 14026, has_tags, 14728 14026, has_tags, 36066 14026, has_tags, 37497 14026, in_language, 16200 24467, has_genre, 10509 24467, has_imdb_rating, 11565 30812, directed_by, 15959 30812, has_genre, 10509 30812, has_imdb_votes, 22958 30812, has_tags, 36066 30812, has_tags, 15959 30812, starred_actors, 15959 26726, has_genre, 10509 26726, has_imdb_rating, 11565 17956, directed_by, 15757 17956, has_genre, 10509 17956, has_tags, 15757 17956, release_year, 26257 35551, has_tags, 10509 35551, has_tags, 16200 35551, has_tags, 37497 35551, has_tags, 13081 35551, in_language, 16200 37999, has_imdb_rating, 11565 37999, written_by, 19691 18537, directed_by, 15757 18537, has_genre, 10509 18537, release_year, 35798 12162, has_tags, 10509 12162, has_tags, 13081 Question: How are BLACK DEATH, FAMILY, and MAUDE T. HOWELL related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BLACK DEATH", "FAMILY", "MAUDE T. HOWELL" ], "valid_edges": [ [ "2010", "has_tags", "JOHN LITHGOW" ], [ "2010", "has_tags", "SCIENCE FICTION" ], [ "2010", "starred_actors", "JOHN LITHGOW" ], [ "BEETHOVEN", "directed_by", "BRIAN LEVANT" ], [ "BEETHOVEN", "has_genre", "FAMILY" ], [ "BEETHOVEN", "has_tags", "BRIAN LEVANT" ], [ "BEETHOVEN", "has_tags", "FAMILY" ], [ "BLACK DEATH", "release_year", "2010" ], [ "DEATH AT A FUNERAL", "directed_by", "FRANK OZ" ], [ "DEATH AT A FUNERAL", "has_tags", "DEATH" ], [ "DEATH AT A FUNERAL", "has_tags", "FAMILY" ], [ "DEATH AT A FUNERAL", "has_tags", "FRANK OZ" ], [ "DEATH AT A FUNERAL", "has_tags", "R" ], [ "DEATH AT A FUNERAL", "release_year", "2010" ], [ "FLY AWAY HOME", "has_genre", "FAMILY" ], [ "FLY AWAY HOME", "has_tags", "DEATH" ], [ "FLY AWAY HOME", "release_year", "1996" ], [ "HARRY AND THE HENDERSONS", "has_genre", "FAMILY" ], [ "HARRY AND THE HENDERSONS", "has_genre", "FANTASY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "FAMILY" ], [ "HARRY AND THE HENDERSONS", "has_tags", "JOHN LITHGOW" ], [ "HARRY AND THE HENDERSONS", "starred_actors", "JOHN LITHGOW" ], [ "HOTEL TRANSYLVANIA", "has_genre", "ANIMATION" ], [ "HOTEL TRANSYLVANIA", "has_genre", "FAMILY" ], [ "HOTEL TRANSYLVANIA", "has_imdb_votes", "FAMOUS" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANIMATED" ], [ "HOTEL TRANSYLVANIA", "has_tags", "ANIMATION" ], [ "HOTEL TRANSYLVANIA", "has_tags", "MONSTERS" ], [ "JINGLE ALL THE WAY", "directed_by", "BRIAN LEVANT" ], [ "JINGLE ALL THE WAY", "has_genre", "FAMILY" ], [ "JINGLE ALL THE WAY", "has_tags", "BRIAN LEVANT" ], [ "JINGLE ALL THE WAY", "release_year", "1996" ], [ "LITTLE WOMEN", "has_genre", "FAMILY" ], [ "LITTLE WOMEN", "has_imdb_rating", "GOOD" ], [ "LITTLE WOMEN", "has_tags", "CHARACTERS" ], [ "LITTLE WOMEN", "has_tags", "CLASSIC" ], [ "LITTLE WOMEN", "release_year", "1994" ], [ "LOST IN SPACE", "has_genre", "FAMILY" ], [ "LOST IN SPACE", "has_tags", "SCIENCE FICTION" ], [ "MARMADUKE", "has_genre", "FAMILY" ], [ "MARMADUKE", "release_year", "2010" ], [ "MONSTERS", "release_year", "2010" ], [ "PINOCCHIO", "has_genre", "ANIMATION" ], [ "PINOCCHIO", "has_genre", "FAMILY" ], [ "PINOCCHIO", "has_genre", "FANTASY" ], [ "PINOCCHIO", "has_imdb_rating", "GOOD" ], [ "PINOCCHIO", "has_tags", "ANIMATED" ], [ "PINOCCHIO", "has_tags", "ANIMATION" ], [ "PINOCCHIO", "has_tags", "CHARACTERS" ], [ "PINOCCHIO", "has_tags", "CLASSIC" ], [ "PINOCCHIO", "has_tags", "FANTASY" ], [ "PINOCCHIO", "has_tags", "NATIONAL FILM REGISTRY" ], [ "PINOCCHIO", "in_language", "ITALIAN" ], [ "SPEED RACER", "has_genre", "FAMILY" ], [ "SPEED RACER", "has_imdb_rating", "GOOD" ], [ "THE DARK CRYSTAL", "directed_by", "FRANK OZ" ], [ "THE DARK CRYSTAL", "has_genre", "FAMILY" ], [ "THE DARK CRYSTAL", "has_imdb_votes", "FAMOUS" ], [ "THE DARK CRYSTAL", "has_tags", "FANTASY" ], [ "THE DARK CRYSTAL", "has_tags", "FRANK OZ" ], [ "THE DARK CRYSTAL", "starred_actors", "FRANK OZ" ], [ "THE DIARY OF ANNE FRANK", "has_genre", "FAMILY" ], [ "THE DIARY OF ANNE FRANK", "has_imdb_rating", "GOOD" ], [ "THE FLINTSTONES", "directed_by", "BRIAN LEVANT" ], [ "THE FLINTSTONES", "has_genre", "FAMILY" ], [ "THE FLINTSTONES", "has_tags", "BRIAN LEVANT" ], [ "THE FLINTSTONES", "release_year", "1994" ], [ "THE GODFATHER", "has_tags", "FAMILY" ], [ "THE GODFATHER", "has_tags", "ITALIAN" ], [ "THE GODFATHER", "has_tags", "NATIONAL FILM REGISTRY" ], [ "THE GODFATHER", "has_tags", "R" ], [ "THE GODFATHER", "in_language", "ITALIAN" ], [ "THE MAN WHO PLAYED GOD", "has_imdb_rating", "GOOD" ], [ "THE MAN WHO PLAYED GOD", "written_by", "MAUDE T. HOWELL" ], [ "THE SPY NEXT DOOR", "directed_by", "BRIAN LEVANT" ], [ "THE SPY NEXT DOOR", "has_genre", "FAMILY" ], [ "THE SPY NEXT DOOR", "release_year", "2010" ], [ "YOU CAN COUNT ON ME", "has_tags", "FAMILY" ], [ "YOU CAN COUNT ON ME", "has_tags", "R" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 39435, 1975 32646, AT LONG LAST LOVE 30463, COMEDY 12489, CRAZY MAMA 2221, DOLEMITE 4649, HAPPY TEARS 35856, HEARTS OF THE WEST 13183, LOVE AND DEATH 33190, MAX SCHOTT 32834, MONTY PYTHON AND THE HOLY GRAIL 5237, MURPHY'S ROMANCE 32916, MY FRIENDS 18416, ONE OF OUR DINOSAURS IS MISSING 34930, RANCHO DELUXE 1045, SMILE 10409, THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER 32237, THE FORTUNE 21920, THE OLSEN GANG ON THE TRACK 21459, THE PASSENGER 10721, THE ROCKY HORROR PICTURE SHOW 23847, THE STEPFORD WIVES 26081, THE SUNSHINE BOYS src, edge_attr, dst 32646, has_genre, 30463 32646, release_year, 39435 12489, has_genre, 30463 12489, release_year, 39435 2221, has_genre, 30463 2221, release_year, 39435 4649, has_genre, 30463 35856, has_genre, 30463 35856, release_year, 39435 13183, has_genre, 30463 13183, has_tags, 30463 13183, release_year, 39435 32834, has_genre, 30463 32834, has_tags, 30463 32834, release_year, 39435 5237, has_genre, 30463 5237, written_by, 33190 32916, has_genre, 30463 32916, release_year, 39435 18416, has_genre, 30463 18416, release_year, 39435 34930, has_genre, 30463 34930, release_year, 39435 1045, has_genre, 30463 1045, release_year, 39435 10409, has_genre, 30463 10409, release_year, 39435 32237, has_genre, 30463 32237, release_year, 39435 21920, has_genre, 30463 21920, release_year, 39435 21459, release_year, 39435 10721, has_genre, 30463 10721, release_year, 39435 23847, has_genre, 30463 23847, release_year, 39435 26081, has_genre, 30463 26081, release_year, 39435 Question: How are HAPPY TEARS, MAX SCHOTT, and THE PASSENGER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "HAPPY TEARS", "MAX SCHOTT", "THE PASSENGER" ], "valid_edges": [ [ "AT LONG LAST LOVE", "has_genre", "COMEDY" ], [ "AT LONG LAST LOVE", "release_year", "1975" ], [ "CRAZY MAMA", "has_genre", "COMEDY" ], [ "CRAZY MAMA", "release_year", "1975" ], [ "DOLEMITE", "has_genre", "COMEDY" ], [ "DOLEMITE", "release_year", "1975" ], [ "HAPPY TEARS", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "has_genre", "COMEDY" ], [ "HEARTS OF THE WEST", "release_year", "1975" ], [ "LOVE AND DEATH", "has_genre", "COMEDY" ], [ "LOVE AND DEATH", "has_tags", "COMEDY" ], [ "LOVE AND DEATH", "release_year", "1975" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_genre", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "has_tags", "COMEDY" ], [ "MONTY PYTHON AND THE HOLY GRAIL", "release_year", "1975" ], [ "MURPHY'S ROMANCE", "has_genre", "COMEDY" ], [ "MURPHY'S ROMANCE", "written_by", "MAX SCHOTT" ], [ "MY FRIENDS", "has_genre", "COMEDY" ], [ "MY FRIENDS", "release_year", "1975" ], [ "ONE OF OUR DINOSAURS IS MISSING", "has_genre", "COMEDY" ], [ "ONE OF OUR DINOSAURS IS MISSING", "release_year", "1975" ], [ "RANCHO DELUXE", "has_genre", "COMEDY" ], [ "RANCHO DELUXE", "release_year", "1975" ], [ "SMILE", "has_genre", "COMEDY" ], [ "SMILE", "release_year", "1975" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "has_genre", "COMEDY" ], [ "THE ADVENTURE OF SHERLOCK HOLMES' SMARTER BROTHER", "release_year", "1975" ], [ "THE FORTUNE", "has_genre", "COMEDY" ], [ "THE FORTUNE", "release_year", "1975" ], [ "THE OLSEN GANG ON THE TRACK", "has_genre", "COMEDY" ], [ "THE OLSEN GANG ON THE TRACK", "release_year", "1975" ], [ "THE PASSENGER", "release_year", "1975" ], [ "THE ROCKY HORROR PICTURE SHOW", "has_genre", "COMEDY" ], [ "THE ROCKY HORROR PICTURE SHOW", "release_year", "1975" ], [ "THE STEPFORD WIVES", "has_genre", "COMEDY" ], [ "THE STEPFORD WIVES", "release_year", "1975" ], [ "THE SUNSHINE BOYS", "has_genre", "COMEDY" ], [ "THE SUNSHINE BOYS", "release_year", "1975" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 3863, 1962 37484, 2004 1421, 2013 7603, CARY GRANT 847, JACK THE GIANT KILLER 37050, SHARKNADO 17493, SOUL PLANE 24322, THAT TOUCH OF MINK 38611, THE INTRUDER 32881, TOUCH OF PINK src, edge_attr, dst 847, release_year, 3863 847, release_year, 1421 37050, release_year, 1421 17493, release_year, 37484 24322, has_tags, 7603 24322, release_year, 3863 24322, starred_actors, 7603 38611, release_year, 3863 38611, release_year, 37484 32881, has_tags, 7603 32881, release_year, 37484 Question: For what reason are SHARKNADO, SOUL PLANE, and THAT TOUCH OF MINK associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "SHARKNADO", "SOUL PLANE", "THAT TOUCH OF MINK" ], "valid_edges": [ [ "JACK THE GIANT KILLER", "release_year", "1962" ], [ "JACK THE GIANT KILLER", "release_year", "2013" ], [ "SHARKNADO", "release_year", "2013" ], [ "SOUL PLANE", "release_year", "2004" ], [ "THAT TOUCH OF MINK", "has_tags", "CARY GRANT" ], [ "THAT TOUCH OF MINK", "release_year", "1962" ], [ "THAT TOUCH OF MINK", "starred_actors", "CARY GRANT" ], [ "THE INTRUDER", "release_year", "1962" ], [ "THE INTRUDER", "release_year", "2004" ], [ "TOUCH OF PINK", "has_tags", "CARY GRANT" ], [ "TOUCH OF PINK", "release_year", "2004" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24004, 10 21931, 1941 724, 1979 1188, A FORCE OF ONE 12649, A LITTLE ROMANCE 4763, ADVENTURE 1216, AMERICATHON 34744, BEING THERE 37601, BREAKING AWAY 13302, CHAPTER TWO 38678, CHILLY SCENES OF WINTER 30463, COMEDY 15436, EPIC 19367, ESCAPE TO ATHENA 35760, H.O.T.S. 20263, HAIR 15547, HOMER 11331, LOVE AT FIRST BITE 33790, MANHATTAN 6108, MEATBALLS 26484, MORE AMERICAN GRAFFITI 14797, O BROTHER, WHERE ART THOU? 6773, REAL LIFE 22107, ROCK 'N' ROLL HIGH SCHOOL 27231, STARTING OVER 16018, THE APPLE DUMPLING GANG RIDES AGAIN 28510, THE FRISCO KID 19104, THE IN-LAWS 33024, THE JERK 4091, THE LADY VANISHES 32382, THE MAIN EVENT 12809, THE MUPPET MOVIE 31851, THE PRISONER OF ZENDA 26036, THE TEMPEST 33449, THE WEDDING PLANNER 5729, TROY 32079, ULYSSES 31435, UNCLE MARIN, THE BILLIONAIRE 22774, WISE BLOOD src, edge_attr, dst 24004, has_genre, 30463 24004, release_year, 724 21931, has_genre, 30463 21931, release_year, 724 1188, release_year, 724 12649, has_genre, 30463 12649, release_year, 724 1216, has_genre, 30463 1216, release_year, 724 34744, has_genre, 30463 34744, release_year, 724 37601, has_genre, 30463 37601, release_year, 724 13302, has_genre, 30463 13302, release_year, 724 38678, has_genre, 30463 38678, release_year, 724 19367, has_genre, 30463 19367, release_year, 724 35760, has_genre, 30463 35760, release_year, 724 20263, has_genre, 30463 20263, release_year, 724 11331, has_genre, 30463 11331, release_year, 724 33790, has_genre, 30463 33790, has_tags, 30463 33790, release_year, 724 6108, has_genre, 30463 6108, release_year, 724 26484, has_genre, 30463 26484, release_year, 724 14797, has_genre, 4763 14797, has_genre, 30463 14797, has_tags, 4763 14797, has_tags, 30463 14797, has_tags, 15436 14797, written_by, 15547 6773, has_genre, 30463 6773, release_year, 724 22107, has_genre, 30463 22107, release_year, 724 27231, has_genre, 30463 27231, release_year, 724 16018, has_genre, 30463 16018, release_year, 724 28510, has_genre, 30463 28510, release_year, 724 19104, has_genre, 30463 19104, release_year, 724 33024, has_genre, 30463 33024, release_year, 724 4091, has_genre, 30463 4091, release_year, 724 32382, has_genre, 30463 32382, release_year, 724 12809, has_genre, 30463 12809, release_year, 724 31851, has_genre, 30463 31851, release_year, 724 26036, has_genre, 30463 26036, release_year, 724 33449, has_genre, 30463 5729, has_genre, 4763 5729, has_tags, 15436 5729, has_tags, 15547 5729, written_by, 15547 32079, has_genre, 4763 32079, has_tags, 15547 32079, written_by, 15547 31435, has_genre, 30463 31435, release_year, 724 22774, has_genre, 30463 22774, release_year, 724 Question: In what context are A FORCE OF ONE, HOMER, and THE WEDDING PLANNER connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A FORCE OF ONE", "HOMER", "THE WEDDING PLANNER" ], "valid_edges": [ [ "10", "has_genre", "COMEDY" ], [ "10", "release_year", "1979" ], [ "1941", "has_genre", "COMEDY" ], [ "1941", "release_year", "1979" ], [ "A FORCE OF ONE", "release_year", "1979" ], [ "A LITTLE ROMANCE", "has_genre", "COMEDY" ], [ "A LITTLE ROMANCE", "release_year", "1979" ], [ "AMERICATHON", "has_genre", "COMEDY" ], [ "AMERICATHON", "release_year", "1979" ], [ "BEING THERE", "has_genre", "COMEDY" ], [ "BEING THERE", "release_year", "1979" ], [ "BREAKING AWAY", "has_genre", "COMEDY" ], [ "BREAKING AWAY", "release_year", "1979" ], [ "CHAPTER TWO", "has_genre", "COMEDY" ], [ "CHAPTER TWO", "release_year", "1979" ], [ "CHILLY SCENES OF WINTER", "has_genre", "COMEDY" ], [ "CHILLY SCENES OF WINTER", "release_year", "1979" ], [ "ESCAPE TO ATHENA", "has_genre", "COMEDY" ], [ "ESCAPE TO ATHENA", "release_year", "1979" ], [ "H.O.T.S.", "has_genre", "COMEDY" ], [ "H.O.T.S.", "release_year", "1979" ], [ "HAIR", "has_genre", "COMEDY" ], [ "HAIR", "release_year", "1979" ], [ "LOVE AT FIRST BITE", "has_genre", "COMEDY" ], [ "LOVE AT FIRST BITE", "release_year", "1979" ], [ "MANHATTAN", "has_genre", "COMEDY" ], [ "MANHATTAN", "has_tags", "COMEDY" ], [ "MANHATTAN", "release_year", "1979" ], [ "MEATBALLS", "has_genre", "COMEDY" ], [ "MEATBALLS", "release_year", "1979" ], [ "MORE AMERICAN GRAFFITI", "has_genre", "COMEDY" ], [ "MORE AMERICAN GRAFFITI", "release_year", "1979" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_genre", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "ADVENTURE" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "COMEDY" ], [ "O BROTHER, WHERE ART THOU?", "has_tags", "EPIC" ], [ "O BROTHER, WHERE ART THOU?", "written_by", "HOMER" ], [ "REAL LIFE", "has_genre", "COMEDY" ], [ "REAL LIFE", "release_year", "1979" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "has_genre", "COMEDY" ], [ "ROCK 'N' ROLL HIGH SCHOOL", "release_year", "1979" ], [ "STARTING OVER", "has_genre", "COMEDY" ], [ "STARTING OVER", "release_year", "1979" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "has_genre", "COMEDY" ], [ "THE APPLE DUMPLING GANG RIDES AGAIN", "release_year", "1979" ], [ "THE FRISCO KID", "has_genre", "COMEDY" ], [ "THE FRISCO KID", "release_year", "1979" ], [ "THE IN-LAWS", "has_genre", "COMEDY" ], [ "THE IN-LAWS", "release_year", "1979" ], [ "THE JERK", "has_genre", "COMEDY" ], [ "THE JERK", "release_year", "1979" ], [ "THE LADY VANISHES", "has_genre", "COMEDY" ], [ "THE LADY VANISHES", "release_year", "1979" ], [ "THE MAIN EVENT", "has_genre", "COMEDY" ], [ "THE MAIN EVENT", "release_year", "1979" ], [ "THE MUPPET MOVIE", "has_genre", "COMEDY" ], [ "THE MUPPET MOVIE", "release_year", "1979" ], [ "THE PRISONER OF ZENDA", "has_genre", "COMEDY" ], [ "THE PRISONER OF ZENDA", "release_year", "1979" ], [ "THE TEMPEST", "has_genre", "COMEDY" ], [ "THE TEMPEST", "release_year", "1979" ], [ "THE WEDDING PLANNER", "has_genre", "COMEDY" ], [ "TROY", "has_genre", "ADVENTURE" ], [ "TROY", "has_tags", "EPIC" ], [ "TROY", "has_tags", "HOMER" ], [ "TROY", "written_by", "HOMER" ], [ "ULYSSES", "has_genre", "ADVENTURE" ], [ "ULYSSES", "has_tags", "HOMER" ], [ "ULYSSES", "written_by", "HOMER" ], [ "UNCLE MARIN, THE BILLIONAIRE", "has_genre", "COMEDY" ], [ "UNCLE MARIN, THE BILLIONAIRE", "release_year", "1979" ], [ "WISE BLOOD", "has_genre", "COMEDY" ], [ "WISE BLOOD", "release_year", "1979" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 21136, 10 MINUTES 3458, 1951 35935, 2002 4310, 24 HOUR PARTY PEOPLE 11069, 25TH HOUR 37315, A BRONX TALE 30846, A WALK TO REMEMBER 6008, ABOUT A BOY 37599, ABOUT SCHMIDT 27949, AKA 35288, ALL OR NOTHING 20584, AMERICAN GANGSTER 26599, AMERICAN GUN 28374, ANTWONE FISHER 24409, ARARAT 23513, ASH WEDNESDAY 20199, AUTO FOCUS 12144, BAD BOYS 10516, BANG BANG YOU'RE DEAD 10045, BD-R 12954, BEAR'S KISS 15433, BEND IT LIKE BECKHAM 12228, BETTER LUCK TOMORROW 36708, BLUE CAR 22703, BOMB THE SYSTEM 16809, BOYS' NIGHT OUT 1637, BOYZ N THE HOOD 23286, CARNAGE 27059, CATCH ME IF YOU CAN 26946, CHANGING LANES 20073, CHERISH 10349, CHICAGO 61, CITY OF GHOSTS 33387, CITY OF GOD 30463, COMEDY 14724, CRIME 30019, CROSSROADS 16536, CYRANO DE BERGERAC 21730, DAY OF THE WACKO 24410, DEMONLOVER 30729, DENZEL WASHINGTON 30734, DEREK LUKE 23027, DEUCES WILD 31163, DIRECTORIAL DEBUT 9641, DIRTY PRETTY THINGS 32958, DIVINE SECRETS OF THE YA-YA SISTERHOOD 38750, DRAGONFLY 36212, DRAMA 25651, DUMMY 26714, EDGE OF MADNESS 12259, ENOUGH 11866, EVELYN 11422, FAR FROM HEAVEN 5563, FLIGHT 6012, FRENCH 23808, G 17400, GANGS OF NEW YORK 34145, GEORGES DARIEN 9759, GLORY 14023, GLORY ROAD 36646, HE GOT GAME 951, HEART OF AMERICA 10990, HEARTLANDS 39351, HEAVY 1292, HEDWIG AND THE ANGRY INCH 17118, HENRY V 3829, HERO 19943, HOUSE OF FOOLS 22024, I CAN GET IT FOR YOU WHOLESALE 17197, IGBY GOES DOWN 19412, IN AMERICA 25271, IN THIS WORLD 6092, INTERVIEW WITH THE ASSASSIN 6713, KAMCHATKA 30206, KEN PARK 29840, LAUREL CANYON 26893, LITTLE MAN TATE 26784, LITTLE WOMEN 39755, LIVE FROM BAGHDAD 17395, LUSTER 10058, MADAME SATÃ 19549, MALCOLM X 2445, MAX 23502, MICHAEL GORDON 14165, MISSISSIPPI MASALA 37076, MO' BETTER BLUES 1052, MOONLIGHT MILE 34696, MORVERN CALLAR 35534, MUJHSE DOSTI KAROGE! 38585, NICHOLAS NICKLEBY 25269, NINE LIVES 26644, OK 11093, OPEN HEARTS 22991, OUT OF THE BLUE 32999, PAID IN FULL 11222, PATHER PANCHALI 14744, PEOPLE I KNOW 3389, PHILADELPHIA 6579, PILLOW TALK 5286, POOLHALL JUNKIES 31588, PORTRAIT IN BLACK 39284, POSSESSION 34602, PUNCH-DRUNK LOVE 25023, QUARTET 24073, RABBIT-PROOF FENCE 5193, REMEMBER THE TITANS 25769, ROGER DODGER 10881, SAFE CONDUCT 22312, SAY ANYTHING... 25921, SOAP GIRL 6014, SOLARIS 7083, SONNY 35843, SPUN 39016, STOLEN SUMMER 28935, SUNSHINE STATE 33414, SWEET SIXTEEN 26790, SWEPT AWAY 32105, SYNECDOCHE, NEW YORK 9972, TALK TO HER 34235, TEXAS ACROSS THE RIVER 40106, THE ADVERSARY 2316, THE ANARCHIST COOKBOOK 38704, THE BRIDGE TO NOWHERE 19351, THE COUNT OF MONTE CRISTO 11696, THE CUCKOO 3324, THE DANGEROUS LIVES OF ALTAR BOYS 13044, THE EMPEROR'S CLUB 9522, THE ESCAPIST 11635, THE FOUR FEATHERS 10213, THE GREAT DEBATERS 31443, THE GUYS 11713, THE HOURS 13534, THE IMPORTANCE OF BEING EARNEST 32805, THE INTENDED 16288, THE LARAMIE PROJECT 36676, THE MAN WITHOUT A FACE 2147, THE MAN WITHOUT A PAST 12614, THE PIANIST 13761, THE ROOKIE 31401, THE RULES OF ATTRACTION 38139, THE SECRET LIFE OF ZOEY 18326, THE SECRET LIVES OF DENTISTS 28829, THE SECRET OF CONVICT LAKE 8251, THE SECRET OF NIMH 11654, THE THIEF OF PARIS 27415, THE THREE MARIAS 39555, THE TRACKER 32772, UNFAITHFUL 4705, WAITING FOR HAPPINESS 8949, WE WERE SOLDIERS 36026, WESTERN 40043, WHALE RIDER 19262, WHIP IT 13026, WHITE OLEANDER 18995, XX/XY src, edge_attr, dst 21136, has_genre, 36212 21136, release_year, 35935 4310, has_genre, 36212 4310, release_year, 35935 11069, has_genre, 36212 11069, release_year, 35935 37315, has_genre, 36212 37315, has_tags, 31163 30846, has_genre, 36212 30846, has_tags, 36212 30846, release_year, 35935 6008, has_genre, 36212 6008, has_tags, 36212 6008, release_year, 35935 37599, has_genre, 36212 37599, has_tags, 36212 37599, release_year, 35935 27949, has_genre, 36212 27949, release_year, 35935 35288, has_genre, 36212 35288, release_year, 35935 20584, has_genre, 36212 20584, has_tags, 30729 20584, starred_actors, 30729 26599, has_genre, 36212 26599, release_year, 35935 28374, directed_by, 30729 28374, has_genre, 36212 28374, has_tags, 30729 28374, has_tags, 31163 28374, has_tags, 26644 28374, release_year, 35935 28374, starred_actors, 30729 28374, starred_actors, 30734 28374, written_by, 28374 24409, has_genre, 36212 24409, release_year, 35935 23513, has_genre, 36212 23513, release_year, 35935 20199, has_genre, 36212 20199, release_year, 35935 12144, has_genre, 36212 12144, has_tags, 31163 10516, has_genre, 36212 10516, release_year, 35935 12954, has_genre, 36212 12954, release_year, 35935 15433, has_genre, 36212 15433, release_year, 35935 12228, has_genre, 36212 12228, release_year, 35935 36708, has_genre, 36212 36708, release_year, 35935 22703, has_genre, 36212 22703, release_year, 35935 16809, directed_by, 23502 16809, has_genre, 30463 1637, has_genre, 36212 1637, has_tags, 31163 1637, has_tags, 36212 23286, has_genre, 36212 23286, release_year, 35935 27059, has_genre, 36212 27059, has_tags, 36212 27059, release_year, 35935 26946, has_genre, 36212 26946, release_year, 35935 20073, has_genre, 36212 20073, release_year, 35935 10349, has_genre, 36212 10349, release_year, 35935 61, has_genre, 36212 61, release_year, 35935 33387, has_genre, 36212 33387, has_tags, 36212 33387, release_year, 35935 30019, has_genre, 36212 30019, release_year, 35935 16536, directed_by, 23502 16536, has_genre, 30463 16536, has_genre, 36212 16536, has_tags, 10045 16536, has_tags, 36212 16536, has_tags, 6012 16536, has_tags, 23502 16536, in_language, 6012 21730, has_genre, 36212 21730, release_year, 35935 24410, has_genre, 36212 24410, release_year, 35935 23027, has_genre, 36212 23027, release_year, 35935 9641, has_genre, 36212 9641, release_year, 35935 32958, has_genre, 36212 32958, release_year, 35935 38750, has_genre, 36212 38750, release_year, 35935 25651, has_genre, 36212 25651, release_year, 35935 26714, has_genre, 36212 26714, release_year, 35935 12259, has_genre, 36212 12259, release_year, 35935 11866, has_genre, 36212 11866, release_year, 35935 11422, has_genre, 36212 11422, release_year, 35935 5563, has_genre, 36212 5563, has_tags, 30729 5563, starred_actors, 30729 23808, has_genre, 36212 23808, release_year, 35935 17400, has_genre, 36212 17400, release_year, 35935 9759, has_genre, 36212 9759, has_tags, 30729 9759, starred_actors, 30729 14023, has_genre, 36212 14023, starred_actors, 30734 36646, has_genre, 36212 36646, starred_actors, 30729 951, has_genre, 36212 951, release_year, 35935 10990, has_genre, 36212 10990, release_year, 35935 39351, has_genre, 36212 39351, has_tags, 31163 1292, has_genre, 36212 1292, has_tags, 31163 17118, has_genre, 36212 17118, has_tags, 31163 3829, has_genre, 36212 3829, release_year, 35935 19943, has_genre, 36212 19943, release_year, 35935 22024, directed_by, 23502 22024, has_genre, 36212 22024, release_year, 3458 17197, has_genre, 36212 17197, release_year, 35935 19412, has_genre, 36212 19412, release_year, 35935 25271, has_genre, 36212 25271, release_year, 35935 6092, has_genre, 36212 6092, release_year, 35935 6713, has_genre, 36212 6713, release_year, 35935 30206, has_genre, 36212 30206, release_year, 35935 29840, has_genre, 36212 29840, release_year, 35935 26893, has_genre, 36212 26893, has_tags, 31163 26784, has_genre, 36212 26784, has_tags, 36212 26784, has_tags, 26644 39755, has_genre, 36212 39755, release_year, 35935 17395, has_genre, 36212 17395, release_year, 35935 10058, has_genre, 36212 10058, release_year, 35935 19549, has_genre, 36212 19549, has_tags, 30729 19549, starred_actors, 30729 2445, has_genre, 36212 2445, release_year, 35935 14165, has_genre, 36212 14165, starred_actors, 30729 37076, has_genre, 36212 37076, starred_actors, 30729 1052, has_genre, 36212 1052, release_year, 35935 34696, has_genre, 36212 34696, release_year, 35935 35534, has_genre, 36212 35534, release_year, 35935 38585, has_genre, 36212 38585, release_year, 35935 25269, has_genre, 36212 25269, release_year, 35935 11093, has_genre, 36212 11093, has_tags, 36212 11093, release_year, 35935 22991, has_genre, 36212 22991, release_year, 35935 32999, has_genre, 36212 32999, release_year, 35935 11222, has_genre, 36212 11222, has_tags, 31163 14744, has_genre, 36212 14744, release_year, 35935 3389, has_genre, 36212 3389, has_tags, 30729 3389, starred_actors, 30729 6579, directed_by, 23502 6579, has_genre, 30463 6579, has_tags, 10045 6579, has_tags, 30463 6579, has_tags, 23502 5286, has_genre, 36212 5286, release_year, 35935 31588, directed_by, 23502 31588, has_genre, 14724 31588, has_genre, 36212 39284, has_genre, 36212 39284, release_year, 35935 34602, has_genre, 36212 34602, release_year, 35935 25023, has_genre, 36212 25023, has_tags, 31163 24073, has_genre, 36212 24073, release_year, 35935 5193, has_genre, 36212 5193, has_tags, 30729 5193, has_tags, 36212 5193, starred_actors, 30729 25769, has_genre, 36212 25769, release_year, 35935 10881, has_genre, 36212 10881, release_year, 35935 22312, has_genre, 36212 22312, has_tags, 31163 25921, has_genre, 36212 25921, release_year, 35935 6014, has_genre, 36212 6014, release_year, 35935 7083, has_genre, 36212 7083, release_year, 35935 35843, has_genre, 36212 35843, release_year, 35935 39016, has_genre, 36212 39016, release_year, 35935 28935, has_genre, 36212 28935, release_year, 35935 33414, has_genre, 36212 33414, release_year, 35935 26790, has_genre, 36212 26790, release_year, 35935 32105, has_genre, 36212 32105, has_tags, 31163 9972, has_genre, 36212 9972, has_tags, 36212 9972, release_year, 35935 34235, directed_by, 23502 34235, has_genre, 30463 34235, has_genre, 36026 40106, has_genre, 36212 40106, release_year, 35935 2316, has_genre, 36212 2316, release_year, 35935 38704, has_genre, 36212 38704, has_tags, 31163 19351, has_genre, 36212 19351, release_year, 35935 11696, has_genre, 36212 11696, release_year, 35935 3324, has_genre, 36212 3324, release_year, 35935 13044, has_genre, 36212 13044, release_year, 35935 9522, has_genre, 36212 9522, release_year, 35935 11635, has_genre, 36212 11635, release_year, 35935 10213, directed_by, 30729 10213, has_genre, 36212 10213, has_tags, 30729 10213, starred_actors, 30729 31443, has_genre, 36212 31443, release_year, 35935 11713, has_genre, 36212 11713, has_tags, 36212 11713, release_year, 35935 13534, has_genre, 36212 13534, release_year, 35935 32805, has_genre, 36212 32805, release_year, 35935 16288, has_genre, 36212 16288, release_year, 35935 36676, has_genre, 36212 36676, has_tags, 31163 36676, has_tags, 36212 2147, has_genre, 36212 2147, has_tags, 36212 2147, release_year, 35935 12614, has_genre, 36212 12614, has_tags, 36212 12614, release_year, 35935 13761, has_genre, 36212 13761, release_year, 35935 31401, has_genre, 36212 31401, release_year, 35935 38139, has_genre, 36212 38139, release_year, 35935 18326, has_genre, 36212 18326, release_year, 35935 28829, directed_by, 23502 28829, has_genre, 36026 28829, release_year, 3458 8251, has_genre, 36212 8251, has_tags, 31163 11654, has_genre, 14724 11654, in_language, 6012 11654, written_by, 34145 27415, has_genre, 36212 27415, release_year, 35935 39555, has_genre, 36212 39555, release_year, 35935 32772, has_genre, 36212 32772, release_year, 35935 4705, has_genre, 36212 4705, release_year, 35935 8949, has_genre, 36212 8949, release_year, 35935 40043, has_genre, 36212 40043, has_tags, 36212 40043, release_year, 35935 19262, has_genre, 36212 19262, has_tags, 31163 13026, has_genre, 36212 13026, release_year, 35935 18995, has_genre, 36212 18995, release_year, 35935 Question: For what reason are ANTWONE FISHER, GEORGES DARIEN, and MICHAEL GORDON associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANTWONE FISHER", "GEORGES DARIEN", "MICHAEL GORDON" ], "valid_edges": [ [ "10 MINUTES", "has_genre", "DRAMA" ], [ "10 MINUTES", "release_year", "2002" ], [ "24 HOUR PARTY PEOPLE", "has_genre", "DRAMA" ], [ "24 HOUR PARTY PEOPLE", "release_year", "2002" ], [ "25TH HOUR", "has_genre", "DRAMA" ], [ "25TH HOUR", "release_year", "2002" ], [ "A BRONX TALE", "has_genre", "DRAMA" ], [ "A BRONX TALE", "has_tags", "DIRECTORIAL DEBUT" ], [ "A WALK TO REMEMBER", "has_genre", "DRAMA" ], [ "A WALK TO REMEMBER", "has_tags", "DRAMA" ], [ "A WALK TO REMEMBER", "release_year", "2002" ], [ "ABOUT A BOY", "has_genre", "DRAMA" ], [ "ABOUT A BOY", "has_tags", "DRAMA" ], [ "ABOUT A BOY", "release_year", "2002" ], [ "ABOUT SCHMIDT", "has_genre", "DRAMA" ], [ "ABOUT SCHMIDT", "has_tags", "DRAMA" ], [ "ABOUT SCHMIDT", "release_year", "2002" ], [ "AKA", "has_genre", "DRAMA" ], [ "AKA", "release_year", "2002" ], [ "ALL OR NOTHING", "has_genre", "DRAMA" ], [ "ALL OR NOTHING", "release_year", "2002" ], [ "AMERICAN GANGSTER", "has_genre", "DRAMA" ], [ "AMERICAN GANGSTER", "has_tags", "DENZEL WASHINGTON" ], [ "AMERICAN GANGSTER", "starred_actors", "DENZEL WASHINGTON" ], [ "AMERICAN GUN", "has_genre", "DRAMA" ], [ "AMERICAN GUN", "release_year", "2002" ], [ "ANTWONE FISHER", "directed_by", "DENZEL WASHINGTON" ], [ "ANTWONE FISHER", "has_genre", "DRAMA" ], [ "ANTWONE FISHER", "has_tags", "DENZEL WASHINGTON" ], [ "ANTWONE FISHER", "has_tags", "DIRECTORIAL DEBUT" ], [ "ANTWONE FISHER", "has_tags", "OK" ], [ "ANTWONE FISHER", "release_year", "2002" ], [ "ANTWONE FISHER", "starred_actors", "DENZEL WASHINGTON" ], [ "ANTWONE FISHER", "starred_actors", "DEREK LUKE" ], [ "ANTWONE FISHER", "written_by", "ANTWONE FISHER" ], [ "ARARAT", "has_genre", "DRAMA" ], [ "ARARAT", "release_year", "2002" ], [ "ASH WEDNESDAY", "has_genre", "DRAMA" ], [ "ASH WEDNESDAY", "release_year", "2002" ], [ "AUTO FOCUS", "has_genre", "DRAMA" ], [ "AUTO FOCUS", "release_year", "2002" ], [ "BAD BOYS", "has_genre", "DRAMA" ], [ "BAD BOYS", "has_tags", "DIRECTORIAL DEBUT" ], [ "BANG BANG YOU'RE DEAD", "has_genre", "DRAMA" ], [ "BANG BANG YOU'RE DEAD", "release_year", "2002" ], [ "BEAR'S KISS", "has_genre", "DRAMA" ], [ "BEAR'S KISS", "release_year", "2002" ], [ "BEND IT LIKE BECKHAM", "has_genre", "DRAMA" ], [ "BEND IT LIKE BECKHAM", "release_year", "2002" ], [ "BETTER LUCK TOMORROW", "has_genre", "DRAMA" ], [ "BETTER LUCK TOMORROW", "release_year", "2002" ], [ "BLUE CAR", "has_genre", "DRAMA" ], [ "BLUE CAR", "release_year", "2002" ], [ "BOMB THE SYSTEM", "has_genre", "DRAMA" ], [ "BOMB THE SYSTEM", "release_year", "2002" ], [ "BOYS' NIGHT OUT", "directed_by", "MICHAEL GORDON" ], [ "BOYS' NIGHT OUT", "has_genre", "COMEDY" ], [ "BOYZ N THE HOOD", "has_genre", "DRAMA" ], [ "BOYZ N THE HOOD", "has_tags", "DIRECTORIAL DEBUT" ], [ "BOYZ N THE HOOD", "has_tags", "DRAMA" ], [ "CARNAGE", "has_genre", "DRAMA" ], [ "CARNAGE", "release_year", "2002" ], [ "CATCH ME IF YOU CAN", "has_genre", "DRAMA" ], [ "CATCH ME IF YOU CAN", "has_tags", "DRAMA" ], [ "CATCH ME IF YOU CAN", "release_year", "2002" ], [ "CHANGING LANES", "has_genre", "DRAMA" ], [ "CHANGING LANES", "release_year", "2002" ], [ "CHERISH", "has_genre", "DRAMA" ], [ "CHERISH", "release_year", "2002" ], [ "CHICAGO", "has_genre", "DRAMA" ], [ "CHICAGO", "release_year", "2002" ], [ "CITY OF GHOSTS", "has_genre", "DRAMA" ], [ "CITY OF GHOSTS", "release_year", "2002" ], [ "CITY OF GOD", "has_genre", "DRAMA" ], [ "CITY OF GOD", "has_tags", "DRAMA" ], [ "CITY OF GOD", "release_year", "2002" ], [ "CROSSROADS", "has_genre", "DRAMA" ], [ "CROSSROADS", "release_year", "2002" ], [ "CYRANO DE BERGERAC", "directed_by", "MICHAEL GORDON" ], [ "CYRANO DE BERGERAC", "has_genre", "COMEDY" ], [ "CYRANO DE BERGERAC", "has_genre", "DRAMA" ], [ "CYRANO DE BERGERAC", "has_tags", "BD-R" ], [ "CYRANO DE BERGERAC", "has_tags", "DRAMA" ], [ "CYRANO DE BERGERAC", "has_tags", "FRENCH" ], [ "CYRANO DE BERGERAC", "has_tags", "MICHAEL GORDON" ], [ "CYRANO DE BERGERAC", "in_language", "FRENCH" ], [ "DAY OF THE WACKO", "has_genre", "DRAMA" ], [ "DAY OF THE WACKO", "release_year", "2002" ], [ "DEMONLOVER", "has_genre", "DRAMA" ], [ "DEMONLOVER", "release_year", "2002" ], [ "DEUCES WILD", "has_genre", "DRAMA" ], [ "DEUCES WILD", "release_year", "2002" ], [ "DIRTY PRETTY THINGS", "has_genre", "DRAMA" ], [ "DIRTY PRETTY THINGS", "release_year", "2002" ], [ "DIVINE SECRETS OF THE YA-YA SISTERHOOD", "has_genre", "DRAMA" ], [ "DIVINE SECRETS OF THE YA-YA SISTERHOOD", "release_year", "2002" ], [ "DRAGONFLY", "has_genre", "DRAMA" ], [ "DRAGONFLY", "release_year", "2002" ], [ "DUMMY", "has_genre", "DRAMA" ], [ "DUMMY", "release_year", "2002" ], [ "EDGE OF MADNESS", "has_genre", "DRAMA" ], [ "EDGE OF MADNESS", "release_year", "2002" ], [ "ENOUGH", "has_genre", "DRAMA" ], [ "ENOUGH", "release_year", "2002" ], [ "EVELYN", "has_genre", "DRAMA" ], [ "EVELYN", "release_year", "2002" ], [ "FAR FROM HEAVEN", "has_genre", "DRAMA" ], [ "FAR FROM HEAVEN", "release_year", "2002" ], [ "FLIGHT", "has_genre", "DRAMA" ], [ "FLIGHT", "has_tags", "DENZEL WASHINGTON" ], [ "FLIGHT", "starred_actors", "DENZEL WASHINGTON" ], [ "G", "has_genre", "DRAMA" ], [ "G", "release_year", "2002" ], [ "GANGS OF NEW YORK", "has_genre", "DRAMA" ], [ "GANGS OF NEW YORK", "release_year", "2002" ], [ "GLORY", "has_genre", "DRAMA" ], [ "GLORY", "has_tags", "DENZEL WASHINGTON" ], [ "GLORY", "starred_actors", "DENZEL WASHINGTON" ], [ "GLORY ROAD", "has_genre", "DRAMA" ], [ "GLORY ROAD", "starred_actors", "DEREK LUKE" ], [ "HE GOT GAME", "has_genre", "DRAMA" ], [ "HE GOT GAME", "starred_actors", "DENZEL WASHINGTON" ], [ "HEART OF AMERICA", "has_genre", "DRAMA" ], [ "HEART OF AMERICA", "release_year", "2002" ], [ "HEARTLANDS", "has_genre", "DRAMA" ], [ "HEARTLANDS", "release_year", "2002" ], [ "HEAVY", "has_genre", "DRAMA" ], [ "HEAVY", "has_tags", "DIRECTORIAL DEBUT" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "DRAMA" ], [ "HEDWIG AND THE ANGRY INCH", "has_tags", "DIRECTORIAL DEBUT" ], [ "HENRY V", "has_genre", "DRAMA" ], [ "HENRY V", "has_tags", "DIRECTORIAL DEBUT" ], [ "HERO", "has_genre", "DRAMA" ], [ "HERO", "release_year", "2002" ], [ "HOUSE OF FOOLS", "has_genre", "DRAMA" ], [ "HOUSE OF FOOLS", "release_year", "2002" ], [ "I CAN GET IT FOR YOU WHOLESALE", "directed_by", "MICHAEL GORDON" ], [ "I CAN GET IT FOR YOU WHOLESALE", "has_genre", "DRAMA" ], [ "I CAN GET IT FOR YOU WHOLESALE", "release_year", "1951" ], [ "IGBY GOES DOWN", "has_genre", "DRAMA" ], [ "IGBY GOES DOWN", "release_year", "2002" ], [ "IN AMERICA", "has_genre", "DRAMA" ], [ "IN AMERICA", "release_year", "2002" ], [ "IN THIS WORLD", "has_genre", "DRAMA" ], [ "IN THIS WORLD", "release_year", "2002" ], [ "INTERVIEW WITH THE ASSASSIN", "has_genre", "DRAMA" ], [ "INTERVIEW WITH THE ASSASSIN", "release_year", "2002" ], [ "KAMCHATKA", "has_genre", "DRAMA" ], [ "KAMCHATKA", "release_year", "2002" ], [ "KEN PARK", "has_genre", "DRAMA" ], [ "KEN PARK", "release_year", "2002" ], [ "LAUREL CANYON", "has_genre", "DRAMA" ], [ "LAUREL CANYON", "release_year", "2002" ], [ "LITTLE MAN TATE", "has_genre", "DRAMA" ], [ "LITTLE MAN TATE", "has_tags", "DIRECTORIAL DEBUT" ], [ "LITTLE WOMEN", "has_genre", "DRAMA" ], [ "LITTLE WOMEN", "has_tags", "DRAMA" ], [ "LITTLE WOMEN", "has_tags", "OK" ], [ "LIVE FROM BAGHDAD", "has_genre", "DRAMA" ], [ "LIVE FROM BAGHDAD", "release_year", "2002" ], [ "LUSTER", "has_genre", "DRAMA" ], [ "LUSTER", "release_year", "2002" ], [ "MADAME SATÃ", "has_genre", "DRAMA" ], [ "MADAME SATÃ", "release_year", "2002" ], [ "MALCOLM X", "has_genre", "DRAMA" ], [ "MALCOLM X", "has_tags", "DENZEL WASHINGTON" ], [ "MALCOLM X", "starred_actors", "DENZEL WASHINGTON" ], [ "MAX", "has_genre", "DRAMA" ], [ "MAX", "release_year", "2002" ], [ "MISSISSIPPI MASALA", "has_genre", "DRAMA" ], [ "MISSISSIPPI MASALA", "starred_actors", "DENZEL WASHINGTON" ], [ "MO' BETTER BLUES", "has_genre", "DRAMA" ], [ "MO' BETTER BLUES", "starred_actors", "DENZEL WASHINGTON" ], [ "MOONLIGHT MILE", "has_genre", "DRAMA" ], [ "MOONLIGHT MILE", "release_year", "2002" ], [ "MORVERN CALLAR", "has_genre", "DRAMA" ], [ "MORVERN CALLAR", "release_year", "2002" ], [ "MUJHSE DOSTI KAROGE!", "has_genre", "DRAMA" ], [ "MUJHSE DOSTI KAROGE!", "release_year", "2002" ], [ "NICHOLAS NICKLEBY", "has_genre", "DRAMA" ], [ "NICHOLAS NICKLEBY", "release_year", "2002" ], [ "NINE LIVES", "has_genre", "DRAMA" ], [ "NINE LIVES", "release_year", "2002" ], [ "OPEN HEARTS", "has_genre", "DRAMA" ], [ "OPEN HEARTS", "has_tags", "DRAMA" ], [ "OPEN HEARTS", "release_year", "2002" ], [ "OUT OF THE BLUE", "has_genre", "DRAMA" ], [ "OUT OF THE BLUE", "release_year", "2002" ], [ "PAID IN FULL", "has_genre", "DRAMA" ], [ "PAID IN FULL", "release_year", "2002" ], [ "PATHER PANCHALI", "has_genre", "DRAMA" ], [ "PATHER PANCHALI", "has_tags", "DIRECTORIAL DEBUT" ], [ "PEOPLE I KNOW", "has_genre", "DRAMA" ], [ "PEOPLE I KNOW", "release_year", "2002" ], [ "PHILADELPHIA", "has_genre", "DRAMA" ], [ "PHILADELPHIA", "has_tags", "DENZEL WASHINGTON" ], [ "PHILADELPHIA", "starred_actors", "DENZEL WASHINGTON" ], [ "PILLOW TALK", "directed_by", "MICHAEL GORDON" ], [ "PILLOW TALK", "has_genre", "COMEDY" ], [ "PILLOW TALK", "has_tags", "BD-R" ], [ "PILLOW TALK", "has_tags", "COMEDY" ], [ "PILLOW TALK", "has_tags", "MICHAEL GORDON" ], [ "POOLHALL JUNKIES", "has_genre", "DRAMA" ], [ "POOLHALL JUNKIES", "release_year", "2002" ], [ "PORTRAIT IN BLACK", "directed_by", "MICHAEL GORDON" ], [ "PORTRAIT IN BLACK", "has_genre", "CRIME" ], [ "PORTRAIT IN BLACK", "has_genre", "DRAMA" ], [ "POSSESSION", "has_genre", "DRAMA" ], [ "POSSESSION", "release_year", "2002" ], [ "PUNCH-DRUNK LOVE", "has_genre", "DRAMA" ], [ "PUNCH-DRUNK LOVE", "release_year", "2002" ], [ "QUARTET", "has_genre", "DRAMA" ], [ "QUARTET", "has_tags", "DIRECTORIAL DEBUT" ], [ "RABBIT-PROOF FENCE", "has_genre", "DRAMA" ], [ "RABBIT-PROOF FENCE", "release_year", "2002" ], [ "REMEMBER THE TITANS", "has_genre", "DRAMA" ], [ "REMEMBER THE TITANS", "has_tags", "DENZEL WASHINGTON" ], [ "REMEMBER THE TITANS", "has_tags", "DRAMA" ], [ "REMEMBER THE TITANS", "starred_actors", "DENZEL WASHINGTON" ], [ "ROGER DODGER", "has_genre", "DRAMA" ], [ "ROGER DODGER", "release_year", "2002" ], [ "SAFE CONDUCT", "has_genre", "DRAMA" ], [ "SAFE CONDUCT", "release_year", "2002" ], [ "SAY ANYTHING...", "has_genre", "DRAMA" ], [ "SAY ANYTHING...", "has_tags", "DIRECTORIAL DEBUT" ], [ "SOAP GIRL", "has_genre", "DRAMA" ], [ "SOAP GIRL", "release_year", "2002" ], [ "SOLARIS", "has_genre", "DRAMA" ], [ "SOLARIS", "release_year", "2002" ], [ "SONNY", "has_genre", "DRAMA" ], [ "SONNY", "release_year", "2002" ], [ "SPUN", "has_genre", "DRAMA" ], [ "SPUN", "release_year", "2002" ], [ "STOLEN SUMMER", "has_genre", "DRAMA" ], [ "STOLEN SUMMER", "release_year", "2002" ], [ "SUNSHINE STATE", "has_genre", "DRAMA" ], [ "SUNSHINE STATE", "release_year", "2002" ], [ "SWEET SIXTEEN", "has_genre", "DRAMA" ], [ "SWEET SIXTEEN", "release_year", "2002" ], [ "SWEPT AWAY", "has_genre", "DRAMA" ], [ "SWEPT AWAY", "release_year", "2002" ], [ "SYNECDOCHE, NEW YORK", "has_genre", "DRAMA" ], [ "SYNECDOCHE, NEW YORK", "has_tags", "DIRECTORIAL DEBUT" ], [ "TALK TO HER", "has_genre", "DRAMA" ], [ "TALK TO HER", "has_tags", "DRAMA" ], [ "TALK TO HER", "release_year", "2002" ], [ "TEXAS ACROSS THE RIVER", "directed_by", "MICHAEL GORDON" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "COMEDY" ], [ "TEXAS ACROSS THE RIVER", "has_genre", "WESTERN" ], [ "THE ADVERSARY", "has_genre", "DRAMA" ], [ "THE ADVERSARY", "release_year", "2002" ], [ "THE ANARCHIST COOKBOOK", "has_genre", "DRAMA" ], [ "THE ANARCHIST COOKBOOK", "release_year", "2002" ], [ "THE BRIDGE TO NOWHERE", "has_genre", "DRAMA" ], [ "THE BRIDGE TO NOWHERE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE COUNT OF MONTE CRISTO", "has_genre", "DRAMA" ], [ "THE COUNT OF MONTE CRISTO", "release_year", "2002" ], [ "THE CUCKOO", "has_genre", "DRAMA" ], [ "THE CUCKOO", "release_year", "2002" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "has_genre", "DRAMA" ], [ "THE DANGEROUS LIVES OF ALTAR BOYS", "release_year", "2002" ], [ "THE EMPEROR'S CLUB", "has_genre", "DRAMA" ], [ "THE EMPEROR'S CLUB", "release_year", "2002" ], [ "THE ESCAPIST", "has_genre", "DRAMA" ], [ "THE ESCAPIST", "release_year", "2002" ], [ "THE FOUR FEATHERS", "has_genre", "DRAMA" ], [ "THE FOUR FEATHERS", "release_year", "2002" ], [ "THE GREAT DEBATERS", "directed_by", "DENZEL WASHINGTON" ], [ "THE GREAT DEBATERS", "has_genre", "DRAMA" ], [ "THE GREAT DEBATERS", "has_tags", "DENZEL WASHINGTON" ], [ "THE GREAT DEBATERS", "starred_actors", "DENZEL WASHINGTON" ], [ "THE GUYS", "has_genre", "DRAMA" ], [ "THE GUYS", "release_year", "2002" ], [ "THE HOURS", "has_genre", "DRAMA" ], [ "THE HOURS", "has_tags", "DRAMA" ], [ "THE HOURS", "release_year", "2002" ], [ "THE IMPORTANCE OF BEING EARNEST", "has_genre", "DRAMA" ], [ "THE IMPORTANCE OF BEING EARNEST", "release_year", "2002" ], [ "THE INTENDED", "has_genre", "DRAMA" ], [ "THE INTENDED", "release_year", "2002" ], [ "THE LARAMIE PROJECT", "has_genre", "DRAMA" ], [ "THE LARAMIE PROJECT", "release_year", "2002" ], [ "THE MAN WITHOUT A FACE", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A FACE", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE MAN WITHOUT A FACE", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_genre", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "has_tags", "DRAMA" ], [ "THE MAN WITHOUT A PAST", "release_year", "2002" ], [ "THE PIANIST", "has_genre", "DRAMA" ], [ "THE PIANIST", "has_tags", "DRAMA" ], [ "THE PIANIST", "release_year", "2002" ], [ "THE ROOKIE", "has_genre", "DRAMA" ], [ "THE ROOKIE", "release_year", "2002" ], [ "THE RULES OF ATTRACTION", "has_genre", "DRAMA" ], [ "THE RULES OF ATTRACTION", "release_year", "2002" ], [ "THE SECRET LIFE OF ZOEY", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF ZOEY", "release_year", "2002" ], [ "THE SECRET LIVES OF DENTISTS", "has_genre", "DRAMA" ], [ "THE SECRET LIVES OF DENTISTS", "release_year", "2002" ], [ "THE SECRET OF CONVICT LAKE", "directed_by", "MICHAEL GORDON" ], [ "THE SECRET OF CONVICT LAKE", "has_genre", "WESTERN" ], [ "THE SECRET OF CONVICT LAKE", "release_year", "1951" ], [ "THE SECRET OF NIMH", "has_genre", "DRAMA" ], [ "THE SECRET OF NIMH", "has_tags", "DIRECTORIAL DEBUT" ], [ "THE THIEF OF PARIS", "has_genre", "CRIME" ], [ "THE THIEF OF PARIS", "in_language", "FRENCH" ], [ "THE THIEF OF PARIS", "written_by", "GEORGES DARIEN" ], [ "THE THREE MARIAS", "has_genre", "DRAMA" ], [ "THE THREE MARIAS", "release_year", "2002" ], [ "THE TRACKER", "has_genre", "DRAMA" ], [ "THE TRACKER", "release_year", "2002" ], [ "UNFAITHFUL", "has_genre", "DRAMA" ], [ "UNFAITHFUL", "release_year", "2002" ], [ "WAITING FOR HAPPINESS", "has_genre", "DRAMA" ], [ "WAITING FOR HAPPINESS", "release_year", "2002" ], [ "WE WERE SOLDIERS", "has_genre", "DRAMA" ], [ "WE WERE SOLDIERS", "release_year", "2002" ], [ "WHALE RIDER", "has_genre", "DRAMA" ], [ "WHALE RIDER", "has_tags", "DRAMA" ], [ "WHALE RIDER", "release_year", "2002" ], [ "WHIP IT", "has_genre", "DRAMA" ], [ "WHIP IT", "has_tags", "DIRECTORIAL DEBUT" ], [ "WHITE OLEANDER", "has_genre", "DRAMA" ], [ "WHITE OLEANDER", "release_year", "2002" ], [ "XX/XY", "has_genre", "DRAMA" ], [ "XX/XY", "release_year", "2002" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 7977, 1969 30643, ACROSS THE UNIVERSE 8284, ANTHONY QUINN 14405, CHANGE OF HABIT 36000, CLAUDE CHABROL 22519, LAST TRAIN FROM GUN HILL 39572, LES COUSINS 22845, MUSIC 30889, ON THE BEACH 36122, STANLEY KRAMER 24926, SWEET CHARITY 25988, THE SECRET OF SANTA VITTORIA 10179, THIS MAN MUST DIE 10352, WARLOCK src, edge_attr, dst 30643, has_tags, 22845 14405, has_genre, 22845 14405, release_year, 7977 22519, release_year, 33637 22519, starred_actors, 8284 39572, directed_by, 36000 39572, has_tags, 36000 39572, release_year, 33637 39572, written_by, 36000 30889, directed_by, 36122 30889, has_tags, 36122 30889, release_year, 33637 24926, has_genre, 22845 24926, release_year, 7977 25988, directed_by, 36122 25988, has_tags, 36122 25988, release_year, 7977 25988, starred_actors, 8284 10179, directed_by, 36000 10179, has_tags, 36000 10179, release_year, 7977 10179, written_by, 36000 10352, release_year, 33637 10352, starred_actors, 8284 Question: For what reason are ACROSS THE UNIVERSE, LES COUSINS, and THE SECRET OF SANTA VITTORIA associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ACROSS THE UNIVERSE", "LES COUSINS", "THE SECRET OF SANTA VITTORIA" ], "valid_edges": [ [ "ACROSS THE UNIVERSE", "has_tags", "MUSIC" ], [ "CHANGE OF HABIT", "has_genre", "MUSIC" ], [ "CHANGE OF HABIT", "release_year", "1969" ], [ "LAST TRAIN FROM GUN HILL", "release_year", "1959" ], [ "LAST TRAIN FROM GUN HILL", "starred_actors", "ANTHONY QUINN" ], [ "LES COUSINS", "directed_by", "CLAUDE CHABROL" ], [ "LES COUSINS", "has_tags", "CLAUDE CHABROL" ], [ "LES COUSINS", "release_year", "1959" ], [ "LES COUSINS", "written_by", "CLAUDE CHABROL" ], [ "ON THE BEACH", "directed_by", "STANLEY KRAMER" ], [ "ON THE BEACH", "has_tags", "STANLEY KRAMER" ], [ "ON THE BEACH", "release_year", "1959" ], [ "SWEET CHARITY", "has_genre", "MUSIC" ], [ "SWEET CHARITY", "release_year", "1969" ], [ "THE SECRET OF SANTA VITTORIA", "directed_by", "STANLEY KRAMER" ], [ "THE SECRET OF SANTA VITTORIA", "has_tags", "STANLEY KRAMER" ], [ "THE SECRET OF SANTA VITTORIA", "release_year", "1969" ], [ "THE SECRET OF SANTA VITTORIA", "starred_actors", "ANTHONY QUINN" ], [ "THIS MAN MUST DIE", "directed_by", "CLAUDE CHABROL" ], [ "THIS MAN MUST DIE", "has_tags", "CLAUDE CHABROL" ], [ "THIS MAN MUST DIE", "release_year", "1969" ], [ "THIS MAN MUST DIE", "written_by", "CLAUDE CHABROL" ], [ "WARLOCK", "release_year", "1959" ], [ "WARLOCK", "starred_actors", "ANTHONY QUINN" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11112, 1939 10393, ALLEGHENY UPRISING 15585, CITY SLICKERS 31347, DANIEL STERN 7159, DESTRY RIDES AGAIN 28651, DODGE CITY 32474, EMMANUELLE 33897, EMMANUELLE ARSAN 4691, ERROL FLYNN 6012, FRENCH 13889, MICHAEL CURTIZ 31613, SAN ANTONIO 3226, STAGECOACH 23804, THE COMANCHEROS 37528, THE OKLAHOMA KID 33147, UNION PACIFIC 36026, WESTERN src, edge_attr, dst 10393, has_genre, 36026 10393, release_year, 11112 15585, has_genre, 36026 15585, has_tags, 31347 15585, starred_actors, 31347 7159, has_genre, 36026 7159, release_year, 11112 28651, directed_by, 13889 28651, has_genre, 36026 28651, has_tags, 13889 28651, release_year, 11112 28651, starred_actors, 4691 32474, in_language, 6012 32474, written_by, 33897 31613, has_genre, 36026 31613, starred_actors, 4691 3226, has_genre, 36026 3226, has_tags, 36026 3226, release_year, 11112 23804, directed_by, 13889 23804, has_genre, 36026 37528, has_genre, 36026 37528, has_tags, 36026 37528, release_year, 11112 33147, has_genre, 36026 33147, release_year, 11112 36026, in_language, 6012 Question: How are DANIEL STERN, DODGE CITY, and EMMANUELLE ARSAN related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DANIEL STERN", "DODGE CITY", "EMMANUELLE ARSAN" ], "valid_edges": [ [ "ALLEGHENY UPRISING", "has_genre", "WESTERN" ], [ "ALLEGHENY UPRISING", "release_year", "1939" ], [ "CITY SLICKERS", "has_genre", "WESTERN" ], [ "CITY SLICKERS", "has_tags", "DANIEL STERN" ], [ "CITY SLICKERS", "starred_actors", "DANIEL STERN" ], [ "DESTRY RIDES AGAIN", "has_genre", "WESTERN" ], [ "DESTRY RIDES AGAIN", "release_year", "1939" ], [ "DODGE CITY", "directed_by", "MICHAEL CURTIZ" ], [ "DODGE CITY", "has_genre", "WESTERN" ], [ "DODGE CITY", "has_tags", "MICHAEL CURTIZ" ], [ "DODGE CITY", "release_year", "1939" ], [ "DODGE CITY", "starred_actors", "ERROL FLYNN" ], [ "EMMANUELLE", "in_language", "FRENCH" ], [ "EMMANUELLE", "written_by", "EMMANUELLE ARSAN" ], [ "SAN ANTONIO", "has_genre", "WESTERN" ], [ "SAN ANTONIO", "starred_actors", "ERROL FLYNN" ], [ "STAGECOACH", "has_genre", "WESTERN" ], [ "STAGECOACH", "has_tags", "WESTERN" ], [ "STAGECOACH", "release_year", "1939" ], [ "THE COMANCHEROS", "directed_by", "MICHAEL CURTIZ" ], [ "THE COMANCHEROS", "has_genre", "WESTERN" ], [ "THE OKLAHOMA KID", "has_genre", "WESTERN" ], [ "THE OKLAHOMA KID", "has_tags", "WESTERN" ], [ "THE OKLAHOMA KID", "release_year", "1939" ], [ "UNION PACIFIC", "has_genre", "WESTERN" ], [ "UNION PACIFIC", "release_year", "1939" ], [ "WESTERN", "in_language", "FRENCH" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 16363, ACROSS THE WIDE MISSOURI 39480, CHARLTON HESTON 31362, CLARK GABLE 37236, EDWARD DMYTRYK 20693, GONE WITH THE WIND 19802, LOVE 30629, NIGHT NURSE 20748, RECKLESS 655, SOLDIER OF FORTUNE 38416, SUSAN HAYWARD 572, THE CALL OF THE WILD 7272, THE PRESIDENT'S LADY 29044, WHERE LOVE HAS GONE 24706, WILLIAM A. WELLMAN src, edge_attr, dst 16363, directed_by, 24706 16363, starred_actors, 31362 20693, has_tags, 31362 20693, has_tags, 19802 30629, directed_by, 24706 30629, has_tags, 31362 30629, has_tags, 24706 30629, starred_actors, 31362 20748, has_tags, 19802 655, directed_by, 37236 655, starred_actors, 31362 655, starred_actors, 38416 572, directed_by, 24706 572, starred_actors, 39480 572, starred_actors, 31362 7272, starred_actors, 39480 7272, starred_actors, 38416 29044, directed_by, 37236 29044, starred_actors, 38416 Question: How are RECKLESS, SUSAN HAYWARD, and THE CALL OF THE WILD related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "RECKLESS", "SUSAN HAYWARD", "THE CALL OF THE WILD" ], "valid_edges": [ [ "ACROSS THE WIDE MISSOURI", "directed_by", "WILLIAM A. WELLMAN" ], [ "ACROSS THE WIDE MISSOURI", "starred_actors", "CLARK GABLE" ], [ "GONE WITH THE WIND", "has_tags", "CLARK GABLE" ], [ "GONE WITH THE WIND", "has_tags", "LOVE" ], [ "NIGHT NURSE", "directed_by", "WILLIAM A. WELLMAN" ], [ "NIGHT NURSE", "has_tags", "CLARK GABLE" ], [ "NIGHT NURSE", "has_tags", "WILLIAM A. WELLMAN" ], [ "NIGHT NURSE", "starred_actors", "CLARK GABLE" ], [ "RECKLESS", "has_tags", "LOVE" ], [ "SOLDIER OF FORTUNE", "directed_by", "EDWARD DMYTRYK" ], [ "SOLDIER OF FORTUNE", "starred_actors", "CLARK GABLE" ], [ "SOLDIER OF FORTUNE", "starred_actors", "SUSAN HAYWARD" ], [ "THE CALL OF THE WILD", "directed_by", "WILLIAM A. WELLMAN" ], [ "THE CALL OF THE WILD", "starred_actors", "CHARLTON HESTON" ], [ "THE CALL OF THE WILD", "starred_actors", "CLARK GABLE" ], [ "THE PRESIDENT'S LADY", "starred_actors", "CHARLTON HESTON" ], [ "THE PRESIDENT'S LADY", "starred_actors", "SUSAN HAYWARD" ], [ "WHERE LOVE HAS GONE", "directed_by", "EDWARD DMYTRYK" ], [ "WHERE LOVE HAS GONE", "starred_actors", "SUSAN HAYWARD" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 33637, 1959 36212, DRAMA 25651, DUMMY 12847, EDITH EVANS 23543, LOOK BACK IN ANGER 825, THE LIFEGUARD 23973, THE NUN'S STORY src, edge_attr, dst 25651, has_genre, 36212 23543, has_genre, 36212 23543, release_year, 33637 23543, starred_actors, 12847 825, has_genre, 36212 23973, release_year, 33637 23973, starred_actors, 12847 Question: How are DUMMY, EDITH EVANS, and THE LIFEGUARD related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DUMMY", "EDITH EVANS", "THE LIFEGUARD" ], "valid_edges": [ [ "DUMMY", "has_genre", "DRAMA" ], [ "LOOK BACK IN ANGER", "has_genre", "DRAMA" ], [ "LOOK BACK IN ANGER", "release_year", "1959" ], [ "LOOK BACK IN ANGER", "starred_actors", "EDITH EVANS" ], [ "THE LIFEGUARD", "has_genre", "DRAMA" ], [ "THE NUN'S STORY", "release_year", "1959" ], [ "THE NUN'S STORY", "starred_actors", "EDITH EVANS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 11479, BAPSI SIDHWA 29159, BENOÎT JAUBERT 36212, DRAMA 26751, EARTH 1321, IRON ISLAND 33870, MOHAMMAD RASOULOF 39594, REBELLION src, edge_attr, dst 26751, has_genre, 36212 26751, has_tags, 26751 26751, written_by, 11479 1321, directed_by, 33870 1321, has_genre, 36212 1321, written_by, 33870 39594, has_genre, 36212 39594, written_by, 29159 Question: How are BAPSI SIDHWA, BENOÎT JAUBERT, and MOHAMMAD RASOULOF related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "BAPSI SIDHWA", "BENOÎT JAUBERT", "MOHAMMAD RASOULOF" ], "valid_edges": [ [ "EARTH", "has_genre", "DRAMA" ], [ "EARTH", "has_tags", "EARTH" ], [ "EARTH", "written_by", "BAPSI SIDHWA" ], [ "IRON ISLAND", "directed_by", "MOHAMMAD RASOULOF" ], [ "IRON ISLAND", "has_genre", "DRAMA" ], [ "IRON ISLAND", "written_by", "MOHAMMAD RASOULOF" ], [ "REBELLION", "has_genre", "DRAMA" ], [ "REBELLION", "written_by", "BENOÎT JAUBERT" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 29598, AKI KAURISMÄKI 4017, ARIEL 30463, COMEDY 2246, CRITERION 36212, DRAMA 6666, FINNISH 28101, JACK TREVOR STORY 38003, KINYARWANDA 6838, MATTI PELLONPÄÄ 14976, MUNYURANGABO 64, PROLETARIAT TRILOGY 37803, SHADOWS IN PARADISE 13187, THE TROUBLE WITH HARRY src, edge_attr, dst 4017, directed_by, 29598 4017, has_genre, 36212 4017, has_tags, 29598 4017, has_tags, 2246 4017, has_tags, 6666 4017, has_tags, 64 4017, in_language, 6666 4017, starred_actors, 6838 4017, written_by, 29598 38003, has_genre, 36212 38003, in_language, 38003 14976, in_language, 38003 37803, directed_by, 29598 37803, has_genre, 30463 37803, has_genre, 36212 37803, has_tags, 29598 37803, has_tags, 2246 37803, has_tags, 64 37803, in_language, 6666 37803, starred_actors, 6838 37803, written_by, 29598 13187, has_genre, 30463 13187, written_by, 28101 Question: For what reason are JACK TREVOR STORY, MUNYURANGABO, and PROLETARIAT TRILOGY associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JACK TREVOR STORY", "MUNYURANGABO", "PROLETARIAT TRILOGY" ], "valid_edges": [ [ "ARIEL", "directed_by", "AKI KAURISMÄKI" ], [ "ARIEL", "has_genre", "DRAMA" ], [ "ARIEL", "has_tags", "AKI KAURISMÄKI" ], [ "ARIEL", "has_tags", "CRITERION" ], [ "ARIEL", "has_tags", "FINNISH" ], [ "ARIEL", "has_tags", "PROLETARIAT TRILOGY" ], [ "ARIEL", "in_language", "FINNISH" ], [ "ARIEL", "starred_actors", "MATTI PELLONPÄÄ" ], [ "ARIEL", "written_by", "AKI KAURISMÄKI" ], [ "KINYARWANDA", "has_genre", "DRAMA" ], [ "KINYARWANDA", "in_language", "KINYARWANDA" ], [ "MUNYURANGABO", "in_language", "KINYARWANDA" ], [ "SHADOWS IN PARADISE", "directed_by", "AKI KAURISMÄKI" ], [ "SHADOWS IN PARADISE", "has_genre", "COMEDY" ], [ "SHADOWS IN PARADISE", "has_genre", "DRAMA" ], [ "SHADOWS IN PARADISE", "has_tags", "AKI KAURISMÄKI" ], [ "SHADOWS IN PARADISE", "has_tags", "CRITERION" ], [ "SHADOWS IN PARADISE", "has_tags", "PROLETARIAT TRILOGY" ], [ "SHADOWS IN PARADISE", "in_language", "FINNISH" ], [ "SHADOWS IN PARADISE", "starred_actors", "MATTI PELLONPÄÄ" ], [ "SHADOWS IN PARADISE", "written_by", "AKI KAURISMÄKI" ], [ "THE TROUBLE WITH HARRY", "has_genre", "COMEDY" ], [ "THE TROUBLE WITH HARRY", "written_by", "JACK TREVOR STORY" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6540, 12 25221, 1981 24438, 1993 17315, 2007 29424, 2011 20033, ANGEL 21731, BETRAYED 14984, BLOW OUT 28956, DEBRA WINGER 12628, EASTERN PROMISES 31783, ENGLISH 22423, GEORG 38465, HITMAN 27999, JOHN TRAVOLTA 22527, LANA TURNER 35491, LOOK WHO'S TALKING NOW 38169, MAD CITY 2990, MERMAID 17474, MICHAEL 34978, OLD DOGS 16206, RUSSIAN 30385, THE BANISHMENT 14131, THE POSTMAN ALWAYS RINGS TWICE 7816, THE THREE MUSKETEERS 13388, URBAN COWBOY 12255, WALT BECKER 18586, WILD HOGS src, edge_attr, dst 6540, in_language, 16206 6540, release_year, 17315 20033, release_year, 17315 21731, starred_actors, 28956 21731, starred_actors, 22527 14984, release_year, 25221 14984, starred_actors, 27999 12628, has_tags, 16206 12628, in_language, 16206 12628, release_year, 17315 22423, in_language, 16206 22423, release_year, 17315 38465, in_language, 16206 38465, release_year, 17315 35491, release_year, 24438 35491, starred_actors, 27999 38169, in_language, 31783 38169, starred_actors, 27999 2990, in_language, 16206 2990, release_year, 17315 17474, has_tags, 20033 17474, has_tags, 27999 17474, release_year, 29424 17474, starred_actors, 27999 34978, directed_by, 12255 34978, has_tags, 27999 34978, starred_actors, 27999 30385, in_language, 16206 30385, release_year, 17315 14131, in_language, 31783 14131, release_year, 25221 14131, starred_actors, 22527 7816, release_year, 24438 7816, release_year, 29424 7816, starred_actors, 22527 13388, starred_actors, 28956 13388, starred_actors, 27999 18586, directed_by, 12255 18586, has_tags, 27999 18586, release_year, 17315 18586, starred_actors, 27999 Question: For what reason are JOHN TRAVOLTA, LANA TURNER, and THE BANISHMENT associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOHN TRAVOLTA", "LANA TURNER", "THE BANISHMENT" ], "valid_edges": [ [ "12", "in_language", "RUSSIAN" ], [ "12", "release_year", "2007" ], [ "ANGEL", "release_year", "2007" ], [ "BETRAYED", "starred_actors", "DEBRA WINGER" ], [ "BETRAYED", "starred_actors", "LANA TURNER" ], [ "BLOW OUT", "release_year", "1981" ], [ "BLOW OUT", "starred_actors", "JOHN TRAVOLTA" ], [ "EASTERN PROMISES", "has_tags", "RUSSIAN" ], [ "EASTERN PROMISES", "in_language", "RUSSIAN" ], [ "EASTERN PROMISES", "release_year", "2007" ], [ "GEORG", "in_language", "RUSSIAN" ], [ "GEORG", "release_year", "2007" ], [ "HITMAN", "in_language", "RUSSIAN" ], [ "HITMAN", "release_year", "2007" ], [ "LOOK WHO'S TALKING NOW", "release_year", "1993" ], [ "LOOK WHO'S TALKING NOW", "starred_actors", "JOHN TRAVOLTA" ], [ "MAD CITY", "in_language", "ENGLISH" ], [ "MAD CITY", "starred_actors", "JOHN TRAVOLTA" ], [ "MERMAID", "in_language", "RUSSIAN" ], [ "MERMAID", "release_year", "2007" ], [ "MICHAEL", "has_tags", "ANGEL" ], [ "MICHAEL", "has_tags", "JOHN TRAVOLTA" ], [ "MICHAEL", "release_year", "2011" ], [ "MICHAEL", "starred_actors", "JOHN TRAVOLTA" ], [ "OLD DOGS", "directed_by", "WALT BECKER" ], [ "OLD DOGS", "has_tags", "JOHN TRAVOLTA" ], [ "OLD DOGS", "starred_actors", "JOHN TRAVOLTA" ], [ "THE BANISHMENT", "in_language", "RUSSIAN" ], [ "THE BANISHMENT", "release_year", "2007" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "in_language", "ENGLISH" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "release_year", "1981" ], [ "THE POSTMAN ALWAYS RINGS TWICE", "starred_actors", "LANA TURNER" ], [ "THE THREE MUSKETEERS", "release_year", "1993" ], [ "THE THREE MUSKETEERS", "release_year", "2011" ], [ "THE THREE MUSKETEERS", "starred_actors", "LANA TURNER" ], [ "URBAN COWBOY", "starred_actors", "DEBRA WINGER" ], [ "URBAN COWBOY", "starred_actors", "JOHN TRAVOLTA" ], [ "WILD HOGS", "directed_by", "WALT BECKER" ], [ "WILD HOGS", "has_tags", "JOHN TRAVOLTA" ], [ "WILD HOGS", "release_year", "2007" ], [ "WILD HOGS", "starred_actors", "JOHN TRAVOLTA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 37484, 2004 18598, APPLESEED 2182, BLOOD AND BONES 231, CASSHERN 5113, DEAD LEAVES 23809, DOG NAIL CLIPPER 13409, HANA AND ALICE 12087, HOWL'S MOVING CASTLE 34710, IN THE REALM OF THE SENSES 13174, INFECTION 8164, IZO 36874, JAPANESE 15150, KAMIKAZE GIRLS 30532, MIND GAME 25709, NOBODY KNOWS 6302, ONIBABA 31842, SURVIVE STYLE 5+ 786, THE GRUDGE 9554, THROW DOWN 28132, TONY TAKITANI 12437, VITAL src, edge_attr, dst 18598, in_language, 36874 18598, release_year, 37484 2182, in_language, 36874 2182, release_year, 37484 231, has_tags, 36874 231, in_language, 36874 231, release_year, 37484 5113, in_language, 36874 5113, release_year, 37484 23809, release_year, 37484 13409, in_language, 36874 13409, release_year, 37484 12087, in_language, 36874 12087, release_year, 37484 34710, has_tags, 36874 34710, in_language, 36874 13174, in_language, 36874 13174, release_year, 37484 8164, in_language, 36874 8164, release_year, 37484 15150, has_tags, 36874 15150, in_language, 36874 15150, release_year, 37484 30532, in_language, 36874 30532, release_year, 37484 25709, in_language, 36874 25709, release_year, 37484 6302, in_language, 36874 31842, has_tags, 36874 31842, in_language, 36874 31842, release_year, 37484 786, in_language, 36874 786, release_year, 37484 9554, in_language, 36874 9554, release_year, 37484 28132, in_language, 36874 28132, release_year, 37484 12437, in_language, 36874 12437, release_year, 37484 Question: In what context are DOG NAIL CLIPPER, IN THE REALM OF THE SENSES, and ONIBABA connected? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "DOG NAIL CLIPPER", "IN THE REALM OF THE SENSES", "ONIBABA" ], "valid_edges": [ [ "APPLESEED", "in_language", "JAPANESE" ], [ "APPLESEED", "release_year", "2004" ], [ "BLOOD AND BONES", "in_language", "JAPANESE" ], [ "BLOOD AND BONES", "release_year", "2004" ], [ "CASSHERN", "has_tags", "JAPANESE" ], [ "CASSHERN", "in_language", "JAPANESE" ], [ "CASSHERN", "release_year", "2004" ], [ "DEAD LEAVES", "in_language", "JAPANESE" ], [ "DEAD LEAVES", "release_year", "2004" ], [ "DOG NAIL CLIPPER", "release_year", "2004" ], [ "HANA AND ALICE", "in_language", "JAPANESE" ], [ "HANA AND ALICE", "release_year", "2004" ], [ "HOWL'S MOVING CASTLE", "in_language", "JAPANESE" ], [ "HOWL'S MOVING CASTLE", "release_year", "2004" ], [ "IN THE REALM OF THE SENSES", "has_tags", "JAPANESE" ], [ "IN THE REALM OF THE SENSES", "in_language", "JAPANESE" ], [ "INFECTION", "in_language", "JAPANESE" ], [ "INFECTION", "release_year", "2004" ], [ "IZO", "in_language", "JAPANESE" ], [ "IZO", "release_year", "2004" ], [ "KAMIKAZE GIRLS", "has_tags", "JAPANESE" ], [ "KAMIKAZE GIRLS", "in_language", "JAPANESE" ], [ "KAMIKAZE GIRLS", "release_year", "2004" ], [ "MIND GAME", "in_language", "JAPANESE" ], [ "MIND GAME", "release_year", "2004" ], [ "NOBODY KNOWS", "in_language", "JAPANESE" ], [ "NOBODY KNOWS", "release_year", "2004" ], [ "ONIBABA", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "has_tags", "JAPANESE" ], [ "SURVIVE STYLE 5+", "in_language", "JAPANESE" ], [ "SURVIVE STYLE 5+", "release_year", "2004" ], [ "THE GRUDGE", "in_language", "JAPANESE" ], [ "THE GRUDGE", "release_year", "2004" ], [ "THROW DOWN", "in_language", "JAPANESE" ], [ "THROW DOWN", "release_year", "2004" ], [ "TONY TAKITANI", "in_language", "JAPANESE" ], [ "TONY TAKITANI", "release_year", "2004" ], [ "VITAL", "in_language", "JAPANESE" ], [ "VITAL", "release_year", "2004" ] ] }

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You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 19407, 8½ 9677, ANATOMY OF A MURDER 19978, BEN GAZZARA 13577, CITY OF WOMEN 22958, FAMOUS 3353, FEDERICO FELLINI 34311, GENA ROWLANDS 15135, GINGER AND FRED 17549, MARCELLO MASTROIANNI 5343, OPENING NIGHT 6002, PAULIE src, edge_attr, dst 19407, directed_by, 3353 19407, has_imdb_votes, 22958 19407, has_tags, 3353 19407, starred_actors, 17549 19407, written_by, 3353 9677, has_imdb_votes, 22958 9677, starred_actors, 19978 13577, directed_by, 3353 13577, starred_actors, 17549 13577, written_by, 3353 15135, directed_by, 3353 15135, starred_actors, 17549 15135, written_by, 3353 5343, starred_actors, 19978 5343, starred_actors, 34311 6002, starred_actors, 34311 Question: How are ANATOMY OF A MURDER, GINGER AND FRED, and PAULIE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ANATOMY OF A MURDER", "GINGER AND FRED", "PAULIE" ], "valid_edges": [ [ "8½", "directed_by", "FEDERICO FELLINI" ], [ "8½", "has_imdb_votes", "FAMOUS" ], [ "8½", "has_tags", "FEDERICO FELLINI" ], [ "8½", "starred_actors", "MARCELLO MASTROIANNI" ], [ "8½", "written_by", "FEDERICO FELLINI" ], [ "ANATOMY OF A MURDER", "has_imdb_votes", "FAMOUS" ], [ "ANATOMY OF A MURDER", "starred_actors", "BEN GAZZARA" ], [ "CITY OF WOMEN", "directed_by", "FEDERICO FELLINI" ], [ "CITY OF WOMEN", "starred_actors", "MARCELLO MASTROIANNI" ], [ "CITY OF WOMEN", "written_by", "FEDERICO FELLINI" ], [ "GINGER AND FRED", "directed_by", "FEDERICO FELLINI" ], [ "GINGER AND FRED", "starred_actors", "MARCELLO MASTROIANNI" ], [ "GINGER AND FRED", "written_by", "FEDERICO FELLINI" ], [ "OPENING NIGHT", "starred_actors", "BEN GAZZARA" ], [ "OPENING NIGHT", "starred_actors", "GENA ROWLANDS" ], [ "PAULIE", "starred_actors", "GENA ROWLANDS" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 6750, 10 RILLINGTON PLACE 30146, A CHRISTMAS CAROL 1698, ALFIE 9677, ANATOMY OF A MURDER 10045, BD-R 15771, BENGAZI 19826, BLACK DEATH 39111, BORN FREE 38680, COMPULSION 2149, DOG DAY AFTERNOON 36212, DRAMA 17986, GABRIEL OVER THE WHITE HOUSE 24900, JOHN RICHARDSON 35463, JUSTIN CHON 14209, KING OF HEARTS 36639, LADIES THEY TALK ABOUT 30029, LAWRENCE OF ARABIA 5996, MEET JOHN DOE 30629, NIGHT NURSE 35865, ON THE WATERFRONT 27496, ONE MILLION YEARS B.C. 29534, REVENGE OF THE GREEN DRAGONS 35586, SAHARA 6056, SCARFACE 15003, THE BATTLE OF ALGIERS 33978, THE BRIBE 11635, THE FOUR FEATHERS 37567, THE OSCAR 31851, THE PRISONER OF ZENDA 7478, THE RACKET 30746, THE SECRET LIFE OF WALTER MITTY 31647, THE SON OF THE SHEIK 7816, THE THREE MUSKETEERS 983, THE TREASURE OF THE SIERRA MADRE 28744, THE UNHOLY THREE 34407, THE WRONG MAN 873, THEY MADE ME A CRIMINAL 18596, THREE ON A MATCH 35212, WHO'S AFRAID OF VIRGINIA WOOLF? 297, WINGS src, edge_attr, dst 6750, has_genre, 36212 6750, has_tags, 10045 30146, has_genre, 36212 30146, has_tags, 10045 1698, has_genre, 36212 1698, has_tags, 10045 9677, has_genre, 36212 9677, has_tags, 10045 15771, has_genre, 36212 15771, has_tags, 10045 19826, has_genre, 36212 19826, has_tags, 10045 39111, has_genre, 36212 39111, has_tags, 10045 38680, has_genre, 36212 38680, has_tags, 10045 2149, has_genre, 36212 2149, has_tags, 10045 17986, has_genre, 36212 17986, has_tags, 10045 14209, has_genre, 36212 14209, has_tags, 10045 36639, has_genre, 36212 36639, has_tags, 10045 30029, has_genre, 36212 30029, has_tags, 10045 5996, has_genre, 36212 5996, has_tags, 10045 30629, has_genre, 36212 30629, has_tags, 10045 35865, has_genre, 36212 35865, has_tags, 10045 27496, has_tags, 10045 27496, starred_actors, 24900 29534, has_genre, 36212 29534, starred_actors, 35463 35586, has_genre, 36212 35586, has_tags, 10045 6056, has_genre, 36212 6056, has_tags, 10045 6056, has_tags, 36212 15003, has_genre, 36212 15003, has_tags, 10045 33978, has_genre, 36212 33978, has_tags, 10045 11635, has_genre, 36212 11635, has_tags, 10045 37567, has_genre, 36212 37567, has_tags, 10045 31851, has_genre, 36212 31851, has_tags, 10045 7478, has_genre, 36212 7478, has_tags, 10045 30746, has_genre, 36212 30746, has_tags, 10045 31647, has_genre, 36212 31647, has_tags, 10045 7816, has_genre, 36212 7816, has_tags, 10045 983, has_genre, 36212 983, has_tags, 10045 28744, has_genre, 36212 28744, has_tags, 10045 34407, has_genre, 36212 34407, has_tags, 10045 873, has_genre, 36212 873, has_tags, 10045 18596, has_genre, 36212 18596, has_tags, 10045 35212, has_genre, 36212 35212, has_tags, 10045 297, has_genre, 36212 297, has_tags, 10045 Question: How are JOHN RICHARDSON, JUSTIN CHON, and MEET JOHN DOE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "JOHN RICHARDSON", "JUSTIN CHON", "MEET JOHN DOE" ], "valid_edges": [ [ "10 RILLINGTON PLACE", "has_genre", "DRAMA" ], [ "10 RILLINGTON PLACE", "has_tags", "BD-R" ], [ "A CHRISTMAS CAROL", "has_genre", "DRAMA" ], [ "A CHRISTMAS CAROL", "has_tags", "BD-R" ], [ "ALFIE", "has_genre", "DRAMA" ], [ "ALFIE", "has_tags", "BD-R" ], [ "ANATOMY OF A MURDER", "has_genre", "DRAMA" ], [ "ANATOMY OF A MURDER", "has_tags", "BD-R" ], [ "BENGAZI", "has_genre", "DRAMA" ], [ "BENGAZI", "has_tags", "BD-R" ], [ "BLACK DEATH", "has_genre", "DRAMA" ], [ "BLACK DEATH", "has_tags", "BD-R" ], [ "BORN FREE", "has_genre", "DRAMA" ], [ "BORN FREE", "has_tags", "BD-R" ], [ "COMPULSION", "has_genre", "DRAMA" ], [ "COMPULSION", "has_tags", "BD-R" ], [ "DOG DAY AFTERNOON", "has_genre", "DRAMA" ], [ "DOG DAY AFTERNOON", "has_tags", "BD-R" ], [ "GABRIEL OVER THE WHITE HOUSE", "has_genre", "DRAMA" ], [ "GABRIEL OVER THE WHITE HOUSE", "has_tags", "BD-R" ], [ "KING OF HEARTS", "has_genre", "DRAMA" ], [ "KING OF HEARTS", "has_tags", "BD-R" ], [ "LADIES THEY TALK ABOUT", "has_genre", "DRAMA" ], [ "LADIES THEY TALK ABOUT", "has_tags", "BD-R" ], [ "LAWRENCE OF ARABIA", "has_genre", "DRAMA" ], [ "LAWRENCE OF ARABIA", "has_tags", "BD-R" ], [ "MEET JOHN DOE", "has_genre", "DRAMA" ], [ "MEET JOHN DOE", "has_tags", "BD-R" ], [ "NIGHT NURSE", "has_genre", "DRAMA" ], [ "NIGHT NURSE", "has_tags", "BD-R" ], [ "ON THE WATERFRONT", "has_genre", "DRAMA" ], [ "ON THE WATERFRONT", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "has_tags", "BD-R" ], [ "ONE MILLION YEARS B.C.", "starred_actors", "JOHN RICHARDSON" ], [ "REVENGE OF THE GREEN DRAGONS", "has_genre", "DRAMA" ], [ "REVENGE OF THE GREEN DRAGONS", "starred_actors", "JUSTIN CHON" ], [ "SAHARA", "has_genre", "DRAMA" ], [ "SAHARA", "has_tags", "BD-R" ], [ "SCARFACE", "has_genre", "DRAMA" ], [ "SCARFACE", "has_tags", "BD-R" ], [ "SCARFACE", "has_tags", "DRAMA" ], [ "THE BATTLE OF ALGIERS", "has_genre", "DRAMA" ], [ "THE BATTLE OF ALGIERS", "has_tags", "BD-R" ], [ "THE BRIBE", "has_genre", "DRAMA" ], [ "THE BRIBE", "has_tags", "BD-R" ], [ "THE FOUR FEATHERS", "has_genre", "DRAMA" ], [ "THE FOUR FEATHERS", "has_tags", "BD-R" ], [ "THE OSCAR", "has_genre", "DRAMA" ], [ "THE OSCAR", "has_tags", "BD-R" ], [ "THE PRISONER OF ZENDA", "has_genre", "DRAMA" ], [ "THE PRISONER OF ZENDA", "has_tags", "BD-R" ], [ "THE RACKET", "has_genre", "DRAMA" ], [ "THE RACKET", "has_tags", "BD-R" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_genre", "DRAMA" ], [ "THE SECRET LIFE OF WALTER MITTY", "has_tags", "BD-R" ], [ "THE SON OF THE SHEIK", "has_genre", "DRAMA" ], [ "THE SON OF THE SHEIK", "has_tags", "BD-R" ], [ "THE THREE MUSKETEERS", "has_genre", "DRAMA" ], [ "THE THREE MUSKETEERS", "has_tags", "BD-R" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_genre", "DRAMA" ], [ "THE TREASURE OF THE SIERRA MADRE", "has_tags", "BD-R" ], [ "THE UNHOLY THREE", "has_genre", "DRAMA" ], [ "THE UNHOLY THREE", "has_tags", "BD-R" ], [ "THE WRONG MAN", "has_genre", "DRAMA" ], [ "THE WRONG MAN", "has_tags", "BD-R" ], [ "THEY MADE ME A CRIMINAL", "has_genre", "DRAMA" ], [ "THEY MADE ME A CRIMINAL", "has_tags", "BD-R" ], [ "THREE ON A MATCH", "has_genre", "DRAMA" ], [ "THREE ON A MATCH", "has_tags", "BD-R" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_genre", "DRAMA" ], [ "WHO'S AFRAID OF VIRGINIA WOOLF?", "has_tags", "BD-R" ], [ "WINGS", "has_genre", "DRAMA" ], [ "WINGS", "has_tags", "BD-R" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 20720, BLACK LIKE ME 755, CHARLES MATTHAU 36212, DRAMA 6274, FRANK CRAVEN 10869, GERDA LERNER 23553, OUR TOWN 39138, THE GRASS HARP src, edge_attr, dst 20720, has_genre, 36212 20720, written_by, 10869 23553, has_genre, 36212 23553, written_by, 6274 39138, directed_by, 755 39138, has_genre, 36212 Question: How are CHARLES MATTHAU, FRANK CRAVEN, and GERDA LERNER related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHARLES MATTHAU", "FRANK CRAVEN", "GERDA LERNER" ], "valid_edges": [ [ "BLACK LIKE ME", "has_genre", "DRAMA" ], [ "BLACK LIKE ME", "written_by", "GERDA LERNER" ], [ "OUR TOWN", "has_genre", "DRAMA" ], [ "OUR TOWN", "written_by", "FRANK CRAVEN" ], [ "THE GRASS HARP", "directed_by", "CHARLES MATTHAU" ], [ "THE GRASS HARP", "has_genre", "DRAMA" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 9377, 2014 10023, 99 HOMES 10054, A WALK AMONG THE TOMBSTONES 23806, ADDICTED 38361, AFFLUENZA 17534, ALOFT 34713, AN EDUCATION 37270, AND SO IT GOES 39876, ANNIE 18725, BAREFOOT 28764, BEGIN AGAIN 25930, BETTER LIVING THROUGH CHEMISTRY 36169, BEYOND THE LIGHTS 22684, BIG EYES 2975, BIRD PEOPLE 28685, BLIND 16290, BOYHOOD 37883, BROKEN EMBRACES 19993, C.O.G. 19004, CAKE 13812, CALVARY 17633, CAMP X-RAY 14816, CHARMING 20757, CLOUDS OF SILS MARIA 34890, COMET 9864, COMMON 33976, DAYS AND NIGHTS 10518, DEAR WHITE PEOPLE 17921, DRAFT DAY 36212, DRAMA 4838, EAT PRAY LOVE 7480, EDEN 13700, ENDLESS LOVE 34996, FORCE MAJEURE 32235, FOXCATCHER 38339, FRANK 5287, FROZEN 39145, FURY 25582, GIRLHOOD 7291, GOD HELP THE GIRL 24733, GOD'S NOT DEAD 31512, GOD'S POCKET 7319, GOODBYE TO LANGUAGE 28947, HAIDER 8617, HAPPY CHRISTMAS 6599, HEALING 9610, HEAVEN IS FOR REAL 20139, HELLION 29012, HER 6025, HIGHWAY 16788, INBETWEEN WORLDS 9748, INHERENT VICE 8793, JAMESY BOY 12031, JAMIE MARKS IS DEAD 21080, JAUJA 4246, JERSEY BOYS 17871, JONATHAN GROFF 1073, KILL THE MESSENGER 29887, KUMIKO, THE TREASURE HUNTER 37258, LARRY KRAMER 12760, LATE PHASES 824, LATITUDES 36329, LEVIATHAN 35542, LILTING 21502, LISTEN UP PHILIP 27480, LITTLE ACCIDENTS 24601, LOST HORIZON 31635, LOVE IS STRANGE 13249, LULLABY 7203, MAPS TO THE STARS 6592, MARGARET 5032, MARK RUFFALO 35271, MELODRAMA 35465, MILLION DOLLAR ARM 1911, MOMMY 9635, MR. TURNER 12944, MY LIFE WITHOUT ME 40064, MY OLD LADY 6766, PERFECT SISTERS 34922, PK 23152, PRIDE 12428, RAGE 17082, RESERVATION ROAD 28797, ROB THE MOB 3126, ROSEWATER 30895, RUDDERLESS 5766, RUNNING WITH SCISSORS 31492, RYAN MURPHY 32252, SAINT LAURENT 33939, SALTING THE BATTLEFIELD 38319, SELMA 26687, SENSO 3096, SERENA 19715, ST. VINCENT 23194, STATIONS OF THE CROSS 13635, STILL ALICE 34516, SYMPATHY FOR DELICIOUS 21160, THANK YOU A LOT 19501, THANKS FOR SHARING 9114, THE ANGRIEST MAN IN BROOKLYN 29460, THE BEST OF ME 5013, THE CIRCLE 11375, THE COBBLER 23306, THE DROP 4766, THE FAULT IN OUR STARS 32416, THE GOOD LIE 14626, THE HOMESMAN 36793, THE HUNDRED-FOOT JOURNEY 9406, THE IMITATION GAME 19629, THE JUDGE 4143, THE LAST CASTLE 30805, THE NEW GIRLFRIEND 35470, THE NORMAL HEART 3765, THE OTHER WOMAN 14064, THE OUTSIDER 8660, THE RECKONING 14115, THE ROVER 1492, THE SINGLE MOMS CLUB 9568, THE SKELETON TWINS 2559, THE THEORY OF EVERYTHING 31381, THE WAY HE LOOKS 34649, THE WONDERS 14919, THERE'S ALWAYS TOMORROW 698, THIS IS WHERE I LEAVE YOU 7969, TIMBUKTU 17726, TUSK 14504, UNBROKEN 36178, VERONICA MARS 10185, WELCOME TO NEW YORK 5465, WHAT DOESN'T KILL YOU 15726, WHEN ANIMALS DREAM 38804, WHIPLASH 14840, WHITE GOD 142, WILD 26235, WINTER SLEEP 4820, WISH I WAS HERE 37252, WOMEN IN LOVE 18995, XX/XY 12162, YOU CAN COUNT ON ME 5209, YVES SAINT LAURENT src, edge_attr, dst 10023, has_genre, 36212 10023, release_year, 9377 10054, has_genre, 36212 10054, release_year, 9377 23806, has_genre, 36212 23806, release_year, 9377 38361, has_genre, 36212 38361, release_year, 9377 17534, has_genre, 36212 17534, release_year, 9377 34713, has_genre, 36212 34713, has_tags, 14816 34713, release_year, 27261 37270, has_genre, 36212 37270, release_year, 9377 39876, has_genre, 36212 39876, release_year, 9377 18725, has_genre, 36212 18725, release_year, 9377 28764, has_genre, 36212 28764, has_tags, 5032 28764, starred_actors, 5032 25930, has_genre, 36212 25930, release_year, 9377 36169, has_genre, 36212 36169, release_year, 9377 22684, has_genre, 36212 22684, release_year, 9377 2975, has_genre, 36212 2975, release_year, 9377 28685, has_genre, 36212 28685, release_year, 9377 16290, has_genre, 36212 16290, has_tags, 9377 16290, release_year, 9377 37883, has_genre, 36212 37883, has_tags, 35271 37883, release_year, 27261 19993, has_genre, 36212 19993, starred_actors, 17871 19004, has_genre, 36212 19004, release_year, 9377 13812, has_genre, 36212 13812, release_year, 9377 17633, has_genre, 36212 17633, release_year, 9377 20757, has_genre, 36212 20757, release_year, 9377 34890, has_genre, 36212 34890, release_year, 9377 9864, has_genre, 36212 9864, release_year, 9377 33976, has_genre, 36212 33976, release_year, 9377 10518, has_genre, 36212 10518, release_year, 9377 17921, has_genre, 36212 17921, release_year, 9377 4838, directed_by, 31492 4838, has_genre, 36212 4838, written_by, 31492 7480, has_genre, 36212 7480, release_year, 9377 13700, has_genre, 36212 13700, release_year, 9377 34996, has_genre, 36212 34996, has_tags, 9377 34996, release_year, 9377 32235, has_genre, 36212 32235, has_tags, 5032 32235, release_year, 9377 32235, starred_actors, 5032 38339, has_genre, 36212 38339, release_year, 9377 5287, has_genre, 36212 5287, starred_actors, 17871 39145, has_genre, 36212 39145, release_year, 9377 25582, has_genre, 36212 25582, release_year, 9377 7291, has_genre, 36212 7291, release_year, 9377 24733, has_genre, 36212 24733, release_year, 9377 31512, has_genre, 36212 31512, release_year, 9377 7319, has_genre, 36212 7319, release_year, 9377 28947, has_genre, 36212 28947, release_year, 9377 8617, has_genre, 36212 8617, release_year, 9377 6599, has_genre, 36212 6599, release_year, 9377 9610, has_genre, 36212 9610, release_year, 9377 20139, has_genre, 36212 20139, release_year, 9377 29012, has_genre, 36212 29012, has_tags, 9377 6025, has_genre, 36212 6025, release_year, 9377 16788, has_genre, 36212 16788, release_year, 9377 9748, has_genre, 36212 9748, release_year, 9377 8793, has_genre, 36212 8793, release_year, 9377 12031, has_genre, 36212 12031, release_year, 9377 21080, has_genre, 36212 21080, release_year, 9377 4246, has_genre, 36212 4246, release_year, 9377 1073, has_genre, 36212 1073, release_year, 9377 29887, has_genre, 36212 29887, release_year, 9377 12760, has_genre, 36212 12760, release_year, 9377 824, has_genre, 36212 824, release_year, 9377 36329, has_genre, 36212 36329, release_year, 9377 35542, has_genre, 36212 35542, release_year, 9377 21502, has_genre, 36212 21502, release_year, 9377 27480, has_genre, 36212 27480, release_year, 9377 24601, has_genre, 36212 24601, written_by, 37258 31635, has_genre, 36212 31635, release_year, 9377 13249, has_genre, 36212 13249, release_year, 9377 7203, has_genre, 36212 7203, has_tags, 36212 7203, release_year, 9377 6592, has_genre, 36212 6592, has_tags, 36212 6592, starred_actors, 5032 35465, has_genre, 36212 35465, release_year, 9377 1911, has_genre, 36212 1911, release_year, 9377 9635, has_genre, 36212 9635, release_year, 9377 12944, has_genre, 36212 12944, has_tags, 5032 40064, has_genre, 36212 40064, release_year, 9377 6766, has_genre, 36212 6766, release_year, 9377 34922, has_genre, 36212 34922, release_year, 9377 23152, has_genre, 36212 23152, release_year, 9377 12428, has_genre, 36212 12428, release_year, 9377 17082, has_genre, 36212 17082, has_tags, 5032 28797, has_genre, 36212 28797, release_year, 9377 3126, has_genre, 36212 3126, release_year, 9377 30895, has_genre, 36212 30895, release_year, 9377 5766, directed_by, 31492 5766, has_genre, 36212 5766, written_by, 31492 32252, has_genre, 36212 32252, release_year, 9377 33939, has_genre, 36212 33939, release_year, 9377 38319, has_genre, 36212 38319, release_year, 9377 26687, has_genre, 36212 26687, has_tags, 35271 3096, has_genre, 36212 3096, release_year, 9377 19715, has_genre, 36212 19715, release_year, 9377 23194, has_genre, 36212 23194, release_year, 9377 13635, has_genre, 36212 13635, release_year, 9377 34516, directed_by, 5032 34516, has_genre, 36212 34516, starred_actors, 5032 21160, has_genre, 36212 21160, release_year, 9377 19501, has_genre, 36212 19501, starred_actors, 5032 9114, has_genre, 36212 9114, release_year, 9377 29460, has_genre, 36212 29460, release_year, 9377 5013, has_genre, 36212 5013, release_year, 9377 11375, has_genre, 36212 11375, release_year, 9377 23306, has_genre, 36212 23306, release_year, 9377 4766, has_genre, 36212 4766, has_tags, 36212 4766, release_year, 9377 32416, has_genre, 36212 32416, release_year, 9377 14626, has_genre, 36212 14626, release_year, 9377 36793, has_genre, 36212 36793, release_year, 9377 9406, has_genre, 36212 9406, release_year, 9377 19629, has_genre, 36212 19629, release_year, 9377 4143, has_genre, 36212 4143, starred_actors, 5032 30805, has_genre, 36212 30805, release_year, 9377 35470, directed_by, 31492 35470, has_genre, 36212 35470, release_year, 9377 35470, starred_actors, 17871 35470, starred_actors, 5032 35470, written_by, 37258 3765, has_genre, 36212 3765, release_year, 9377 14064, has_genre, 36212 14064, release_year, 9377 8660, has_genre, 36212 8660, release_year, 9377 14115, has_genre, 36212 14115, release_year, 9377 1492, has_genre, 36212 1492, release_year, 9377 9568, has_genre, 36212 9568, release_year, 9377 2559, has_genre, 36212 2559, release_year, 9377 31381, has_genre, 36212 31381, has_tags, 36212 31381, release_year, 9377 34649, has_genre, 36212 34649, release_year, 9377 14919, has_genre, 36212 14919, has_tags, 35271 698, has_genre, 36212 698, release_year, 9377 7969, has_genre, 36212 7969, release_year, 9377 17726, has_genre, 36212 17726, release_year, 9377 14504, has_genre, 36212 14504, release_year, 9377 36178, has_genre, 36212 36178, release_year, 9377 10185, has_genre, 36212 10185, release_year, 9377 5465, has_genre, 36212 5465, has_tags, 5032 5465, starred_actors, 5032 15726, has_genre, 36212 15726, release_year, 9377 38804, has_genre, 36212 38804, release_year, 9377 14840, has_genre, 36212 14840, release_year, 9377 142, has_genre, 36212 142, release_year, 9377 26235, has_genre, 36212 26235, release_year, 9377 4820, has_genre, 36212 4820, release_year, 9377 37252, has_genre, 36212 37252, written_by, 37258 18995, has_genre, 36212 18995, starred_actors, 5032 12162, has_genre, 36212 12162, has_tags, 5032 12162, starred_actors, 5032 5209, has_genre, 36212 5209, release_year, 9377 Question: For what reason are CHARMING, MELODRAMA, and THE NORMAL HEART associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "CHARMING", "MELODRAMA", "THE NORMAL HEART" ], "valid_edges": [ [ "99 HOMES", "has_genre", "DRAMA" ], [ "99 HOMES", "release_year", "2014" ], [ "A WALK AMONG THE TOMBSTONES", "has_genre", "DRAMA" ], [ "A WALK AMONG THE TOMBSTONES", "release_year", "2014" ], [ "ADDICTED", "has_genre", "DRAMA" ], [ "ADDICTED", "release_year", "2014" ], [ "AFFLUENZA", "has_genre", "DRAMA" ], [ "AFFLUENZA", "release_year", "2014" ], [ "ALOFT", "has_genre", "DRAMA" ], [ "ALOFT", "release_year", "2014" ], [ "AN EDUCATION", "has_genre", "DRAMA" ], [ "AN EDUCATION", "has_tags", "CHARMING" ], [ "AN EDUCATION", "release_year", "2009" ], [ "AND SO IT GOES", "has_genre", "DRAMA" ], [ "AND SO IT GOES", "release_year", "2014" ], [ "ANNIE", "has_genre", "DRAMA" ], [ "ANNIE", "release_year", "2014" ], [ "BAREFOOT", "has_genre", "DRAMA" ], [ "BAREFOOT", "release_year", "2014" ], [ "BEGIN AGAIN", "has_genre", "DRAMA" ], [ "BEGIN AGAIN", "has_tags", "MARK RUFFALO" ], [ "BEGIN AGAIN", "starred_actors", "MARK RUFFALO" ], [ "BETTER LIVING THROUGH CHEMISTRY", "has_genre", "DRAMA" ], [ "BETTER LIVING THROUGH CHEMISTRY", "release_year", "2014" ], [ "BEYOND THE LIGHTS", "has_genre", "DRAMA" ], [ "BEYOND THE LIGHTS", "release_year", "2014" ], [ "BIG EYES", "has_genre", "DRAMA" ], [ "BIG EYES", "release_year", "2014" ], [ "BIRD PEOPLE", "has_genre", "DRAMA" ], [ "BIRD PEOPLE", "release_year", "2014" ], [ "BLIND", "has_genre", "DRAMA" ], [ "BLIND", "release_year", "2014" ], [ "BOYHOOD", "has_genre", "DRAMA" ], [ "BOYHOOD", "has_tags", "2014" ], [ "BOYHOOD", "release_year", "2014" ], [ "BROKEN EMBRACES", "has_genre", "DRAMA" ], [ "BROKEN EMBRACES", "has_tags", "MELODRAMA" ], [ "BROKEN EMBRACES", "release_year", "2009" ], [ "C.O.G.", "has_genre", "DRAMA" ], [ "C.O.G.", "starred_actors", "JONATHAN GROFF" ], [ "CAKE", "has_genre", "DRAMA" ], [ "CAKE", "release_year", "2014" ], [ "CALVARY", "has_genre", "DRAMA" ], [ "CALVARY", "release_year", "2014" ], [ "CAMP X-RAY", "has_genre", "DRAMA" ], [ "CAMP X-RAY", "release_year", "2014" ], [ "CLOUDS OF SILS MARIA", "has_genre", "DRAMA" ], [ "CLOUDS OF SILS MARIA", "release_year", "2014" ], [ "COMET", "has_genre", "DRAMA" ], [ "COMET", "release_year", "2014" ], [ "COMMON", "has_genre", "DRAMA" ], [ "COMMON", "release_year", "2014" ], [ "DAYS AND NIGHTS", "has_genre", "DRAMA" ], [ "DAYS AND NIGHTS", "release_year", "2014" ], [ "DEAR WHITE PEOPLE", "has_genre", "DRAMA" ], [ "DEAR WHITE PEOPLE", "release_year", "2014" ], [ "DRAFT DAY", "has_genre", "DRAMA" ], [ "DRAFT DAY", "release_year", "2014" ], [ "EAT PRAY LOVE", "directed_by", "RYAN MURPHY" ], [ "EAT PRAY LOVE", "has_genre", "DRAMA" ], [ "EAT PRAY LOVE", "written_by", "RYAN MURPHY" ], [ "EDEN", "has_genre", "DRAMA" ], [ "EDEN", "release_year", "2014" ], [ "ENDLESS LOVE", "has_genre", "DRAMA" ], [ "ENDLESS LOVE", "release_year", "2014" ], [ "FORCE MAJEURE", "has_genre", "DRAMA" ], [ "FORCE MAJEURE", "has_tags", "2014" ], [ "FORCE MAJEURE", "release_year", "2014" ], [ "FOXCATCHER", "has_genre", "DRAMA" ], [ "FOXCATCHER", "has_tags", "MARK RUFFALO" ], [ "FOXCATCHER", "release_year", "2014" ], [ "FOXCATCHER", "starred_actors", "MARK RUFFALO" ], [ "FRANK", "has_genre", "DRAMA" ], [ "FRANK", "release_year", "2014" ], [ "FROZEN", "has_genre", "DRAMA" ], [ "FROZEN", "starred_actors", "JONATHAN GROFF" ], [ "FURY", "has_genre", "DRAMA" ], [ "FURY", "release_year", "2014" ], [ "GIRLHOOD", "has_genre", "DRAMA" ], [ "GIRLHOOD", "release_year", "2014" ], [ "GOD HELP THE GIRL", "has_genre", "DRAMA" ], [ "GOD HELP THE GIRL", "release_year", "2014" ], [ "GOD'S NOT DEAD", "has_genre", "DRAMA" ], [ "GOD'S NOT DEAD", "release_year", "2014" ], [ "GOD'S POCKET", "has_genre", "DRAMA" ], [ "GOD'S POCKET", "release_year", "2014" ], [ "GOODBYE TO LANGUAGE", "has_genre", "DRAMA" ], [ "GOODBYE TO LANGUAGE", "release_year", "2014" ], [ "HAIDER", "has_genre", "DRAMA" ], [ "HAIDER", "release_year", "2014" ], [ "HAPPY CHRISTMAS", "has_genre", "DRAMA" ], [ "HAPPY CHRISTMAS", "release_year", "2014" ], [ "HEALING", "has_genre", "DRAMA" ], [ "HEALING", "release_year", "2014" ], [ "HEAVEN IS FOR REAL", "has_genre", "DRAMA" ], [ "HEAVEN IS FOR REAL", "release_year", "2014" ], [ "HELLION", "has_genre", "DRAMA" ], [ "HELLION", "release_year", "2014" ], [ "HER", "has_genre", "DRAMA" ], [ "HER", "has_tags", "2014" ], [ "HIGHWAY", "has_genre", "DRAMA" ], [ "HIGHWAY", "release_year", "2014" ], [ "INBETWEEN WORLDS", "has_genre", "DRAMA" ], [ "INBETWEEN WORLDS", "release_year", "2014" ], [ "INHERENT VICE", "has_genre", "DRAMA" ], [ "INHERENT VICE", "release_year", "2014" ], [ "JAMESY BOY", "has_genre", "DRAMA" ], [ "JAMESY BOY", "release_year", "2014" ], [ "JAMIE MARKS IS DEAD", "has_genre", "DRAMA" ], [ "JAMIE MARKS IS DEAD", "release_year", "2014" ], [ "JAUJA", "has_genre", "DRAMA" ], [ "JAUJA", "release_year", "2014" ], [ "JERSEY BOYS", "has_genre", "DRAMA" ], [ "JERSEY BOYS", "release_year", "2014" ], [ "KILL THE MESSENGER", "has_genre", "DRAMA" ], [ "KILL THE MESSENGER", "release_year", "2014" ], [ "KUMIKO, THE TREASURE HUNTER", "has_genre", "DRAMA" ], [ "KUMIKO, THE TREASURE HUNTER", "release_year", "2014" ], [ "LATE PHASES", "has_genre", "DRAMA" ], [ "LATE PHASES", "release_year", "2014" ], [ "LATITUDES", "has_genre", "DRAMA" ], [ "LATITUDES", "release_year", "2014" ], [ "LEVIATHAN", "has_genre", "DRAMA" ], [ "LEVIATHAN", "release_year", "2014" ], [ "LILTING", "has_genre", "DRAMA" ], [ "LILTING", "release_year", "2014" ], [ "LISTEN UP PHILIP", "has_genre", "DRAMA" ], [ "LISTEN UP PHILIP", "release_year", "2014" ], [ "LITTLE ACCIDENTS", "has_genre", "DRAMA" ], [ "LITTLE ACCIDENTS", "release_year", "2014" ], [ "LOST HORIZON", "has_genre", "DRAMA" ], [ "LOST HORIZON", "written_by", "LARRY KRAMER" ], [ "LOVE IS STRANGE", "has_genre", "DRAMA" ], [ "LOVE IS STRANGE", "release_year", "2014" ], [ "LULLABY", "has_genre", "DRAMA" ], [ "LULLABY", "release_year", "2014" ], [ "MAPS TO THE STARS", "has_genre", "DRAMA" ], [ "MAPS TO THE STARS", "has_tags", "DRAMA" ], [ "MAPS TO THE STARS", "release_year", "2014" ], [ "MARGARET", "has_genre", "DRAMA" ], [ "MARGARET", "has_tags", "DRAMA" ], [ "MARGARET", "starred_actors", "MARK RUFFALO" ], [ "MILLION DOLLAR ARM", "has_genre", "DRAMA" ], [ "MILLION DOLLAR ARM", "release_year", "2014" ], [ "MOMMY", "has_genre", "DRAMA" ], [ "MOMMY", "release_year", "2014" ], [ "MR. TURNER", "has_genre", "DRAMA" ], [ "MR. TURNER", "release_year", "2014" ], [ "MY LIFE WITHOUT ME", "has_genre", "DRAMA" ], [ "MY LIFE WITHOUT ME", "has_tags", "MARK RUFFALO" ], [ "MY OLD LADY", "has_genre", "DRAMA" ], [ "MY OLD LADY", "release_year", "2014" ], [ "PERFECT SISTERS", "has_genre", "DRAMA" ], [ "PERFECT SISTERS", "release_year", "2014" ], [ "PK", "has_genre", "DRAMA" ], [ "PK", "release_year", "2014" ], [ "PRIDE", "has_genre", "DRAMA" ], [ "PRIDE", "release_year", "2014" ], [ "RAGE", "has_genre", "DRAMA" ], [ "RAGE", "release_year", "2014" ], [ "RESERVATION ROAD", "has_genre", "DRAMA" ], [ "RESERVATION ROAD", "has_tags", "MARK RUFFALO" ], [ "ROB THE MOB", "has_genre", "DRAMA" ], [ "ROB THE MOB", "release_year", "2014" ], [ "ROSEWATER", "has_genre", "DRAMA" ], [ "ROSEWATER", "release_year", "2014" ], [ "RUDDERLESS", "has_genre", "DRAMA" ], [ "RUDDERLESS", "release_year", "2014" ], [ "RUNNING WITH SCISSORS", "directed_by", "RYAN MURPHY" ], [ "RUNNING WITH SCISSORS", "has_genre", "DRAMA" ], [ "RUNNING WITH SCISSORS", "written_by", "RYAN MURPHY" ], [ "SAINT LAURENT", "has_genre", "DRAMA" ], [ "SAINT LAURENT", "release_year", "2014" ], [ "SALTING THE BATTLEFIELD", "has_genre", "DRAMA" ], [ "SALTING THE BATTLEFIELD", "release_year", "2014" ], [ "SELMA", "has_genre", "DRAMA" ], [ "SELMA", "release_year", "2014" ], [ "SENSO", "has_genre", "DRAMA" ], [ "SENSO", "has_tags", "MELODRAMA" ], [ "SERENA", "has_genre", "DRAMA" ], [ "SERENA", "release_year", "2014" ], [ "ST. VINCENT", "has_genre", "DRAMA" ], [ "ST. VINCENT", "release_year", "2014" ], [ "STATIONS OF THE CROSS", "has_genre", "DRAMA" ], [ "STATIONS OF THE CROSS", "release_year", "2014" ], [ "STILL ALICE", "has_genre", "DRAMA" ], [ "STILL ALICE", "release_year", "2014" ], [ "SYMPATHY FOR DELICIOUS", "directed_by", "MARK RUFFALO" ], [ "SYMPATHY FOR DELICIOUS", "has_genre", "DRAMA" ], [ "SYMPATHY FOR DELICIOUS", "starred_actors", "MARK RUFFALO" ], [ "THANK YOU A LOT", "has_genre", "DRAMA" ], [ "THANK YOU A LOT", "release_year", "2014" ], [ "THANKS FOR SHARING", "has_genre", "DRAMA" ], [ "THANKS FOR SHARING", "starred_actors", "MARK RUFFALO" ], [ "THE ANGRIEST MAN IN BROOKLYN", "has_genre", "DRAMA" ], [ "THE ANGRIEST MAN IN BROOKLYN", "release_year", "2014" ], [ "THE BEST OF ME", "has_genre", "DRAMA" ], [ "THE BEST OF ME", "release_year", "2014" ], [ "THE CIRCLE", "has_genre", "DRAMA" ], [ "THE CIRCLE", "release_year", "2014" ], [ "THE COBBLER", "has_genre", "DRAMA" ], [ "THE COBBLER", "release_year", "2014" ], [ "THE DROP", "has_genre", "DRAMA" ], [ "THE DROP", "release_year", "2014" ], [ "THE FAULT IN OUR STARS", "has_genre", "DRAMA" ], [ "THE FAULT IN OUR STARS", "has_tags", "DRAMA" ], [ "THE FAULT IN OUR STARS", "release_year", "2014" ], [ "THE GOOD LIE", "has_genre", "DRAMA" ], [ "THE GOOD LIE", "release_year", "2014" ], [ "THE HOMESMAN", "has_genre", "DRAMA" ], [ "THE HOMESMAN", "release_year", "2014" ], [ "THE HUNDRED-FOOT JOURNEY", "has_genre", "DRAMA" ], [ "THE HUNDRED-FOOT JOURNEY", "release_year", "2014" ], [ "THE IMITATION GAME", "has_genre", "DRAMA" ], [ "THE IMITATION GAME", "release_year", "2014" ], [ "THE JUDGE", "has_genre", "DRAMA" ], [ "THE JUDGE", "release_year", "2014" ], [ "THE LAST CASTLE", "has_genre", "DRAMA" ], [ "THE LAST CASTLE", "starred_actors", "MARK RUFFALO" ], [ "THE NEW GIRLFRIEND", "has_genre", "DRAMA" ], [ "THE NEW GIRLFRIEND", "release_year", "2014" ], [ "THE NORMAL HEART", "directed_by", "RYAN MURPHY" ], [ "THE NORMAL HEART", "has_genre", "DRAMA" ], [ "THE NORMAL HEART", "release_year", "2014" ], [ "THE NORMAL HEART", "starred_actors", "JONATHAN GROFF" ], [ "THE NORMAL HEART", "starred_actors", "MARK RUFFALO" ], [ "THE NORMAL HEART", "written_by", "LARRY KRAMER" ], [ "THE OTHER WOMAN", "has_genre", "DRAMA" ], [ "THE OTHER WOMAN", "release_year", "2014" ], [ "THE OUTSIDER", "has_genre", "DRAMA" ], [ "THE OUTSIDER", "release_year", "2014" ], [ "THE RECKONING", "has_genre", "DRAMA" ], [ "THE RECKONING", "release_year", "2014" ], [ "THE ROVER", "has_genre", "DRAMA" ], [ "THE ROVER", "release_year", "2014" ], [ "THE SINGLE MOMS CLUB", "has_genre", "DRAMA" ], [ "THE SINGLE MOMS CLUB", "release_year", "2014" ], [ "THE SKELETON TWINS", "has_genre", "DRAMA" ], [ "THE SKELETON TWINS", "release_year", "2014" ], [ "THE THEORY OF EVERYTHING", "has_genre", "DRAMA" ], [ "THE THEORY OF EVERYTHING", "release_year", "2014" ], [ "THE WAY HE LOOKS", "has_genre", "DRAMA" ], [ "THE WAY HE LOOKS", "has_tags", "DRAMA" ], [ "THE WAY HE LOOKS", "release_year", "2014" ], [ "THE WONDERS", "has_genre", "DRAMA" ], [ "THE WONDERS", "release_year", "2014" ], [ "THERE'S ALWAYS TOMORROW", "has_genre", "DRAMA" ], [ "THERE'S ALWAYS TOMORROW", "has_tags", "MELODRAMA" ], [ "THIS IS WHERE I LEAVE YOU", "has_genre", "DRAMA" ], [ "THIS IS WHERE I LEAVE YOU", "release_year", "2014" ], [ "TIMBUKTU", "has_genre", "DRAMA" ], [ "TIMBUKTU", "release_year", "2014" ], [ "TUSK", "has_genre", "DRAMA" ], [ "TUSK", "release_year", "2014" ], [ "UNBROKEN", "has_genre", "DRAMA" ], [ "UNBROKEN", "release_year", "2014" ], [ "VERONICA MARS", "has_genre", "DRAMA" ], [ "VERONICA MARS", "release_year", "2014" ], [ "WELCOME TO NEW YORK", "has_genre", "DRAMA" ], [ "WELCOME TO NEW YORK", "release_year", "2014" ], [ "WHAT DOESN'T KILL YOU", "has_genre", "DRAMA" ], [ "WHAT DOESN'T KILL YOU", "has_tags", "MARK RUFFALO" ], [ "WHAT DOESN'T KILL YOU", "starred_actors", "MARK RUFFALO" ], [ "WHEN ANIMALS DREAM", "has_genre", "DRAMA" ], [ "WHEN ANIMALS DREAM", "release_year", "2014" ], [ "WHIPLASH", "has_genre", "DRAMA" ], [ "WHIPLASH", "release_year", "2014" ], [ "WHITE GOD", "has_genre", "DRAMA" ], [ "WHITE GOD", "release_year", "2014" ], [ "WILD", "has_genre", "DRAMA" ], [ "WILD", "release_year", "2014" ], [ "WINTER SLEEP", "has_genre", "DRAMA" ], [ "WINTER SLEEP", "release_year", "2014" ], [ "WISH I WAS HERE", "has_genre", "DRAMA" ], [ "WISH I WAS HERE", "release_year", "2014" ], [ "WOMEN IN LOVE", "has_genre", "DRAMA" ], [ "WOMEN IN LOVE", "written_by", "LARRY KRAMER" ], [ "XX/XY", "has_genre", "DRAMA" ], [ "XX/XY", "starred_actors", "MARK RUFFALO" ], [ "YOU CAN COUNT ON ME", "has_genre", "DRAMA" ], [ "YOU CAN COUNT ON ME", "has_tags", "MARK RUFFALO" ], [ "YOU CAN COUNT ON ME", "starred_actors", "MARK RUFFALO" ], [ "YVES SAINT LAURENT", "has_genre", "DRAMA" ], [ "YVES SAINT LAURENT", "release_year", "2014" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 24438, 1993 35845, 2006 39289, ACTION 40074, BLACK BOOK 16664, BLOOD DIAMOND 22435, CHILDREN OF MEN 17602, DAS MILLIONENSPIEL 3567, DAYS OF GLORY 10315, FLAGS OF OUR FATHERS 36601, FLANDERS 1273, FLYBOYS 3990, GETTYSBURG 18934, LETTERS FROM IWO JIMA 39852, PAN'S LABYRINTH 34732, PLATOON 16772, SNIPER 11124, STALINGRAD 9355, THE MARSH 32618, THE RAPE OF EUROPA 4294, THE SUBSTITUTE 2783, THE WIND THAT SHAKES THE BARLEY 2930, TOM BERENGER 11413, TOM TOELLE 22214, WAR src, edge_attr, dst 40074, has_genre, 22214 40074, release_year, 35845 16664, has_tags, 22214 16664, release_year, 35845 22435, has_tags, 22214 22435, release_year, 35845 17602, directed_by, 11413 17602, has_genre, 39289 3567, has_genre, 22214 3567, has_tags, 22214 3567, release_year, 35845 10315, has_genre, 22214 10315, has_tags, 22214 10315, release_year, 35845 36601, has_genre, 22214 36601, release_year, 35845 1273, has_tags, 22214 1273, release_year, 35845 3990, has_genre, 22214 3990, release_year, 24438 3990, starred_actors, 2930 18934, has_genre, 22214 18934, has_tags, 22214 18934, release_year, 35845 39852, has_genre, 22214 39852, has_tags, 22214 39852, release_year, 35845 34732, has_genre, 22214 34732, has_tags, 2930 34732, has_tags, 22214 34732, starred_actors, 2930 16772, release_year, 24438 16772, starred_actors, 2930 11124, has_genre, 22214 11124, release_year, 24438 9355, release_year, 35845 32618, has_genre, 22214 32618, release_year, 35845 4294, release_year, 24438 4294, starred_actors, 2930 2783, has_genre, 22214 2783, release_year, 35845 22214, has_genre, 39289 Question: How are GETTYSBURG, THE MARSH, and TOM TOELLE related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "GETTYSBURG", "THE MARSH", "TOM TOELLE" ], "valid_edges": [ [ "BLACK BOOK", "has_genre", "WAR" ], [ "BLACK BOOK", "release_year", "2006" ], [ "BLOOD DIAMOND", "has_tags", "WAR" ], [ "BLOOD DIAMOND", "release_year", "2006" ], [ "CHILDREN OF MEN", "has_tags", "WAR" ], [ "CHILDREN OF MEN", "release_year", "2006" ], [ "DAS MILLIONENSPIEL", "directed_by", "TOM TOELLE" ], [ "DAS MILLIONENSPIEL", "has_genre", "ACTION" ], [ "DAYS OF GLORY", "has_genre", "WAR" ], [ "DAYS OF GLORY", "has_tags", "WAR" ], [ "DAYS OF GLORY", "release_year", "2006" ], [ "FLAGS OF OUR FATHERS", "has_genre", "WAR" ], [ "FLAGS OF OUR FATHERS", "has_tags", "WAR" ], [ "FLAGS OF OUR FATHERS", "release_year", "2006" ], [ "FLANDERS", "has_genre", "WAR" ], [ "FLANDERS", "release_year", "2006" ], [ "FLYBOYS", "has_tags", "WAR" ], [ "FLYBOYS", "release_year", "2006" ], [ "GETTYSBURG", "has_genre", "WAR" ], [ "GETTYSBURG", "release_year", "1993" ], [ "GETTYSBURG", "starred_actors", "TOM BERENGER" ], [ "LETTERS FROM IWO JIMA", "has_genre", "WAR" ], [ "LETTERS FROM IWO JIMA", "has_tags", "WAR" ], [ "LETTERS FROM IWO JIMA", "release_year", "2006" ], [ "PAN'S LABYRINTH", "has_genre", "WAR" ], [ "PAN'S LABYRINTH", "has_tags", "WAR" ], [ "PAN'S LABYRINTH", "release_year", "2006" ], [ "PLATOON", "has_genre", "WAR" ], [ "PLATOON", "has_tags", "TOM BERENGER" ], [ "PLATOON", "has_tags", "WAR" ], [ "PLATOON", "starred_actors", "TOM BERENGER" ], [ "SNIPER", "release_year", "1993" ], [ "SNIPER", "starred_actors", "TOM BERENGER" ], [ "STALINGRAD", "has_genre", "WAR" ], [ "STALINGRAD", "release_year", "1993" ], [ "THE MARSH", "release_year", "2006" ], [ "THE RAPE OF EUROPA", "has_genre", "WAR" ], [ "THE RAPE OF EUROPA", "release_year", "2006" ], [ "THE SUBSTITUTE", "release_year", "1993" ], [ "THE SUBSTITUTE", "starred_actors", "TOM BERENGER" ], [ "THE WIND THAT SHAKES THE BARLEY", "has_genre", "WAR" ], [ "THE WIND THAT SHAKES THE BARLEY", "release_year", "2006" ], [ "WAR", "has_genre", "ACTION" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 27261, 2009 34443, 31 NORTH 62 EAST 28568, A PERFECT GETAWAY 12694, A PISTOL FOR RINGO 12088, ACCIDENT 22144, ALEC BALDWIN 29167, AMER 23227, ARMORED 6891, BAARÌA 31895, BERBERIAN SOUND STUDIO 2570, BLACK SUNDAY 39539, BLOOD AND BLACK LACE 20961, BLOOD RIVER 4197, BLUEBEARD 37883, BROKEN EMBRACES 37594, BROTHERHOOD 6283, CARGO 7143, CHLOE 31844, COSMONAUT 8438, CUT AND RUN 10313, DEAD AGAIN 3645, DEADLINE 8381, DETOUR 6692, DISTRICT 9 17274, DOLAN'S CADILLAC 11127, DON MCKAY 27842, DON'T LOOK NOW 30123, DORIAN GRAY 23387, EVERYBODY'S FINE 14585, EXAM 8176, FAREWELL 4159, FEAR ISLAND 31919, FORMOSA BETRAYED 3724, GAMER 12638, GLORIOUS 39 3345, HEAVEN'S PRISONERS 27937, HIERRO 37563, HOMECOMING 23780, HURT 4749, I AM LOVE 24167, INFERNO 16200, ITALIAN 30872, KILL THEORY 14653, LAW ABIDING CITIZEN 11652, LONELY STREET 38786, MALICE 14537, NOT FORGOTTEN 36387, OBSESSED 1827, ORPHAN 738, PLOT OF FEAR 25809, PUSH 12428, RAGE 2010, RAMPAGE 3091, SCOTT FRANK 6119, SLEUTH 40102, THE CANYON 16442, THE COLLECTOR 4337, THE CRY OF THE OWL 15205, THE DISAPPEARANCE OF ALICE CREED 32932, THE DOUBLE HOUR 24006, THE FIFTH CORD 19760, THE FRIENDS AT THE MARGHERITA CAFE 35772, THE GIRL BY THE LAKE 36893, THE GIRL ON THE TRAIN 38083, THE GIRL WHO KICKED THE HORNETS' NEST 21338, THE GIRL WHO PLAYED WITH FIRE 7240, THE GIRL WITH THE DRAGON TATTOO 23333, THE HOLE 28886, THE KILLING ROOM 11542, THE LAUGHING WOMAN 37148, THE SECRET IN THEIR EYES 35993, THE STEPFATHER 17719, THE THAW 24489, THE TOURNAMENT 25030, THE UNKNOWN WOMAN 5463, THE WAGES OF FEAR 24811, THRILLER 17396, TORSO 37099, TRIANGLE 8129, VIDEOCRACY 15645, VINCERE 15036, WHITEOUT src, edge_attr, dst 34443, has_genre, 24811 34443, release_year, 27261 28568, has_genre, 24811 28568, release_year, 27261 12694, in_language, 16200 12088, has_genre, 24811 12088, release_year, 27261 29167, has_genre, 24811 29167, release_year, 27261 23227, has_genre, 24811 23227, release_year, 27261 6891, in_language, 16200 6891, release_year, 27261 31895, has_genre, 24811 31895, in_language, 16200 2570, has_genre, 24811 2570, in_language, 16200 39539, has_genre, 24811 39539, in_language, 16200 20961, has_genre, 24811 20961, release_year, 27261 4197, has_genre, 24811 4197, release_year, 27261 37883, has_genre, 24811 37883, release_year, 27261 37594, has_genre, 24811 37594, release_year, 27261 6283, has_genre, 24811 6283, release_year, 27261 7143, has_genre, 24811 7143, release_year, 27261 31844, in_language, 16200 31844, release_year, 27261 8438, has_genre, 24811 8438, in_language, 16200 10313, has_genre, 24811 10313, written_by, 3091 3645, has_genre, 24811 3645, release_year, 27261 8381, has_genre, 24811 8381, release_year, 27261 6692, has_genre, 24811 6692, has_tags, 24811 6692, release_year, 27261 17274, has_genre, 24811 17274, release_year, 27261 11127, has_genre, 24811 11127, release_year, 27261 27842, has_genre, 24811 27842, in_language, 16200 30123, has_genre, 24811 30123, release_year, 27261 23387, in_language, 16200 23387, release_year, 27261 14585, has_genre, 24811 14585, release_year, 27261 8176, has_genre, 24811 8176, release_year, 27261 4159, has_genre, 24811 4159, release_year, 27261 31919, has_genre, 24811 31919, release_year, 27261 3724, has_genre, 24811 3724, release_year, 27261 12638, has_genre, 24811 12638, release_year, 27261 3345, has_genre, 24811 3345, starred_actors, 22144 3345, written_by, 3091 27937, has_genre, 24811 27937, release_year, 27261 37563, has_genre, 24811 37563, release_year, 27261 23780, has_genre, 24811 23780, release_year, 27261 4749, in_language, 16200 4749, release_year, 27261 24167, has_genre, 24811 24167, in_language, 16200 30872, has_genre, 24811 30872, release_year, 27261 14653, has_genre, 24811 14653, release_year, 27261 11652, has_genre, 24811 11652, release_year, 27261 38786, has_genre, 24811 38786, starred_actors, 22144 38786, written_by, 3091 14537, has_genre, 24811 14537, release_year, 27261 36387, has_genre, 24811 36387, release_year, 27261 1827, has_genre, 24811 1827, release_year, 27261 738, has_genre, 24811 738, in_language, 16200 25809, has_genre, 24811 25809, release_year, 27261 12428, has_genre, 24811 12428, release_year, 27261 2010, has_genre, 24811 2010, release_year, 27261 6119, has_genre, 24811 6119, in_language, 16200 40102, has_genre, 24811 40102, release_year, 27261 16442, has_genre, 24811 16442, release_year, 27261 4337, has_genre, 24811 4337, release_year, 27261 15205, has_genre, 24811 15205, release_year, 27261 32932, in_language, 16200 32932, release_year, 27261 24006, has_genre, 24811 24006, in_language, 16200 19760, in_language, 16200 19760, release_year, 27261 35772, has_genre, 24811 35772, in_language, 16200 36893, has_genre, 24811 36893, release_year, 27261 38083, has_genre, 24811 38083, has_tags, 24811 38083, release_year, 27261 21338, has_tags, 24811 21338, release_year, 27261 7240, has_tags, 24811 7240, release_year, 27261 23333, has_genre, 24811 23333, release_year, 27261 28886, has_genre, 24811 28886, release_year, 27261 11542, has_genre, 24811 11542, in_language, 16200 37148, has_genre, 24811 37148, release_year, 27261 35993, has_genre, 24811 35993, release_year, 27261 17719, has_genre, 24811 17719, release_year, 27261 24489, has_genre, 24811 24489, release_year, 27261 25030, has_genre, 24811 25030, in_language, 16200 5463, has_genre, 24811 5463, in_language, 16200 17396, has_genre, 24811 17396, in_language, 16200 37099, has_genre, 24811 37099, release_year, 27261 8129, in_language, 16200 8129, release_year, 27261 15645, in_language, 16200 15645, release_year, 27261 15036, has_tags, 24811 15036, release_year, 27261 Question: For what reason are A PISTOL FOR RINGO, SCOTT FRANK, and THE CANYON associated? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A PISTOL FOR RINGO", "SCOTT FRANK", "THE CANYON" ], "valid_edges": [ [ "31 NORTH 62 EAST", "has_genre", "THRILLER" ], [ "31 NORTH 62 EAST", "release_year", "2009" ], [ "A PERFECT GETAWAY", "has_genre", "THRILLER" ], [ "A PERFECT GETAWAY", "release_year", "2009" ], [ "A PISTOL FOR RINGO", "in_language", "ITALIAN" ], [ "ACCIDENT", "has_genre", "THRILLER" ], [ "ACCIDENT", "release_year", "2009" ], [ "AMER", "has_genre", "THRILLER" ], [ "AMER", "release_year", "2009" ], [ "ARMORED", "has_genre", "THRILLER" ], [ "ARMORED", "release_year", "2009" ], [ "BAARÌA", "in_language", "ITALIAN" ], [ "BAARÌA", "release_year", "2009" ], [ "BERBERIAN SOUND STUDIO", "has_genre", "THRILLER" ], [ "BERBERIAN SOUND STUDIO", "in_language", "ITALIAN" ], [ "BLACK SUNDAY", "has_genre", "THRILLER" ], [ "BLACK SUNDAY", "in_language", "ITALIAN" ], [ "BLOOD AND BLACK LACE", "has_genre", "THRILLER" ], [ "BLOOD AND BLACK LACE", "in_language", "ITALIAN" ], [ "BLOOD RIVER", "has_genre", "THRILLER" ], [ "BLOOD RIVER", "release_year", "2009" ], [ "BLUEBEARD", "has_genre", "THRILLER" ], [ "BLUEBEARD", "release_year", "2009" ], [ "BROKEN EMBRACES", "has_genre", "THRILLER" ], [ "BROKEN EMBRACES", "release_year", "2009" ], [ "BROTHERHOOD", "has_genre", "THRILLER" ], [ "BROTHERHOOD", "release_year", "2009" ], [ "CARGO", "has_genre", "THRILLER" ], [ "CARGO", "release_year", "2009" ], [ "CHLOE", "has_genre", "THRILLER" ], [ "CHLOE", "release_year", "2009" ], [ "COSMONAUT", "in_language", "ITALIAN" ], [ "COSMONAUT", "release_year", "2009" ], [ "CUT AND RUN", "has_genre", "THRILLER" ], [ "CUT AND RUN", "in_language", "ITALIAN" ], [ "DEAD AGAIN", "has_genre", "THRILLER" ], [ "DEAD AGAIN", "written_by", "SCOTT FRANK" ], [ "DEADLINE", "has_genre", "THRILLER" ], [ "DEADLINE", "release_year", "2009" ], [ "DETOUR", "has_genre", "THRILLER" ], [ "DETOUR", "release_year", "2009" ], [ "DISTRICT 9", "has_genre", "THRILLER" ], [ "DISTRICT 9", "has_tags", "THRILLER" ], [ "DISTRICT 9", "release_year", "2009" ], [ "DOLAN'S CADILLAC", "has_genre", "THRILLER" ], [ "DOLAN'S CADILLAC", "release_year", "2009" ], [ "DON MCKAY", "has_genre", "THRILLER" ], [ "DON MCKAY", "release_year", "2009" ], [ "DON'T LOOK NOW", "has_genre", "THRILLER" ], [ "DON'T LOOK NOW", "in_language", "ITALIAN" ], [ "DORIAN GRAY", "has_genre", "THRILLER" ], [ "DORIAN GRAY", "release_year", "2009" ], [ "EVERYBODY'S FINE", "in_language", "ITALIAN" ], [ "EVERYBODY'S FINE", "release_year", "2009" ], [ "EXAM", "has_genre", "THRILLER" ], [ "EXAM", "release_year", "2009" ], [ "FAREWELL", "has_genre", "THRILLER" ], [ "FAREWELL", "release_year", "2009" ], [ "FEAR ISLAND", "has_genre", "THRILLER" ], [ "FEAR ISLAND", "release_year", "2009" ], [ "FORMOSA BETRAYED", "has_genre", "THRILLER" ], [ "FORMOSA BETRAYED", "release_year", "2009" ], [ "GAMER", "has_genre", "THRILLER" ], [ "GAMER", "release_year", "2009" ], [ "GLORIOUS 39", "has_genre", "THRILLER" ], [ "GLORIOUS 39", "release_year", "2009" ], [ "HEAVEN'S PRISONERS", "has_genre", "THRILLER" ], [ "HEAVEN'S PRISONERS", "starred_actors", "ALEC BALDWIN" ], [ "HEAVEN'S PRISONERS", "written_by", "SCOTT FRANK" ], [ "HIERRO", "has_genre", "THRILLER" ], [ "HIERRO", "release_year", "2009" ], [ "HOMECOMING", "has_genre", "THRILLER" ], [ "HOMECOMING", "release_year", "2009" ], [ "HURT", "has_genre", "THRILLER" ], [ "HURT", "release_year", "2009" ], [ "I AM LOVE", "in_language", "ITALIAN" ], [ "I AM LOVE", "release_year", "2009" ], [ "INFERNO", "has_genre", "THRILLER" ], [ "INFERNO", "in_language", "ITALIAN" ], [ "KILL THEORY", "has_genre", "THRILLER" ], [ "KILL THEORY", "release_year", "2009" ], [ "LAW ABIDING CITIZEN", "has_genre", "THRILLER" ], [ "LAW ABIDING CITIZEN", "release_year", "2009" ], [ "LONELY STREET", "has_genre", "THRILLER" ], [ "LONELY STREET", "release_year", "2009" ], [ "MALICE", "has_genre", "THRILLER" ], [ "MALICE", "starred_actors", "ALEC BALDWIN" ], [ "MALICE", "written_by", "SCOTT FRANK" ], [ "NOT FORGOTTEN", "has_genre", "THRILLER" ], [ "NOT FORGOTTEN", "release_year", "2009" ], [ "OBSESSED", "has_genre", "THRILLER" ], [ "OBSESSED", "release_year", "2009" ], [ "ORPHAN", "has_genre", "THRILLER" ], [ "ORPHAN", "release_year", "2009" ], [ "PLOT OF FEAR", "has_genre", "THRILLER" ], [ "PLOT OF FEAR", "in_language", "ITALIAN" ], [ "PUSH", "has_genre", "THRILLER" ], [ "PUSH", "release_year", "2009" ], [ "RAGE", "has_genre", "THRILLER" ], [ "RAGE", "release_year", "2009" ], [ "RAMPAGE", "has_genre", "THRILLER" ], [ "RAMPAGE", "release_year", "2009" ], [ "SLEUTH", "has_genre", "THRILLER" ], [ "SLEUTH", "in_language", "ITALIAN" ], [ "THE CANYON", "has_genre", "THRILLER" ], [ "THE CANYON", "release_year", "2009" ], [ "THE COLLECTOR", "has_genre", "THRILLER" ], [ "THE COLLECTOR", "release_year", "2009" ], [ "THE CRY OF THE OWL", "has_genre", "THRILLER" ], [ "THE CRY OF THE OWL", "release_year", "2009" ], [ "THE DISAPPEARANCE OF ALICE CREED", "has_genre", "THRILLER" ], [ "THE DISAPPEARANCE OF ALICE CREED", "release_year", "2009" ], [ "THE DOUBLE HOUR", "in_language", "ITALIAN" ], [ "THE DOUBLE HOUR", "release_year", "2009" ], [ "THE FIFTH CORD", "has_genre", "THRILLER" ], [ "THE FIFTH CORD", "in_language", "ITALIAN" ], [ "THE FRIENDS AT THE MARGHERITA CAFE", "in_language", "ITALIAN" ], [ "THE FRIENDS AT THE MARGHERITA CAFE", "release_year", "2009" ], [ "THE GIRL BY THE LAKE", "has_genre", "THRILLER" ], [ "THE GIRL BY THE LAKE", "in_language", "ITALIAN" ], [ "THE GIRL ON THE TRAIN", "has_genre", "THRILLER" ], [ "THE GIRL ON THE TRAIN", "release_year", "2009" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "has_genre", "THRILLER" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "has_tags", "THRILLER" ], [ "THE GIRL WHO KICKED THE HORNETS' NEST", "release_year", "2009" ], [ "THE GIRL WHO PLAYED WITH FIRE", "has_tags", "THRILLER" ], [ "THE GIRL WHO PLAYED WITH FIRE", "release_year", "2009" ], [ "THE GIRL WITH THE DRAGON TATTOO", "has_tags", "THRILLER" ], [ "THE GIRL WITH THE DRAGON TATTOO", "release_year", "2009" ], [ "THE HOLE", "has_genre", "THRILLER" ], [ "THE HOLE", "release_year", "2009" ], [ "THE KILLING ROOM", "has_genre", "THRILLER" ], [ "THE KILLING ROOM", "release_year", "2009" ], [ "THE LAUGHING WOMAN", "has_genre", "THRILLER" ], [ "THE LAUGHING WOMAN", "in_language", "ITALIAN" ], [ "THE SECRET IN THEIR EYES", "has_genre", "THRILLER" ], [ "THE SECRET IN THEIR EYES", "release_year", "2009" ], [ "THE STEPFATHER", "has_genre", "THRILLER" ], [ "THE STEPFATHER", "release_year", "2009" ], [ "THE THAW", "has_genre", "THRILLER" ], [ "THE THAW", "release_year", "2009" ], [ "THE TOURNAMENT", "has_genre", "THRILLER" ], [ "THE TOURNAMENT", "release_year", "2009" ], [ "THE UNKNOWN WOMAN", "has_genre", "THRILLER" ], [ "THE UNKNOWN WOMAN", "in_language", "ITALIAN" ], [ "THE WAGES OF FEAR", "has_genre", "THRILLER" ], [ "THE WAGES OF FEAR", "in_language", "ITALIAN" ], [ "TORSO", "has_genre", "THRILLER" ], [ "TORSO", "in_language", "ITALIAN" ], [ "TRIANGLE", "has_genre", "THRILLER" ], [ "TRIANGLE", "release_year", "2009" ], [ "VIDEOCRACY", "in_language", "ITALIAN" ], [ "VIDEOCRACY", "release_year", "2009" ], [ "VINCERE", "in_language", "ITALIAN" ], [ "VINCERE", "release_year", "2009" ], [ "WHITEOUT", "has_tags", "THRILLER" ], [ "WHITEOUT", "release_year", "2009" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 13408, 2001 13747, 25 WATTS 5478, 30 YEARS TO LIFE 8200, ALL OVER THE GUY 32427, ALL THE QUEEN'S MEN 17687, AMERICA'S SWEETHEARTS 34899, AMERICAN PIE 2 12224, AMÉLIE 5593, BABY BOY 23952, BANDITS 13418, BARTLEBY 9654, BLACK KNIGHT 35213, BLOW DRY 18692, BOB THE BUTLER 23128, BRIDGET JONES'S DIARY 19026, BUBBLE BOY 17892, CAMOUFLAGE 30463, COMEDY 2605, CORKY ROMANO 18980, CROCODILE DUNDEE IN LOS ANGELES 1915, DIL CHAHTA HAI 12217, DON'T TEMPT ME 7023, DOUBLE TAKE 19756, DOWN TO EARTH 8704, DR. DOLITTLE 2 28808, ESCANABA IN DA MOONLIGHT 23470, EVOLUTION 6915, FOCUS 21322, FREDDY GOT FINGERED 30712, FREEBIE AND THE BEAN 5287, FROZEN 23511, GAUDI AFTERNOON 37949, GET OVER IT 12664, GHOST WORLD 18445, GOD IS GREAT AND I'M NOT 10113, GOOD ADVICE 8648, HAPPY CAMPERS 21060, HARVARD MAN 37229, HE DIED WITH A FELAFEL IN HIS HAND 11344, HEARTBREAKERS 1292, HEDWIG AND THE ANGRY INCH 38901, HIGH HEELS AND LOW LIFES 10703, HOW HIGH 35625, HUMAN NATURE 4358, ICE 16371, ICE AGE 23526, JACKPOT 263, JAY AND SILENT BOB STRIKE BACK 32383, JOE DIRT 12610, JOE SOMEBODY 10109, JOSIE AND THE PUSSYCATS 30384, JUMP TOMORROW 16839, JUST VISITING 7699, KINGDOM COME 20428, KISSING JESSICA STEIN 17559, LEGALLY BLONDE 29734, LITTLE SECRETS 26731, LUCKY BREAK 28660, MADE 6068, MAX KEEBLE'S BIG MOVE 33714, MEAN MACHINE 33853, MONKEYBONE 20003, MONSTERS, INC. 24616, MOSTLY MARTHA 26151, NOBODY'S BABY 5731, NOT ANOTHER TEEN MOVIE 29029, NOVOCAINE 21875, OCEAN'S ELEVEN 6959, ON THE LINE 32186, ONE MAN UP 8935, ONE NIGHT AT MCCOOL'S 28044, PAULINE AND PAULETTE 31445, PONTEROSA 13381, POOTIE TANG 28182, RARE BIRDS 32180, RAT RACE 30422, RICHARD RUSH 38381, ROCK STAR 9530, RUSH HOUR 2 1789, SAVING SILVERMAN 37244, SAY IT ISN'T SO 5880, SERENDIPITY 35100, SHALLOW HAL 7519, SHAOLIN SOCCER 36159, SHREK 30089, SIDEWALKS OF NEW YORK 2407, SON OF THE BRIDE 24221, SPEAKING OF SEX 5170, STEALING HARVARD 7949, STORYTELLING 2235, SUMMER CATCH 4783, SUPER TROOPERS 27762, SWEET NOVEMBER 345, TANGUY 23280, THE ANIMAL 15795, THE ANNIVERSARY PARTY 25674, THE BROTHERS 30164, THE CLOSET 4927, THE CURSE OF THE JADE SCORPION 17778, THE HAPPINESS OF THE KATAKURIS 28107, THE LAST KISS 10353, THE MAN WHO SUED GOD 27713, THE MEXICAN 23086, THE PRINCESS DIARIES 20728, THE ROYAL TENENBAUMS 36231, THE SHRINK IS IN 37184, THE TRIUMPH OF LOVE 33449, THE WEDDING PLANNER 8644, TOM GREEN 11027, TOMCATS 35988, TORTILLA SOUP 19451, TWO CAN PLAY THAT GAME 21790, VERY ANNIE MARY 3137, VISITOR Q 35443, VIZONTELE 29077, WASABI 25414, WATERBOYS 27083, WET HOT AMERICAN SUMMER 37358, WHAT'S THE WORST THAT COULD HAPPEN? 23844, WHO IS CLETIS TOUT? 4063, ZOOLANDER src, edge_attr, dst 13747, has_genre, 30463 13747, release_year, 13408 5478, has_genre, 30463 5478, release_year, 13408 8200, has_genre, 30463 8200, release_year, 13408 32427, has_genre, 30463 32427, release_year, 13408 17687, has_genre, 30463 17687, release_year, 13408 34899, has_genre, 30463 34899, has_tags, 30463 34899, release_year, 13408 12224, has_genre, 30463 12224, has_tags, 30463 12224, release_year, 13408 5593, has_genre, 30463 5593, release_year, 13408 23952, has_genre, 30463 23952, release_year, 13408 13418, has_genre, 30463 13418, release_year, 13408 9654, has_genre, 30463 9654, has_tags, 30463 9654, release_year, 13408 35213, has_genre, 30463 35213, release_year, 13408 18692, has_genre, 30463 18692, starred_actors, 8644 23128, has_genre, 30463 23128, has_tags, 30463 23128, release_year, 13408 19026, has_genre, 30463 19026, release_year, 13408 17892, has_genre, 30463 17892, release_year, 13408 2605, has_genre, 30463 2605, release_year, 13408 18980, has_genre, 30463 18980, release_year, 13408 1915, has_genre, 30463 1915, has_tags, 30463 1915, release_year, 13408 12217, has_genre, 30463 12217, release_year, 13408 7023, has_genre, 30463 7023, release_year, 13408 19756, has_genre, 30463 19756, release_year, 13408 8704, has_genre, 30463 8704, release_year, 13408 28808, has_genre, 30463 28808, release_year, 13408 23470, has_genre, 30463 23470, has_tags, 30463 23470, release_year, 13408 6915, has_genre, 30463 6915, release_year, 13408 21322, directed_by, 8644 21322, has_genre, 30463 21322, has_tags, 8644 21322, release_year, 13408 21322, starred_actors, 8644 21322, written_by, 8644 30712, directed_by, 30422 30712, has_genre, 30463 5287, has_genre, 30463 5287, has_tags, 4358 23511, has_genre, 30463 23511, release_year, 13408 37949, has_genre, 30463 37949, has_tags, 30463 37949, release_year, 13408 12664, has_genre, 30463 12664, release_year, 13408 18445, has_genre, 30463 18445, release_year, 13408 10113, has_genre, 30463 10113, release_year, 13408 8648, has_genre, 30463 8648, release_year, 13408 21060, has_genre, 30463 21060, release_year, 13408 37229, has_genre, 30463 37229, release_year, 13408 11344, has_genre, 30463 11344, release_year, 13408 1292, has_genre, 30463 1292, release_year, 13408 38901, has_genre, 30463 38901, release_year, 13408 10703, has_genre, 30463 10703, release_year, 13408 35625, has_genre, 30463 35625, release_year, 13408 16371, has_genre, 30463 16371, has_tags, 30463 16371, has_tags, 4358 23526, has_genre, 30463 23526, release_year, 13408 263, has_genre, 30463 263, has_tags, 30463 263, release_year, 13408 32383, has_genre, 30463 32383, release_year, 13408 12610, has_genre, 30463 12610, release_year, 13408 10109, has_genre, 30463 10109, release_year, 13408 30384, has_genre, 30463 30384, release_year, 13408 16839, has_genre, 30463 16839, release_year, 13408 7699, has_genre, 30463 7699, release_year, 13408 20428, has_genre, 30463 20428, release_year, 13408 17559, has_genre, 30463 17559, has_tags, 30463 17559, release_year, 13408 29734, has_genre, 30463 29734, release_year, 13408 26731, has_genre, 30463 26731, release_year, 13408 28660, has_genre, 30463 28660, release_year, 13408 6068, has_genre, 30463 6068, release_year, 13408 33714, has_genre, 30463 33714, release_year, 13408 33853, has_genre, 30463 33853, release_year, 13408 20003, has_genre, 30463 20003, has_tags, 30463 20003, release_year, 13408 24616, has_genre, 30463 24616, release_year, 13408 26151, has_genre, 30463 26151, release_year, 13408 5731, has_genre, 30463 5731, release_year, 13408 29029, has_genre, 30463 29029, release_year, 13408 21875, has_tags, 30463 21875, release_year, 13408 6959, has_genre, 30463 6959, release_year, 13408 32186, has_genre, 30463 32186, release_year, 13408 8935, has_genre, 30463 8935, release_year, 13408 28044, has_genre, 30463 28044, release_year, 13408 31445, has_genre, 30463 31445, has_tags, 30463 31445, release_year, 13408 13381, has_genre, 30463 13381, release_year, 13408 28182, has_genre, 30463 28182, release_year, 13408 32180, has_genre, 30463 32180, has_tags, 30463 32180, release_year, 13408 38381, has_genre, 30463 38381, release_year, 13408 9530, has_genre, 30463 9530, has_tags, 30463 9530, release_year, 13408 1789, has_genre, 30463 1789, has_tags, 30463 1789, release_year, 13408 37244, has_genre, 30463 37244, release_year, 13408 5880, has_genre, 30463 5880, release_year, 13408 35100, has_genre, 30463 35100, release_year, 13408 7519, has_genre, 30463 7519, release_year, 13408 36159, has_genre, 30463 36159, has_tags, 30463 36159, release_year, 13408 30089, has_genre, 30463 30089, release_year, 13408 2407, has_genre, 30463 2407, release_year, 13408 24221, has_genre, 30463 24221, release_year, 13408 5170, has_genre, 30463 5170, starred_actors, 8644 7949, has_genre, 30463 7949, release_year, 13408 2235, has_genre, 30463 2235, release_year, 13408 4783, has_genre, 30463 4783, has_tags, 30463 4783, release_year, 13408 27762, has_genre, 30463 27762, release_year, 13408 345, has_genre, 30463 345, release_year, 13408 23280, has_genre, 30463 23280, release_year, 13408 15795, has_genre, 30463 15795, release_year, 13408 25674, has_genre, 30463 25674, release_year, 13408 30164, has_genre, 30463 30164, has_tags, 30463 30164, release_year, 13408 4927, has_genre, 30463 4927, release_year, 13408 17778, has_genre, 30463 17778, release_year, 13408 28107, has_genre, 30463 28107, release_year, 13408 10353, has_genre, 30463 10353, release_year, 13408 27713, has_genre, 30463 27713, has_tags, 30463 27713, release_year, 13408 23086, has_genre, 30463 23086, has_tags, 30463 23086, release_year, 13408 20728, has_genre, 30463 20728, has_tags, 30463 20728, release_year, 13408 36231, has_genre, 30463 36231, release_year, 13408 37184, has_genre, 30463 37184, release_year, 13408 33449, has_genre, 30463 33449, release_year, 13408 11027, has_genre, 30463 11027, release_year, 13408 35988, has_genre, 30463 35988, release_year, 13408 19451, has_genre, 30463 19451, release_year, 13408 21790, has_genre, 30463 21790, release_year, 13408 3137, has_genre, 30463 3137, release_year, 13408 35443, has_genre, 30463 35443, has_tags, 30463 35443, release_year, 13408 29077, has_genre, 30463 29077, has_tags, 30463 29077, release_year, 13408 25414, has_genre, 30463 25414, release_year, 13408 27083, has_genre, 30463 27083, release_year, 13408 37358, has_genre, 30463 37358, release_year, 13408 23844, has_genre, 30463 23844, release_year, 13408 4063, has_genre, 30463 4063, has_tags, 30463 4063, release_year, 13408 Question: How are FREDDY GOT FINGERED, ICE, and RICHARD RUSH related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "FREDDY GOT FINGERED", "ICE", "RICHARD RUSH" ], "valid_edges": [ [ "25 WATTS", "has_genre", "COMEDY" ], [ "25 WATTS", "release_year", "2001" ], [ "30 YEARS TO LIFE", "has_genre", "COMEDY" ], [ "30 YEARS TO LIFE", "release_year", "2001" ], [ "ALL OVER THE GUY", "has_genre", "COMEDY" ], [ "ALL OVER THE GUY", "release_year", "2001" ], [ "ALL THE QUEEN'S MEN", "has_genre", "COMEDY" ], [ "ALL THE QUEEN'S MEN", "release_year", "2001" ], [ "AMERICA'S SWEETHEARTS", "has_genre", "COMEDY" ], [ "AMERICA'S SWEETHEARTS", "release_year", "2001" ], [ "AMERICAN PIE 2", "has_genre", "COMEDY" ], [ "AMERICAN PIE 2", "has_tags", "COMEDY" ], [ "AMERICAN PIE 2", "release_year", "2001" ], [ "AMÉLIE", "has_genre", "COMEDY" ], [ "AMÉLIE", "has_tags", "COMEDY" ], [ "AMÉLIE", "release_year", "2001" ], [ "BABY BOY", "has_genre", "COMEDY" ], [ "BABY BOY", "release_year", "2001" ], [ "BANDITS", "has_genre", "COMEDY" ], [ "BANDITS", "release_year", "2001" ], [ "BARTLEBY", "has_genre", "COMEDY" ], [ "BARTLEBY", "release_year", "2001" ], [ "BLACK KNIGHT", "has_genre", "COMEDY" ], [ "BLACK KNIGHT", "has_tags", "COMEDY" ], [ "BLACK KNIGHT", "release_year", "2001" ], [ "BLOW DRY", "has_genre", "COMEDY" ], [ "BLOW DRY", "release_year", "2001" ], [ "BOB THE BUTLER", "has_genre", "COMEDY" ], [ "BOB THE BUTLER", "starred_actors", "TOM GREEN" ], [ "BRIDGET JONES'S DIARY", "has_genre", "COMEDY" ], [ "BRIDGET JONES'S DIARY", "has_tags", "COMEDY" ], [ "BRIDGET JONES'S DIARY", "release_year", "2001" ], [ "BUBBLE BOY", "has_genre", "COMEDY" ], [ "BUBBLE BOY", "release_year", "2001" ], [ "CAMOUFLAGE", "has_genre", "COMEDY" ], [ "CAMOUFLAGE", "release_year", "2001" ], [ "CORKY ROMANO", "has_genre", "COMEDY" ], [ "CORKY ROMANO", "release_year", "2001" ], [ "CROCODILE DUNDEE IN LOS ANGELES", "has_genre", "COMEDY" ], [ "CROCODILE DUNDEE IN LOS ANGELES", "release_year", "2001" ], [ "DIL CHAHTA HAI", "has_genre", "COMEDY" ], [ "DIL CHAHTA HAI", "has_tags", "COMEDY" ], [ "DIL CHAHTA HAI", "release_year", "2001" ], [ "DON'T TEMPT ME", "has_genre", "COMEDY" ], [ "DON'T TEMPT ME", "release_year", "2001" ], [ "DOUBLE TAKE", "has_genre", "COMEDY" ], [ "DOUBLE TAKE", "release_year", "2001" ], [ "DOWN TO EARTH", "has_genre", "COMEDY" ], [ "DOWN TO EARTH", "release_year", "2001" ], [ "DR. DOLITTLE 2", "has_genre", "COMEDY" ], [ "DR. DOLITTLE 2", "release_year", "2001" ], [ "ESCANABA IN DA MOONLIGHT", "has_genre", "COMEDY" ], [ "ESCANABA IN DA MOONLIGHT", "release_year", "2001" ], [ "EVOLUTION", "has_genre", "COMEDY" ], [ "EVOLUTION", "has_tags", "COMEDY" ], [ "EVOLUTION", "release_year", "2001" ], [ "FOCUS", "has_genre", "COMEDY" ], [ "FOCUS", "release_year", "2001" ], [ "FREDDY GOT FINGERED", "directed_by", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "has_genre", "COMEDY" ], [ "FREDDY GOT FINGERED", "has_tags", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "release_year", "2001" ], [ "FREDDY GOT FINGERED", "starred_actors", "TOM GREEN" ], [ "FREDDY GOT FINGERED", "written_by", "TOM GREEN" ], [ "FREEBIE AND THE BEAN", "directed_by", "RICHARD RUSH" ], [ "FREEBIE AND THE BEAN", "has_genre", "COMEDY" ], [ "FROZEN", "has_genre", "COMEDY" ], [ "FROZEN", "has_tags", "ICE" ], [ "GAUDI AFTERNOON", "has_genre", "COMEDY" ], [ "GAUDI AFTERNOON", "release_year", "2001" ], [ "GET OVER IT", "has_genre", "COMEDY" ], [ "GET OVER IT", "has_tags", "COMEDY" ], [ "GET OVER IT", "release_year", "2001" ], [ "GHOST WORLD", "has_genre", "COMEDY" ], [ "GHOST WORLD", "release_year", "2001" ], [ "GOD IS GREAT AND I'M NOT", "has_genre", "COMEDY" ], [ "GOD IS GREAT AND I'M NOT", "release_year", "2001" ], [ "GOOD ADVICE", "has_genre", "COMEDY" ], [ "GOOD ADVICE", "release_year", "2001" ], [ "HAPPY CAMPERS", "has_genre", "COMEDY" ], [ "HAPPY CAMPERS", "release_year", "2001" ], [ "HARVARD MAN", "has_genre", "COMEDY" ], [ "HARVARD MAN", "release_year", "2001" ], [ "HE DIED WITH A FELAFEL IN HIS HAND", "has_genre", "COMEDY" ], [ "HE DIED WITH A FELAFEL IN HIS HAND", "release_year", "2001" ], [ "HEARTBREAKERS", "has_genre", "COMEDY" ], [ "HEARTBREAKERS", "release_year", "2001" ], [ "HEDWIG AND THE ANGRY INCH", "has_genre", "COMEDY" ], [ "HEDWIG AND THE ANGRY INCH", "release_year", "2001" ], [ "HIGH HEELS AND LOW LIFES", "has_genre", "COMEDY" ], [ "HIGH HEELS AND LOW LIFES", "release_year", "2001" ], [ "HOW HIGH", "has_genre", "COMEDY" ], [ "HOW HIGH", "release_year", "2001" ], [ "HUMAN NATURE", "has_genre", "COMEDY" ], [ "HUMAN NATURE", "release_year", "2001" ], [ "ICE AGE", "has_genre", "COMEDY" ], [ "ICE AGE", "has_tags", "COMEDY" ], [ "ICE AGE", "has_tags", "ICE" ], [ "JACKPOT", "has_genre", "COMEDY" ], [ "JACKPOT", "release_year", "2001" ], [ "JAY AND SILENT BOB STRIKE BACK", "has_genre", "COMEDY" ], [ "JAY AND SILENT BOB STRIKE BACK", "has_tags", "COMEDY" ], [ "JAY AND SILENT BOB STRIKE BACK", "release_year", "2001" ], [ "JOE DIRT", "has_genre", "COMEDY" ], [ "JOE DIRT", "release_year", "2001" ], [ "JOE SOMEBODY", "has_genre", "COMEDY" ], [ "JOE SOMEBODY", "release_year", "2001" ], [ "JOSIE AND THE PUSSYCATS", "has_genre", "COMEDY" ], [ "JOSIE AND THE PUSSYCATS", "release_year", "2001" ], [ "JUMP TOMORROW", "has_genre", "COMEDY" ], [ "JUMP TOMORROW", "release_year", "2001" ], [ "JUST VISITING", "has_genre", "COMEDY" ], [ "JUST VISITING", "release_year", "2001" ], [ "KINGDOM COME", "has_genre", "COMEDY" ], [ "KINGDOM COME", "release_year", "2001" ], [ "KISSING JESSICA STEIN", "has_genre", "COMEDY" ], [ "KISSING JESSICA STEIN", "release_year", "2001" ], [ "LEGALLY BLONDE", "has_genre", "COMEDY" ], [ "LEGALLY BLONDE", "has_tags", "COMEDY" ], [ "LEGALLY BLONDE", "release_year", "2001" ], [ "LITTLE SECRETS", "has_genre", "COMEDY" ], [ "LITTLE SECRETS", "release_year", "2001" ], [ "LUCKY BREAK", "has_genre", "COMEDY" ], [ "LUCKY BREAK", "release_year", "2001" ], [ "MADE", "has_genre", "COMEDY" ], [ "MADE", "release_year", "2001" ], [ "MAX KEEBLE'S BIG MOVE", "has_genre", "COMEDY" ], [ "MAX KEEBLE'S BIG MOVE", "release_year", "2001" ], [ "MEAN MACHINE", "has_genre", "COMEDY" ], [ "MEAN MACHINE", "release_year", "2001" ], [ "MONKEYBONE", "has_genre", "COMEDY" ], [ "MONKEYBONE", "release_year", "2001" ], [ "MONSTERS, INC.", "has_genre", "COMEDY" ], [ "MONSTERS, INC.", "has_tags", "COMEDY" ], [ "MONSTERS, INC.", "release_year", "2001" ], [ "MOSTLY MARTHA", "has_genre", "COMEDY" ], [ "MOSTLY MARTHA", "release_year", "2001" ], [ "NOBODY'S BABY", "has_genre", "COMEDY" ], [ "NOBODY'S BABY", "release_year", "2001" ], [ "NOT ANOTHER TEEN MOVIE", "has_genre", "COMEDY" ], [ "NOT ANOTHER TEEN MOVIE", "release_year", "2001" ], [ "NOVOCAINE", "has_genre", "COMEDY" ], [ "NOVOCAINE", "release_year", "2001" ], [ "OCEAN'S ELEVEN", "has_tags", "COMEDY" ], [ "OCEAN'S ELEVEN", "release_year", "2001" ], [ "ON THE LINE", "has_genre", "COMEDY" ], [ "ON THE LINE", "release_year", "2001" ], [ "ONE MAN UP", "has_genre", "COMEDY" ], [ "ONE MAN UP", "release_year", "2001" ], [ "ONE NIGHT AT MCCOOL'S", "has_genre", "COMEDY" ], [ "ONE NIGHT AT MCCOOL'S", "release_year", "2001" ], [ "PAULINE AND PAULETTE", "has_genre", "COMEDY" ], [ "PAULINE AND PAULETTE", "release_year", "2001" ], [ "PONTEROSA", "has_genre", "COMEDY" ], [ "PONTEROSA", "has_tags", "COMEDY" ], [ "PONTEROSA", "release_year", "2001" ], [ "POOTIE TANG", "has_genre", "COMEDY" ], [ "POOTIE TANG", "release_year", "2001" ], [ "RARE BIRDS", "has_genre", "COMEDY" ], [ "RARE BIRDS", "release_year", "2001" ], [ "RAT RACE", "has_genre", "COMEDY" ], [ "RAT RACE", "has_tags", "COMEDY" ], [ "RAT RACE", "release_year", "2001" ], [ "ROCK STAR", "has_genre", "COMEDY" ], [ "ROCK STAR", "release_year", "2001" ], [ "RUSH HOUR 2", "has_genre", "COMEDY" ], [ "RUSH HOUR 2", "has_tags", "COMEDY" ], [ "RUSH HOUR 2", "release_year", "2001" ], [ "SAVING SILVERMAN", "has_genre", "COMEDY" ], [ "SAVING SILVERMAN", "has_tags", "COMEDY" ], [ "SAVING SILVERMAN", "release_year", "2001" ], [ "SAY IT ISN'T SO", "has_genre", "COMEDY" ], [ "SAY IT ISN'T SO", "release_year", "2001" ], [ "SERENDIPITY", "has_genre", "COMEDY" ], [ "SERENDIPITY", "release_year", "2001" ], [ "SHALLOW HAL", "has_genre", "COMEDY" ], [ "SHALLOW HAL", "release_year", "2001" ], [ "SHAOLIN SOCCER", "has_genre", "COMEDY" ], [ "SHAOLIN SOCCER", "release_year", "2001" ], [ "SHREK", "has_genre", "COMEDY" ], [ "SHREK", "has_tags", "COMEDY" ], [ "SHREK", "release_year", "2001" ], [ "SIDEWALKS OF NEW YORK", "has_genre", "COMEDY" ], [ "SIDEWALKS OF NEW YORK", "release_year", "2001" ], [ "SON OF THE BRIDE", "has_genre", "COMEDY" ], [ "SON OF THE BRIDE", "release_year", "2001" ], [ "SPEAKING OF SEX", "has_genre", "COMEDY" ], [ "SPEAKING OF SEX", "release_year", "2001" ], [ "STEALING HARVARD", "has_genre", "COMEDY" ], [ "STEALING HARVARD", "starred_actors", "TOM GREEN" ], [ "STORYTELLING", "has_genre", "COMEDY" ], [ "STORYTELLING", "release_year", "2001" ], [ "SUMMER CATCH", "has_genre", "COMEDY" ], [ "SUMMER CATCH", "release_year", "2001" ], [ "SUPER TROOPERS", "has_genre", "COMEDY" ], [ "SUPER TROOPERS", "has_tags", "COMEDY" ], [ "SUPER TROOPERS", "release_year", "2001" ], [ "SWEET NOVEMBER", "has_genre", "COMEDY" ], [ "SWEET NOVEMBER", "release_year", "2001" ], [ "TANGUY", "has_genre", "COMEDY" ], [ "TANGUY", "release_year", "2001" ], [ "THE ANIMAL", "has_genre", "COMEDY" ], [ "THE ANIMAL", "release_year", "2001" ], [ "THE ANNIVERSARY PARTY", "has_genre", "COMEDY" ], [ "THE ANNIVERSARY PARTY", "release_year", "2001" ], [ "THE BROTHERS", "has_genre", "COMEDY" ], [ "THE BROTHERS", "release_year", "2001" ], [ "THE CLOSET", "has_genre", "COMEDY" ], [ "THE CLOSET", "has_tags", "COMEDY" ], [ "THE CLOSET", "release_year", "2001" ], [ "THE CURSE OF THE JADE SCORPION", "has_genre", "COMEDY" ], [ "THE CURSE OF THE JADE SCORPION", "release_year", "2001" ], [ "THE HAPPINESS OF THE KATAKURIS", "has_genre", "COMEDY" ], [ "THE HAPPINESS OF THE KATAKURIS", "release_year", "2001" ], [ "THE LAST KISS", "has_genre", "COMEDY" ], [ "THE LAST KISS", "release_year", "2001" ], [ "THE MAN WHO SUED GOD", "has_genre", "COMEDY" ], [ "THE MAN WHO SUED GOD", "release_year", "2001" ], [ "THE MEXICAN", "has_genre", "COMEDY" ], [ "THE MEXICAN", "has_tags", "COMEDY" ], [ "THE MEXICAN", "release_year", "2001" ], [ "THE PRINCESS DIARIES", "has_genre", "COMEDY" ], [ "THE PRINCESS DIARIES", "has_tags", "COMEDY" ], [ "THE PRINCESS DIARIES", "release_year", "2001" ], [ "THE ROYAL TENENBAUMS", "has_genre", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "has_tags", "COMEDY" ], [ "THE ROYAL TENENBAUMS", "release_year", "2001" ], [ "THE SHRINK IS IN", "has_genre", "COMEDY" ], [ "THE SHRINK IS IN", "release_year", "2001" ], [ "THE TRIUMPH OF LOVE", "has_genre", "COMEDY" ], [ "THE TRIUMPH OF LOVE", "release_year", "2001" ], [ "THE WEDDING PLANNER", "has_genre", "COMEDY" ], [ "THE WEDDING PLANNER", "release_year", "2001" ], [ "TOMCATS", "has_genre", "COMEDY" ], [ "TOMCATS", "release_year", "2001" ], [ "TORTILLA SOUP", "has_genre", "COMEDY" ], [ "TORTILLA SOUP", "release_year", "2001" ], [ "TWO CAN PLAY THAT GAME", "has_genre", "COMEDY" ], [ "TWO CAN PLAY THAT GAME", "release_year", "2001" ], [ "VERY ANNIE MARY", "has_genre", "COMEDY" ], [ "VERY ANNIE MARY", "release_year", "2001" ], [ "VISITOR Q", "has_genre", "COMEDY" ], [ "VISITOR Q", "release_year", "2001" ], [ "VIZONTELE", "has_genre", "COMEDY" ], [ "VIZONTELE", "has_tags", "COMEDY" ], [ "VIZONTELE", "release_year", "2001" ], [ "WASABI", "has_genre", "COMEDY" ], [ "WASABI", "has_tags", "COMEDY" ], [ "WASABI", "release_year", "2001" ], [ "WATERBOYS", "has_genre", "COMEDY" ], [ "WATERBOYS", "release_year", "2001" ], [ "WET HOT AMERICAN SUMMER", "has_genre", "COMEDY" ], [ "WET HOT AMERICAN SUMMER", "release_year", "2001" ], [ "WHAT'S THE WORST THAT COULD HAPPEN?", "has_genre", "COMEDY" ], [ "WHAT'S THE WORST THAT COULD HAPPEN?", "release_year", "2001" ], [ "WHO IS CLETIS TOUT?", "has_genre", "COMEDY" ], [ "WHO IS CLETIS TOUT?", "release_year", "2001" ], [ "ZOOLANDER", "has_genre", "COMEDY" ], [ "ZOOLANDER", "has_tags", "COMEDY" ], [ "ZOOLANDER", "release_year", "2001" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 9377, 2014 8165, BAD 10987, HALEY JOEL OSMENT 1919, ROLLING THUNDER 1725, THE BEAST OF YUCCA FLATS 7013, THE COUNTRY BEARS 14626, THE HOMESMAN 38537, TOMMY LEE JONES 17726, TUSK src, edge_attr, dst 1919, starred_actors, 38537 1725, has_imdb_rating, 8165 7013, has_imdb_rating, 8165 7013, starred_actors, 10987 14626, directed_by, 38537 14626, has_tags, 38537 14626, release_year, 9377 14626, starred_actors, 38537 14626, written_by, 38537 17726, release_year, 9377 17726, starred_actors, 10987 Question: How are ROLLING THUNDER, THE BEAST OF YUCCA FLATS, and TUSK related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "ROLLING THUNDER", "THE BEAST OF YUCCA FLATS", "TUSK" ], "valid_edges": [ [ "ROLLING THUNDER", "starred_actors", "TOMMY LEE JONES" ], [ "THE BEAST OF YUCCA FLATS", "has_imdb_rating", "BAD" ], [ "THE COUNTRY BEARS", "has_imdb_rating", "BAD" ], [ "THE COUNTRY BEARS", "starred_actors", "HALEY JOEL OSMENT" ], [ "THE HOMESMAN", "directed_by", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "has_tags", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "release_year", "2014" ], [ "THE HOMESMAN", "starred_actors", "TOMMY LEE JONES" ], [ "THE HOMESMAN", "written_by", "TOMMY LEE JONES" ], [ "TUSK", "release_year", "2014" ], [ "TUSK", "starred_actors", "HALEY JOEL OSMENT" ] ] }

metaqa

You are given a directed graph as two CSV-like sections in this order: 1) Node table (header included): node_id, node_attr 2) Edge table (header included): src, edge_attr, dst Task - Use ONLY edges from the Edge table to answer the question by outputting a path. - When printing each edge, replace IDs with the exact node_attr from the Node table. - Output MUST be text triples, not numeric IDs. Output format (STRICT — no extra text): PATH: ("subject"|predicate|"object") ... END Rules - Use only listed edges; do NOT invent edges. - Map IDs → node_attr; preserve node_attr exactly. - Output NOTHING outside the PATH block. - If no path exists, output exactly: PATH: END Graph: node_id, node_attr 18366, 1960 10825, 1973 22798, A RAGE IN HARLEM 25522, A WARM DECEMBER 34348, ALL THE YOUNG MEN 16346, DRACULA A.D. 1972 34032, HARLEM 5810, HELL UP IN HARLEM 26647, NOTHING BUT THE NIGHT 23249, PETER CUSHING 1777, SIDNEY POITIER 2709, THE BRIDES OF DRACULA 38676, THE CREEPING FLESH 14162, THE SATANIC RITES OF DRACULA 19088, VAN HELSING src, edge_attr, dst 22798, has_tags, 34032 25522, directed_by, 1777 25522, release_year, 10825 25522, starred_actors, 1777 34348, release_year, 18366 34348, starred_actors, 1777 16346, has_tags, 23249 16346, has_tags, 19088 16346, starred_actors, 23249 5810, has_tags, 34032 5810, release_year, 10825 26647, release_year, 10825 26647, starred_actors, 23249 2709, has_tags, 23249 2709, has_tags, 19088 2709, release_year, 18366 2709, starred_actors, 23249 38676, release_year, 10825 38676, starred_actors, 23249 14162, has_tags, 23249 14162, has_tags, 19088 14162, release_year, 10825 14162, starred_actors, 23249 19088, has_tags, 19088 Question: How are A RAGE IN HARLEM, A WARM DECEMBER, and THE BRIDES OF DRACULA related? Your output must be ONLY the PATH block.

graph_path

{ "style": "rule" }

{ "entities": [ "A RAGE IN HARLEM", "A WARM DECEMBER", "THE BRIDES OF DRACULA" ], "valid_edges": [ [ "A RAGE IN HARLEM", "has_tags", "HARLEM" ], [ "A WARM DECEMBER", "directed_by", "SIDNEY POITIER" ], [ "A WARM DECEMBER", "release_year", "1973" ], [ "A WARM DECEMBER", "starred_actors", "SIDNEY POITIER" ], [ "ALL THE YOUNG MEN", "release_year", "1960" ], [ "ALL THE YOUNG MEN", "starred_actors", "SIDNEY POITIER" ], [ "DRACULA A.D. 1972", "has_tags", "PETER CUSHING" ], [ "DRACULA A.D. 1972", "has_tags", "VAN HELSING" ], [ "DRACULA A.D. 1972", "starred_actors", "PETER CUSHING" ], [ "HELL UP IN HARLEM", "has_tags", "HARLEM" ], [ "HELL UP IN HARLEM", "release_year", "1973" ], [ "NOTHING BUT THE NIGHT", "release_year", "1973" ], [ "NOTHING BUT THE NIGHT", "starred_actors", "PETER CUSHING" ], [ "THE BRIDES OF DRACULA", "has_tags", "PETER CUSHING" ], [ "THE BRIDES OF DRACULA", "has_tags", "VAN HELSING" ], [ "THE BRIDES OF DRACULA", "release_year", "1960" ], [ "THE BRIDES OF DRACULA", "starred_actors", "PETER CUSHING" ], [ "THE CREEPING FLESH", "release_year", "1973" ], [ "THE CREEPING FLESH", "starred_actors", "PETER CUSHING" ], [ "THE SATANIC RITES OF DRACULA", "has_tags", "PETER CUSHING" ], [ "THE SATANIC RITES OF DRACULA", "has_tags", "VAN HELSING" ], [ "THE SATANIC RITES OF DRACULA", "release_year", "1973" ], [ "THE SATANIC RITES OF DRACULA", "starred_actors", "PETER CUSHING" ], [ "VAN HELSING", "has_tags", "VAN HELSING" ] ] }