data_source
stringclasses 1
value | prompt
stringlengths 987
17k
| ability
stringclasses 1
value | reward_model
dict | extra_info
dict |
|---|---|---|---|---|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1810, 59th_Golden_Globe_Awards
3884, 74th_Academy_Awards
8215, 7th_Critics'_Choice_Awards
8732, AACTA_Award_for_Best_Lead_Actress
4704, Akiva_Goldsman
12158, Alan_Ball
3161, Attention_deficit_hyperactivity_disorder
3032, Baz_Luhrmann
1168, Brittany_Snow
2784, Craig_Armstrong
3006, Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media
13969, In_the_Bedroom
2557, Jennifer_Connelly
14022, Judy_Davis
6216, London_Film_Critics_Circle_Award_for_Actress_of_the_Year
3632, Moulin_Rouge!
998, Taylor_Hackford
src, edge_attr, dst
1810, award_winner, 4704
1810, award_winner, 12158
1810, award_winner, 3032
1810, award_winner, 2784
1810, award_winner, 2557
1810, award_winner, 14022
1810, honored_for, 13969
1810, honored_for, 3632
3884, award_winner, 4704
3884, award_winner, 2557
3884, honored_for, 3632
8215, award_winner, 3032
8215, award_winner, 2557
8215, award_winner, 14022
8215, honored_for, 13969
8215, honored_for, 3632
8732, nominated_for, 3632
12158, award, 3006
3161, notable_people_with_this_condition, 1168
3161, notable_people_with_this_condition, 2557
3032, film, 3632
3032, nominated_for, 3632
2784, award_nominee, 998
2784, award_winner, 998
2784, nominated_for, 3632
3006, award_winner, 998
14022, award, 8732
6216, award_winner, 14022
3632, award_honor_award, 6216
3632, award_winner, 3032
3632, award_winner, 2784
3632, film_music, 2784
3632, produced_by, 3032
3632, written_by, 3032
998, award, 3006
998, award_nominee, 2784
998, award_winner, 2784
Question: How are Brittany_Snow, Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media, and Moulin_Rouge! related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Brittany_Snow",
"Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media",
"Moulin_Rouge!"
],
"valid_edges": [
[
"59th_Golden_Globe_Awards",
"award_winner",
"Akiva_Goldsman"
],
[
"59th_Golden_Globe_Awards",
"award_winner",
"Alan_Ball"
],
[
"59th_Golden_Globe_Awards",
"award_winner",
"Baz_Luhrmann"
],
[
"59th_Golden_Globe_Awards",
"award_winner",
"Craig_Armstrong"
],
[
"59th_Golden_Globe_Awards",
"award_winner",
"Jennifer_Connelly"
],
[
"59th_Golden_Globe_Awards",
"award_winner",
"Judy_Davis"
],
[
"59th_Golden_Globe_Awards",
"honored_for",
"In_the_Bedroom"
],
[
"59th_Golden_Globe_Awards",
"honored_for",
"Moulin_Rouge!"
],
[
"74th_Academy_Awards",
"award_winner",
"Akiva_Goldsman"
],
[
"74th_Academy_Awards",
"award_winner",
"Jennifer_Connelly"
],
[
"74th_Academy_Awards",
"honored_for",
"Moulin_Rouge!"
],
[
"7th_Critics'_Choice_Awards",
"award_winner",
"Baz_Luhrmann"
],
[
"7th_Critics'_Choice_Awards",
"award_winner",
"Jennifer_Connelly"
],
[
"7th_Critics'_Choice_Awards",
"award_winner",
"Judy_Davis"
],
[
"7th_Critics'_Choice_Awards",
"honored_for",
"In_the_Bedroom"
],
[
"7th_Critics'_Choice_Awards",
"honored_for",
"Moulin_Rouge!"
],
[
"AACTA_Award_for_Best_Lead_Actress",
"nominated_for",
"Moulin_Rouge!"
],
[
"Alan_Ball",
"award",
"Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media"
],
[
"Attention_deficit_hyperactivity_disorder",
"notable_people_with_this_condition",
"Brittany_Snow"
],
[
"Attention_deficit_hyperactivity_disorder",
"notable_people_with_this_condition",
"Jennifer_Connelly"
],
[
"Baz_Luhrmann",
"film",
"Moulin_Rouge!"
],
[
"Baz_Luhrmann",
"nominated_for",
"Moulin_Rouge!"
],
[
"Craig_Armstrong",
"award_nominee",
"Taylor_Hackford"
],
[
"Craig_Armstrong",
"award_winner",
"Taylor_Hackford"
],
[
"Craig_Armstrong",
"nominated_for",
"Moulin_Rouge!"
],
[
"Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media",
"award_winner",
"Taylor_Hackford"
],
[
"Judy_Davis",
"award",
"AACTA_Award_for_Best_Lead_Actress"
],
[
"London_Film_Critics_Circle_Award_for_Actress_of_the_Year",
"award_winner",
"Judy_Davis"
],
[
"Moulin_Rouge!",
"award_honor_award",
"London_Film_Critics_Circle_Award_for_Actress_of_the_Year"
],
[
"Moulin_Rouge!",
"award_winner",
"Baz_Luhrmann"
],
[
"Moulin_Rouge!",
"award_winner",
"Craig_Armstrong"
],
[
"Moulin_Rouge!",
"film_music",
"Craig_Armstrong"
],
[
"Moulin_Rouge!",
"produced_by",
"Baz_Luhrmann"
],
[
"Moulin_Rouge!",
"written_by",
"Baz_Luhrmann"
],
[
"Taylor_Hackford",
"award",
"Grammy_Award_for_Best_Compilation_Soundtrack_for_Visual_Media"
],
[
"Taylor_Hackford",
"award_nominee",
"Craig_Armstrong"
],
[
"Taylor_Hackford",
"award_winner",
"Craig_Armstrong"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
670, 15th_Screen_Actors_Guild_Awards
2463, 30_Rock
4152, 60th_Primetime_Emmy_Awards
9983, 65th_Golden_Globe_Awards
13826, 66th_Golden_Globe_Awards
9261, A_Separation
3541, Cannes_Film_Festival
8756, Cosmopolis
2022, David_Miner
5005, Don_Scardino
10035, Focus_Features
2436, Golden_Globe_Award_for_Best_Foreign_Language_Film
5538, In_America
512, Independent_Spirit_Award_for_Best_Supporting_Male
9475, John_Adams
2451, Judah_Friedlander
4319, Laura_Linney
1602, Lorne_Michaels
4659, Luxembourg
1946, Mad_Men
11340, Marci_Klein
2855, Matthew_Weiner
3634, Maulik_Pancholy
6449, Milk
8835, On_the_Road
11369, Panama
5848, Paul_Giamatti
10441, Recount
11920, Republic_of_Macedonia
12620, Robert_Carlock
4025, Samantha_Morton
8706, Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Comedy_Series
14207, Serine
9211, Set_decorator-GB
7069, Steve_Buscemi
5441, The_Fifth_Element
898, Tina_Fey
2401, Tom_Wilkinson
src, edge_attr, dst
670, award_winner, 898
670, honored_for, 2463
670, honored_for, 6449
2463, actor, 2451
2463, actor, 3634
2463, actor, 898
2463, award_honor_award, 8706
2463, award_winner, 5005
2463, award_winner, 2451
2463, award_winner, 1602
2463, award_winner, 11340
2463, award_winner, 898
2463, program_creator, 898
4152, award_winner, 2022
4152, award_winner, 5005
4152, award_winner, 4319
4152, award_winner, 1602
4152, award_winner, 11340
4152, award_winner, 2855
4152, award_winner, 5848
4152, award_winner, 12620
4152, award_winner, 898
4152, award_winner, 2401
4152, honored_for, 2463
4152, honored_for, 9475
4152, honored_for, 1946
4152, honored_for, 10441
9983, award_winner, 898
9983, honored_for, 2463
13826, award_winner, 2022
13826, award_winner, 5005
13826, award_winner, 4319
13826, award_winner, 1602
13826, award_winner, 11340
13826, award_winner, 2855
13826, award_winner, 5848
13826, award_winner, 12620
13826, award_winner, 898
13826, award_winner, 2401
13826, honored_for, 2463
13826, honored_for, 9475
13826, honored_for, 1946
13826, honored_for, 10441
9261, film_release_region, 4659
9261, film_release_region, 11920
8756, film_regional_debut_venue, 3541
8756, film_release_region, 4659
2022, award_nominee, 5005
2022, award_nominee, 1602
2022, award_nominee, 11340
2022, award_nominee, 12620
2022, award_nominee, 898
2022, award_winner, 5005
2022, award_winner, 11340
2022, award_winner, 12620
2022, award_winner, 898
2022, program, 2463
5005, award_nominee, 1602
5005, award_nominee, 12620
5005, award_nominee, 898
5005, award_winner, 2022
5005, award_winner, 1602
5005, award_winner, 12620
5005, nominated_for, 2463
5005, program, 2463
10035, film, 6449
10035, film, 8835
10035, nominated_for, 6449
2436, ceremony, 13826
2436, nominated_for, 9261
5538, award_honor_award, 512
5538, film_crew_role, 9211
5538, film_release_region, 4659
5538, film_release_region, 11369
512, nominated_for, 5538
512, nominated_for, 6449
2451, award_nominee, 898
2451, nominated_for, 2463
1602, award_nominee, 2022
1602, award_nominee, 11340
1602, award_nominee, 898
1602, award_winner, 2022
1602, award_winner, 11340
1602, award_winner, 12620
1602, award_winner, 898
1602, nominated_for, 2463
1602, program, 2463
4659, capital, 4659
4659, contains, 4659
11340, award_nominee, 2022
11340, award_nominee, 5005
11340, award_nominee, 898
11340, award_winner, 5005
11340, award_winner, 1602
11340, award_winner, 12620
11340, award_winner, 898
11340, nominated_for, 2463
11340, program, 2463
3634, award_nominee, 898
3634, nominated_for, 2463
6449, award_honor_award, 512
6449, food_nutrient, 14207
6449, production_companies, 10035
8835, film_crew_role, 9211
8835, film_regional_debut_venue, 3541
8835, film_release_region, 4659
8835, film_release_region, 11920
5848, acted_in, 8756
12620, award_nominee, 2022
12620, award_nominee, 5005
12620, award_nominee, 1602
12620, award_nominee, 11340
12620, award_nominee, 898
12620, award_winner, 2022
12620, award_winner, 5005
12620, award_winner, 1602
12620, award_winner, 11340
12620, award_winner, 898
12620, program, 2463
12620, tv_program, 2463
4025, acted_in, 8756
4025, acted_in, 5538
4025, nominated_for, 5538
8706, award_winner, 898
8706, nominated_for, 2463
7069, acted_in, 8835
7069, nominated_for, 2463
5441, film_release_region, 4659
5441, film_release_region, 11369
898, award_nominee, 2022
898, award_nominee, 1602
898, award_nominee, 11340
898, award_nominee, 12620
898, award_winner, 2022
898, award_winner, 5005
898, award_winner, 2451
898, award_winner, 1602
898, award_winner, 11340
898, award_winner, 3634
898, award_winner, 12620
898, nominated_for, 2463
Question: For what reason are David_Miner, Luxembourg, and Serine associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"David_Miner",
"Luxembourg",
"Serine"
],
"valid_edges": [
[
"15th_Screen_Actors_Guild_Awards",
"award_winner",
"Tina_Fey"
],
[
"15th_Screen_Actors_Guild_Awards",
"honored_for",
"30_Rock"
],
[
"15th_Screen_Actors_Guild_Awards",
"honored_for",
"Milk"
],
[
"30_Rock",
"actor",
"Judah_Friedlander"
],
[
"30_Rock",
"actor",
"Maulik_Pancholy"
],
[
"30_Rock",
"actor",
"Tina_Fey"
],
[
"30_Rock",
"award_honor_award",
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Comedy_Series"
],
[
"30_Rock",
"award_winner",
"Don_Scardino"
],
[
"30_Rock",
"award_winner",
"Judah_Friedlander"
],
[
"30_Rock",
"award_winner",
"Lorne_Michaels"
],
[
"30_Rock",
"award_winner",
"Marci_Klein"
],
[
"30_Rock",
"award_winner",
"Tina_Fey"
],
[
"30_Rock",
"program_creator",
"Tina_Fey"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"David_Miner"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Don_Scardino"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Laura_Linney"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Lorne_Michaels"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Marci_Klein"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Matthew_Weiner"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Paul_Giamatti"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Robert_Carlock"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Tina_Fey"
],
[
"60th_Primetime_Emmy_Awards",
"award_winner",
"Tom_Wilkinson"
],
[
"60th_Primetime_Emmy_Awards",
"honored_for",
"30_Rock"
],
[
"60th_Primetime_Emmy_Awards",
"honored_for",
"John_Adams"
],
[
"60th_Primetime_Emmy_Awards",
"honored_for",
"Mad_Men"
],
[
"60th_Primetime_Emmy_Awards",
"honored_for",
"Recount"
],
[
"65th_Golden_Globe_Awards",
"award_winner",
"Tina_Fey"
],
[
"65th_Golden_Globe_Awards",
"honored_for",
"30_Rock"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"David_Miner"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Don_Scardino"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Laura_Linney"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Lorne_Michaels"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Marci_Klein"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Matthew_Weiner"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Paul_Giamatti"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Robert_Carlock"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Tina_Fey"
],
[
"66th_Golden_Globe_Awards",
"award_winner",
"Tom_Wilkinson"
],
[
"66th_Golden_Globe_Awards",
"honored_for",
"30_Rock"
],
[
"66th_Golden_Globe_Awards",
"honored_for",
"John_Adams"
],
[
"66th_Golden_Globe_Awards",
"honored_for",
"Mad_Men"
],
[
"66th_Golden_Globe_Awards",
"honored_for",
"Recount"
],
[
"A_Separation",
"film_release_region",
"Luxembourg"
],
[
"A_Separation",
"film_release_region",
"Republic_of_Macedonia"
],
[
"Cosmopolis",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Cosmopolis",
"film_release_region",
"Luxembourg"
],
[
"David_Miner",
"award_nominee",
"Don_Scardino"
],
[
"David_Miner",
"award_nominee",
"Lorne_Michaels"
],
[
"David_Miner",
"award_nominee",
"Marci_Klein"
],
[
"David_Miner",
"award_nominee",
"Robert_Carlock"
],
[
"David_Miner",
"award_nominee",
"Tina_Fey"
],
[
"David_Miner",
"award_winner",
"Don_Scardino"
],
[
"David_Miner",
"award_winner",
"Marci_Klein"
],
[
"David_Miner",
"award_winner",
"Robert_Carlock"
],
[
"David_Miner",
"award_winner",
"Tina_Fey"
],
[
"David_Miner",
"program",
"30_Rock"
],
[
"Don_Scardino",
"award_nominee",
"Lorne_Michaels"
],
[
"Don_Scardino",
"award_nominee",
"Robert_Carlock"
],
[
"Don_Scardino",
"award_nominee",
"Tina_Fey"
],
[
"Don_Scardino",
"award_winner",
"David_Miner"
],
[
"Don_Scardino",
"award_winner",
"Lorne_Michaels"
],
[
"Don_Scardino",
"award_winner",
"Robert_Carlock"
],
[
"Don_Scardino",
"nominated_for",
"30_Rock"
],
[
"Don_Scardino",
"program",
"30_Rock"
],
[
"Focus_Features",
"film",
"Milk"
],
[
"Focus_Features",
"film",
"On_the_Road"
],
[
"Focus_Features",
"nominated_for",
"Milk"
],
[
"Golden_Globe_Award_for_Best_Foreign_Language_Film",
"ceremony",
"66th_Golden_Globe_Awards"
],
[
"Golden_Globe_Award_for_Best_Foreign_Language_Film",
"nominated_for",
"A_Separation"
],
[
"In_America",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Supporting_Male"
],
[
"In_America",
"film_crew_role",
"Set_decorator-GB"
],
[
"In_America",
"film_release_region",
"Luxembourg"
],
[
"In_America",
"film_release_region",
"Panama"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Male",
"nominated_for",
"In_America"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Male",
"nominated_for",
"Milk"
],
[
"Judah_Friedlander",
"award_nominee",
"Tina_Fey"
],
[
"Judah_Friedlander",
"nominated_for",
"30_Rock"
],
[
"Lorne_Michaels",
"award_nominee",
"David_Miner"
],
[
"Lorne_Michaels",
"award_nominee",
"Marci_Klein"
],
[
"Lorne_Michaels",
"award_nominee",
"Tina_Fey"
],
[
"Lorne_Michaels",
"award_winner",
"David_Miner"
],
[
"Lorne_Michaels",
"award_winner",
"Marci_Klein"
],
[
"Lorne_Michaels",
"award_winner",
"Robert_Carlock"
],
[
"Lorne_Michaels",
"award_winner",
"Tina_Fey"
],
[
"Lorne_Michaels",
"nominated_for",
"30_Rock"
],
[
"Lorne_Michaels",
"program",
"30_Rock"
],
[
"Luxembourg",
"capital",
"Luxembourg"
],
[
"Luxembourg",
"contains",
"Luxembourg"
],
[
"Marci_Klein",
"award_nominee",
"David_Miner"
],
[
"Marci_Klein",
"award_nominee",
"Don_Scardino"
],
[
"Marci_Klein",
"award_nominee",
"Tina_Fey"
],
[
"Marci_Klein",
"award_winner",
"Don_Scardino"
],
[
"Marci_Klein",
"award_winner",
"Lorne_Michaels"
],
[
"Marci_Klein",
"award_winner",
"Robert_Carlock"
],
[
"Marci_Klein",
"award_winner",
"Tina_Fey"
],
[
"Marci_Klein",
"nominated_for",
"30_Rock"
],
[
"Marci_Klein",
"program",
"30_Rock"
],
[
"Maulik_Pancholy",
"award_nominee",
"Tina_Fey"
],
[
"Maulik_Pancholy",
"nominated_for",
"30_Rock"
],
[
"Milk",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Supporting_Male"
],
[
"Milk",
"food_nutrient",
"Serine"
],
[
"Milk",
"production_companies",
"Focus_Features"
],
[
"On_the_Road",
"film_crew_role",
"Set_decorator-GB"
],
[
"On_the_Road",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"On_the_Road",
"film_release_region",
"Luxembourg"
],
[
"On_the_Road",
"film_release_region",
"Republic_of_Macedonia"
],
[
"Paul_Giamatti",
"acted_in",
"Cosmopolis"
],
[
"Robert_Carlock",
"award_nominee",
"David_Miner"
],
[
"Robert_Carlock",
"award_nominee",
"Don_Scardino"
],
[
"Robert_Carlock",
"award_nominee",
"Lorne_Michaels"
],
[
"Robert_Carlock",
"award_nominee",
"Marci_Klein"
],
[
"Robert_Carlock",
"award_nominee",
"Tina_Fey"
],
[
"Robert_Carlock",
"award_winner",
"David_Miner"
],
[
"Robert_Carlock",
"award_winner",
"Don_Scardino"
],
[
"Robert_Carlock",
"award_winner",
"Lorne_Michaels"
],
[
"Robert_Carlock",
"award_winner",
"Marci_Klein"
],
[
"Robert_Carlock",
"award_winner",
"Tina_Fey"
],
[
"Robert_Carlock",
"program",
"30_Rock"
],
[
"Robert_Carlock",
"tv_program",
"30_Rock"
],
[
"Samantha_Morton",
"acted_in",
"Cosmopolis"
],
[
"Samantha_Morton",
"acted_in",
"In_America"
],
[
"Samantha_Morton",
"nominated_for",
"In_America"
],
[
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Comedy_Series",
"award_winner",
"Tina_Fey"
],
[
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Comedy_Series",
"nominated_for",
"30_Rock"
],
[
"Steve_Buscemi",
"acted_in",
"On_the_Road"
],
[
"Steve_Buscemi",
"nominated_for",
"30_Rock"
],
[
"The_Fifth_Element",
"film_release_region",
"Luxembourg"
],
[
"The_Fifth_Element",
"film_release_region",
"Panama"
],
[
"Tina_Fey",
"award_nominee",
"David_Miner"
],
[
"Tina_Fey",
"award_nominee",
"Lorne_Michaels"
],
[
"Tina_Fey",
"award_nominee",
"Marci_Klein"
],
[
"Tina_Fey",
"award_nominee",
"Robert_Carlock"
],
[
"Tina_Fey",
"award_winner",
"David_Miner"
],
[
"Tina_Fey",
"award_winner",
"Don_Scardino"
],
[
"Tina_Fey",
"award_winner",
"Judah_Friedlander"
],
[
"Tina_Fey",
"award_winner",
"Lorne_Michaels"
],
[
"Tina_Fey",
"award_winner",
"Marci_Klein"
],
[
"Tina_Fey",
"award_winner",
"Maulik_Pancholy"
],
[
"Tina_Fey",
"award_winner",
"Robert_Carlock"
],
[
"Tina_Fey",
"nominated_for",
"30_Rock"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1454, 2010_Toronto_International_Film_Festival
564, 20th_Century_Fox
11774, 35_mm_film
8857, Academy_Award_for_Best_Actor
7506, Academy_Award_for_Best_Director
6569, Academy_Award_for_Best_Original_Screenplay
7377, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography
1407, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design
3877, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing
9668, Alachua_County
5268, Alliance_Films
4774, Argentina
3375, Atlantic_City
13215, Atlantic_County
4389, Austria
2732, BAFTA_Award_for_Best_Actor_in_a_Leading_Role
8091, BAFTA_Award_for_Best_Direction
1486, BAFTA_Award_for_Best_Film
11644, Bangor
11332, Belgium
9704, Black_Robe
10479, Brevard_County
6549, Broward_County
7594, Carmarthen
2840, Carol_Spier
2125, Citrus_County
3525, Collier_County
8527, Contiguous_United_States
13455, Coral_Gables
7753, Crash
8453, Crime_Fiction
12407, David_Cronenberg
6360, Dead_Ringers
12757, Denmark-GB
4693, Dialogue_Editor
7705, Duval_County
1163, Eastern_Promises
10846, Eastern_Time_Zone
8009, Film_adaptation
11702, Fine_Line_Features
1273, Finland
1311, Florida
5507, Fort_Lauderdale
10665, Fort_Myers
638, French_Language
13251, Gainesville
9457, Genie_Award_for_Best_Achievement_in_Art_Direction/Production_Design
7557, Genie_Award_for_Best_Achievement_in_Editing
12240, Genie_Award_for_Best_Achievement_in_Overall_Sound
9846, Georgia
2436, Golden_Globe_Award_for_Best_Foreign_Language_Film
11072, Golden_Reel_Award
7712, Heartbeats
6381, Hillsborough_County
5193, Hollywood
7355, Hong_Kong
3210, Horror
13587, Howard_Shore
6222, Hungary
5105, Ian_Holm
10357, Indian_River_County
7414, Indie_film
491, Jacksonville
1222, Jeremy_Thomas
10066, LGBT
4287, Lake_County
9418, Lakeland
3919, Lee_County
614, Library_of_Congress_Classification
3833, Lionsgate_Entertainment
7334, London
1521, Marion_County
9267, Mark_Irwin
12301, Melbourne
9693, Miami
6622, Miami_Beach
9391, Monroe_County
13811, Montreal
5768, Murder_by_Decree
11312, Mychael_Danna
2086, Mystery
8808, Naked_Lunch
2703, Naples
5906, National_Society_of_Film_Critics_Award_for_Best_Actor
3320, National_Society_of_Film_Critics_Award_for_Best_Director
3701, National_Society_of_Film_Critics_Award_for_Best_Film
485, National_Society_of_Film_Critics_Award_for_Best_Supporting_Actress
5127, New_Jersey
4780, New_Line_Cinema
6684, New_York_Film_Critics_Circle_Award_for_Best_Actor
6950, Newport
9528, Orange_County
7822, Orlando
4431, Palm_Beach
10736, Palm_Beach_County
9735, Pasco_County
12539, Period_piece
7071, Pinellas_County
12212, Poland
7063, Polk_County
7975, Pompano_Beach
161, Portugal
3978, Psychological_thriller
4669, QuΓ©bec
117, Robert_Lantos
7255, Romance_Film
1811, Sarasota
9109, Satellite_Award_for_Best_Original_Screenplay
770, Sound_Editor-GB
2750, South_Korea
6452, St._Augustine
2824, Standard_Mandarin
10530, Tallahassee
5421, Tampa
6015, The_Red_Violin
11311, The_Sweet_Hereafter
5948, Toronto
4032, Turkey
10256, Volusia_County
9048, Wales
11776, Water
6096, West_Palm_Beach
7458, World_cinema
src, edge_attr, dst
564, film, 6360
564, film, 8808
8857, nominated_for, 3375
8857, nominated_for, 1163
7506, nominated_for, 3375
7506, nominated_for, 7753
7506, nominated_for, 11311
6569, nominated_for, 3375
7377, nominated_for, 3375
7377, nominated_for, 9704
7377, nominated_for, 7753
7377, nominated_for, 6360
7377, nominated_for, 1163
7377, nominated_for, 7712
7377, nominated_for, 5768
7377, nominated_for, 6015
7377, nominated_for, 11311
1407, nominated_for, 3375
1407, nominated_for, 9704
1407, nominated_for, 6360
1407, nominated_for, 1163
1407, nominated_for, 8808
1407, nominated_for, 6015
1407, nominated_for, 11311
1407, nominated_for, 11776
3877, nominated_for, 7753
3877, nominated_for, 6360
3877, nominated_for, 5768
3877, nominated_for, 6015
3877, nominated_for, 11311
9668, time_zones, 10846
5268, film, 7753
5268, film, 1163
5268, film, 6015
3375, award_honor_award, 2732
3375, award_honor_award, 9457
3375, award_honor_award, 5906
3375, award_honor_award, 6684
3375, county, 13215
3375, genre, 8453
3375, genre, 7255
3375, language, 638
3375, place, 3375
3375, time_zones, 10846
13215, time_zones, 10846
2732, nominated_for, 1163
8091, nominated_for, 3375
8091, nominated_for, 7753
1486, nominated_for, 3375
1486, nominated_for, 7753
11644, time_zones, 10846
9704, award_honor_award, 7377
9704, award_honor_award, 9457
9704, award_honor_award, 11072
9704, award_winner, 117
10479, time_zones, 10846
6549, time_zones, 10846
2840, film_sets_designed, 8808
2840, nominated_for, 6360
2840, nominated_for, 1163
2125, administrative_parent, 1311
2125, time_zones, 10846
3525, time_zones, 10846
8527, contains, 1311
8527, time_zones, 10846
13455, state, 1311
13455, time_zones, 10846
7753, award_honor_award, 6569
7753, award_honor_award, 3877
7753, award_honor_award, 7557
7753, award_winner, 12407
7753, award_winner, 1222
7753, award_winner, 117
7753, executive_produced_by, 1222
7753, executive_produced_by, 117
7753, featured_film_locations, 5948
7753, film_crew_role, 4693
7753, film_festivals, 1454
7753, film_music, 13587
7753, film_production_design_by, 2840
7753, genre, 8453
7753, genre, 8009
7753, genre, 7414
7753, genre, 10066
7753, genre, 3978
7753, language, 2824
7753, produced_by, 12407
7753, written_by, 12407
12407, film, 7753
12407, film, 6360
12407, film, 1163
12407, nominated_for, 7753
12407, nominated_for, 6360
12407, nominated_for, 8808
6360, award_honor_award, 7377
6360, award_honor_award, 3877
6360, award_honor_award, 9457
6360, award_honor_award, 6684
6360, award_winner, 2840
6360, award_winner, 12407
6360, award_winner, 13587
6360, featured_film_locations, 5948
6360, film_crew_role, 770
6360, film_music, 13587
6360, film_production_design_by, 2840
6360, genre, 3210
6360, genre, 3978
6360, produced_by, 12407
6360, written_by, 12407
7705, contains, 491
7705, county_seat, 491
7705, time_zones, 10846
1163, award_honor_award, 3877
1163, award_honor_award, 7557
1163, award_honor_award, 12240
1163, award_winner, 13587
1163, featured_film_locations, 7334
1163, film_music, 13587
1163, film_production_design_by, 2840
1163, genre, 8453
1163, genre, 2086
1163, produced_by, 117
11702, film, 7753
11702, film, 11311
1311, adjoins, 9846
1311, contains, 9668
1311, contains, 10479
1311, contains, 6549
1311, contains, 2125
1311, contains, 3525
1311, contains, 13455
1311, contains, 7705
1311, contains, 5507
1311, contains, 10665
1311, contains, 13251
1311, contains, 6381
1311, contains, 5193
1311, contains, 10357
1311, contains, 491
1311, contains, 4287
1311, contains, 9418
1311, contains, 3919
1311, contains, 1521
1311, contains, 12301
1311, contains, 9693
1311, contains, 6622
1311, contains, 2703
1311, contains, 9528
1311, contains, 7822
1311, contains, 4431
1311, contains, 10736
1311, contains, 9735
1311, contains, 7071
1311, contains, 7063
1311, contains, 7975
1311, contains, 1811
1311, contains, 6452
1311, contains, 10530
1311, contains, 5421
1311, contains, 10256
1311, contains, 6096
1311, taxonomy, 614
1311, time_zones, 10846
5507, time_zones, 10846
10665, time_zones, 10846
13251, state, 1311
13251, time_zones, 10846
9457, nominated_for, 3375
9457, nominated_for, 9704
9457, nominated_for, 1163
9457, nominated_for, 6015
9457, nominated_for, 11311
9457, nominated_for, 11776
7557, nominated_for, 6015
7557, nominated_for, 11311
7557, nominated_for, 11776
12240, nominated_for, 7753
12240, nominated_for, 6360
12240, nominated_for, 1163
12240, nominated_for, 5768
12240, nominated_for, 8808
12240, nominated_for, 6015
12240, nominated_for, 11311
9846, adjoins, 1311
9846, time_zones, 10846
2436, nominated_for, 3375
2436, nominated_for, 6015
11072, nominated_for, 9704
11072, nominated_for, 7753
7712, featured_film_locations, 13811
7712, film_festivals, 1454
7712, film_format, 11774
7712, film_regional_debut_venue, 4669
7712, film_release_region, 4774
7712, film_release_region, 11332
7712, film_release_region, 12757
7712, film_release_region, 1273
7712, film_release_region, 6222
7712, film_release_region, 12212
7712, film_release_region, 161
7712, film_release_region, 2750
7712, film_release_region, 4032
7712, genre, 7414
7712, genre, 10066
7712, genre, 7255
7712, genre, 7458
7712, language, 638
6381, time_zones, 10846
5193, state, 1311
5193, time_zones, 10846
13587, nominated_for, 6360
13587, nominated_for, 1163
13587, nominated_for, 8808
5105, acted_in, 8808
5105, acted_in, 11311
5105, nominated_for, 11311
10357, time_zones, 10846
491, administrative_division, 7705
491, place, 491
491, state, 1311
491, time_zones, 10846
1222, nominated_for, 7753
4287, time_zones, 10846
9418, time_zones, 10846
3919, time_zones, 10846
3833, film, 7753
3833, film, 6015
3833, nominated_for, 6015
7334, time_zones, 10846
1521, time_zones, 10846
9267, award, 7377
9267, location, 5948
9267, place_of_birth, 5948
12301, state, 1311
12301, time_zones, 10846
9693, state, 1311
9693, time_zones, 10846
6622, time_zones, 10846
9391, administrative_parent, 1311
9391, time_zones, 10846
13811, time_zones, 10846
5768, featured_film_locations, 7334
5768, film_format, 11774
5768, film_release_region, 1273
5768, film_release_region, 7355
5768, genre, 8453
5768, genre, 8009
5768, genre, 3210
5768, genre, 2086
5768, genre, 12539
11312, nominated_for, 11311
11312, nominated_for, 11776
2086, titles, 6015
8808, award_honor_award, 7377
8808, award_honor_award, 3877
8808, award_honor_award, 9457
8808, award_honor_award, 12240
8808, award_honor_award, 3320
8808, award_winner, 2840
8808, award_winner, 12407
8808, film_format, 11774
8808, film_music, 13587
8808, film_production_design_by, 2840
8808, film_release_region, 4389
8808, film_release_region, 12757
8808, film_release_region, 1273
8808, film_release_region, 6222
8808, film_release_region, 161
8808, film_release_region, 4032
8808, produced_by, 1222
8808, written_by, 12407
2703, state, 1311
2703, time_zones, 10846
5906, nominated_for, 3375
5906, nominated_for, 11311
3320, nominated_for, 3375
3320, nominated_for, 8808
3320, nominated_for, 11311
3701, nominated_for, 3375
3701, nominated_for, 8808
3701, nominated_for, 11311
485, nominated_for, 8808
485, nominated_for, 11311
5127, contains, 3375
5127, time_zones, 10846
4780, film, 7753
6950, administrative_parent, 9048
6950, first_level_division, 9048
6950, time_zones, 10846
9528, time_zones, 10846
7822, state, 1311
7822, time_zones, 10846
4431, time_zones, 10846
10736, time_zones, 10846
9735, time_zones, 10846
12539, titles, 6015
7071, time_zones, 10846
7063, time_zones, 10846
7975, time_zones, 10846
3978, titles, 7753
3978, titles, 6360
3978, titles, 8808
4669, time_zones, 10846
117, nominated_for, 9704
117, nominated_for, 7753
1811, state, 1311
1811, time_zones, 10846
9109, nominated_for, 7753
9109, nominated_for, 1163
6452, time_zones, 10846
10530, administrative_division, 1311
10530, state, 1311
10530, time_zones, 10846
5421, state, 1311
5421, time_zones, 10846
6015, award_honor_award, 7377
6015, award_honor_award, 1407
6015, award_honor_award, 9457
6015, award_honor_award, 12240
6015, featured_film_locations, 13811
6015, film_crew_role, 770
6015, film_release_region, 4774
6015, film_release_region, 4389
6015, film_release_region, 11332
6015, film_release_region, 1273
6015, film_release_region, 7355
6015, film_release_region, 6222
6015, film_release_region, 12212
6015, film_release_region, 161
6015, film_release_region, 2750
6015, genre, 2086
6015, genre, 7255
6015, language, 638
6015, language, 2824
6015, production_companies, 4780
11311, award_honor_award, 3877
11311, award_honor_award, 12240
11311, award_winner, 5105
11311, award_winner, 11312
11311, executive_produced_by, 117
11311, film_crew_role, 4693
11311, film_music, 11312
11311, genre, 8009
11311, genre, 7414
5948, time_zones, 10846
10256, time_zones, 10846
9048, contains, 11644
9048, contains, 7594
9048, contains, 6950
9048, taxonomy, 614
11776, award_honor_award, 7377
11776, award_winner, 11312
11776, film_festivals, 1454
11776, film_music, 11312
11776, genre, 7255
11776, genre, 7458
6096, time_zones, 10846
Question: For what reason are Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography, Carmarthen, and Duval_County associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"Carmarthen",
"Duval_County"
],
"valid_edges": [
[
"20th_Century_Fox",
"film",
"Dead_Ringers"
],
[
"20th_Century_Fox",
"film",
"Naked_Lunch"
],
[
"Academy_Award_for_Best_Actor",
"nominated_for",
"Atlantic_City"
],
[
"Academy_Award_for_Best_Actor",
"nominated_for",
"Eastern_Promises"
],
[
"Academy_Award_for_Best_Director",
"nominated_for",
"Atlantic_City"
],
[
"Academy_Award_for_Best_Director",
"nominated_for",
"Crash"
],
[
"Academy_Award_for_Best_Director",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"Academy_Award_for_Best_Original_Screenplay",
"nominated_for",
"Atlantic_City"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Atlantic_City"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Black_Robe"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Crash"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Dead_Ringers"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Eastern_Promises"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Heartbeats"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Murder_by_Decree"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"The_Red_Violin"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design",
"nominated_for",
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"Naked_Lunch",
"award_honor_award",
"National_Society_of_Film_Critics_Award_for_Best_Director"
],
[
"Naked_Lunch",
"award_winner",
"Carol_Spier"
],
[
"Naked_Lunch",
"award_winner",
"David_Cronenberg"
],
[
"Naked_Lunch",
"film_format",
"35_mm_film"
],
[
"Naked_Lunch",
"film_music",
"Howard_Shore"
],
[
"Naked_Lunch",
"film_production_design_by",
"Carol_Spier"
],
[
"Naked_Lunch",
"film_release_region",
"Austria"
],
[
"Naked_Lunch",
"film_release_region",
"Denmark-GB"
],
[
"Naked_Lunch",
"film_release_region",
"Finland"
],
[
"Naked_Lunch",
"film_release_region",
"Hungary"
],
[
"Naked_Lunch",
"film_release_region",
"Portugal"
],
[
"Naked_Lunch",
"film_release_region",
"Turkey"
],
[
"Naked_Lunch",
"produced_by",
"Jeremy_Thomas"
],
[
"Naked_Lunch",
"written_by",
"David_Cronenberg"
],
[
"Naples",
"state",
"Florida"
],
[
"Naples",
"time_zones",
"Eastern_Time_Zone"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Actor",
"nominated_for",
"Atlantic_City"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Actor",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"Atlantic_City"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"Naked_Lunch"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Film",
"nominated_for",
"Atlantic_City"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Film",
"nominated_for",
"Naked_Lunch"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Film",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actress",
"nominated_for",
"Naked_Lunch"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actress",
"nominated_for",
"The_Sweet_Hereafter"
],
[
"New_Jersey",
"contains",
"Atlantic_City"
],
[
"New_Jersey",
"time_zones",
"Eastern_Time_Zone"
],
[
"New_Line_Cinema",
"film",
"Crash"
],
[
"Newport",
"administrative_parent",
"Wales"
],
[
"Newport",
"first_level_division",
"Wales"
],
[
"Newport",
"time_zones",
"Eastern_Time_Zone"
],
[
"Orange_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Orlando",
"state",
"Florida"
],
[
"Orlando",
"time_zones",
"Eastern_Time_Zone"
],
[
"Palm_Beach",
"time_zones",
"Eastern_Time_Zone"
],
[
"Palm_Beach_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Pasco_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Period_piece",
"titles",
"The_Red_Violin"
],
[
"Pinellas_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Polk_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Pompano_Beach",
"time_zones",
"Eastern_Time_Zone"
],
[
"Psychological_thriller",
"titles",
"Crash"
],
[
"Psychological_thriller",
"titles",
"Dead_Ringers"
],
[
"Psychological_thriller",
"titles",
"Naked_Lunch"
],
[
"QuΓ©bec",
"time_zones",
"Eastern_Time_Zone"
],
[
"Robert_Lantos",
"nominated_for",
"Black_Robe"
],
[
"Robert_Lantos",
"nominated_for",
"Crash"
],
[
"Sarasota",
"state",
"Florida"
],
[
"Sarasota",
"time_zones",
"Eastern_Time_Zone"
],
[
"Satellite_Award_for_Best_Original_Screenplay",
"nominated_for",
"Crash"
],
[
"Satellite_Award_for_Best_Original_Screenplay",
"nominated_for",
"Eastern_Promises"
],
[
"St._Augustine",
"time_zones",
"Eastern_Time_Zone"
],
[
"Tallahassee",
"administrative_division",
"Florida"
],
[
"Tallahassee",
"state",
"Florida"
],
[
"Tallahassee",
"time_zones",
"Eastern_Time_Zone"
],
[
"Tampa",
"state",
"Florida"
],
[
"Tampa",
"time_zones",
"Eastern_Time_Zone"
],
[
"The_Red_Violin",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography"
],
[
"The_Red_Violin",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design"
],
[
"The_Red_Violin",
"award_honor_award",
"Genie_Award_for_Best_Achievement_in_Art_Direction/Production_Design"
],
[
"The_Red_Violin",
"award_honor_award",
"Genie_Award_for_Best_Achievement_in_Overall_Sound"
],
[
"The_Red_Violin",
"featured_film_locations",
"Montreal"
],
[
"The_Red_Violin",
"film_crew_role",
"Sound_Editor-GB"
],
[
"The_Red_Violin",
"film_release_region",
"Argentina"
],
[
"The_Red_Violin",
"film_release_region",
"Austria"
],
[
"The_Red_Violin",
"film_release_region",
"Belgium"
],
[
"The_Red_Violin",
"film_release_region",
"Finland"
],
[
"The_Red_Violin",
"film_release_region",
"Hong_Kong"
],
[
"The_Red_Violin",
"film_release_region",
"Hungary"
],
[
"The_Red_Violin",
"film_release_region",
"Poland"
],
[
"The_Red_Violin",
"film_release_region",
"Portugal"
],
[
"The_Red_Violin",
"film_release_region",
"South_Korea"
],
[
"The_Red_Violin",
"genre",
"Mystery"
],
[
"The_Red_Violin",
"genre",
"Romance_Film"
],
[
"The_Red_Violin",
"language",
"French_Language"
],
[
"The_Red_Violin",
"language",
"Standard_Mandarin"
],
[
"The_Red_Violin",
"production_companies",
"New_Line_Cinema"
],
[
"The_Sweet_Hereafter",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing"
],
[
"The_Sweet_Hereafter",
"award_honor_award",
"Genie_Award_for_Best_Achievement_in_Overall_Sound"
],
[
"The_Sweet_Hereafter",
"award_winner",
"Ian_Holm"
],
[
"The_Sweet_Hereafter",
"award_winner",
"Mychael_Danna"
],
[
"The_Sweet_Hereafter",
"executive_produced_by",
"Robert_Lantos"
],
[
"The_Sweet_Hereafter",
"film_crew_role",
"Dialogue_Editor"
],
[
"The_Sweet_Hereafter",
"film_music",
"Mychael_Danna"
],
[
"The_Sweet_Hereafter",
"genre",
"Film_adaptation"
],
[
"The_Sweet_Hereafter",
"genre",
"Indie_film"
],
[
"Toronto",
"time_zones",
"Eastern_Time_Zone"
],
[
"Volusia_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Wales",
"contains",
"Bangor"
],
[
"Wales",
"contains",
"Carmarthen"
],
[
"Wales",
"contains",
"Newport"
],
[
"Wales",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Water",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography"
],
[
"Water",
"award_winner",
"Mychael_Danna"
],
[
"Water",
"film_festivals",
"2010_Toronto_International_Film_Festival"
],
[
"Water",
"film_music",
"Mychael_Danna"
],
[
"Water",
"genre",
"Romance_Film"
],
[
"Water",
"genre",
"World_cinema"
],
[
"West_Palm_Beach",
"time_zones",
"Eastern_Time_Zone"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7878, AC/DC
5541, Aerosmith
2105, Alternative_hip_hop
11752, Beastie_Boys
10088, Brian_Robbins
10553, Channing_Tatum
10229, Coach_Carter
7884, Gangsta_rap
13755, Gulf_War
7610, Guns_N'_Roses
13250, Ice_Cube
3636, Jonah_Hill
13037, Korn
7140, Limp_Bizkit
4469, MTV
7810, MTV2
3516, Metallica
403, Mike_Tollin
13447, Nirvana
2395, One_Tree_Hill
2456, Pearl_Jam
6894, Political_hip_hop
266, Radio
5781, Rapcore
1439, Red_Hot_Chili_Peppers
10684, Saudi_Arabia
13677, Show_jumping
7798, Smallville
11413, Soundgarden
13225, Suicidal_Tendencies
12820, Talking_Heads
5992, Teen_drama
1986, The_Offspring
8187, The_Smashing_Pumpkins
8461, Three_Kings
4823, Tupac_Shakur
539, Van_Halen
4528, West_Coast_hip_hop
src, edge_attr, dst
2105, artists, 11752
2105, artists, 13250
2105, parent_genre, 4528
10088, award_nominee, 403
10088, nominated_for, 10229
10088, program, 2395
10088, program, 7798
10553, acted_in, 10229
10553, award_nominee, 13250
10553, award_nominee, 3636
10229, produced_by, 10088
10229, produced_by, 403
10229, production_companies, 4469
7884, artists, 13250
7884, artists, 4823
7884, parent_genre, 4528
13755, combatants, 10684
13755, films, 8461
13755, locations, 10684
13250, award_nominee, 10553
13250, award_nominee, 3636
13250, nominated_for, 8461
3636, award_nominee, 10553
3636, award_nominee, 13250
4469, artist, 7878
4469, artist, 5541
4469, artist, 11752
4469, artist, 7610
4469, artist, 13250
4469, artist, 13037
4469, artist, 7140
4469, artist, 3516
4469, artist, 13447
4469, artist, 2456
4469, artist, 1439
4469, artist, 11413
4469, artist, 13225
4469, artist, 12820
4469, artist, 1986
4469, artist, 8187
4469, artist, 4823
4469, artist, 539
7810, artist, 7878
7810, artist, 5541
7810, artist, 11752
7810, artist, 7610
7810, artist, 13250
7810, artist, 13037
7810, artist, 7140
7810, artist, 3516
7810, artist, 13447
7810, artist, 2456
7810, artist, 1439
7810, artist, 11413
7810, artist, 13225
7810, artist, 12820
7810, artist, 1986
7810, artist, 8187
7810, artist, 4823
7810, artist, 539
403, film, 266
403, nominated_for, 10229
403, program, 2395
403, program, 7798
6894, artists, 13250
6894, artists, 4823
266, award_winner, 403
266, produced_by, 10088
266, produced_by, 403
5781, artists, 11752
5781, artists, 13250
5781, artists, 7140
5781, artists, 13225
5781, parent_genre, 4528
13677, country, 10684
5992, titles, 2395
5992, titles, 7798
8461, award_winner, 13250
4528, artists, 13250
4528, artists, 4823
Question: For what reason are Ice_Cube, Mike_Tollin, and Show_jumping associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Ice_Cube",
"Mike_Tollin",
"Show_jumping"
],
"valid_edges": [
[
"Alternative_hip_hop",
"artists",
"Beastie_Boys"
],
[
"Alternative_hip_hop",
"artists",
"Ice_Cube"
],
[
"Alternative_hip_hop",
"parent_genre",
"West_Coast_hip_hop"
],
[
"Brian_Robbins",
"award_nominee",
"Mike_Tollin"
],
[
"Brian_Robbins",
"nominated_for",
"Coach_Carter"
],
[
"Brian_Robbins",
"program",
"One_Tree_Hill"
],
[
"Brian_Robbins",
"program",
"Smallville"
],
[
"Channing_Tatum",
"acted_in",
"Coach_Carter"
],
[
"Channing_Tatum",
"award_nominee",
"Ice_Cube"
],
[
"Channing_Tatum",
"award_nominee",
"Jonah_Hill"
],
[
"Coach_Carter",
"produced_by",
"Brian_Robbins"
],
[
"Coach_Carter",
"produced_by",
"Mike_Tollin"
],
[
"Coach_Carter",
"production_companies",
"MTV"
],
[
"Gangsta_rap",
"artists",
"Ice_Cube"
],
[
"Gangsta_rap",
"artists",
"Tupac_Shakur"
],
[
"Gangsta_rap",
"parent_genre",
"West_Coast_hip_hop"
],
[
"Gulf_War",
"combatants",
"Saudi_Arabia"
],
[
"Gulf_War",
"films",
"Three_Kings"
],
[
"Gulf_War",
"locations",
"Saudi_Arabia"
],
[
"Ice_Cube",
"award_nominee",
"Channing_Tatum"
],
[
"Ice_Cube",
"award_nominee",
"Jonah_Hill"
],
[
"Ice_Cube",
"nominated_for",
"Three_Kings"
],
[
"Jonah_Hill",
"award_nominee",
"Channing_Tatum"
],
[
"Jonah_Hill",
"award_nominee",
"Ice_Cube"
],
[
"MTV",
"artist",
"AC/DC"
],
[
"MTV",
"artist",
"Aerosmith"
],
[
"MTV",
"artist",
"Beastie_Boys"
],
[
"MTV",
"artist",
"Guns_N'_Roses"
],
[
"MTV",
"artist",
"Ice_Cube"
],
[
"MTV",
"artist",
"Korn"
],
[
"MTV",
"artist",
"Limp_Bizkit"
],
[
"MTV",
"artist",
"Metallica"
],
[
"MTV",
"artist",
"Nirvana"
],
[
"MTV",
"artist",
"Pearl_Jam"
],
[
"MTV",
"artist",
"Red_Hot_Chili_Peppers"
],
[
"MTV",
"artist",
"Soundgarden"
],
[
"MTV",
"artist",
"Suicidal_Tendencies"
],
[
"MTV",
"artist",
"Talking_Heads"
],
[
"MTV",
"artist",
"The_Offspring"
],
[
"MTV",
"artist",
"The_Smashing_Pumpkins"
],
[
"MTV",
"artist",
"Tupac_Shakur"
],
[
"MTV",
"artist",
"Van_Halen"
],
[
"MTV2",
"artist",
"AC/DC"
],
[
"MTV2",
"artist",
"Aerosmith"
],
[
"MTV2",
"artist",
"Beastie_Boys"
],
[
"MTV2",
"artist",
"Guns_N'_Roses"
],
[
"MTV2",
"artist",
"Ice_Cube"
],
[
"MTV2",
"artist",
"Korn"
],
[
"MTV2",
"artist",
"Limp_Bizkit"
],
[
"MTV2",
"artist",
"Metallica"
],
[
"MTV2",
"artist",
"Nirvana"
],
[
"MTV2",
"artist",
"Pearl_Jam"
],
[
"MTV2",
"artist",
"Red_Hot_Chili_Peppers"
],
[
"MTV2",
"artist",
"Soundgarden"
],
[
"MTV2",
"artist",
"Suicidal_Tendencies"
],
[
"MTV2",
"artist",
"Talking_Heads"
],
[
"MTV2",
"artist",
"The_Offspring"
],
[
"MTV2",
"artist",
"The_Smashing_Pumpkins"
],
[
"MTV2",
"artist",
"Tupac_Shakur"
],
[
"MTV2",
"artist",
"Van_Halen"
],
[
"Mike_Tollin",
"film",
"Radio"
],
[
"Mike_Tollin",
"nominated_for",
"Coach_Carter"
],
[
"Mike_Tollin",
"program",
"One_Tree_Hill"
],
[
"Mike_Tollin",
"program",
"Smallville"
],
[
"Political_hip_hop",
"artists",
"Ice_Cube"
],
[
"Political_hip_hop",
"artists",
"Tupac_Shakur"
],
[
"Radio",
"award_winner",
"Mike_Tollin"
],
[
"Radio",
"produced_by",
"Brian_Robbins"
],
[
"Radio",
"produced_by",
"Mike_Tollin"
],
[
"Rapcore",
"artists",
"Beastie_Boys"
],
[
"Rapcore",
"artists",
"Ice_Cube"
],
[
"Rapcore",
"artists",
"Limp_Bizkit"
],
[
"Rapcore",
"artists",
"Suicidal_Tendencies"
],
[
"Rapcore",
"parent_genre",
"West_Coast_hip_hop"
],
[
"Show_jumping",
"country",
"Saudi_Arabia"
],
[
"Teen_drama",
"titles",
"One_Tree_Hill"
],
[
"Teen_drama",
"titles",
"Smallville"
],
[
"Three_Kings",
"award_winner",
"Ice_Cube"
],
[
"West_Coast_hip_hop",
"artists",
"Ice_Cube"
],
[
"West_Coast_hip_hop",
"artists",
"Tupac_Shakur"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7149, Al_Franken
5009, Alan_Bennett
3669, Alan_Moore
3821, Aldous_Huxley
7860, Allen_Covert
1434, Angela_Lansbury
4815, Anthony_Horowitz
1050, Armando_Iannucci
2612, Author-GB
12195, B._J._Novak
11515, Ben_Elton
1055, Ben_Stein
4251, Bette_Midler
7991, Bill_Hader
9614, Bill_Nighy
4183, Breckin_Meyer
7933, Brian_May
4465, Carl_Reiner
3578, Carol_Burnett
1325, Catherine_Tate
3022, Charles_Dickens
5436, Charlie_Chaplin
10461, Chris_Elliott
5128, Comedian
1210, Cradle_of_Filth
11377, D._H._Lawrence
14110, David_Attenborough
1491, David_Spade
696, David_Walliams
13482, Dirk_Bogarde
1200, Douglas_Adams
13546, Elaine_May
4138, Ellie_Kemper
8797, Emma_Thompson
10044, England
10901, Eric_Idle
2708, Frank_Skinner
9088, G._K._Chesterton
4036, Garry_Shandling
6624, Gene_Wilder
11496, George_Carlin
13448, George_Orwell
10026, Gerry_Anderson
7988, Graham_Chapman
5093, Graham_Greene
4778, Guy_Ritchie
13074, H._G._Wells
12472, H._Jon_Benjamin
4719, Harold_Pinter
13410, Harold_Ramis
13197, Henry_Rollins
2358, Hugh_Laurie
8525, Ian_Fleming
5351, J._G._Ballard
8319, J._K._Rowling
7857, Jane_Austen
5518, Jay_Baruchel
7125, Jay_Leno
7861, Jeremy_Clarkson
8135, Jim_Dale
4600, John_Lennon
11806, John_Milton
10237, John_Osborne
8828, Jonathan_Lynn
1911, Julian_Fellowes
228, Julie_Walters
13100, Keenen_Ivory_Wayans
12200, Keith_Allen
9719, Kenan_Thompson
11294, Kevin_Nealon
13456, Kevin_Pollak
11662, Kristen_Wiig
2324, Lewis_Black
3546, Lewis_Carroll
12322, Lily_Tomlin
10871, Margaret_Cho
4233, Mark_Gatiss
7413, Mark_Williams
6508, Mary_Shelley
8496, Mel_Brooks
3109, Michael_Moorcock
12147, Michael_Palin
5210, Mike_Epps
8635, Mike_Figgis
10118, Mike_Henry
8273, Naomi_Campbell
1972, Neil_Gaiman
532, Nick_Cannon
5787, Nicole_Sullivan
9234, Nuclear_Blast
12479, Pamela_Anderson
1623, Patton_Oswalt
2342, Paul_Reiser
11899, Penelope_Wilton
14187, Penn_Jillette
3460, Peter_Cook
9578, Peter_Sellers
12319, Peter_Ustinov
1935, Philip_Pullman
6209, Rainn_Wilson
4875, Richard_Hammond
8407, Ricky_Gervais
9964, Robert_Klein
7790, Robert_Smigel
6263, Rowan_Atkinson
3834, Rudyard_Kipling
9181, Rupert_Holmes
9286, Ruth_Prawer_Jhabvala
605, Sacha_Baron_Cohen
7196, Sam_Shepard
1943, Shawn_Wayans
507, Sid_James
816, Simon_Callow
8108, South_Cambridgeshire
11543, Spike_Milligan
11682, Stan_Laurel
6279, Stephen_Chow
10663, Stephen_Colbert
7447, Stephen_Fry
3852, Stephen_Hawking
14165, Stephen_Merchant
4039, Steve_Allen
6473, Steve_Martin
12998, Steve_Oedekerk
14231, Steven_Wright
5724, Suffolk
8475, T._S._Eliot
10408, Television_producer-GB
827, Terry_Jones
1721, Thomas_Hardy
2929, Tim_Rice
898, Tina_Fey
10673, Tracey_Ullman
9819, Vernon_Chatman
740, Virginia_Woolf
3011, Warren_Ellis
13174, William_Morris
3484, Woody_Allen
870, Writer-GB
5012, Wyatt_Cenac
src, edge_attr, dst
7149, profession, 5128
7149, profession, 870
5009, nationality, 10044
5009, profession, 870
3669, nationality, 10044
3669, profession, 870
3821, nationality, 10044
3821, profession, 870
7860, profession, 5128
7860, profession, 870
1434, nationality, 10044
1434, profession, 870
4815, nationality, 10044
4815, profession, 870
1050, profession, 5128
1050, profession, 870
2612, specialization_of, 870
12195, profession, 5128
12195, profession, 870
11515, nationality, 10044
11515, profession, 5128
11515, profession, 870
1055, profession, 5128
1055, profession, 870
4251, profession, 5128
4251, profession, 870
7991, profession, 5128
7991, profession, 870
9614, nationality, 10044
9614, profession, 5128
4183, profession, 5128
4183, profession, 870
7933, nationality, 10044
7933, profession, 870
4465, profession, 5128
4465, profession, 870
3578, profession, 5128
3578, profession, 870
1325, profession, 5128
1325, profession, 870
3022, nationality, 10044
3022, profession, 870
5436, nationality, 10044
5436, profession, 5128
10461, profession, 5128
10461, profession, 870
1210, artist_origin, 5724
11377, nationality, 10044
11377, profession, 870
14110, nationality, 10044
14110, profession, 870
1491, participant, 12479
1491, profession, 5128
696, nationality, 10044
696, profession, 5128
13482, nationality, 10044
13482, profession, 870
1200, nationality, 10044
1200, profession, 870
13546, profession, 5128
13546, profession, 870
4138, profession, 5128
4138, profession, 870
8797, nationality, 10044
8797, profession, 5128
10044, contains, 8108
10044, second_level_divisions, 5724
10901, nationality, 10044
10901, profession, 5128
10901, profession, 870
2708, nationality, 10044
2708, profession, 5128
9088, nationality, 10044
9088, profession, 870
4036, profession, 5128
4036, profession, 870
6624, profession, 5128
6624, profession, 870
11496, profession, 5128
11496, profession, 870
13448, nationality, 10044
13448, profession, 870
10026, nationality, 10044
10026, profession, 870
7988, nationality, 10044
7988, profession, 5128
7988, profession, 870
5093, nationality, 10044
5093, profession, 870
4778, nationality, 10044
4778, profession, 870
13074, nationality, 10044
13074, profession, 870
12472, profession, 5128
12472, profession, 870
4719, nationality, 10044
4719, profession, 870
13410, profession, 5128
13410, profession, 870
13197, profession, 5128
13197, profession, 870
2358, nationality, 10044
2358, profession, 5128
8525, nationality, 10044
8525, profession, 870
5351, nationality, 10044
5351, profession, 870
8319, nationality, 10044
8319, profession, 870
7857, nationality, 10044
7857, profession, 870
5518, profession, 5128
5518, profession, 870
7125, profession, 5128
7125, profession, 870
7861, nationality, 10044
7861, profession, 870
8135, nationality, 10044
8135, profession, 5128
4600, nationality, 10044
4600, profession, 870
11806, nationality, 10044
11806, profession, 870
10237, nationality, 10044
10237, profession, 870
8828, nationality, 10044
8828, profession, 5128
1911, nationality, 10044
1911, profession, 870
228, nationality, 10044
228, profession, 5128
13100, profession, 5128
13100, profession, 10408
12200, profession, 5128
12200, profession, 870
9719, profession, 5128
9719, profession, 870
11294, profession, 5128
11294, profession, 870
13456, profession, 5128
13456, profession, 870
11662, profession, 5128
11662, profession, 870
2324, profession, 5128
2324, profession, 870
3546, nationality, 10044
3546, profession, 870
12322, profession, 5128
12322, profession, 870
10871, profession, 5128
10871, profession, 870
4233, nationality, 10044
4233, profession, 5128
4233, profession, 870
7413, nationality, 10044
7413, profession, 5128
6508, nationality, 10044
6508, profession, 870
8496, profession, 5128
8496, profession, 870
3109, nationality, 10044
3109, profession, 870
12147, nationality, 10044
12147, profession, 5128
12147, profession, 870
5210, profession, 5128
5210, profession, 870
8635, nationality, 10044
8635, profession, 870
10118, profession, 5128
10118, profession, 870
8273, nationality, 10044
8273, profession, 870
1972, nationality, 10044
1972, profession, 870
532, profession, 5128
532, profession, 870
5787, profession, 5128
5787, profession, 870
9234, artist, 1210
12479, participant, 605
12479, participant, 1943
12479, profession, 2612
12479, profession, 10408
1623, profession, 5128
1623, profession, 870
2342, profession, 5128
2342, profession, 870
11899, nationality, 10044
11899, profession, 5128
14187, profession, 5128
14187, profession, 870
3460, nationality, 10044
3460, profession, 5128
9578, nationality, 10044
9578, profession, 5128
12319, nationality, 10044
12319, profession, 5128
1935, nationality, 10044
1935, profession, 870
6209, profession, 5128
6209, profession, 870
4875, nationality, 10044
4875, profession, 870
8407, nationality, 10044
8407, profession, 5128
8407, profession, 870
9964, profession, 5128
9964, profession, 870
7790, profession, 5128
7790, profession, 870
6263, nationality, 10044
6263, profession, 5128
3834, nationality, 10044
3834, profession, 870
9181, nationality, 10044
9181, profession, 870
9286, nationality, 10044
9286, profession, 870
605, participant, 12479
605, profession, 5128
605, profession, 870
7196, location, 10044
7196, profession, 870
1943, award_nominee, 13100
1943, participant, 12479
1943, profession, 5128
1943, profession, 870
1943, sibling, 13100
507, nationality, 10044
507, profession, 5128
816, nationality, 10044
816, profession, 870
11543, profession, 5128
11543, profession, 870
11682, nationality, 10044
11682, profession, 5128
6279, profession, 5128
6279, profession, 870
10663, profession, 5128
10663, profession, 870
7447, profession, 5128
7447, profession, 870
3852, nationality, 10044
3852, profession, 870
14165, nationality, 10044
14165, profession, 5128
14165, profession, 870
4039, profession, 5128
4039, profession, 870
6473, profession, 5128
6473, profession, 870
12998, profession, 5128
12998, profession, 870
14231, profession, 5128
14231, profession, 870
8475, nationality, 10044
8475, profession, 870
827, profession, 5128
827, profession, 870
1721, nationality, 10044
1721, profession, 870
2929, nationality, 10044
2929, profession, 870
898, profession, 5128
898, profession, 870
10673, location, 10044
10673, profession, 5128
9819, profession, 5128
9819, profession, 870
740, nationality, 10044
740, profession, 870
3011, nationality, 10044
3011, profession, 870
13174, nationality, 10044
13174, profession, 870
3484, profession, 5128
3484, profession, 870
5012, profession, 5128
5012, profession, 870
Question: For what reason are Nuclear_Blast, Shawn_Wayans, and South_Cambridgeshire associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Nuclear_Blast",
"Shawn_Wayans",
"South_Cambridgeshire"
],
"valid_edges": [
[
"Al_Franken",
"profession",
"Comedian"
],
[
"Al_Franken",
"profession",
"Writer-GB"
],
[
"Alan_Bennett",
"nationality",
"England"
],
[
"Alan_Bennett",
"profession",
"Writer-GB"
],
[
"Alan_Moore",
"nationality",
"England"
],
[
"Alan_Moore",
"profession",
"Writer-GB"
],
[
"Aldous_Huxley",
"nationality",
"England"
],
[
"Aldous_Huxley",
"profession",
"Writer-GB"
],
[
"Allen_Covert",
"profession",
"Comedian"
],
[
"Allen_Covert",
"profession",
"Writer-GB"
],
[
"Angela_Lansbury",
"nationality",
"England"
],
[
"Angela_Lansbury",
"profession",
"Writer-GB"
],
[
"Anthony_Horowitz",
"nationality",
"England"
],
[
"Anthony_Horowitz",
"profession",
"Writer-GB"
],
[
"Armando_Iannucci",
"profession",
"Comedian"
],
[
"Armando_Iannucci",
"profession",
"Writer-GB"
],
[
"Author-GB",
"specialization_of",
"Writer-GB"
],
[
"B._J._Novak",
"profession",
"Comedian"
],
[
"B._J._Novak",
"profession",
"Writer-GB"
],
[
"Ben_Elton",
"nationality",
"England"
],
[
"Ben_Elton",
"profession",
"Comedian"
],
[
"Ben_Elton",
"profession",
"Writer-GB"
],
[
"Ben_Stein",
"profession",
"Comedian"
],
[
"Ben_Stein",
"profession",
"Writer-GB"
],
[
"Bette_Midler",
"profession",
"Comedian"
],
[
"Bette_Midler",
"profession",
"Writer-GB"
],
[
"Bill_Hader",
"profession",
"Comedian"
],
[
"Bill_Hader",
"profession",
"Writer-GB"
],
[
"Bill_Nighy",
"nationality",
"England"
],
[
"Bill_Nighy",
"profession",
"Comedian"
],
[
"Breckin_Meyer",
"profession",
"Comedian"
],
[
"Breckin_Meyer",
"profession",
"Writer-GB"
],
[
"Brian_May",
"nationality",
"England"
],
[
"Brian_May",
"profession",
"Writer-GB"
],
[
"Carl_Reiner",
"profession",
"Comedian"
],
[
"Carl_Reiner",
"profession",
"Writer-GB"
],
[
"Carol_Burnett",
"profession",
"Comedian"
],
[
"Carol_Burnett",
"profession",
"Writer-GB"
],
[
"Catherine_Tate",
"profession",
"Comedian"
],
[
"Catherine_Tate",
"profession",
"Writer-GB"
],
[
"Charles_Dickens",
"nationality",
"England"
],
[
"Charles_Dickens",
"profession",
"Writer-GB"
],
[
"Charlie_Chaplin",
"nationality",
"England"
],
[
"Charlie_Chaplin",
"profession",
"Comedian"
],
[
"Chris_Elliott",
"profession",
"Comedian"
],
[
"Chris_Elliott",
"profession",
"Writer-GB"
],
[
"Cradle_of_Filth",
"artist_origin",
"Suffolk"
],
[
"D._H._Lawrence",
"nationality",
"England"
],
[
"D._H._Lawrence",
"profession",
"Writer-GB"
],
[
"David_Attenborough",
"nationality",
"England"
],
[
"David_Attenborough",
"profession",
"Writer-GB"
],
[
"David_Spade",
"participant",
"Pamela_Anderson"
],
[
"David_Spade",
"profession",
"Comedian"
],
[
"David_Walliams",
"nationality",
"England"
],
[
"David_Walliams",
"profession",
"Comedian"
],
[
"Dirk_Bogarde",
"nationality",
"England"
],
[
"Dirk_Bogarde",
"profession",
"Writer-GB"
],
[
"Douglas_Adams",
"nationality",
"England"
],
[
"Douglas_Adams",
"profession",
"Writer-GB"
],
[
"Elaine_May",
"profession",
"Comedian"
],
[
"Elaine_May",
"profession",
"Writer-GB"
],
[
"Ellie_Kemper",
"profession",
"Comedian"
],
[
"Ellie_Kemper",
"profession",
"Writer-GB"
],
[
"Emma_Thompson",
"nationality",
"England"
],
[
"Emma_Thompson",
"profession",
"Comedian"
],
[
"England",
"contains",
"South_Cambridgeshire"
],
[
"England",
"second_level_divisions",
"Suffolk"
],
[
"Eric_Idle",
"nationality",
"England"
],
[
"Eric_Idle",
"profession",
"Comedian"
],
[
"Eric_Idle",
"profession",
"Writer-GB"
],
[
"Frank_Skinner",
"nationality",
"England"
],
[
"Frank_Skinner",
"profession",
"Comedian"
],
[
"G._K._Chesterton",
"nationality",
"England"
],
[
"G._K._Chesterton",
"profession",
"Writer-GB"
],
[
"Garry_Shandling",
"profession",
"Comedian"
],
[
"Garry_Shandling",
"profession",
"Writer-GB"
],
[
"Gene_Wilder",
"profession",
"Comedian"
],
[
"Gene_Wilder",
"profession",
"Writer-GB"
],
[
"George_Carlin",
"profession",
"Comedian"
],
[
"George_Carlin",
"profession",
"Writer-GB"
],
[
"George_Orwell",
"nationality",
"England"
],
[
"George_Orwell",
"profession",
"Writer-GB"
],
[
"Gerry_Anderson",
"nationality",
"England"
],
[
"Gerry_Anderson",
"profession",
"Writer-GB"
],
[
"Graham_Chapman",
"nationality",
"England"
],
[
"Graham_Chapman",
"profession",
"Comedian"
],
[
"Graham_Chapman",
"profession",
"Writer-GB"
],
[
"Graham_Greene",
"nationality",
"England"
],
[
"Graham_Greene",
"profession",
"Writer-GB"
],
[
"Guy_Ritchie",
"nationality",
"England"
],
[
"Guy_Ritchie",
"profession",
"Writer-GB"
],
[
"H._G._Wells",
"nationality",
"England"
],
[
"H._G._Wells",
"profession",
"Writer-GB"
],
[
"H._Jon_Benjamin",
"profession",
"Comedian"
],
[
"H._Jon_Benjamin",
"profession",
"Writer-GB"
],
[
"Harold_Pinter",
"nationality",
"England"
],
[
"Harold_Pinter",
"profession",
"Writer-GB"
],
[
"Harold_Ramis",
"profession",
"Comedian"
],
[
"Harold_Ramis",
"profession",
"Writer-GB"
],
[
"Henry_Rollins",
"profession",
"Comedian"
],
[
"Henry_Rollins",
"profession",
"Writer-GB"
],
[
"Hugh_Laurie",
"nationality",
"England"
],
[
"Hugh_Laurie",
"profession",
"Comedian"
],
[
"Ian_Fleming",
"nationality",
"England"
],
[
"Ian_Fleming",
"profession",
"Writer-GB"
],
[
"J._G._Ballard",
"nationality",
"England"
],
[
"J._G._Ballard",
"profession",
"Writer-GB"
],
[
"J._K._Rowling",
"nationality",
"England"
],
[
"J._K._Rowling",
"profession",
"Writer-GB"
],
[
"Jane_Austen",
"nationality",
"England"
],
[
"Jane_Austen",
"profession",
"Writer-GB"
],
[
"Jay_Baruchel",
"profession",
"Comedian"
],
[
"Jay_Baruchel",
"profession",
"Writer-GB"
],
[
"Jay_Leno",
"profession",
"Comedian"
],
[
"Jay_Leno",
"profession",
"Writer-GB"
],
[
"Jeremy_Clarkson",
"nationality",
"England"
],
[
"Jeremy_Clarkson",
"profession",
"Writer-GB"
],
[
"Jim_Dale",
"nationality",
"England"
],
[
"Jim_Dale",
"profession",
"Comedian"
],
[
"John_Lennon",
"nationality",
"England"
],
[
"John_Lennon",
"profession",
"Writer-GB"
],
[
"John_Milton",
"nationality",
"England"
],
[
"John_Milton",
"profession",
"Writer-GB"
],
[
"John_Osborne",
"nationality",
"England"
],
[
"John_Osborne",
"profession",
"Writer-GB"
],
[
"Jonathan_Lynn",
"nationality",
"England"
],
[
"Jonathan_Lynn",
"profession",
"Comedian"
],
[
"Julian_Fellowes",
"nationality",
"England"
],
[
"Julian_Fellowes",
"profession",
"Writer-GB"
],
[
"Julie_Walters",
"nationality",
"England"
],
[
"Julie_Walters",
"profession",
"Comedian"
],
[
"Keenen_Ivory_Wayans",
"profession",
"Comedian"
],
[
"Keenen_Ivory_Wayans",
"profession",
"Television_producer-GB"
],
[
"Keith_Allen",
"profession",
"Comedian"
],
[
"Keith_Allen",
"profession",
"Writer-GB"
],
[
"Kenan_Thompson",
"profession",
"Comedian"
],
[
"Kenan_Thompson",
"profession",
"Writer-GB"
],
[
"Kevin_Nealon",
"profession",
"Comedian"
],
[
"Kevin_Nealon",
"profession",
"Writer-GB"
],
[
"Kevin_Pollak",
"profession",
"Comedian"
],
[
"Kevin_Pollak",
"profession",
"Writer-GB"
],
[
"Kristen_Wiig",
"profession",
"Comedian"
],
[
"Kristen_Wiig",
"profession",
"Writer-GB"
],
[
"Lewis_Black",
"profession",
"Comedian"
],
[
"Lewis_Black",
"profession",
"Writer-GB"
],
[
"Lewis_Carroll",
"nationality",
"England"
],
[
"Lewis_Carroll",
"profession",
"Writer-GB"
],
[
"Lily_Tomlin",
"profession",
"Comedian"
],
[
"Lily_Tomlin",
"profession",
"Writer-GB"
],
[
"Margaret_Cho",
"profession",
"Comedian"
],
[
"Margaret_Cho",
"profession",
"Writer-GB"
],
[
"Mark_Gatiss",
"nationality",
"England"
],
[
"Mark_Gatiss",
"profession",
"Comedian"
],
[
"Mark_Gatiss",
"profession",
"Writer-GB"
],
[
"Mark_Williams",
"nationality",
"England"
],
[
"Mark_Williams",
"profession",
"Comedian"
],
[
"Mary_Shelley",
"nationality",
"England"
],
[
"Mary_Shelley",
"profession",
"Writer-GB"
],
[
"Mel_Brooks",
"profession",
"Comedian"
],
[
"Mel_Brooks",
"profession",
"Writer-GB"
],
[
"Michael_Moorcock",
"nationality",
"England"
],
[
"Michael_Moorcock",
"profession",
"Writer-GB"
],
[
"Michael_Palin",
"nationality",
"England"
],
[
"Michael_Palin",
"profession",
"Comedian"
],
[
"Michael_Palin",
"profession",
"Writer-GB"
],
[
"Mike_Epps",
"profession",
"Comedian"
],
[
"Mike_Epps",
"profession",
"Writer-GB"
],
[
"Mike_Figgis",
"nationality",
"England"
],
[
"Mike_Figgis",
"profession",
"Writer-GB"
],
[
"Mike_Henry",
"profession",
"Comedian"
],
[
"Mike_Henry",
"profession",
"Writer-GB"
],
[
"Naomi_Campbell",
"nationality",
"England"
],
[
"Naomi_Campbell",
"profession",
"Writer-GB"
],
[
"Neil_Gaiman",
"nationality",
"England"
],
[
"Neil_Gaiman",
"profession",
"Writer-GB"
],
[
"Nick_Cannon",
"profession",
"Comedian"
],
[
"Nick_Cannon",
"profession",
"Writer-GB"
],
[
"Nicole_Sullivan",
"profession",
"Comedian"
],
[
"Nicole_Sullivan",
"profession",
"Writer-GB"
],
[
"Nuclear_Blast",
"artist",
"Cradle_of_Filth"
],
[
"Pamela_Anderson",
"participant",
"Sacha_Baron_Cohen"
],
[
"Pamela_Anderson",
"participant",
"Shawn_Wayans"
],
[
"Pamela_Anderson",
"profession",
"Author-GB"
],
[
"Pamela_Anderson",
"profession",
"Television_producer-GB"
],
[
"Patton_Oswalt",
"profession",
"Comedian"
],
[
"Patton_Oswalt",
"profession",
"Writer-GB"
],
[
"Paul_Reiser",
"profession",
"Comedian"
],
[
"Paul_Reiser",
"profession",
"Writer-GB"
],
[
"Penelope_Wilton",
"nationality",
"England"
],
[
"Penelope_Wilton",
"profession",
"Comedian"
],
[
"Penn_Jillette",
"profession",
"Comedian"
],
[
"Penn_Jillette",
"profession",
"Writer-GB"
],
[
"Peter_Cook",
"nationality",
"England"
],
[
"Peter_Cook",
"profession",
"Comedian"
],
[
"Peter_Sellers",
"nationality",
"England"
],
[
"Peter_Sellers",
"profession",
"Comedian"
],
[
"Peter_Ustinov",
"nationality",
"England"
],
[
"Peter_Ustinov",
"profession",
"Comedian"
],
[
"Philip_Pullman",
"nationality",
"England"
],
[
"Philip_Pullman",
"profession",
"Writer-GB"
],
[
"Rainn_Wilson",
"profession",
"Comedian"
],
[
"Rainn_Wilson",
"profession",
"Writer-GB"
],
[
"Richard_Hammond",
"nationality",
"England"
],
[
"Richard_Hammond",
"profession",
"Writer-GB"
],
[
"Ricky_Gervais",
"nationality",
"England"
],
[
"Ricky_Gervais",
"profession",
"Comedian"
],
[
"Ricky_Gervais",
"profession",
"Writer-GB"
],
[
"Robert_Klein",
"profession",
"Comedian"
],
[
"Robert_Klein",
"profession",
"Writer-GB"
],
[
"Robert_Smigel",
"profession",
"Comedian"
],
[
"Robert_Smigel",
"profession",
"Writer-GB"
],
[
"Rowan_Atkinson",
"nationality",
"England"
],
[
"Rowan_Atkinson",
"profession",
"Comedian"
],
[
"Rudyard_Kipling",
"nationality",
"England"
],
[
"Rudyard_Kipling",
"profession",
"Writer-GB"
],
[
"Rupert_Holmes",
"nationality",
"England"
],
[
"Rupert_Holmes",
"profession",
"Writer-GB"
],
[
"Ruth_Prawer_Jhabvala",
"nationality",
"England"
],
[
"Ruth_Prawer_Jhabvala",
"profession",
"Writer-GB"
],
[
"Sacha_Baron_Cohen",
"participant",
"Pamela_Anderson"
],
[
"Sacha_Baron_Cohen",
"profession",
"Comedian"
],
[
"Sacha_Baron_Cohen",
"profession",
"Writer-GB"
],
[
"Sam_Shepard",
"location",
"England"
],
[
"Sam_Shepard",
"profession",
"Writer-GB"
],
[
"Shawn_Wayans",
"award_nominee",
"Keenen_Ivory_Wayans"
],
[
"Shawn_Wayans",
"participant",
"Pamela_Anderson"
],
[
"Shawn_Wayans",
"profession",
"Comedian"
],
[
"Shawn_Wayans",
"profession",
"Writer-GB"
],
[
"Shawn_Wayans",
"sibling",
"Keenen_Ivory_Wayans"
],
[
"Sid_James",
"nationality",
"England"
],
[
"Sid_James",
"profession",
"Comedian"
],
[
"Simon_Callow",
"nationality",
"England"
],
[
"Simon_Callow",
"profession",
"Writer-GB"
],
[
"Spike_Milligan",
"profession",
"Comedian"
],
[
"Spike_Milligan",
"profession",
"Writer-GB"
],
[
"Stan_Laurel",
"nationality",
"England"
],
[
"Stan_Laurel",
"profession",
"Comedian"
],
[
"Stephen_Chow",
"profession",
"Comedian"
],
[
"Stephen_Chow",
"profession",
"Writer-GB"
],
[
"Stephen_Colbert",
"profession",
"Comedian"
],
[
"Stephen_Colbert",
"profession",
"Writer-GB"
],
[
"Stephen_Fry",
"profession",
"Comedian"
],
[
"Stephen_Fry",
"profession",
"Writer-GB"
],
[
"Stephen_Hawking",
"nationality",
"England"
],
[
"Stephen_Hawking",
"profession",
"Writer-GB"
],
[
"Stephen_Merchant",
"nationality",
"England"
],
[
"Stephen_Merchant",
"profession",
"Comedian"
],
[
"Stephen_Merchant",
"profession",
"Writer-GB"
],
[
"Steve_Allen",
"profession",
"Comedian"
],
[
"Steve_Allen",
"profession",
"Writer-GB"
],
[
"Steve_Martin",
"profession",
"Comedian"
],
[
"Steve_Martin",
"profession",
"Writer-GB"
],
[
"Steve_Oedekerk",
"profession",
"Comedian"
],
[
"Steve_Oedekerk",
"profession",
"Writer-GB"
],
[
"Steven_Wright",
"profession",
"Comedian"
],
[
"Steven_Wright",
"profession",
"Writer-GB"
],
[
"T._S._Eliot",
"nationality",
"England"
],
[
"T._S._Eliot",
"profession",
"Writer-GB"
],
[
"Terry_Jones",
"profession",
"Comedian"
],
[
"Terry_Jones",
"profession",
"Writer-GB"
],
[
"Thomas_Hardy",
"nationality",
"England"
],
[
"Thomas_Hardy",
"profession",
"Writer-GB"
],
[
"Tim_Rice",
"nationality",
"England"
],
[
"Tim_Rice",
"profession",
"Writer-GB"
],
[
"Tina_Fey",
"profession",
"Comedian"
],
[
"Tina_Fey",
"profession",
"Writer-GB"
],
[
"Tracey_Ullman",
"location",
"England"
],
[
"Tracey_Ullman",
"profession",
"Comedian"
],
[
"Vernon_Chatman",
"profession",
"Comedian"
],
[
"Vernon_Chatman",
"profession",
"Writer-GB"
],
[
"Virginia_Woolf",
"nationality",
"England"
],
[
"Virginia_Woolf",
"profession",
"Writer-GB"
],
[
"Warren_Ellis",
"nationality",
"England"
],
[
"Warren_Ellis",
"profession",
"Writer-GB"
],
[
"William_Morris",
"nationality",
"England"
],
[
"William_Morris",
"profession",
"Writer-GB"
],
[
"Woody_Allen",
"profession",
"Comedian"
],
[
"Woody_Allen",
"profession",
"Writer-GB"
],
[
"Wyatt_Cenac",
"profession",
"Comedian"
],
[
"Wyatt_Cenac",
"profession",
"Writer-GB"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3669, Alan_Moore
3821, Aldous_Huxley
5836, Anglicanism
70, Anne_Rice
1342, Anthony_Burgess
4815, Anthony_Horowitz
10425, Arthur_Schopenhauer
5761, Astrid_Lindgren_Memorial_Award
9903, Boeing
3022, Charles_Dickens
12519, Chief_Operating_Officer
3986, Clive_Barker
11949, Cormac_McCarthy
4556, Critic
11377, D._H._Lawrence
4134, Daniel_Handler
7766, David_Hemmings
8637, Don_DeLillo
7463, Doris_Lessing
9479, Edgar_Allan_Poe
8269, Ernest_Hemingway
3521, Ezra_Pound
2074, Fiction
13463, Franz_Kafka
8393, From_Hell
9088, G._K._Chesterton
12368, Gene_Wolfe
5123, George_Bernard_Shaw
13448, George_Orwell
1947, George_R._R._Martin
11101, Gilles_Deleuze
6630, Gore_Vidal
8364, Great_Expectations
8700, Guildford
9864, Gustave_Flaubert
13074, H._G._Wells
11379, H._P._Lovecraft
9515, Harlan_Ellison
4719, Harold_Pinter
1221, Henry_James
3671, Herman_Melville
461, Hunter_S._Thompson
4360, Italo_Calvino
5156, J._D._Salinger
10004, J._M._Coetzee
12842, James_Baldwin
1025, Jason_Flemyng
11833, Jean-Paul_Sartre
9581, John_Irving
1652, John_Keats
6877, John_Steinbeck
13821, John_Updike
13768, Jonathan_Lethem
13505, Joseph_Conrad
179, Joseph_Heller
7002, Joyce_Carol_Oates
9625, Leo_Tolstoy
3546, Lewis_Carroll
8450, Marcel_Proust
10101, Margaret_Atwood
11013, Mark_Twain
4379, Maya_Angelou
7709, Michael_Chabon
5365, Miguel_de_Cervantes
12323, Nathaniel_Hawthorne
4900, National_Book_Award_for_Fiction
1972, Neil_Gaiman
4681, New_York_Mets
113, Nobel_Prize_in_Literature
2335, Norman_Mailer
12725, PEN/Faulkner_Award_for_Fiction
7505, Paul_Auster
1303, Philip_Roth
11987, Pulitzer_Prize_for_Fiction
8877, Ray_Bradbury
2507, Rice_University
4514, Robert_Louis_Stevenson
13262, Rod_Serling
3834, Rudyard_Kipling
5595, Saul_Bellow
13859, Stardust
3345, Steampunk
6829, Stephen_King
4566, Superhero
8475, T._S._Eliot
8079, The_League_of_Extraordinary_Gentlemen
1721, Thomas_Hardy
4926, Thomas_Mann
12895, Thomas_Pynchon
2783, Tom_Wolfe
10573, Toni_Morrison
6939, Truman_Capote
84, Tuberculosis
4882, Ursula_K._Le_Guin
13234, Vladimir_Vladimirovich_Nabokov
5535, Walt_Whitman
9253, Watchmen
9362, William_Faulkner
src, edge_attr, dst
3669, influenced_by, 3986
3669, influenced_by, 9479
3669, influenced_by, 13074
3669, influenced_by, 11379
3669, influenced_by, 12895
3821, influenced_by, 3022
3821, peers, 11377
70, influenced_by, 3022
70, influenced_by, 8269
70, influenced_by, 1221
1342, influenced_by, 11377
1342, influenced_by, 8269
1342, profession, 4556
4815, influenced_by, 3022
4815, influenced_by, 11379
5761, category_of, 5761
3022, influenced_by, 5365
3022, religion, 5836
12519, company, 9903
12519, company, 4681
3986, influenced_by, 9479
3986, influenced_by, 11379
11949, award, 4900
11949, award, 11987
11949, influenced_by, 8269
11949, influenced_by, 9362
11377, influenced_by, 10425
11377, influenced_by, 3671
11377, influenced_by, 13505
11377, influenced_by, 1721
11377, influenced_by, 5535
4134, influenced_by, 9479
4134, influenced_by, 13463
7766, acted_in, 8079
7766, place_of_birth, 8700
8637, award, 4900
8637, award, 12725
8637, award, 11987
8637, influenced_by, 8269
8637, influenced_by, 13463
8637, influenced_by, 1221
8637, influenced_by, 9362
7463, influenced_by, 11377
7463, influenced_by, 11833
9479, influenced_by, 3022
8269, award, 4900
8269, award, 113
8269, influenced_by, 3521
8269, influenced_by, 9088
8269, influenced_by, 1652
8269, influenced_by, 13505
8269, influenced_by, 9625
8269, influenced_by, 11013
8269, influenced_by, 4514
8269, influenced_by, 3834
8269, influenced_by, 9362
3521, influenced_by, 1221
13463, influenced_by, 10425
13463, influenced_by, 3022
13463, influenced_by, 9479
13463, influenced_by, 9088
13463, influenced_by, 9864
13463, influenced_by, 4926
8393, story_by, 3669
9088, influenced_by, 3022
12368, influenced_by, 3022
12368, influenced_by, 11379
12368, influenced_by, 3546
5123, influenced_by, 3022
5123, profession, 4556
13448, influenced_by, 3022
13448, influenced_by, 11377
1947, influenced_by, 3022
1947, influenced_by, 11379
1947, influenced_by, 9362
11101, influenced_by, 3546
11101, influenced_by, 9362
6630, award, 4900
6630, influenced_by, 1221
8364, story_by, 3022
11379, influenced_by, 9479
11379, influenced_by, 13074
11379, influenced_by, 12323
9515, influenced_by, 9479
9515, influenced_by, 13463
4719, influenced_by, 8269
4719, influenced_by, 13463
1221, award, 113
1221, influenced_by, 3022
1221, influenced_by, 9479
1221, influenced_by, 9864
1221, influenced_by, 12323
1221, influenced_by, 3834
3671, influenced_by, 9479
461, influenced_by, 8269
461, influenced_by, 9362
4360, influenced_by, 9479
4360, influenced_by, 8269
4360, influenced_by, 13463
5156, award, 4900
5156, influenced_by, 8269
5156, influenced_by, 13463
10004, influenced_by, 13463
10004, influenced_by, 9362
12842, award, 4900
12842, influenced_by, 1221
1025, acted_in, 8393
1025, acted_in, 8364
1025, acted_in, 13859
1025, acted_in, 8079
11833, influenced_by, 13463
9581, award, 4900
9581, influenced_by, 3022
6877, award, 4900
6877, influenced_by, 9362
13821, award, 4900
13821, award, 12725
13821, award, 11987
13821, influenced_by, 8269
13821, influenced_by, 13463
13821, profession, 4556
13768, influenced_by, 3022
13768, influenced_by, 13463
13768, influenced_by, 11379
13768, influenced_by, 3546
13505, influenced_by, 1221
179, award, 4900
179, influenced_by, 13463
179, influenced_by, 9362
7002, award, 5761
7002, award, 12725
7002, award, 11987
7002, influenced_by, 3022
7002, influenced_by, 11377
7002, influenced_by, 7463
7002, influenced_by, 9479
7002, influenced_by, 8269
7002, influenced_by, 13463
7002, influenced_by, 11379
7002, influenced_by, 1221
7002, influenced_by, 3546
7002, influenced_by, 9362
7002, profession, 4556
9625, influenced_by, 3022
3546, place_of_death, 8700
3546, religion, 5836
8450, influenced_by, 9479
8450, profession, 4556
10101, influenced_by, 3022
10101, influenced_by, 7463
11013, influenced_by, 3022
4379, influenced_by, 3022
4379, influenced_by, 9479
7709, award, 12725
7709, award, 11987
7709, influenced_by, 1221
4900, award_winner, 11949
4900, award_winner, 13821
4900, award_winner, 7002
4900, award_winner, 1303
4900, award_winner, 5595
4900, award_winner, 9362
1972, award, 5761
1972, influenced_by, 3669
1972, influenced_by, 11379
1972, influenced_by, 3546
4681, school, 2507
113, award_winner, 7463
113, award_winner, 8269
113, award_winner, 9362
2335, award, 4900
2335, award, 11987
2335, influenced_by, 8269
2335, influenced_by, 1221
2335, influenced_by, 9362
12725, award_winner, 8637
12725, award_winner, 13821
12725, award_winner, 1303
12725, category_of, 12725
12725, disciplines_or_subjects, 2074
7505, award, 12725
7505, influenced_by, 3022
7505, influenced_by, 9479
7505, influenced_by, 13463
7505, influenced_by, 9362
1303, award, 4900
1303, award, 11987
1303, influenced_by, 8269
1303, influenced_by, 13463
1303, influenced_by, 1221
1303, influenced_by, 9362
11987, award_winner, 8269
11987, award_winner, 6877
11987, award_winner, 13821
11987, award_winner, 7709
11987, award_winner, 2335
11987, award_winner, 5595
11987, award_winner, 10573
11987, award_winner, 9362
11987, disciplines_or_subjects, 2074
8877, influenced_by, 3022
8877, influenced_by, 9479
8877, influenced_by, 11379
2507, campuses, 2507
2507, educational_institution, 2507
2507, student, 7002
4514, influenced_by, 3022
4514, influenced_by, 9479
13262, influenced_by, 9479
13262, influenced_by, 8269
13262, influenced_by, 11379
5595, award, 4900
5595, influenced_by, 13463
13859, genre, 3345
6829, influenced_by, 9479
6829, influenced_by, 11379
6829, influenced_by, 1221
6829, influenced_by, 9362
8475, influenced_by, 3022
8079, genre, 3345
8079, genre, 4566
8079, story_by, 3669
1721, influenced_by, 3022
4926, award, 4900
4926, influenced_by, 9479
12895, award, 4900
2783, award, 4900
2783, influenced_by, 3022
2783, influenced_by, 8269
10573, award, 4900
10573, award, 11987
10573, influenced_by, 7463
10573, influenced_by, 9362
6939, award, 4900
6939, influenced_by, 9479
6939, influenced_by, 1221
6939, influenced_by, 9362
84, people, 11377
84, people, 9479
84, people, 13463
4882, award, 5761
4882, award, 4900
4882, award, 11987
13234, award, 4900
13234, influenced_by, 9479
13234, influenced_by, 13463
5535, influenced_by, 9479
9253, genre, 4566
9253, story_by, 3669
9362, award, 4900
9362, award, 113
9362, influenced_by, 3022
9362, influenced_by, 9479
9362, influenced_by, 9864
9362, influenced_by, 3671
9362, influenced_by, 1652
9362, influenced_by, 13505
9362, influenced_by, 9625
9362, influenced_by, 11013
9362, influenced_by, 5365
9362, influenced_by, 8475
9362, influenced_by, 4926
Question: In what context are Boeing, Joyce_Carol_Oates, and The_League_of_Extraordinary_Gentlemen connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Boeing",
"Joyce_Carol_Oates",
"The_League_of_Extraordinary_Gentlemen"
],
"valid_edges": [
[
"Alan_Moore",
"influenced_by",
"Clive_Barker"
],
[
"Alan_Moore",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Alan_Moore",
"influenced_by",
"H._G._Wells"
],
[
"Alan_Moore",
"influenced_by",
"H._P._Lovecraft"
],
[
"Alan_Moore",
"influenced_by",
"Thomas_Pynchon"
],
[
"Aldous_Huxley",
"influenced_by",
"Charles_Dickens"
],
[
"Aldous_Huxley",
"peers",
"D._H._Lawrence"
],
[
"Anne_Rice",
"influenced_by",
"Charles_Dickens"
],
[
"Anne_Rice",
"influenced_by",
"Ernest_Hemingway"
],
[
"Anne_Rice",
"influenced_by",
"Henry_James"
],
[
"Anthony_Burgess",
"influenced_by",
"D._H._Lawrence"
],
[
"Anthony_Burgess",
"influenced_by",
"Ernest_Hemingway"
],
[
"Anthony_Burgess",
"profession",
"Critic"
],
[
"Anthony_Horowitz",
"influenced_by",
"Charles_Dickens"
],
[
"Anthony_Horowitz",
"influenced_by",
"H._P._Lovecraft"
],
[
"Astrid_Lindgren_Memorial_Award",
"category_of",
"Astrid_Lindgren_Memorial_Award"
],
[
"Charles_Dickens",
"influenced_by",
"Miguel_de_Cervantes"
],
[
"Charles_Dickens",
"religion",
"Anglicanism"
],
[
"Chief_Operating_Officer",
"company",
"Boeing"
],
[
"Chief_Operating_Officer",
"company",
"New_York_Mets"
],
[
"Clive_Barker",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Clive_Barker",
"influenced_by",
"H._P._Lovecraft"
],
[
"Cormac_McCarthy",
"award",
"National_Book_Award_for_Fiction"
],
[
"Cormac_McCarthy",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Cormac_McCarthy",
"influenced_by",
"Ernest_Hemingway"
],
[
"Cormac_McCarthy",
"influenced_by",
"William_Faulkner"
],
[
"D._H._Lawrence",
"influenced_by",
"Arthur_Schopenhauer"
],
[
"D._H._Lawrence",
"influenced_by",
"Herman_Melville"
],
[
"D._H._Lawrence",
"influenced_by",
"Joseph_Conrad"
],
[
"D._H._Lawrence",
"influenced_by",
"Thomas_Hardy"
],
[
"D._H._Lawrence",
"influenced_by",
"Walt_Whitman"
],
[
"Daniel_Handler",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Daniel_Handler",
"influenced_by",
"Franz_Kafka"
],
[
"David_Hemmings",
"acted_in",
"The_League_of_Extraordinary_Gentlemen"
],
[
"David_Hemmings",
"place_of_birth",
"Guildford"
],
[
"Don_DeLillo",
"award",
"National_Book_Award_for_Fiction"
],
[
"Don_DeLillo",
"award",
"PEN/Faulkner_Award_for_Fiction"
],
[
"Don_DeLillo",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Don_DeLillo",
"influenced_by",
"Ernest_Hemingway"
],
[
"Don_DeLillo",
"influenced_by",
"Franz_Kafka"
],
[
"Don_DeLillo",
"influenced_by",
"Henry_James"
],
[
"Don_DeLillo",
"influenced_by",
"William_Faulkner"
],
[
"Doris_Lessing",
"influenced_by",
"D._H._Lawrence"
],
[
"Doris_Lessing",
"influenced_by",
"Jean-Paul_Sartre"
],
[
"Edgar_Allan_Poe",
"influenced_by",
"Charles_Dickens"
],
[
"Ernest_Hemingway",
"award",
"National_Book_Award_for_Fiction"
],
[
"Ernest_Hemingway",
"award",
"Nobel_Prize_in_Literature"
],
[
"Ernest_Hemingway",
"influenced_by",
"Ezra_Pound"
],
[
"Ernest_Hemingway",
"influenced_by",
"G._K._Chesterton"
],
[
"Ernest_Hemingway",
"influenced_by",
"John_Keats"
],
[
"Ernest_Hemingway",
"influenced_by",
"Joseph_Conrad"
],
[
"Ernest_Hemingway",
"influenced_by",
"Leo_Tolstoy"
],
[
"Ernest_Hemingway",
"influenced_by",
"Mark_Twain"
],
[
"Ernest_Hemingway",
"influenced_by",
"Robert_Louis_Stevenson"
],
[
"Ernest_Hemingway",
"influenced_by",
"Rudyard_Kipling"
],
[
"Ernest_Hemingway",
"influenced_by",
"William_Faulkner"
],
[
"Ezra_Pound",
"influenced_by",
"Henry_James"
],
[
"Franz_Kafka",
"influenced_by",
"Arthur_Schopenhauer"
],
[
"Franz_Kafka",
"influenced_by",
"Charles_Dickens"
],
[
"Franz_Kafka",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Franz_Kafka",
"influenced_by",
"G._K._Chesterton"
],
[
"Franz_Kafka",
"influenced_by",
"Gustave_Flaubert"
],
[
"Franz_Kafka",
"influenced_by",
"Thomas_Mann"
],
[
"From_Hell",
"story_by",
"Alan_Moore"
],
[
"G._K._Chesterton",
"influenced_by",
"Charles_Dickens"
],
[
"Gene_Wolfe",
"influenced_by",
"Charles_Dickens"
],
[
"Gene_Wolfe",
"influenced_by",
"H._P._Lovecraft"
],
[
"Gene_Wolfe",
"influenced_by",
"Lewis_Carroll"
],
[
"George_Bernard_Shaw",
"influenced_by",
"Charles_Dickens"
],
[
"George_Bernard_Shaw",
"profession",
"Critic"
],
[
"George_Orwell",
"influenced_by",
"Charles_Dickens"
],
[
"George_Orwell",
"influenced_by",
"D._H._Lawrence"
],
[
"George_R._R._Martin",
"influenced_by",
"Charles_Dickens"
],
[
"George_R._R._Martin",
"influenced_by",
"H._P._Lovecraft"
],
[
"George_R._R._Martin",
"influenced_by",
"William_Faulkner"
],
[
"Gilles_Deleuze",
"influenced_by",
"Lewis_Carroll"
],
[
"Gilles_Deleuze",
"influenced_by",
"William_Faulkner"
],
[
"Gore_Vidal",
"award",
"National_Book_Award_for_Fiction"
],
[
"Gore_Vidal",
"influenced_by",
"Henry_James"
],
[
"Great_Expectations",
"story_by",
"Charles_Dickens"
],
[
"H._P._Lovecraft",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"H._P._Lovecraft",
"influenced_by",
"H._G._Wells"
],
[
"H._P._Lovecraft",
"influenced_by",
"Nathaniel_Hawthorne"
],
[
"Harlan_Ellison",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Harlan_Ellison",
"influenced_by",
"Franz_Kafka"
],
[
"Harold_Pinter",
"influenced_by",
"Ernest_Hemingway"
],
[
"Harold_Pinter",
"influenced_by",
"Franz_Kafka"
],
[
"Henry_James",
"award",
"Nobel_Prize_in_Literature"
],
[
"Henry_James",
"influenced_by",
"Charles_Dickens"
],
[
"Henry_James",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Henry_James",
"influenced_by",
"Gustave_Flaubert"
],
[
"Henry_James",
"influenced_by",
"Nathaniel_Hawthorne"
],
[
"Henry_James",
"influenced_by",
"Rudyard_Kipling"
],
[
"Herman_Melville",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Hunter_S._Thompson",
"influenced_by",
"Ernest_Hemingway"
],
[
"Hunter_S._Thompson",
"influenced_by",
"William_Faulkner"
],
[
"Italo_Calvino",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Italo_Calvino",
"influenced_by",
"Ernest_Hemingway"
],
[
"Italo_Calvino",
"influenced_by",
"Franz_Kafka"
],
[
"J._D._Salinger",
"award",
"National_Book_Award_for_Fiction"
],
[
"J._D._Salinger",
"influenced_by",
"Ernest_Hemingway"
],
[
"J._D._Salinger",
"influenced_by",
"Franz_Kafka"
],
[
"J._M._Coetzee",
"influenced_by",
"Franz_Kafka"
],
[
"J._M._Coetzee",
"influenced_by",
"William_Faulkner"
],
[
"James_Baldwin",
"award",
"National_Book_Award_for_Fiction"
],
[
"James_Baldwin",
"influenced_by",
"Henry_James"
],
[
"Jason_Flemyng",
"acted_in",
"From_Hell"
],
[
"Jason_Flemyng",
"acted_in",
"Great_Expectations"
],
[
"Jason_Flemyng",
"acted_in",
"Stardust"
],
[
"Jason_Flemyng",
"acted_in",
"The_League_of_Extraordinary_Gentlemen"
],
[
"Jean-Paul_Sartre",
"influenced_by",
"Franz_Kafka"
],
[
"John_Irving",
"award",
"National_Book_Award_for_Fiction"
],
[
"John_Irving",
"influenced_by",
"Charles_Dickens"
],
[
"John_Steinbeck",
"award",
"National_Book_Award_for_Fiction"
],
[
"John_Steinbeck",
"influenced_by",
"William_Faulkner"
],
[
"John_Updike",
"award",
"National_Book_Award_for_Fiction"
],
[
"John_Updike",
"award",
"PEN/Faulkner_Award_for_Fiction"
],
[
"John_Updike",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"John_Updike",
"influenced_by",
"Ernest_Hemingway"
],
[
"John_Updike",
"influenced_by",
"Franz_Kafka"
],
[
"John_Updike",
"profession",
"Critic"
],
[
"Jonathan_Lethem",
"influenced_by",
"Charles_Dickens"
],
[
"Jonathan_Lethem",
"influenced_by",
"Franz_Kafka"
],
[
"Jonathan_Lethem",
"influenced_by",
"H._P._Lovecraft"
],
[
"Jonathan_Lethem",
"influenced_by",
"Lewis_Carroll"
],
[
"Joseph_Conrad",
"influenced_by",
"Henry_James"
],
[
"Joseph_Heller",
"award",
"National_Book_Award_for_Fiction"
],
[
"Joseph_Heller",
"influenced_by",
"Franz_Kafka"
],
[
"Joseph_Heller",
"influenced_by",
"William_Faulkner"
],
[
"Joyce_Carol_Oates",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Joyce_Carol_Oates",
"award",
"PEN/Faulkner_Award_for_Fiction"
],
[
"Joyce_Carol_Oates",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Charles_Dickens"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"D._H._Lawrence"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Doris_Lessing"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Ernest_Hemingway"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Franz_Kafka"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"H._P._Lovecraft"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Henry_James"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"Lewis_Carroll"
],
[
"Joyce_Carol_Oates",
"influenced_by",
"William_Faulkner"
],
[
"Joyce_Carol_Oates",
"profession",
"Critic"
],
[
"Leo_Tolstoy",
"influenced_by",
"Charles_Dickens"
],
[
"Lewis_Carroll",
"place_of_death",
"Guildford"
],
[
"Lewis_Carroll",
"religion",
"Anglicanism"
],
[
"Marcel_Proust",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Marcel_Proust",
"profession",
"Critic"
],
[
"Margaret_Atwood",
"influenced_by",
"Charles_Dickens"
],
[
"Margaret_Atwood",
"influenced_by",
"Doris_Lessing"
],
[
"Mark_Twain",
"influenced_by",
"Charles_Dickens"
],
[
"Maya_Angelou",
"influenced_by",
"Charles_Dickens"
],
[
"Maya_Angelou",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Michael_Chabon",
"award",
"PEN/Faulkner_Award_for_Fiction"
],
[
"Michael_Chabon",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Michael_Chabon",
"influenced_by",
"Henry_James"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"Cormac_McCarthy"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"John_Updike"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"Joyce_Carol_Oates"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"Philip_Roth"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"Saul_Bellow"
],
[
"National_Book_Award_for_Fiction",
"award_winner",
"William_Faulkner"
],
[
"Neil_Gaiman",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Neil_Gaiman",
"influenced_by",
"Alan_Moore"
],
[
"Neil_Gaiman",
"influenced_by",
"H._P._Lovecraft"
],
[
"Neil_Gaiman",
"influenced_by",
"Lewis_Carroll"
],
[
"New_York_Mets",
"school",
"Rice_University"
],
[
"Nobel_Prize_in_Literature",
"award_winner",
"Doris_Lessing"
],
[
"Nobel_Prize_in_Literature",
"award_winner",
"Ernest_Hemingway"
],
[
"Nobel_Prize_in_Literature",
"award_winner",
"William_Faulkner"
],
[
"Norman_Mailer",
"award",
"National_Book_Award_for_Fiction"
],
[
"Norman_Mailer",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Norman_Mailer",
"influenced_by",
"Ernest_Hemingway"
],
[
"Norman_Mailer",
"influenced_by",
"Henry_James"
],
[
"Norman_Mailer",
"influenced_by",
"William_Faulkner"
],
[
"PEN/Faulkner_Award_for_Fiction",
"award_winner",
"Don_DeLillo"
],
[
"PEN/Faulkner_Award_for_Fiction",
"award_winner",
"John_Updike"
],
[
"PEN/Faulkner_Award_for_Fiction",
"award_winner",
"Philip_Roth"
],
[
"PEN/Faulkner_Award_for_Fiction",
"category_of",
"PEN/Faulkner_Award_for_Fiction"
],
[
"PEN/Faulkner_Award_for_Fiction",
"disciplines_or_subjects",
"Fiction"
],
[
"Paul_Auster",
"award",
"PEN/Faulkner_Award_for_Fiction"
],
[
"Paul_Auster",
"influenced_by",
"Charles_Dickens"
],
[
"Paul_Auster",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Paul_Auster",
"influenced_by",
"Franz_Kafka"
],
[
"Paul_Auster",
"influenced_by",
"William_Faulkner"
],
[
"Philip_Roth",
"award",
"National_Book_Award_for_Fiction"
],
[
"Philip_Roth",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Philip_Roth",
"influenced_by",
"Ernest_Hemingway"
],
[
"Philip_Roth",
"influenced_by",
"Franz_Kafka"
],
[
"Philip_Roth",
"influenced_by",
"Henry_James"
],
[
"Philip_Roth",
"influenced_by",
"William_Faulkner"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"Ernest_Hemingway"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"John_Steinbeck"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"John_Updike"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"Michael_Chabon"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"Norman_Mailer"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"Saul_Bellow"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"Toni_Morrison"
],
[
"Pulitzer_Prize_for_Fiction",
"award_winner",
"William_Faulkner"
],
[
"Pulitzer_Prize_for_Fiction",
"disciplines_or_subjects",
"Fiction"
],
[
"Ray_Bradbury",
"influenced_by",
"Charles_Dickens"
],
[
"Ray_Bradbury",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Ray_Bradbury",
"influenced_by",
"H._P._Lovecraft"
],
[
"Rice_University",
"campuses",
"Rice_University"
],
[
"Rice_University",
"educational_institution",
"Rice_University"
],
[
"Rice_University",
"student",
"Joyce_Carol_Oates"
],
[
"Robert_Louis_Stevenson",
"influenced_by",
"Charles_Dickens"
],
[
"Robert_Louis_Stevenson",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Rod_Serling",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Rod_Serling",
"influenced_by",
"Ernest_Hemingway"
],
[
"Rod_Serling",
"influenced_by",
"H._P._Lovecraft"
],
[
"Saul_Bellow",
"award",
"National_Book_Award_for_Fiction"
],
[
"Saul_Bellow",
"influenced_by",
"Franz_Kafka"
],
[
"Stardust",
"genre",
"Steampunk"
],
[
"Stephen_King",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Stephen_King",
"influenced_by",
"H._P._Lovecraft"
],
[
"Stephen_King",
"influenced_by",
"Henry_James"
],
[
"Stephen_King",
"influenced_by",
"William_Faulkner"
],
[
"T._S._Eliot",
"influenced_by",
"Charles_Dickens"
],
[
"The_League_of_Extraordinary_Gentlemen",
"genre",
"Steampunk"
],
[
"The_League_of_Extraordinary_Gentlemen",
"genre",
"Superhero"
],
[
"The_League_of_Extraordinary_Gentlemen",
"story_by",
"Alan_Moore"
],
[
"Thomas_Hardy",
"influenced_by",
"Charles_Dickens"
],
[
"Thomas_Mann",
"award",
"National_Book_Award_for_Fiction"
],
[
"Thomas_Mann",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Thomas_Pynchon",
"award",
"National_Book_Award_for_Fiction"
],
[
"Tom_Wolfe",
"award",
"National_Book_Award_for_Fiction"
],
[
"Tom_Wolfe",
"influenced_by",
"Charles_Dickens"
],
[
"Tom_Wolfe",
"influenced_by",
"Ernest_Hemingway"
],
[
"Toni_Morrison",
"award",
"National_Book_Award_for_Fiction"
],
[
"Toni_Morrison",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Toni_Morrison",
"influenced_by",
"Doris_Lessing"
],
[
"Toni_Morrison",
"influenced_by",
"William_Faulkner"
],
[
"Truman_Capote",
"award",
"National_Book_Award_for_Fiction"
],
[
"Truman_Capote",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Truman_Capote",
"influenced_by",
"Henry_James"
],
[
"Truman_Capote",
"influenced_by",
"William_Faulkner"
],
[
"Tuberculosis",
"people",
"D._H._Lawrence"
],
[
"Tuberculosis",
"people",
"Edgar_Allan_Poe"
],
[
"Tuberculosis",
"people",
"Franz_Kafka"
],
[
"Ursula_K._Le_Guin",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Ursula_K._Le_Guin",
"award",
"National_Book_Award_for_Fiction"
],
[
"Ursula_K._Le_Guin",
"award",
"Pulitzer_Prize_for_Fiction"
],
[
"Vladimir_Vladimirovich_Nabokov",
"award",
"National_Book_Award_for_Fiction"
],
[
"Vladimir_Vladimirovich_Nabokov",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Vladimir_Vladimirovich_Nabokov",
"influenced_by",
"Franz_Kafka"
],
[
"Walt_Whitman",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Watchmen",
"genre",
"Superhero"
],
[
"Watchmen",
"story_by",
"Alan_Moore"
],
[
"William_Faulkner",
"award",
"National_Book_Award_for_Fiction"
],
[
"William_Faulkner",
"award",
"Nobel_Prize_in_Literature"
],
[
"William_Faulkner",
"influenced_by",
"Charles_Dickens"
],
[
"William_Faulkner",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"William_Faulkner",
"influenced_by",
"Gustave_Flaubert"
],
[
"William_Faulkner",
"influenced_by",
"Herman_Melville"
],
[
"William_Faulkner",
"influenced_by",
"John_Keats"
],
[
"William_Faulkner",
"influenced_by",
"Joseph_Conrad"
],
[
"William_Faulkner",
"influenced_by",
"Leo_Tolstoy"
],
[
"William_Faulkner",
"influenced_by",
"Mark_Twain"
],
[
"William_Faulkner",
"influenced_by",
"Miguel_de_Cervantes"
],
[
"William_Faulkner",
"influenced_by",
"T._S._Eliot"
],
[
"William_Faulkner",
"influenced_by",
"Thomas_Mann"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7898, 1900_Summer_Olympics
10047, 1904_Summer_Olympics
3309, 1908_Summer_Olympics
7962, 1912_Summer_Olympics
9784, 1920_Summer_Olympics
4416, 1924_Summer_Olympics
7085, 1928_Summer_Olympics
4954, 1932_Summer_Olympics
11367, 1936_Summer_Olympics
11590, 1948_Summer_Olympics
12466, 1956_Summer_Olympics
5561, 1960_Summer_Olympics
8933, 1964_Summer_Olympics
2827, 1968_Summer_Olympics
7928, 1972_Summer_Olympics
4549, 1976_Summer_Olympics
680, 1980_Summer_Olympics
6985, 1984_Summer_Olympics
8737, 36th_Annual_Grammy_Awards
2407, Adele
9565, Adult_contemporary_music
3335, Alan_Cumming
5126, Alanis_Morissette
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3563, Albanian_language
3644, Algeria
7308, Amanda_Lear
9657, Amy_Grant
6685, Annie_Lennox
8817, Armenia
9374, Arthur_Christmas
5996, Azerbaijan
5083, Belarus
4251, Bette_Midler
6386, Billy_Boyd
12511, Bosnia_and_Herzegovina
873, Britney_Spears
4784, Cambodia
8211, Cameroon
5695, Canoe_Sprint
11657, Carly_Simon
3268, Carole_King
13137, Celine_Dion
8068, Central_African_Republic
2037, Cher
10243, Chris_Brown
10334, Christina_Aguilera
13151, Council_of_Europe
10349, Cuba
2914, Cyndi_Lauper
12402, Cyprus
6955, CΓ΄te_dβIvoire
2998, Dance-pop
8789, David_Tennant
4052, Debbie_Gibson
2531, Destiny's_Child
9812, Donna_Summer
4148, Ecuador
9838, Eurasia
2596, Eva_Longoria
5013, Federated_States_of_Micronesia
3485, Fergie
329, For_Your_Eyes_Only
13477, Freestyle_wrestling
6518, Gloria_Estefan
9447, Grace_Jones
5678, Grammy_Award_for_Best_Female_Pop_Vocal_Performance
5293, Greco-Roman_wrestling
6102, Greek_Language
824, Guinea-Bissau
8583, Gwen_Stefani
6627, Handball
11602, Harry_Gregson-Williams
2183, Iran
6908, Iraq
6933, Irene_Cara
8906, James_McAvoy
10980, Janet_Jackson
12558, Jessica_Simpson
7000, Jewel
1652, John_Keats
591, KT_Tunstall
3910, Katy_Perry
9661, Kelly_Clarkson
8790, Kylie_Minogue
9130, Kyrgyzstan
10345, Las_Vegas
4755, Latvia
10952, Lebanon
3174, Linda_Ronstadt
10507, Luis_Miguel
4659, Luxembourg
8757, Malta
10073, Mandy_Moore
3955, Marc_Anthony
11282, Mariah_Carey
5531, Miley_Cyrus
13570, Moldova
5608, Monaco
7491, Mongolia
12361, Montenegro
3832, Myanmar
2168, Namibia
11354, Nelly_Furtado
8020, Nicaragua
2322, Nigeria
12824, Norah_Jones
8195, North_Korea
10643, P!nk
9949, Palau
1498, Paraguay
10501, Patrick_Doyle
10818, Paula_Abdul
6883, Phyllis_Logan
13991, Puerto_Rico
4869, Republic
11920, Republic_of_Macedonia
6782, Robbie_Williams
2515, Robert_Carlyle
4735, Ryan_Tedder
9777, Sailing
5929, Scotland
1802, Senegal
4310, Seychelles
858, Shakira
12987, Sheena_Easton
4989, Sierra_Leone
2413, Sri_Lanka
11060, Substance-related_disorder
4956, Taylor_Swift
10675, The_Lorax
3455, The_Royal_Conservatoire_of_Scotland
12379, Timor-Leste
89, Tina_Turner
3276, Toni_Braxton
84, Tuberculosis
3760, Tunisia
6571, Turkmenistan
2889, Ulysses'_Gaze
2445, United_Arab_Emirates
12403, Urban_contemporary
2869, Uzbekistan
8753, Vanessa_L._Williams
4001, Video_game_music
14230, Vietnam
9803, Water_polo
11981, Whitney_Houston
src, edge_attr, dst
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7928, sports, 5293
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7928, sports, 9777
7928, sports, 9803
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4549, sports, 5293
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680, sports, 5293
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680, sports, 9803
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3268, award, 5678
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2914, award, 5678
12402, organization, 13151
6955, form_of_government, 4869
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2998, artists, 7308
2998, artists, 873
2998, artists, 13137
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2998, artists, 10243
2998, artists, 10334
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2998, artists, 4052
2998, artists, 2531
2998, artists, 9812
2998, artists, 3485
2998, artists, 6518
2998, artists, 9447
2998, artists, 8583
2998, artists, 6933
2998, artists, 10980
2998, artists, 12558
2998, artists, 3910
2998, artists, 9661
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2998, artists, 10073
2998, artists, 3955
2998, artists, 5531
2998, artists, 11354
2998, artists, 10643
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2998, artists, 6782
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2998, artists, 858
2998, artists, 12987
2998, artists, 4956
2998, artists, 89
2998, artists, 3276
2998, artists, 11981
8789, nationality, 5929
9812, award, 5678
9838, contains, 7330
9838, contains, 8817
9838, contains, 5996
9838, contains, 5083
9838, contains, 12511
9838, contains, 4784
9838, contains, 12402
9838, contains, 2183
9838, contains, 6908
9838, contains, 9130
9838, contains, 4755
9838, contains, 10952
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9838, contains, 8757
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9838, contains, 7491
9838, contains, 12361
9838, contains, 3832
9838, contains, 8195
9838, contains, 11920
9838, contains, 2413
9838, contains, 12379
9838, contains, 6571
9838, contains, 2445
9838, contains, 2869
9838, contains, 14230
2596, acted_in, 9374
2596, location_of_ceremony, 10345
5013, form_of_government, 4869
3485, award, 5678
329, language, 6102
13477, country, 7330
13477, country, 3644
13477, country, 8817
13477, country, 5996
13477, country, 5083
13477, country, 4784
13477, country, 8211
13477, country, 8068
13477, country, 10349
13477, country, 6955
13477, country, 4148
13477, country, 824
13477, country, 2183
13477, country, 9130
13477, country, 4755
13477, country, 13570
13477, country, 7491
13477, country, 12361
13477, country, 2168
13477, country, 2322
13477, country, 8195
13477, country, 9949
13477, country, 13991
13477, country, 1802
13477, country, 4989
13477, country, 3760
13477, country, 6571
13477, country, 2445
13477, country, 2869
13477, country, 14230
13477, olympics, 10047
13477, olympics, 9784
13477, olympics, 11590
6518, award, 5678
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5678, award_winner, 6685
5678, award_winner, 4251
5678, award_winner, 13137
5678, award_winner, 10334
5678, award_winner, 6933
5678, award_winner, 9661
5678, award_winner, 3174
5678, award_winner, 11354
5678, award_winner, 12824
5678, award_winner, 89
5678, award_winner, 3276
5678, award_winner, 11981
5678, ceremony, 8737
5293, country, 7330
5293, country, 3644
5293, country, 8817
5293, country, 5996
5293, country, 5083
5293, country, 10349
5293, country, 4148
5293, country, 5013
5293, country, 2183
5293, country, 6908
5293, country, 9130
5293, country, 12361
5293, country, 2168
5293, country, 8020
5293, country, 2322
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5293, country, 9949
5293, country, 4989
5293, country, 3760
5293, country, 2869
5293, olympics, 9784
5293, olympics, 7928
6102, countries_spoken_in, 7330
824, form_of_government, 4869
8583, award, 5678
6627, country, 12361
6627, country, 3760
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6627, olympics, 4549
6627, olympics, 680
6627, olympics, 6985
6908, form_of_government, 4869
6933, award, 5678
8906, acted_in, 9374
10980, award, 5678
7000, award, 5678
1652, location, 5929
591, award, 5678
591, nationality, 5929
3910, award, 5678
9661, award, 5678
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10345, place, 10345
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10345, vacationer, 10073
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4755, organization, 13151
10952, form_of_government, 4869
3174, award, 5678
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10507, award_winner, 12987
10507, celebrity, 11282
10507, nationality, 13991
10507, participant, 11282
4659, organizations_founded, 13151
8757, organization, 13151
3955, location_of_ceremony, 10345
11282, award, 5678
11282, celebrity, 10507
11282, participant, 10507
13570, organization, 13151
5608, organization, 13151
12361, adjoins, 7330
12361, adjoins, 12511
12361, form_of_government, 4869
12361, organization, 13151
3832, form_of_government, 4869
2168, form_of_government, 4869
8020, form_of_government, 4869
12824, award, 5678
10643, award, 5678
9949, form_of_government, 4869
1498, form_of_government, 4869
10501, nationality, 5929
10818, award, 5678
6883, nationality, 5929
13991, form_of_government, 4869
11920, adjoins, 7330
11920, organization, 13151
2515, nationality, 5929
9777, country, 5083
9777, country, 12402
9777, country, 2183
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9777, country, 5608
9777, country, 12361
9777, country, 4310
9777, country, 3760
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9777, olympics, 5561
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4310, form_of_government, 4869
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12987, location_of_ceremony, 5929
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2413, form_of_government, 4869
4956, acted_in, 10675
4956, award, 5678
10675, film_release_region, 10952
10675, film_release_region, 12361
10675, film_release_region, 1498
10675, film_release_region, 2445
10675, film_release_region, 14230
3455, student, 3335
3455, student, 6386
3455, student, 8789
3455, student, 8906
3455, student, 10501
3455, student, 6883
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3455, student, 12987
12379, form_of_government, 4869
89, award, 5678
3276, award, 5678
84, people, 1652
84, risk_factors, 11060
3760, form_of_government, 4869
6571, form_of_government, 4869
2889, film_country, 7330
2889, film_country, 12511
12403, artists, 873
12403, artists, 10243
12403, artists, 2531
12403, artists, 9447
12403, artists, 858
12403, artists, 12987
2869, form_of_government, 4869
8753, award, 5678
4001, artists, 11602
4001, artists, 12987
9803, country, 12361
9803, olympics, 10047
9803, olympics, 11590
9803, olympics, 12466
9803, olympics, 5561
9803, olympics, 8933
9803, olympics, 2827
Question: For what reason are Montenegro, Sheena_Easton, and Substance-related_disorder associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Montenegro",
"Sheena_Easton",
"Substance-related_disorder"
],
"valid_edges": [
[
"1900_Summer_Olympics",
"sports",
"Sailing"
],
[
"1900_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1904_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1908_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1908_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1908_Summer_Olympics",
"sports",
"Sailing"
],
[
"1908_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1912_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1912_Summer_Olympics",
"sports",
"Sailing"
],
[
"1912_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1920_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1920_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1920_Summer_Olympics",
"sports",
"Sailing"
],
[
"1920_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1924_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1924_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1924_Summer_Olympics",
"sports",
"Sailing"
],
[
"1924_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1928_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1928_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1928_Summer_Olympics",
"sports",
"Sailing"
],
[
"1928_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1932_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1932_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1932_Summer_Olympics",
"sports",
"Sailing"
],
[
"1932_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1936_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1936_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1936_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1936_Summer_Olympics",
"sports",
"Handball"
],
[
"1936_Summer_Olympics",
"sports",
"Sailing"
],
[
"1936_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1948_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1948_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1948_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1948_Summer_Olympics",
"sports",
"Sailing"
],
[
"1948_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1956_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1956_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1956_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1956_Summer_Olympics",
"sports",
"Sailing"
],
[
"1956_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1960_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1960_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1960_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1960_Summer_Olympics",
"sports",
"Sailing"
],
[
"1960_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1964_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1964_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1964_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1964_Summer_Olympics",
"sports",
"Sailing"
],
[
"1964_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1968_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1968_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1968_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1968_Summer_Olympics",
"sports",
"Sailing"
],
[
"1968_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1972_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1972_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1972_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1972_Summer_Olympics",
"sports",
"Handball"
],
[
"1972_Summer_Olympics",
"sports",
"Sailing"
],
[
"1972_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1976_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1976_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1976_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1976_Summer_Olympics",
"sports",
"Handball"
],
[
"1976_Summer_Olympics",
"sports",
"Sailing"
],
[
"1976_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1980_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1980_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1980_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1980_Summer_Olympics",
"sports",
"Handball"
],
[
"1980_Summer_Olympics",
"sports",
"Sailing"
],
[
"1980_Summer_Olympics",
"sports",
"Water_polo"
],
[
"1984_Summer_Olympics",
"sports",
"Canoe_Sprint"
],
[
"1984_Summer_Olympics",
"sports",
"Freestyle_wrestling"
],
[
"1984_Summer_Olympics",
"sports",
"Greco-Roman_wrestling"
],
[
"1984_Summer_Olympics",
"sports",
"Handball"
],
[
"1984_Summer_Olympics",
"sports",
"Sailing"
],
[
"1984_Summer_Olympics",
"sports",
"Water_polo"
],
[
"36th_Annual_Grammy_Awards",
"award_winner",
"Luis_Miguel"
],
[
"Adele",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Adult_contemporary_music",
"artists",
"Adele"
],
[
"Adult_contemporary_music",
"artists",
"Amy_Grant"
],
[
"Adult_contemporary_music",
"artists",
"Bette_Midler"
],
[
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[
"Montenegro",
"form_of_government",
"Republic"
],
[
"Montenegro",
"organization",
"Council_of_Europe"
],
[
"Myanmar",
"form_of_government",
"Republic"
],
[
"Namibia",
"form_of_government",
"Republic"
],
[
"Nicaragua",
"form_of_government",
"Republic"
],
[
"Norah_Jones",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"P!nk",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Palau",
"form_of_government",
"Republic"
],
[
"Paraguay",
"form_of_government",
"Republic"
],
[
"Patrick_Doyle",
"nationality",
"Scotland"
],
[
"Paula_Abdul",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Phyllis_Logan",
"nationality",
"Scotland"
],
[
"Puerto_Rico",
"form_of_government",
"Republic"
],
[
"Republic_of_Macedonia",
"adjoins",
"Albania"
],
[
"Republic_of_Macedonia",
"organization",
"Council_of_Europe"
],
[
"Robert_Carlyle",
"nationality",
"Scotland"
],
[
"Sailing",
"country",
"Belarus"
],
[
"Sailing",
"country",
"Cyprus"
],
[
"Sailing",
"country",
"Iran"
],
[
"Sailing",
"country",
"Kyrgyzstan"
],
[
"Sailing",
"country",
"Moldova"
],
[
"Sailing",
"country",
"Monaco"
],
[
"Sailing",
"country",
"Montenegro"
],
[
"Sailing",
"country",
"Seychelles"
],
[
"Sailing",
"country",
"Tunisia"
],
[
"Sailing",
"olympics",
"1920_Summer_Olympics"
],
[
"Sailing",
"olympics",
"1936_Summer_Olympics"
],
[
"Sailing",
"olympics",
"1960_Summer_Olympics"
],
[
"Scotland",
"olympics",
"1928_Summer_Olympics"
],
[
"Senegal",
"form_of_government",
"Republic"
],
[
"Seychelles",
"form_of_government",
"Republic"
],
[
"Sheena_Easton",
"acted_in",
"For_Your_Eyes_Only"
],
[
"Sheena_Easton",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Sheena_Easton",
"award_nominee",
"Luis_Miguel"
],
[
"Sheena_Easton",
"location_of_ceremony",
"Las_Vegas"
],
[
"Sheena_Easton",
"location_of_ceremony",
"Scotland"
],
[
"Sierra_Leone",
"form_of_government",
"Republic"
],
[
"Sri_Lanka",
"form_of_government",
"Republic"
],
[
"Taylor_Swift",
"acted_in",
"The_Lorax"
],
[
"Taylor_Swift",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"The_Lorax",
"film_release_region",
"Lebanon"
],
[
"The_Lorax",
"film_release_region",
"Montenegro"
],
[
"The_Lorax",
"film_release_region",
"Paraguay"
],
[
"The_Lorax",
"film_release_region",
"United_Arab_Emirates"
],
[
"The_Lorax",
"film_release_region",
"Vietnam"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Alan_Cumming"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Billy_Boyd"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"David_Tennant"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"James_McAvoy"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Patrick_Doyle"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Phyllis_Logan"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Robert_Carlyle"
],
[
"The_Royal_Conservatoire_of_Scotland",
"student",
"Sheena_Easton"
],
[
"Timor-Leste",
"form_of_government",
"Republic"
],
[
"Tina_Turner",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Toni_Braxton",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Tuberculosis",
"people",
"John_Keats"
],
[
"Tuberculosis",
"risk_factors",
"Substance-related_disorder"
],
[
"Tunisia",
"form_of_government",
"Republic"
],
[
"Turkmenistan",
"form_of_government",
"Republic"
],
[
"Ulysses'_Gaze",
"film_country",
"Albania"
],
[
"Ulysses'_Gaze",
"film_country",
"Bosnia_and_Herzegovina"
],
[
"Urban_contemporary",
"artists",
"Britney_Spears"
],
[
"Urban_contemporary",
"artists",
"Chris_Brown"
],
[
"Urban_contemporary",
"artists",
"Destiny's_Child"
],
[
"Urban_contemporary",
"artists",
"Grace_Jones"
],
[
"Urban_contemporary",
"artists",
"Shakira"
],
[
"Urban_contemporary",
"artists",
"Sheena_Easton"
],
[
"Uzbekistan",
"form_of_government",
"Republic"
],
[
"Vanessa_L._Williams",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Video_game_music",
"artists",
"Harry_Gregson-Williams"
],
[
"Video_game_music",
"artists",
"Sheena_Easton"
],
[
"Water_polo",
"country",
"Montenegro"
],
[
"Water_polo",
"olympics",
"1904_Summer_Olympics"
],
[
"Water_polo",
"olympics",
"1948_Summer_Olympics"
],
[
"Water_polo",
"olympics",
"1956_Summer_Olympics"
],
[
"Water_polo",
"olympics",
"1960_Summer_Olympics"
],
[
"Water_polo",
"olympics",
"1964_Summer_Olympics"
],
[
"Water_polo",
"olympics",
"1968_Summer_Olympics"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12742, Appleton
5439, Ateneo_de_Manila_University
13397, Belmont_University
4393, Beloit_College
7767, Blue
2849, Bob_Jones_University
1255, Carleton_College
12944, Central_Time_Zone
3424, Columbia_Law_School
3941, Connecticut_College
8527, Contiguous_United_States
12537, Dane_County
7229, Drake_University
12952, Drexel_University
10195, Eau_Claire
1831, Empoli_F.C.
9198, Fairleigh_Dickinson_University
6964, Fisk_University
10632, Fond_du_Lac_County
13725, Franklin_&_Marshall_College
9680, Gettysburg_College
692, Gonzaga_University
2755, Green_Bay
4543, Hamilton_College
10869, Hampton_University
12610, Illinois
2813, Iowa
133, Ithaca_College
4383, Kenosha
4198, La_Crosse
4491, La_Crosse_County
5821, Macalester_College
13865, Madison
3626, Marquette_University
12675, Michigan
29, Milwaukee
5001, Milwaukee_County
5626, Minnesota
12095, Mississippi_River
13472, Outagamie_County
4341, Pepperdine_University
5858, Pomona_College
8941, Private_school
6069, Racine
6874, Saint_Mary's_College_of_California
943, Sauk_County
165, Smith_College
9627, Stetson_University
7039, Suffolk_University_Law_School
6875, Tufts_University
1004, University_of_Delaware
8689, University_of_Notre_Dame
10470, University_of_Richmond
9275, Villanova_University
2370, Waukesha
8639, Waukesha_County
4564, Wellesley_College
7995, Wheaton_College
3151, Wisconsin
4018, Wood_County
5501, Yeshiva_University
src, edge_attr, dst
12742, administrative_division, 13472
12742, place, 12742
12742, time_zones, 12944
5439, colors, 7767
5439, school_type, 8941
13397, colors, 7767
13397, school_type, 8941
4393, colors, 7767
4393, school_type, 8941
4393, state_province_region, 3151
4393, time_zones, 12944
2849, colors, 7767
2849, school_type, 8941
1255, colors, 7767
1255, school_type, 8941
3424, campuses, 3424
3424, educational_institution, 3424
3424, school_type, 8941
3941, colors, 7767
3941, school_type, 8941
8527, contains, 3151
8527, time_zones, 12944
12537, time_zones, 12944
7229, colors, 7767
7229, school_type, 8941
12952, colors, 7767
12952, school_type, 8941
10195, time_zones, 12944
1831, colors, 7767
9198, colors, 7767
9198, school_type, 8941
6964, colors, 7767
6964, school_type, 8941
10632, time_zones, 12944
13725, colors, 7767
13725, school_type, 8941
9680, colors, 7767
9680, school_type, 8941
692, colors, 7767
692, school_type, 8941
2755, time_zones, 12944
4543, colors, 7767
4543, school_type, 8941
10869, colors, 7767
10869, school_type, 8941
12610, adjoins, 3151
12610, time_zones, 12944
2813, adjoins, 3151
2813, time_zones, 12944
133, colors, 7767
133, school_type, 8941
4383, time_zones, 12944
4198, time_zones, 12944
4491, time_zones, 12944
5821, colors, 7767
5821, school_type, 8941
13865, administrative_division, 3151
13865, state, 3151
13865, time_zones, 12944
3626, school_type, 8941
3626, state_province_region, 3151
12675, adjoins, 3151
12675, time_zones, 12944
29, state, 3151
29, time_zones, 12944
5001, time_zones, 12944
5626, adjoins, 3151
5626, time_zones, 12944
12095, time_zones, 12944
13472, contains, 12742
13472, county_seat, 12742
13472, time_zones, 12944
4341, colors, 7767
4341, school_type, 8941
5858, colors, 7767
5858, school_type, 8941
6069, time_zones, 12944
6874, colors, 7767
6874, school_type, 8941
943, time_zones, 12944
165, colors, 7767
165, school_type, 8941
9627, colors, 7767
9627, school_type, 8941
7039, colors, 7767
7039, school_type, 8941
6875, colors, 7767
6875, school_type, 8941
1004, colors, 7767
1004, school_type, 8941
8689, colors, 7767
8689, school_type, 8941
10470, colors, 7767
10470, school_type, 8941
9275, colors, 7767
9275, school_type, 8941
2370, time_zones, 12944
8639, time_zones, 12944
4564, colors, 7767
4564, school_type, 8941
7995, colors, 7767
7995, school_type, 8941
3151, adjoins, 12610
3151, adjoins, 5626
3151, capital, 13865
3151, contains, 12742
3151, contains, 4393
3151, contains, 12537
3151, contains, 10195
3151, contains, 10632
3151, contains, 2755
3151, contains, 4383
3151, contains, 4198
3151, contains, 4491
3151, contains, 13865
3151, contains, 3626
3151, contains, 29
3151, contains, 5001
3151, contains, 13472
3151, contains, 6069
3151, contains, 943
3151, contains, 2370
3151, contains, 8639
3151, contains, 4018
3151, partially_contains, 12095
3151, time_zones, 12944
4018, time_zones, 12944
5501, colors, 7767
5501, school_type, 8941
Question: In what context are Appleton, Columbia_Law_School, and Empoli_F.C. connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Appleton",
"Columbia_Law_School",
"Empoli_F.C."
],
"valid_edges": [
[
"Appleton",
"administrative_division",
"Outagamie_County"
],
[
"Appleton",
"place",
"Appleton"
],
[
"Appleton",
"time_zones",
"Central_Time_Zone"
],
[
"Ateneo_de_Manila_University",
"colors",
"Blue"
],
[
"Ateneo_de_Manila_University",
"school_type",
"Private_school"
],
[
"Belmont_University",
"colors",
"Blue"
],
[
"Belmont_University",
"school_type",
"Private_school"
],
[
"Beloit_College",
"colors",
"Blue"
],
[
"Beloit_College",
"school_type",
"Private_school"
],
[
"Beloit_College",
"state_province_region",
"Wisconsin"
],
[
"Beloit_College",
"time_zones",
"Central_Time_Zone"
],
[
"Bob_Jones_University",
"colors",
"Blue"
],
[
"Bob_Jones_University",
"school_type",
"Private_school"
],
[
"Carleton_College",
"colors",
"Blue"
],
[
"Carleton_College",
"school_type",
"Private_school"
],
[
"Columbia_Law_School",
"campuses",
"Columbia_Law_School"
],
[
"Columbia_Law_School",
"educational_institution",
"Columbia_Law_School"
],
[
"Columbia_Law_School",
"school_type",
"Private_school"
],
[
"Connecticut_College",
"colors",
"Blue"
],
[
"Connecticut_College",
"school_type",
"Private_school"
],
[
"Contiguous_United_States",
"contains",
"Wisconsin"
],
[
"Contiguous_United_States",
"time_zones",
"Central_Time_Zone"
],
[
"Dane_County",
"time_zones",
"Central_Time_Zone"
],
[
"Drake_University",
"colors",
"Blue"
],
[
"Drake_University",
"school_type",
"Private_school"
],
[
"Drexel_University",
"colors",
"Blue"
],
[
"Drexel_University",
"school_type",
"Private_school"
],
[
"Eau_Claire",
"time_zones",
"Central_Time_Zone"
],
[
"Empoli_F.C.",
"colors",
"Blue"
],
[
"Fairleigh_Dickinson_University",
"colors",
"Blue"
],
[
"Fairleigh_Dickinson_University",
"school_type",
"Private_school"
],
[
"Fisk_University",
"colors",
"Blue"
],
[
"Fisk_University",
"school_type",
"Private_school"
],
[
"Fond_du_Lac_County",
"time_zones",
"Central_Time_Zone"
],
[
"Franklin_&_Marshall_College",
"colors",
"Blue"
],
[
"Franklin_&_Marshall_College",
"school_type",
"Private_school"
],
[
"Gettysburg_College",
"colors",
"Blue"
],
[
"Gettysburg_College",
"school_type",
"Private_school"
],
[
"Gonzaga_University",
"colors",
"Blue"
],
[
"Gonzaga_University",
"school_type",
"Private_school"
],
[
"Green_Bay",
"time_zones",
"Central_Time_Zone"
],
[
"Hamilton_College",
"colors",
"Blue"
],
[
"Hamilton_College",
"school_type",
"Private_school"
],
[
"Hampton_University",
"colors",
"Blue"
],
[
"Hampton_University",
"school_type",
"Private_school"
],
[
"Illinois",
"adjoins",
"Wisconsin"
],
[
"Illinois",
"time_zones",
"Central_Time_Zone"
],
[
"Iowa",
"adjoins",
"Wisconsin"
],
[
"Iowa",
"time_zones",
"Central_Time_Zone"
],
[
"Ithaca_College",
"colors",
"Blue"
],
[
"Ithaca_College",
"school_type",
"Private_school"
],
[
"Kenosha",
"time_zones",
"Central_Time_Zone"
],
[
"La_Crosse",
"time_zones",
"Central_Time_Zone"
],
[
"La_Crosse_County",
"time_zones",
"Central_Time_Zone"
],
[
"Macalester_College",
"colors",
"Blue"
],
[
"Macalester_College",
"school_type",
"Private_school"
],
[
"Madison",
"administrative_division",
"Wisconsin"
],
[
"Madison",
"state",
"Wisconsin"
],
[
"Madison",
"time_zones",
"Central_Time_Zone"
],
[
"Marquette_University",
"school_type",
"Private_school"
],
[
"Marquette_University",
"state_province_region",
"Wisconsin"
],
[
"Michigan",
"adjoins",
"Wisconsin"
],
[
"Michigan",
"time_zones",
"Central_Time_Zone"
],
[
"Milwaukee",
"state",
"Wisconsin"
],
[
"Milwaukee",
"time_zones",
"Central_Time_Zone"
],
[
"Milwaukee_County",
"time_zones",
"Central_Time_Zone"
],
[
"Minnesota",
"adjoins",
"Wisconsin"
],
[
"Minnesota",
"time_zones",
"Central_Time_Zone"
],
[
"Mississippi_River",
"time_zones",
"Central_Time_Zone"
],
[
"Outagamie_County",
"contains",
"Appleton"
],
[
"Outagamie_County",
"county_seat",
"Appleton"
],
[
"Outagamie_County",
"time_zones",
"Central_Time_Zone"
],
[
"Pepperdine_University",
"colors",
"Blue"
],
[
"Pepperdine_University",
"school_type",
"Private_school"
],
[
"Pomona_College",
"colors",
"Blue"
],
[
"Pomona_College",
"school_type",
"Private_school"
],
[
"Racine",
"time_zones",
"Central_Time_Zone"
],
[
"Saint_Mary's_College_of_California",
"colors",
"Blue"
],
[
"Saint_Mary's_College_of_California",
"school_type",
"Private_school"
],
[
"Sauk_County",
"time_zones",
"Central_Time_Zone"
],
[
"Smith_College",
"colors",
"Blue"
],
[
"Smith_College",
"school_type",
"Private_school"
],
[
"Stetson_University",
"colors",
"Blue"
],
[
"Stetson_University",
"school_type",
"Private_school"
],
[
"Suffolk_University_Law_School",
"colors",
"Blue"
],
[
"Suffolk_University_Law_School",
"school_type",
"Private_school"
],
[
"Tufts_University",
"colors",
"Blue"
],
[
"Tufts_University",
"school_type",
"Private_school"
],
[
"University_of_Delaware",
"colors",
"Blue"
],
[
"University_of_Delaware",
"school_type",
"Private_school"
],
[
"University_of_Notre_Dame",
"colors",
"Blue"
],
[
"University_of_Notre_Dame",
"school_type",
"Private_school"
],
[
"University_of_Richmond",
"colors",
"Blue"
],
[
"University_of_Richmond",
"school_type",
"Private_school"
],
[
"Villanova_University",
"colors",
"Blue"
],
[
"Villanova_University",
"school_type",
"Private_school"
],
[
"Waukesha",
"time_zones",
"Central_Time_Zone"
],
[
"Waukesha_County",
"time_zones",
"Central_Time_Zone"
],
[
"Wellesley_College",
"colors",
"Blue"
],
[
"Wellesley_College",
"school_type",
"Private_school"
],
[
"Wheaton_College",
"colors",
"Blue"
],
[
"Wheaton_College",
"school_type",
"Private_school"
],
[
"Wisconsin",
"adjoins",
"Illinois"
],
[
"Wisconsin",
"adjoins",
"Minnesota"
],
[
"Wisconsin",
"capital",
"Madison"
],
[
"Wisconsin",
"contains",
"Appleton"
],
[
"Wisconsin",
"contains",
"Beloit_College"
],
[
"Wisconsin",
"contains",
"Dane_County"
],
[
"Wisconsin",
"contains",
"Eau_Claire"
],
[
"Wisconsin",
"contains",
"Fond_du_Lac_County"
],
[
"Wisconsin",
"contains",
"Green_Bay"
],
[
"Wisconsin",
"contains",
"Kenosha"
],
[
"Wisconsin",
"contains",
"La_Crosse"
],
[
"Wisconsin",
"contains",
"La_Crosse_County"
],
[
"Wisconsin",
"contains",
"Madison"
],
[
"Wisconsin",
"contains",
"Marquette_University"
],
[
"Wisconsin",
"contains",
"Milwaukee"
],
[
"Wisconsin",
"contains",
"Milwaukee_County"
],
[
"Wisconsin",
"contains",
"Outagamie_County"
],
[
"Wisconsin",
"contains",
"Racine"
],
[
"Wisconsin",
"contains",
"Sauk_County"
],
[
"Wisconsin",
"contains",
"Waukesha"
],
[
"Wisconsin",
"contains",
"Waukesha_County"
],
[
"Wisconsin",
"contains",
"Wood_County"
],
[
"Wisconsin",
"partially_contains",
"Mississippi_River"
],
[
"Wisconsin",
"time_zones",
"Central_Time_Zone"
],
[
"Wood_County",
"time_zones",
"Central_Time_Zone"
],
[
"Yeshiva_University",
"colors",
"Blue"
],
[
"Yeshiva_University",
"school_type",
"Private_school"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
13550, Animation_Director
12711, Battlefield_Earth
3505, Betty_White
8015, Cook_County
2254, Gary_Goetzman
3872, Greek_American
2314, Oak_Park
10293, Old_Dogs
12896, Rita_Wilson
7674, Space_opera
8596, Star_Wars_Episode_II:_Attack_of_the_Clones
8345, Where_the_Wild_Things_Are
src, edge_attr, dst
12711, genre, 7674
12711, nominated_for, 10293
3505, location, 2314
3505, place_of_birth, 2314
2254, award_nominee, 12896
3872, people, 3505
3872, people, 12896
2314, county, 8015
2314, place, 2314
10293, nominated_for, 12711
12896, acted_in, 10293
12896, award_nominee, 2254
8596, film_crew_role, 13550
8596, genre, 7674
8345, film_crew_role, 13550
8345, produced_by, 2254
Question: In what context are Cook_County, Rita_Wilson, and Star_Wars_Episode_II:_Attack_of_the_Clones connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Cook_County",
"Rita_Wilson",
"Star_Wars_Episode_II:_Attack_of_the_Clones"
],
"valid_edges": [
[
"Battlefield_Earth",
"genre",
"Space_opera"
],
[
"Battlefield_Earth",
"nominated_for",
"Old_Dogs"
],
[
"Betty_White",
"location",
"Oak_Park"
],
[
"Betty_White",
"place_of_birth",
"Oak_Park"
],
[
"Gary_Goetzman",
"award_nominee",
"Rita_Wilson"
],
[
"Greek_American",
"people",
"Betty_White"
],
[
"Greek_American",
"people",
"Rita_Wilson"
],
[
"Oak_Park",
"county",
"Cook_County"
],
[
"Oak_Park",
"place",
"Oak_Park"
],
[
"Old_Dogs",
"nominated_for",
"Battlefield_Earth"
],
[
"Rita_Wilson",
"acted_in",
"Old_Dogs"
],
[
"Rita_Wilson",
"award_nominee",
"Gary_Goetzman"
],
[
"Star_Wars_Episode_II:_Attack_of_the_Clones",
"film_crew_role",
"Animation_Director"
],
[
"Star_Wars_Episode_II:_Attack_of_the_Clones",
"genre",
"Space_opera"
],
[
"Where_the_Wild_Things_Are",
"film_crew_role",
"Animation_Director"
],
[
"Where_the_Wild_Things_Are",
"produced_by",
"Gary_Goetzman"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7898, 1900_Summer_Olympics
10047, 1904_Summer_Olympics
3309, 1908_Summer_Olympics
7962, 1912_Summer_Olympics
9784, 1920_Summer_Olympics
4416, 1924_Summer_Olympics
7085, 1928_Summer_Olympics
11367, 1936_Summer_Olympics
5250, 1952_Summer_Olympics
12466, 1956_Summer_Olympics
8933, 1964_Summer_Olympics
2827, 1968_Summer_Olympics
7928, 1972_Summer_Olympics
4549, 1976_Summer_Olympics
680, 1980_Summer_Olympics
6985, 1984_Summer_Olympics
4829, 1988_Summer_Olympics
7439, 1992_Summer_Olympics
6286, 1996_Summer_Olympics
5468, 2000_Summer_Olympics
1970, 2004_Summer_Olympics
5259, 2008_Summer_Olympics
446, 2012_Summer_Olympics
11007, Aristotle
10565, Australia
11332, Belgium
3966, Brave
7647, Brazil
11678, Canada
7754, Canada_men's_national_soccer_team
11623, Constitutional_monarchy
9993, Elizabeth_II
10308, Football
230, France
3252, Germany
4194, Goalkeeper
12503, Greece
12205, Greece_national_football_team
2570, Hamilton
2646, Hulk
10906, Japan
614, Library_of_Congress_Classification
3605, Mexico
1057, Monarch-GB
7327, Netherlands
8723, New_Zealand
4793, New_Zealand_national_football_team
12212, Poland
7319, Red_Road
5929, Scotland
6556, Scotland_national_football_team
10977, South_Africa
1308, Swimming
8793, Vejle_Boldklub
src, edge_attr, dst
7898, participating_countries, 11678
7898, participating_countries, 12503
9784, participating_countries, 11678
11367, participating_countries, 11678
11367, participating_countries, 12503
11367, participating_countries, 8723
5250, participating_countries, 11678
5250, participating_countries, 12503
5250, participating_countries, 8723
5468, participating_countries, 12503
5468, participating_countries, 8723
1970, participating_countries, 12503
5259, participating_countries, 11678
5259, participating_countries, 12503
5259, participating_countries, 8723
11007, nationality, 12503
10565, adjoins, 8723
10565, combatants, 11678
10565, combatants, 12503
10565, combatants, 8723
10565, film_country, 8723
11332, combatants, 11678
11332, combatants, 12503
11332, combatants, 8723
3966, film_release_region, 11678
3966, film_release_region, 12503
3966, film_release_region, 8723
3966, film_release_region, 5929
7647, combatants, 11678
7647, combatants, 12503
7647, combatants, 8723
11678, combatants, 10565
11678, combatants, 11332
11678, combatants, 7647
11678, combatants, 3252
11678, combatants, 12503
11678, combatants, 3605
11678, combatants, 8723
11678, combatants, 12212
11678, combatants, 10977
11678, contains, 2570
11678, form_of_government, 11623
11678, olympics, 7898
11678, olympics, 10047
11678, olympics, 3309
11678, olympics, 7962
11678, olympics, 9784
11678, olympics, 4416
11678, olympics, 7085
11678, olympics, 11367
11678, olympics, 5250
11678, olympics, 12466
11678, olympics, 8933
11678, olympics, 2827
11678, olympics, 7928
11678, olympics, 4549
11678, olympics, 680
11678, olympics, 6985
11678, olympics, 4829
11678, olympics, 7439
11678, olympics, 6286
11678, olympics, 5468
11678, olympics, 1970
11678, olympics, 5259
11678, olympics, 446
11678, taxonomy, 614
11678, teams, 7754
7754, position, 4194
9993, jurisdiction_of_office, 11678
9993, jurisdiction_of_office, 8723
9993, jurisdiction_of_office, 5929
10308, country, 11678
10308, country, 8723
230, combatants, 11678
230, combatants, 12503
3252, combatants, 11678
3252, combatants, 12503
3252, combatants, 8723
4194, team, 12205
4194, team, 4793
4194, team, 6556
4194, team, 8793
12503, combatants, 10565
12503, combatants, 11332
12503, combatants, 7647
12503, combatants, 11678
12503, combatants, 230
12503, combatants, 3252
12503, combatants, 3605
12503, combatants, 7327
12503, combatants, 12212
12503, combatants, 10977
12503, olympics, 10047
12503, olympics, 3309
12503, olympics, 7962
12503, olympics, 12466
12503, olympics, 2827
12503, olympics, 7928
12503, olympics, 680
12503, olympics, 6985
12503, olympics, 4829
12503, olympics, 7439
12503, olympics, 6286
12503, olympics, 1970
12503, olympics, 5259
12503, olympics, 446
12503, taxonomy, 614
12503, teams, 12205
12205, football_roster_position, 4194
12205, position, 4194
2570, place, 2570
2646, film_release_region, 12503
2646, film_release_region, 8723
10906, exported_to, 11678
3605, combatants, 11678
3605, combatants, 12503
3605, combatants, 8723
1057, jurisdiction_of_office, 11678
1057, jurisdiction_of_office, 8723
1057, jurisdiction_of_office, 5929
7327, combatants, 11678
7327, combatants, 12503
7327, combatants, 8723
8723, adjoins, 10565
8723, combatants, 10565
8723, combatants, 11332
8723, combatants, 7647
8723, combatants, 11678
8723, combatants, 230
8723, combatants, 3252
8723, combatants, 12503
8723, combatants, 3605
8723, combatants, 7327
8723, combatants, 12212
8723, combatants, 10977
8723, contains, 2570
8723, exported_to, 10565
8723, exported_to, 10906
8723, form_of_government, 11623
8723, olympics, 9784
8723, olympics, 4416
8723, olympics, 7085
8723, olympics, 11367
8723, olympics, 5250
8723, olympics, 12466
8723, olympics, 8933
8723, olympics, 2827
8723, olympics, 7928
8723, olympics, 4549
8723, olympics, 6985
8723, olympics, 4829
8723, olympics, 7439
8723, olympics, 6286
8723, olympics, 5468
8723, olympics, 1970
8723, olympics, 5259
8723, olympics, 446
8723, taxonomy, 614
8723, teams, 4793
4793, football_roster_position, 4194
12212, combatants, 11678
12212, combatants, 12503
12212, combatants, 8723
7319, film_country, 5929
7319, film_release_region, 11678
7319, film_release_region, 12503
7319, film_release_region, 8723
5929, contains, 2570
5929, exported_to, 11332
5929, exported_to, 230
5929, exported_to, 3252
5929, exported_to, 7327
5929, form_of_government, 11623
5929, olympics, 7085
5929, taxonomy, 614
5929, teams, 6556
6556, football_roster_position, 4194
10977, combatants, 11678
10977, combatants, 12503
1308, country, 11678
1308, country, 12503
1308, country, 8723
1308, country, 5929
8793, position, 4194
Question: In what context are Aristotle, Hamilton, and Vejle_Boldklub connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Aristotle",
"Hamilton",
"Vejle_Boldklub"
],
"valid_edges": [
[
"1900_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1900_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"1920_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1936_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1936_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"1936_Summer_Olympics",
"participating_countries",
"New_Zealand"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"1952_Summer_Olympics",
"participating_countries",
"New_Zealand"
],
[
"2000_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"2000_Summer_Olympics",
"participating_countries",
"New_Zealand"
],
[
"2004_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"2008_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"2008_Summer_Olympics",
"participating_countries",
"Greece"
],
[
"2008_Summer_Olympics",
"participating_countries",
"New_Zealand"
],
[
"Aristotle",
"nationality",
"Greece"
],
[
"Australia",
"adjoins",
"New_Zealand"
],
[
"Australia",
"combatants",
"Canada"
],
[
"Australia",
"combatants",
"Greece"
],
[
"Australia",
"combatants",
"New_Zealand"
],
[
"Australia",
"film_country",
"New_Zealand"
],
[
"Belgium",
"combatants",
"Canada"
],
[
"Belgium",
"combatants",
"Greece"
],
[
"Belgium",
"combatants",
"New_Zealand"
],
[
"Brave",
"film_release_region",
"Canada"
],
[
"Brave",
"film_release_region",
"Greece"
],
[
"Brave",
"film_release_region",
"New_Zealand"
],
[
"Brave",
"film_release_region",
"Scotland"
],
[
"Brazil",
"combatants",
"Canada"
],
[
"Brazil",
"combatants",
"Greece"
],
[
"Brazil",
"combatants",
"New_Zealand"
],
[
"Canada",
"combatants",
"Australia"
],
[
"Canada",
"combatants",
"Belgium"
],
[
"Canada",
"combatants",
"Brazil"
],
[
"Canada",
"combatants",
"Germany"
],
[
"Canada",
"combatants",
"Greece"
],
[
"Canada",
"combatants",
"Mexico"
],
[
"Canada",
"combatants",
"New_Zealand"
],
[
"Canada",
"combatants",
"Poland"
],
[
"Canada",
"combatants",
"South_Africa"
],
[
"Canada",
"contains",
"Hamilton"
],
[
"Canada",
"form_of_government",
"Constitutional_monarchy"
],
[
"Canada",
"olympics",
"1900_Summer_Olympics"
],
[
"Canada",
"olympics",
"1904_Summer_Olympics"
],
[
"Canada",
"olympics",
"1908_Summer_Olympics"
],
[
"Canada",
"olympics",
"1912_Summer_Olympics"
],
[
"Canada",
"olympics",
"1920_Summer_Olympics"
],
[
"Canada",
"olympics",
"1924_Summer_Olympics"
],
[
"Canada",
"olympics",
"1928_Summer_Olympics"
],
[
"Canada",
"olympics",
"1936_Summer_Olympics"
],
[
"Canada",
"olympics",
"1952_Summer_Olympics"
],
[
"Canada",
"olympics",
"1956_Summer_Olympics"
],
[
"Canada",
"olympics",
"1964_Summer_Olympics"
],
[
"Canada",
"olympics",
"1968_Summer_Olympics"
],
[
"Canada",
"olympics",
"1972_Summer_Olympics"
],
[
"Canada",
"olympics",
"1976_Summer_Olympics"
],
[
"Canada",
"olympics",
"1980_Summer_Olympics"
],
[
"Canada",
"olympics",
"1984_Summer_Olympics"
],
[
"Canada",
"olympics",
"1988_Summer_Olympics"
],
[
"Canada",
"olympics",
"1992_Summer_Olympics"
],
[
"Canada",
"olympics",
"1996_Summer_Olympics"
],
[
"Canada",
"olympics",
"2000_Summer_Olympics"
],
[
"Canada",
"olympics",
"2004_Summer_Olympics"
],
[
"Canada",
"olympics",
"2008_Summer_Olympics"
],
[
"Canada",
"olympics",
"2012_Summer_Olympics"
],
[
"Canada",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Canada",
"teams",
"Canada_men's_national_soccer_team"
],
[
"Canada_men's_national_soccer_team",
"position",
"Goalkeeper"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Canada"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"New_Zealand"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Scotland"
],
[
"Football",
"country",
"Canada"
],
[
"Football",
"country",
"New_Zealand"
],
[
"France",
"combatants",
"Canada"
],
[
"France",
"combatants",
"Greece"
],
[
"Germany",
"combatants",
"Canada"
],
[
"Germany",
"combatants",
"Greece"
],
[
"Germany",
"combatants",
"New_Zealand"
],
[
"Goalkeeper",
"team",
"Greece_national_football_team"
],
[
"Goalkeeper",
"team",
"New_Zealand_national_football_team"
],
[
"Goalkeeper",
"team",
"Scotland_national_football_team"
],
[
"Goalkeeper",
"team",
"Vejle_Boldklub"
],
[
"Greece",
"combatants",
"Australia"
],
[
"Greece",
"combatants",
"Belgium"
],
[
"Greece",
"combatants",
"Brazil"
],
[
"Greece",
"combatants",
"Canada"
],
[
"Greece",
"combatants",
"France"
],
[
"Greece",
"combatants",
"Germany"
],
[
"Greece",
"combatants",
"Mexico"
],
[
"Greece",
"combatants",
"Netherlands"
],
[
"Greece",
"combatants",
"Poland"
],
[
"Greece",
"combatants",
"South_Africa"
],
[
"Greece",
"olympics",
"1904_Summer_Olympics"
],
[
"Greece",
"olympics",
"1908_Summer_Olympics"
],
[
"Greece",
"olympics",
"1912_Summer_Olympics"
],
[
"Greece",
"olympics",
"1956_Summer_Olympics"
],
[
"Greece",
"olympics",
"1968_Summer_Olympics"
],
[
"Greece",
"olympics",
"1972_Summer_Olympics"
],
[
"Greece",
"olympics",
"1980_Summer_Olympics"
],
[
"Greece",
"olympics",
"1984_Summer_Olympics"
],
[
"Greece",
"olympics",
"1988_Summer_Olympics"
],
[
"Greece",
"olympics",
"1992_Summer_Olympics"
],
[
"Greece",
"olympics",
"1996_Summer_Olympics"
],
[
"Greece",
"olympics",
"2004_Summer_Olympics"
],
[
"Greece",
"olympics",
"2008_Summer_Olympics"
],
[
"Greece",
"olympics",
"2012_Summer_Olympics"
],
[
"Greece",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Greece",
"teams",
"Greece_national_football_team"
],
[
"Greece_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Greece_national_football_team",
"position",
"Goalkeeper"
],
[
"Hamilton",
"place",
"Hamilton"
],
[
"Hulk",
"film_release_region",
"Greece"
],
[
"Hulk",
"film_release_region",
"New_Zealand"
],
[
"Japan",
"exported_to",
"Canada"
],
[
"Mexico",
"combatants",
"Canada"
],
[
"Mexico",
"combatants",
"Greece"
],
[
"Mexico",
"combatants",
"New_Zealand"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Canada"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"New_Zealand"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Scotland"
],
[
"Netherlands",
"combatants",
"Canada"
],
[
"Netherlands",
"combatants",
"Greece"
],
[
"Netherlands",
"combatants",
"New_Zealand"
],
[
"New_Zealand",
"adjoins",
"Australia"
],
[
"New_Zealand",
"combatants",
"Australia"
],
[
"New_Zealand",
"combatants",
"Belgium"
],
[
"New_Zealand",
"combatants",
"Brazil"
],
[
"New_Zealand",
"combatants",
"Canada"
],
[
"New_Zealand",
"combatants",
"France"
],
[
"New_Zealand",
"combatants",
"Germany"
],
[
"New_Zealand",
"combatants",
"Greece"
],
[
"New_Zealand",
"combatants",
"Mexico"
],
[
"New_Zealand",
"combatants",
"Netherlands"
],
[
"New_Zealand",
"combatants",
"Poland"
],
[
"New_Zealand",
"combatants",
"South_Africa"
],
[
"New_Zealand",
"contains",
"Hamilton"
],
[
"New_Zealand",
"exported_to",
"Australia"
],
[
"New_Zealand",
"exported_to",
"Japan"
],
[
"New_Zealand",
"form_of_government",
"Constitutional_monarchy"
],
[
"New_Zealand",
"olympics",
"1920_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1924_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1928_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1936_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1952_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1956_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1964_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1968_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1972_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1976_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1984_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1988_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1992_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"1996_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"2000_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"2004_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"2008_Summer_Olympics"
],
[
"New_Zealand",
"olympics",
"2012_Summer_Olympics"
],
[
"New_Zealand",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"New_Zealand",
"teams",
"New_Zealand_national_football_team"
],
[
"New_Zealand_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Poland",
"combatants",
"Canada"
],
[
"Poland",
"combatants",
"Greece"
],
[
"Poland",
"combatants",
"New_Zealand"
],
[
"Red_Road",
"film_country",
"Scotland"
],
[
"Red_Road",
"film_release_region",
"Canada"
],
[
"Red_Road",
"film_release_region",
"Greece"
],
[
"Red_Road",
"film_release_region",
"New_Zealand"
],
[
"Scotland",
"contains",
"Hamilton"
],
[
"Scotland",
"exported_to",
"Belgium"
],
[
"Scotland",
"exported_to",
"France"
],
[
"Scotland",
"exported_to",
"Germany"
],
[
"Scotland",
"exported_to",
"Netherlands"
],
[
"Scotland",
"form_of_government",
"Constitutional_monarchy"
],
[
"Scotland",
"olympics",
"1928_Summer_Olympics"
],
[
"Scotland",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Scotland",
"teams",
"Scotland_national_football_team"
],
[
"Scotland_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"South_Africa",
"combatants",
"Canada"
],
[
"South_Africa",
"combatants",
"Greece"
],
[
"Swimming",
"country",
"Canada"
],
[
"Swimming",
"country",
"Greece"
],
[
"Swimming",
"country",
"New_Zealand"
],
[
"Swimming",
"country",
"Scotland"
],
[
"Vejle_Boldklub",
"position",
"Goalkeeper"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12069, 54th_Academy_Awards
13813, Albany
11699, Alicia_Keys
12306, Allen_Ginsberg
70, Anne_Rice
1342, Anthony_Burgess
5452, Anton_Chekhov
236, Artist-GB
3253, Ashkenazi_Jews
3272, Atheism
2612, Author-GB
11332, Belgium
10342, Billie_Holiday
11622, Blues
11092, Blues-rock
10426, Bob_Dylan
8592, Brian_De_Palma
11569, Bruce_Springsteen
8957, Buddhism
13561, California
6649, Catherine_Deneuve
3303, Catholicism
94, Charles_Baudelaire
840, Chicago
5379, Christianity
7434, Cirrhosis
851, Claudette_Colbert
5206, Columbia
6978, Columbia_College_of_Columbia_University_in_the_City_of_New_York
11566, Columbia_University
5064, Connecticut
11949, Cormac_McCarthy
2604, Country
8574, Country_blues
2323, Dan_Castellaneta
10373, DeWitt_Clinton
4304, Domestic_partnership
6595, DreamWorks
7834, Elmore_Leonard
951, Enrico_Fermi
8269, Ernest_Hemingway
3521, Ezra_Pound
8512, F._Scott_Fitzgerald
10848, Faye_Dunaway
1311, Florida
10308, Football
1698, Frank_Herbert
7223, Fritz_Lang
12717, Fyodor_Dostoyevsky
8701, G-Force
9088, G._K._Chesterton
12505, Gary_Cooper
12368, Gene_Wolfe
752, George_Clooney
11493, George_Lucas
9846, Georgia
5499, Gospel_music
10490, Grammy_Award_for_Album_of_the_Year
13185, Grammy_Award_for_Best_Pop_Collaboration_with_Vocals
12503, Greece
4719, Harold_Pinter
1462, Henry_David_Thoreau
9140, Hepatitis
3671, Herman_Melville
461, Hunter_S._Thompson
5510, IK_Start
12610, Illinois
9308, Jack_Kerouac
2937, James_Joyce
12553, Jan_de_Bont
6111, Jazz
1652, John_Keats
13768, Jonathan_Lethem
13505, Joseph_Conrad
6048, Judaism-GB
2047, Katharine_Hepburn
12011, Kentucky
4405, Kim_Kardashian
4057, Lauren_Bacall
614, Library_of_Congress_Classification
3833, Lionsgate_Entertainment
625, Love_Affair
4659, Luxembourg
6547, Mary_Tyler_Moore
9240, Massachusetts
9289, Melanie_Griffith
3605, Mexico
7171, Mickey_Rourke
5755, New_Moon
3448, New_York
8723, New_Zealand
8798, Nicolas_Cage
2335, Norman_Mailer
9966, Norway
2314, Oak_Park
8835, On_the_Road
4866, Ontario
2752, Paris
5855, Patti_Smith
9310, Philip_K._Dick
6931, Piranha_DD
9985, Poet
161, Portugal
8708, Ray_Charles
9808, Ray_Manzarek
12556, Razzie_Award_for_Worst_Prequel,_Remake,_Rip-off_or_Sequel
5037, Record_producer-GB
10766, Republic_of_Ireland
3693, Rhythm_and_blues
4086, Robert_Zemeckis
159, Rock_and_roll
3834, Rudyard_Kipling
11798, Russia
7122, Salma_Hayek
5277, Singer-songwriter-GB
11972, Songwriter-GB
6711, Taiwan
11137, The_African_Queen
12627, The_Avengers
1384, The_Great_Gatsby
12895, Thomas_Pynchon
6007, Tom_Cruise
2084, Touchstone_Pictures
9886, U.S.A._for_Africa
7618, United_States_men's_national_soccer_team
9203, Vegetarianism
5535, Walt_Whitman
5807, Warren_Beatty
6961, Washington,_D.C.
12922, White
10728, William_Blake
9362, William_Faulkner
13284, William_Shakespeare
src, edge_attr, dst
12069, award_winner, 2047
12069, award_winner, 5807
11699, profession, 9985
12306, influenced_by, 3521
12306, influenced_by, 7223
12306, influenced_by, 12717
12306, influenced_by, 3671
12306, influenced_by, 9308
12306, influenced_by, 2937
12306, influenced_by, 1652
12306, influenced_by, 5535
12306, influenced_by, 10728
12306, influenced_by, 13284
12306, participant, 10426
12306, peers, 9308
12306, profession, 2612
12306, profession, 9985
12306, religion, 8957
12306, religion, 6048
12306, type_of_union, 4304
70, influenced_by, 8269
70, influenced_by, 12717
70, religion, 3303
1342, company, 11566
1342, influenced_by, 8269
1342, influenced_by, 2937
1342, profession, 9985
1342, religion, 3303
5452, influenced_by, 12717
3253, people, 12306
3253, people, 10426
11332, combatants, 3605
10342, religion, 3303
11622, artists, 10426
11622, artists, 8708
11622, artists, 9808
11092, artists, 10426
11092, artists, 9808
10426, award, 10490
10426, award, 13185
10426, diet, 9203
10426, group, 9886
10426, influenced_by, 12306
10426, influenced_by, 5452
10426, influenced_by, 9308
10426, influenced_by, 5535
10426, influenced_by, 10728
10426, participant, 12306
10426, profession, 236
10426, profession, 2612
10426, profession, 9985
10426, profession, 5037
10426, profession, 5277
10426, profession, 11972
10426, religion, 5379
10426, religion, 6048
8592, religion, 3303
11569, influenced_by, 10426
11569, religion, 3303
8957, taxonomy, 614
13561, religion, 8957
13561, religion, 3303
6649, celebrity, 5807
6649, religion, 3303
94, location, 2752
94, place_of_birth, 2752
94, place_of_death, 2752
94, profession, 9985
94, religion, 3303
7434, people, 10342
7434, people, 9308
7434, symptom_of, 9140
851, participant, 2047
851, religion, 3303
5206, artist, 10426
5206, artist, 8708
6978, campuses, 6978
6978, colors, 12922
6978, educational_institution, 6978
6978, state_province_region, 3448
6978, student, 12306
6978, student, 10373
6978, student, 9308
11566, colors, 12922
11566, state_province_region, 3448
11566, student, 11699
11566, student, 12306
11566, student, 8592
11566, student, 10373
11566, student, 461
11566, student, 9308
5064, religion, 3303
11949, influenced_by, 8269
11949, influenced_by, 12717
11949, influenced_by, 3671
11949, influenced_by, 2937
2604, artists, 10426
2604, artists, 8708
8574, artists, 10426
8574, artists, 8708
2323, acted_in, 8701
2323, acted_in, 625
2323, diet, 9203
2323, place_of_birth, 2314
6595, award, 12556
6595, film, 8835
7834, influenced_by, 8269
7834, religion, 3303
951, company, 11566
951, religion, 3303
8269, influenced_by, 5452
8269, influenced_by, 3521
8269, influenced_by, 12717
8269, influenced_by, 9088
8269, influenced_by, 1652
8269, influenced_by, 13505
8269, influenced_by, 3834
8269, influenced_by, 9362
8269, location, 840
8269, location, 2752
8269, participant, 12505
8269, participant, 2047
8269, place_of_birth, 2314
8269, profession, 2612
8269, religion, 3272
8269, religion, 3303
3521, influenced_by, 5535
3521, profession, 9985
8512, influenced_by, 1652
8512, peers, 8269
8512, profession, 9985
8512, religion, 3303
10848, celebrity, 5807
10848, participant, 5807
10848, religion, 3303
1311, religion, 8957
1311, religion, 3303
10308, country, 3605
1698, religion, 8957
1698, religion, 3303
7223, religion, 3303
12717, influenced_by, 13284
12717, nationality, 11798
12717, profession, 2612
12717, religion, 5379
8701, film_release_region, 3605
9088, religion, 3303
12505, participant, 8269
12505, religion, 3303
12368, influenced_by, 3671
12368, influenced_by, 2937
12368, religion, 3303
752, religion, 3303
11493, award, 12556
11493, religion, 8957
9846, religion, 8957
9846, religion, 3303
5499, artists, 10426
5499, artists, 8708
10490, award_winner, 10426
10490, award_winner, 8708
12503, combatants, 3605
4719, influenced_by, 8269
4719, influenced_by, 2937
4719, profession, 9985
4719, religion, 3303
1462, profession, 9985
9140, people, 12306
9140, people, 8708
3671, influenced_by, 1462
3671, influenced_by, 13284
3671, location, 13813
3671, profession, 9985
461, influenced_by, 12306
461, influenced_by, 8269
461, influenced_by, 8512
461, influenced_by, 9308
461, influenced_by, 13505
461, influenced_by, 9362
461, location, 12011
461, profession, 2612
12610, religion, 8957
12610, religion, 3303
9308, influenced_by, 94
9308, influenced_by, 8269
9308, influenced_by, 8512
9308, influenced_by, 12717
9308, influenced_by, 3671
9308, influenced_by, 2937
9308, influenced_by, 5535
9308, location, 3605
9308, profession, 9985
9308, religion, 8957
9308, religion, 3303
2937, influenced_by, 5452
2937, influenced_by, 3521
2937, influenced_by, 12717
2937, influenced_by, 13284
2937, nationality, 10766
2937, profession, 2612
2937, profession, 9985
2937, religion, 3303
12553, award, 12556
12553, religion, 3303
6111, artists, 8708
6111, artists, 9808
1652, profession, 9985
13768, influenced_by, 10426
13768, influenced_by, 12895
13505, religion, 3303
2047, acted_in, 625
2047, acted_in, 11137
2047, location, 5064
2047, nominated_for, 11137
2047, participant, 8269
2047, religion, 3272
12011, religion, 3303
4405, religion, 3303
4057, participant, 8269
4057, participant, 2047
3833, award, 12556
3833, film, 8835
625, produced_by, 5807
625, written_by, 5807
4659, religion, 3303
6547, participant, 5807
6547, religion, 3303
9240, religion, 8957
9240, religion, 3303
9289, participant, 5807
9289, religion, 3303
3605, adjoins, 13561
3605, combatants, 11332
3605, combatants, 12503
3605, combatants, 8723
3605, combatants, 9966
3605, combatants, 11798
3605, combatants, 6711
3605, taxonomy, 614
3605, vacationer, 752
3605, vacationer, 4405
7171, participant, 10426
7171, religion, 3303
5755, film_release_region, 3605
3448, religion, 8957
3448, religion, 3303
8723, combatants, 3605
8723, religion, 8957
8798, award, 12556
8798, religion, 3303
2335, influenced_by, 8269
2335, influenced_by, 12717
9966, combatants, 3605
8835, film_release_region, 11332
8835, film_release_region, 12503
8835, film_release_region, 4659
8835, film_release_region, 8723
8835, film_release_region, 9966
8835, film_release_region, 161
8835, film_release_region, 10766
8835, film_release_region, 11798
8835, film_release_region, 6711
8835, story_by, 9308
4866, religion, 8957
4866, religion, 3303
5855, influenced_by, 12306
5855, profession, 9985
9310, influenced_by, 12717
9310, influenced_by, 2937
6931, film_release_region, 3605
161, exported_to, 3605
161, religion, 3303
8708, acted_in, 625
8708, award, 10490
8708, award, 13185
8708, group, 9886
8708, location, 13813
8708, place_of_birth, 13813
8708, profession, 236
8708, profession, 5277
8708, type_of_union, 4304
9808, artist_origin, 840
9808, influenced_by, 9308
9808, place_of_birth, 840
9808, profession, 5037
9808, profession, 11972
9808, religion, 3303
12556, award_winner, 11493
12556, nominated_for, 625
12556, nominated_for, 5755
12556, nominated_for, 6931
12556, nominated_for, 12627
3693, artists, 10426
3693, artists, 8708
4086, award, 12556
4086, religion, 3303
159, artists, 10426
159, artists, 8708
159, artists, 9808
3834, profession, 9985
11798, combatants, 3605
7122, nationality, 3605
7122, religion, 3303
6711, combatants, 3605
11137, film_release_region, 3605
12627, award_honor_award, 12556
12627, film_release_region, 3605
1384, film_release_region, 3605
1384, story_by, 8512
12895, influenced_by, 12306
12895, influenced_by, 3671
12895, influenced_by, 9308
12895, influenced_by, 2937
12895, influenced_by, 2335
12895, profession, 2612
6007, award, 12556
6007, religion, 3303
2084, award, 12556
2084, film, 8835
7618, current_club, 5510
7618, sport, 10308
5535, location, 3448
5535, profession, 2612
5535, profession, 9985
5807, acted_in, 625
5807, award, 12556
5807, celebrity, 6649
5807, celebrity, 10848
5807, nominated_for, 625
5807, participant, 10848
5807, participant, 6547
5807, type_of_union, 4304
6961, religion, 8957
6961, religion, 3303
10728, profession, 9985
9362, influenced_by, 12717
9362, influenced_by, 3671
9362, influenced_by, 2937
13284, profession, 9985
Question: In what context are IK_Start, Jack_Kerouac, and Love_Affair connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"IK_Start",
"Jack_Kerouac",
"Love_Affair"
],
"valid_edges": [
[
"54th_Academy_Awards",
"award_winner",
"Katharine_Hepburn"
],
[
"54th_Academy_Awards",
"award_winner",
"Warren_Beatty"
],
[
"Alicia_Keys",
"profession",
"Poet"
],
[
"Allen_Ginsberg",
"influenced_by",
"Ezra_Pound"
],
[
"Allen_Ginsberg",
"influenced_by",
"Fritz_Lang"
],
[
"Allen_Ginsberg",
"influenced_by",
"Fyodor_Dostoyevsky"
],
[
"Allen_Ginsberg",
"influenced_by",
"Herman_Melville"
],
[
"Allen_Ginsberg",
"influenced_by",
"Jack_Kerouac"
],
[
"Allen_Ginsberg",
"influenced_by",
"James_Joyce"
],
[
"Allen_Ginsberg",
"influenced_by",
"John_Keats"
],
[
"Allen_Ginsberg",
"influenced_by",
"Walt_Whitman"
],
[
"Allen_Ginsberg",
"influenced_by",
"William_Blake"
],
[
"Allen_Ginsberg",
"influenced_by",
"William_Shakespeare"
],
[
"Allen_Ginsberg",
"participant",
"Bob_Dylan"
],
[
"Allen_Ginsberg",
"peers",
"Jack_Kerouac"
],
[
"Allen_Ginsberg",
"profession",
"Author-GB"
],
[
"Allen_Ginsberg",
"profession",
"Poet"
],
[
"Allen_Ginsberg",
"religion",
"Buddhism"
],
[
"Allen_Ginsberg",
"religion",
"Judaism-GB"
],
[
"Allen_Ginsberg",
"type_of_union",
"Domestic_partnership"
],
[
"Anne_Rice",
"influenced_by",
"Ernest_Hemingway"
],
[
"Anne_Rice",
"influenced_by",
"Fyodor_Dostoyevsky"
],
[
"Anne_Rice",
"religion",
"Catholicism"
],
[
"Anthony_Burgess",
"company",
"Columbia_University"
],
[
"Anthony_Burgess",
"influenced_by",
"Ernest_Hemingway"
],
[
"Anthony_Burgess",
"influenced_by",
"James_Joyce"
],
[
"Anthony_Burgess",
"profession",
"Poet"
],
[
"Anthony_Burgess",
"religion",
"Catholicism"
],
[
"Anton_Chekhov",
"influenced_by",
"Fyodor_Dostoyevsky"
],
[
"Ashkenazi_Jews",
"people",
"Allen_Ginsberg"
],
[
"Ashkenazi_Jews",
"people",
"Bob_Dylan"
],
[
"Belgium",
"combatants",
"Mexico"
],
[
"Billie_Holiday",
"religion",
"Catholicism"
],
[
"Blues",
"artists",
"Bob_Dylan"
],
[
"Blues",
"artists",
"Ray_Charles"
],
[
"Blues",
"artists",
"Ray_Manzarek"
],
[
"Blues-rock",
"artists",
"Bob_Dylan"
],
[
"Blues-rock",
"artists",
"Ray_Manzarek"
],
[
"Bob_Dylan",
"award",
"Grammy_Award_for_Album_of_the_Year"
],
[
"Bob_Dylan",
"award",
"Grammy_Award_for_Best_Pop_Collaboration_with_Vocals"
],
[
"Bob_Dylan",
"diet",
"Vegetarianism"
],
[
"Bob_Dylan",
"group",
"U.S.A._for_Africa"
],
[
"Bob_Dylan",
"influenced_by",
"Allen_Ginsberg"
],
[
"Bob_Dylan",
"influenced_by",
"Anton_Chekhov"
],
[
"Bob_Dylan",
"influenced_by",
"Jack_Kerouac"
],
[
"Bob_Dylan",
"influenced_by",
"Walt_Whitman"
],
[
"Bob_Dylan",
"influenced_by",
"William_Blake"
],
[
"Bob_Dylan",
"participant",
"Allen_Ginsberg"
],
[
"Bob_Dylan",
"profession",
"Artist-GB"
],
[
"Bob_Dylan",
"profession",
"Author-GB"
],
[
"Bob_Dylan",
"profession",
"Poet"
],
[
"Bob_Dylan",
"profession",
"Record_producer-GB"
],
[
"Bob_Dylan",
"profession",
"Singer-songwriter-GB"
],
[
"Bob_Dylan",
"profession",
"Songwriter-GB"
],
[
"Bob_Dylan",
"religion",
"Christianity"
],
[
"Bob_Dylan",
"religion",
"Judaism-GB"
],
[
"Brian_De_Palma",
"religion",
"Catholicism"
],
[
"Bruce_Springsteen",
"influenced_by",
"Bob_Dylan"
],
[
"Bruce_Springsteen",
"religion",
"Catholicism"
],
[
"Buddhism",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"California",
"religion",
"Buddhism"
],
[
"California",
"religion",
"Catholicism"
],
[
"Catherine_Deneuve",
"celebrity",
"Warren_Beatty"
],
[
"Catherine_Deneuve",
"religion",
"Catholicism"
],
[
"Charles_Baudelaire",
"location",
"Paris"
],
[
"Charles_Baudelaire",
"place_of_birth",
"Paris"
],
[
"Charles_Baudelaire",
"place_of_death",
"Paris"
],
[
"Charles_Baudelaire",
"profession",
"Poet"
],
[
"Charles_Baudelaire",
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"Warren_Beatty",
"acted_in",
"Love_Affair"
],
[
"Warren_Beatty",
"award",
"Razzie_Award_for_Worst_Prequel,_Remake,_Rip-off_or_Sequel"
],
[
"Warren_Beatty",
"celebrity",
"Catherine_Deneuve"
],
[
"Warren_Beatty",
"celebrity",
"Faye_Dunaway"
],
[
"Warren_Beatty",
"nominated_for",
"Love_Affair"
],
[
"Warren_Beatty",
"participant",
"Faye_Dunaway"
],
[
"Warren_Beatty",
"participant",
"Mary_Tyler_Moore"
],
[
"Warren_Beatty",
"type_of_union",
"Domestic_partnership"
],
[
"Washington,_D.C.",
"religion",
"Buddhism"
],
[
"Washington,_D.C.",
"religion",
"Catholicism"
],
[
"William_Blake",
"profession",
"Poet"
],
[
"William_Faulkner",
"influenced_by",
"Fyodor_Dostoyevsky"
],
[
"William_Faulkner",
"influenced_by",
"Herman_Melville"
],
[
"William_Faulkner",
"influenced_by",
"James_Joyce"
],
[
"William_Shakespeare",
"profession",
"Poet"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9468, 100th_United_States_Congress
10647, 101st_United_States_Congress
3887, 102nd_United_States_Congress
7474, 103rd_United_States_Congress
14079, 32nd_Academy_Awards
10918, 89th_United_States_Congress
6581, 98th_United_States_Congress
6952, 99th_United_States_Congress
11478, Baptists
13481, Blake_Edwards
10196, Daniel_Inouye
12380, Donald_M._Payne
3635, John_Conyers
429, John_McCain
3862, Lesley_Sharp
7662, Methodism
10697, Montana
7010, Nevada
1889, New_Mexico
4510, North_Dakota
10522, Oklahoma
563, Ralph_E._Winters
7461, Robert_Byrd
6824, The_Diary_of_Anne_Frank
10852, Utah
14025, Victor_Victoria
12366, West_Virginia
src, edge_attr, dst
9468, district_represented, 10697
9468, district_represented, 7010
9468, district_represented, 1889
9468, district_represented, 4510
9468, district_represented, 10852
9468, district_represented, 12366
9468, legislative_sessions, 10647
9468, legislative_sessions, 3887
9468, legislative_sessions, 7474
9468, legislative_sessions, 10918
9468, legislative_sessions, 6581
9468, legislative_sessions, 6952
10647, district_represented, 10697
10647, district_represented, 7010
10647, district_represented, 1889
10647, district_represented, 4510
10647, district_represented, 10852
10647, district_represented, 12366
10647, legislative_sessions, 9468
10647, legislative_sessions, 7474
10647, legislative_sessions, 10918
10647, legislative_sessions, 6581
10647, legislative_sessions, 6952
3887, district_represented, 10697
3887, district_represented, 7010
3887, district_represented, 1889
3887, district_represented, 4510
3887, district_represented, 10852
3887, district_represented, 12366
3887, legislative_sessions, 9468
3887, legislative_sessions, 10647
3887, legislative_sessions, 7474
3887, legislative_sessions, 10918
7474, district_represented, 10697
7474, district_represented, 7010
7474, district_represented, 1889
7474, district_represented, 4510
7474, district_represented, 10522
7474, district_represented, 10852
7474, district_represented, 12366
7474, legislative_sessions, 9468
7474, legislative_sessions, 3887
7474, legislative_sessions, 10918
7474, legislative_sessions, 6581
7474, legislative_sessions, 6952
14079, award_winner, 563
14079, honored_for, 6824
10918, district_represented, 12366
10918, legislative_sessions, 9468
10918, legislative_sessions, 3887
10918, legislative_sessions, 7474
10918, legislative_sessions, 6581
10918, legislative_sessions, 6952
6581, district_represented, 10697
6581, district_represented, 1889
6581, district_represented, 10852
6581, district_represented, 12366
6581, legislative_sessions, 9468
6581, legislative_sessions, 10647
6581, legislative_sessions, 3887
6581, legislative_sessions, 7474
6581, legislative_sessions, 10918
6581, legislative_sessions, 6952
6952, district_represented, 10697
6952, district_represented, 1889
6952, district_represented, 10852
6952, district_represented, 12366
6952, legislative_sessions, 9468
6952, legislative_sessions, 10647
6952, legislative_sessions, 3887
6952, legislative_sessions, 10918
6952, legislative_sessions, 6581
13481, location, 10522
13481, nominated_for, 14025
10196, legislative_sessions, 9468
10196, legislative_sessions, 10647
10196, legislative_sessions, 3887
10196, legislative_sessions, 7474
10196, legislative_sessions, 10918
10196, legislative_sessions, 6581
10196, legislative_sessions, 6952
10196, religion, 7662
12380, legislative_sessions, 10647
12380, legislative_sessions, 3887
12380, legislative_sessions, 7474
3635, legislative_sessions, 9468
3635, legislative_sessions, 10647
3635, legislative_sessions, 3887
3635, legislative_sessions, 7474
3635, legislative_sessions, 10918
3635, legislative_sessions, 6581
3635, legislative_sessions, 6952
3635, religion, 11478
429, legislative_sessions, 9468
429, legislative_sessions, 10647
429, legislative_sessions, 3887
429, legislative_sessions, 7474
429, legislative_sessions, 6581
429, legislative_sessions, 6952
3862, acted_in, 6824
7461, legislative_sessions, 9468
7461, legislative_sessions, 10647
7461, legislative_sessions, 3887
7461, legislative_sessions, 7474
7461, legislative_sessions, 10918
7461, legislative_sessions, 6581
7461, legislative_sessions, 6952
7461, religion, 11478
14025, award_winner, 13481
14025, edited_by, 563
14025, produced_by, 13481
14025, written_by, 13481
12366, religion, 11478
12366, religion, 7662
Question: How are 89th_United_States_Congress, Lesley_Sharp, and Victor_Victoria related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"89th_United_States_Congress",
"Lesley_Sharp",
"Victor_Victoria"
],
"valid_edges": [
[
"100th_United_States_Congress",
"district_represented",
"Montana"
],
[
"100th_United_States_Congress",
"district_represented",
"Nevada"
],
[
"100th_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"100th_United_States_Congress",
"district_represented",
"North_Dakota"
],
[
"100th_United_States_Congress",
"district_represented",
"Utah"
],
[
"100th_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"100th_United_States_Congress",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"101st_United_States_Congress",
"district_represented",
"Montana"
],
[
"101st_United_States_Congress",
"district_represented",
"Nevada"
],
[
"101st_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"101st_United_States_Congress",
"district_represented",
"North_Dakota"
],
[
"101st_United_States_Congress",
"district_represented",
"Utah"
],
[
"101st_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"101st_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"101st_United_States_Congress",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"101st_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"101st_United_States_Congress",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"101st_United_States_Congress",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"102nd_United_States_Congress",
"district_represented",
"Montana"
],
[
"102nd_United_States_Congress",
"district_represented",
"Nevada"
],
[
"102nd_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"102nd_United_States_Congress",
"district_represented",
"North_Dakota"
],
[
"102nd_United_States_Congress",
"district_represented",
"Utah"
],
[
"102nd_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"102nd_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"102nd_United_States_Congress",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"102nd_United_States_Congress",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"102nd_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"103rd_United_States_Congress",
"district_represented",
"Montana"
],
[
"103rd_United_States_Congress",
"district_represented",
"Nevada"
],
[
"103rd_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"103rd_United_States_Congress",
"district_represented",
"North_Dakota"
],
[
"103rd_United_States_Congress",
"district_represented",
"Oklahoma"
],
[
"103rd_United_States_Congress",
"district_represented",
"Utah"
],
[
"103rd_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"103rd_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"103rd_United_States_Congress",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"103rd_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"103rd_United_States_Congress",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"103rd_United_States_Congress",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"32nd_Academy_Awards",
"award_winner",
"Ralph_E._Winters"
],
[
"32nd_Academy_Awards",
"honored_for",
"The_Diary_of_Anne_Frank"
],
[
"89th_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"89th_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"89th_United_States_Congress",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"89th_United_States_Congress",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"89th_United_States_Congress",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"89th_United_States_Congress",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"98th_United_States_Congress",
"district_represented",
"Montana"
],
[
"98th_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"98th_United_States_Congress",
"district_represented",
"Utah"
],
[
"98th_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"98th_United_States_Congress",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"99th_United_States_Congress",
"district_represented",
"Montana"
],
[
"99th_United_States_Congress",
"district_represented",
"New_Mexico"
],
[
"99th_United_States_Congress",
"district_represented",
"Utah"
],
[
"99th_United_States_Congress",
"district_represented",
"West_Virginia"
],
[
"99th_United_States_Congress",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"99th_United_States_Congress",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"99th_United_States_Congress",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"99th_United_States_Congress",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"99th_United_States_Congress",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"Blake_Edwards",
"location",
"Oklahoma"
],
[
"Blake_Edwards",
"nominated_for",
"Victor_Victoria"
],
[
"Daniel_Inouye",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"Daniel_Inouye",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"Daniel_Inouye",
"religion",
"Methodism"
],
[
"Donald_M._Payne",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"Donald_M._Payne",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"Donald_M._Payne",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"John_Conyers",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"John_Conyers",
"religion",
"Baptists"
],
[
"John_McCain",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"John_McCain",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"John_McCain",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"John_McCain",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"John_McCain",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"John_McCain",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"Lesley_Sharp",
"acted_in",
"The_Diary_of_Anne_Frank"
],
[
"Robert_Byrd",
"legislative_sessions",
"100th_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"101st_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"102nd_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"103rd_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"89th_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"98th_United_States_Congress"
],
[
"Robert_Byrd",
"legislative_sessions",
"99th_United_States_Congress"
],
[
"Robert_Byrd",
"religion",
"Baptists"
],
[
"Victor_Victoria",
"award_winner",
"Blake_Edwards"
],
[
"Victor_Victoria",
"edited_by",
"Ralph_E._Winters"
],
[
"Victor_Victoria",
"produced_by",
"Blake_Edwards"
],
[
"Victor_Victoria",
"written_by",
"Blake_Edwards"
],
[
"West_Virginia",
"religion",
"Baptists"
],
[
"West_Virginia",
"religion",
"Methodism"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
8575, 44th_Academy_Awards
1750, Buckethead
2518, Disco
4147, Electronic_dance_music
6084, Electronica
10781, Experimental_rock
8241, Fred_Frith
3593, Free_improvisation
2385, Giorgio_Moroder
4307, Gorillaz
3807, House_music
10393, Isaac_Hayes
3555, Jamiroquai
8497, Jeff_Lynne
6176, John_Frusciante
9580, Kraftwerk
10798, Nicholas_and_Alexandra
2403, Ryuichi_Sakamoto
5288, Techno
9445, Trevor_Horn
8001, Yes
src, edge_attr, dst
8575, award_winner, 10393
8575, honored_for, 10798
2518, artists, 2385
2518, artists, 10393
2518, artists, 3555
2518, artists, 8497
2518, artists, 9445
4147, artists, 1750
4147, artists, 2385
4147, artists, 4307
4147, artists, 6176
4147, artists, 9580
4147, artists, 2403
4147, artists, 9445
6084, artists, 1750
6084, artists, 4307
6084, artists, 3555
6084, artists, 8497
6084, artists, 6176
6084, artists, 9580
6084, artists, 2403
6084, artists, 9445
6084, parent_genre, 3807
6084, parent_genre, 5288
10781, artists, 8241
10781, artists, 8001
3593, artists, 8241
3807, parent_genre, 2518
3807, parent_genre, 4147
5288, parent_genre, 4147
9445, group, 8001
Question: How are Free_improvisation, Nicholas_and_Alexandra, and Trevor_Horn related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Free_improvisation",
"Nicholas_and_Alexandra",
"Trevor_Horn"
],
"valid_edges": [
[
"44th_Academy_Awards",
"award_winner",
"Isaac_Hayes"
],
[
"44th_Academy_Awards",
"honored_for",
"Nicholas_and_Alexandra"
],
[
"Disco",
"artists",
"Giorgio_Moroder"
],
[
"Disco",
"artists",
"Isaac_Hayes"
],
[
"Disco",
"artists",
"Jamiroquai"
],
[
"Disco",
"artists",
"Jeff_Lynne"
],
[
"Disco",
"artists",
"Trevor_Horn"
],
[
"Electronic_dance_music",
"artists",
"Buckethead"
],
[
"Electronic_dance_music",
"artists",
"Giorgio_Moroder"
],
[
"Electronic_dance_music",
"artists",
"Gorillaz"
],
[
"Electronic_dance_music",
"artists",
"John_Frusciante"
],
[
"Electronic_dance_music",
"artists",
"Kraftwerk"
],
[
"Electronic_dance_music",
"artists",
"Ryuichi_Sakamoto"
],
[
"Electronic_dance_music",
"artists",
"Trevor_Horn"
],
[
"Electronica",
"artists",
"Buckethead"
],
[
"Electronica",
"artists",
"Gorillaz"
],
[
"Electronica",
"artists",
"Jamiroquai"
],
[
"Electronica",
"artists",
"Jeff_Lynne"
],
[
"Electronica",
"artists",
"John_Frusciante"
],
[
"Electronica",
"artists",
"Kraftwerk"
],
[
"Electronica",
"artists",
"Ryuichi_Sakamoto"
],
[
"Electronica",
"artists",
"Trevor_Horn"
],
[
"Electronica",
"parent_genre",
"House_music"
],
[
"Electronica",
"parent_genre",
"Techno"
],
[
"Experimental_rock",
"artists",
"Fred_Frith"
],
[
"Experimental_rock",
"artists",
"Yes"
],
[
"Free_improvisation",
"artists",
"Fred_Frith"
],
[
"House_music",
"parent_genre",
"Disco"
],
[
"House_music",
"parent_genre",
"Electronic_dance_music"
],
[
"Techno",
"parent_genre",
"Electronic_dance_music"
],
[
"Trevor_Horn",
"group",
"Yes"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
6985, 1984_Summer_Olympics
7439, 1992_Summer_Olympics
6286, 1996_Summer_Olympics
2072, 2002_Winter_Olympics
1970, 2004_Summer_Olympics
5259, 2008_Summer_Olympics
446, 2012_Summer_Olympics
10288, Artistic_gymnastics
6280, BAFTA_Award_for_Best_Screenplay,_Adapted
10495, Beasts_of_the_Southern_Wild
4, Boxing
10817, Bronze_medal
9757, Cars
6199, China
7411, Crouching_Tiger,_Hidden_Dragon
13546, Elaine_May
13477, Freestyle_wrestling
3980, Judo
10529, Larry_Gelbart
13967, Life_of_Pi
1042, Ponce
13991, Puerto_Rico
4413, Shooting_sport
6332, Silver_medal
1308, Swimming
7294, The_Descendants
10782, The_Help
8567, The_Kite_Runner
11982, The_Lord_of_the_Rings:_The_Return_of_the_King
2425, The_Lord_of_the_Rings:_The_Two_Towers
9470, Tibet
13789, Tootsie
10396, Toy_Story_3
9349, Track_and_field_athletics
src, edge_attr, dst
2072, participating_countries, 6199
2072, participating_countries, 13991
5259, participating_countries, 6199
446, participating_countries, 6199
10288, country, 6199
10288, country, 13991
6280, award_winner, 13546
6280, nominated_for, 10495
6280, nominated_for, 7411
6280, nominated_for, 13967
6280, nominated_for, 7294
6280, nominated_for, 10782
6280, nominated_for, 8567
6280, nominated_for, 11982
6280, nominated_for, 13789
6280, nominated_for, 10396
10495, film_release_region, 13991
4, country, 6199
4, country, 13991
9757, film_release_region, 6199
9757, film_release_region, 13991
6199, medal, 10817
6199, medal, 6332
6199, olympics, 6985
6199, olympics, 7439
6199, olympics, 6286
6199, olympics, 2072
6199, olympics, 1970
6199, olympics, 5259
6199, olympics, 446
6199, titles, 7411
7411, film_country, 6199
13546, award, 6280
13477, country, 6199
13477, country, 13991
3980, country, 6199
3980, country, 13991
10529, award, 6280
10529, nominated_for, 13789
13967, film_release_region, 13991
1042, county_seat, 1042
13991, contains, 1042
13991, medal, 10817
13991, medal, 6332
13991, olympics, 6985
13991, olympics, 7439
13991, olympics, 6286
13991, olympics, 1970
13991, olympics, 5259
13991, olympics, 446
4413, country, 6199
4413, country, 13991
1308, country, 6199
1308, country, 13991
7294, film_release_region, 6199
10782, film_release_region, 6199
8567, film_country, 6199
11982, award_honor_award, 6280
11982, film_release_region, 6199
11982, film_release_region, 13991
2425, film_release_region, 6199
2425, film_release_region, 13991
9470, country, 6199
13789, award_winner, 10529
13789, story_by, 10529
13789, written_by, 13546
13789, written_by, 10529
10396, film_release_region, 6199
9349, country, 6199
9349, country, 13991
Question: For what reason are Larry_Gelbart, Ponce, and Tibet associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Larry_Gelbart",
"Ponce",
"Tibet"
],
"valid_edges": [
[
"2002_Winter_Olympics",
"participating_countries",
"China"
],
[
"2002_Winter_Olympics",
"participating_countries",
"Puerto_Rico"
],
[
"2008_Summer_Olympics",
"participating_countries",
"China"
],
[
"2012_Summer_Olympics",
"participating_countries",
"China"
],
[
"Artistic_gymnastics",
"country",
"China"
],
[
"Artistic_gymnastics",
"country",
"Puerto_Rico"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"award_winner",
"Elaine_May"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"Beasts_of_the_Southern_Wild"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"Crouching_Tiger,_Hidden_Dragon"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"Life_of_Pi"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"The_Descendants"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"The_Help"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"The_Kite_Runner"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"The_Lord_of_the_Rings:_The_Return_of_the_King"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"Tootsie"
],
[
"BAFTA_Award_for_Best_Screenplay,_Adapted",
"nominated_for",
"Toy_Story_3"
],
[
"Beasts_of_the_Southern_Wild",
"film_release_region",
"Puerto_Rico"
],
[
"Boxing",
"country",
"China"
],
[
"Boxing",
"country",
"Puerto_Rico"
],
[
"Cars",
"film_release_region",
"China"
],
[
"Cars",
"film_release_region",
"Puerto_Rico"
],
[
"China",
"medal",
"Bronze_medal"
],
[
"China",
"medal",
"Silver_medal"
],
[
"China",
"olympics",
"1984_Summer_Olympics"
],
[
"China",
"olympics",
"1992_Summer_Olympics"
],
[
"China",
"olympics",
"1996_Summer_Olympics"
],
[
"China",
"olympics",
"2002_Winter_Olympics"
],
[
"China",
"olympics",
"2004_Summer_Olympics"
],
[
"China",
"olympics",
"2008_Summer_Olympics"
],
[
"China",
"olympics",
"2012_Summer_Olympics"
],
[
"China",
"titles",
"Crouching_Tiger,_Hidden_Dragon"
],
[
"Crouching_Tiger,_Hidden_Dragon",
"film_country",
"China"
],
[
"Elaine_May",
"award",
"BAFTA_Award_for_Best_Screenplay,_Adapted"
],
[
"Freestyle_wrestling",
"country",
"China"
],
[
"Freestyle_wrestling",
"country",
"Puerto_Rico"
],
[
"Judo",
"country",
"China"
],
[
"Judo",
"country",
"Puerto_Rico"
],
[
"Larry_Gelbart",
"award",
"BAFTA_Award_for_Best_Screenplay,_Adapted"
],
[
"Larry_Gelbart",
"nominated_for",
"Tootsie"
],
[
"Life_of_Pi",
"film_release_region",
"Puerto_Rico"
],
[
"Ponce",
"county_seat",
"Ponce"
],
[
"Puerto_Rico",
"contains",
"Ponce"
],
[
"Puerto_Rico",
"medal",
"Bronze_medal"
],
[
"Puerto_Rico",
"medal",
"Silver_medal"
],
[
"Puerto_Rico",
"olympics",
"1984_Summer_Olympics"
],
[
"Puerto_Rico",
"olympics",
"1992_Summer_Olympics"
],
[
"Puerto_Rico",
"olympics",
"1996_Summer_Olympics"
],
[
"Puerto_Rico",
"olympics",
"2004_Summer_Olympics"
],
[
"Puerto_Rico",
"olympics",
"2008_Summer_Olympics"
],
[
"Puerto_Rico",
"olympics",
"2012_Summer_Olympics"
],
[
"Shooting_sport",
"country",
"China"
],
[
"Shooting_sport",
"country",
"Puerto_Rico"
],
[
"Swimming",
"country",
"China"
],
[
"Swimming",
"country",
"Puerto_Rico"
],
[
"The_Descendants",
"film_release_region",
"China"
],
[
"The_Help",
"film_release_region",
"China"
],
[
"The_Kite_Runner",
"film_country",
"China"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"BAFTA_Award_for_Best_Screenplay,_Adapted"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"film_release_region",
"China"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"film_release_region",
"Puerto_Rico"
],
[
"The_Lord_of_the_Rings:_The_Two_Towers",
"film_release_region",
"China"
],
[
"The_Lord_of_the_Rings:_The_Two_Towers",
"film_release_region",
"Puerto_Rico"
],
[
"Tibet",
"country",
"China"
],
[
"Tootsie",
"award_winner",
"Larry_Gelbart"
],
[
"Tootsie",
"story_by",
"Larry_Gelbart"
],
[
"Tootsie",
"written_by",
"Elaine_May"
],
[
"Tootsie",
"written_by",
"Larry_Gelbart"
],
[
"Toy_Story_3",
"film_release_region",
"China"
],
[
"Track_and_field_athletics",
"country",
"China"
],
[
"Track_and_field_athletics",
"country",
"Puerto_Rico"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1342, Anthony_Burgess
10409, Composer
10901, Eric_Idle
10308, Football
5540, Football_player
6367, John_Cleese
3920, Liberal_Democrats
186, Mark_Bresciano
9554, Parma_F.C.
7572, Playwright-GB
1606, Rabindranath_Tagore
9181, Rupert_Holmes
11543, Spike_Milligan
7838, Vince_Grella
1016, Vinnie_Jones
13284, William_Shakespeare
src, edge_attr, dst
1342, profession, 10409
1342, profession, 7572
10901, award_nominee, 6367
10901, profession, 10409
10308, athlete, 186
10308, athlete, 7838
10308, athlete, 1016
6367, award_nominee, 10901
6367, influenced_by, 11543
6367, influenced_by, 13284
3920, party_politician, 6367
186, profession, 5540
186, team, 9554
9554, sport, 10308
1606, profession, 10409
1606, profession, 7572
9181, profession, 10409
9181, profession, 7572
11543, profession, 7572
7838, profession, 5540
7838, team, 9554
1016, profession, 10409
13284, profession, 7572
Question: In what context are Liberal_Democrats, Parma_F.C., and Rupert_Holmes connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Liberal_Democrats",
"Parma_F.C.",
"Rupert_Holmes"
],
"valid_edges": [
[
"Anthony_Burgess",
"profession",
"Composer"
],
[
"Anthony_Burgess",
"profession",
"Playwright-GB"
],
[
"Eric_Idle",
"award_nominee",
"John_Cleese"
],
[
"Eric_Idle",
"profession",
"Composer"
],
[
"Football",
"athlete",
"Mark_Bresciano"
],
[
"Football",
"athlete",
"Vince_Grella"
],
[
"Football",
"athlete",
"Vinnie_Jones"
],
[
"John_Cleese",
"award_nominee",
"Eric_Idle"
],
[
"John_Cleese",
"influenced_by",
"Spike_Milligan"
],
[
"John_Cleese",
"influenced_by",
"William_Shakespeare"
],
[
"Liberal_Democrats",
"party_politician",
"John_Cleese"
],
[
"Mark_Bresciano",
"profession",
"Football_player"
],
[
"Mark_Bresciano",
"team",
"Parma_F.C."
],
[
"Parma_F.C.",
"sport",
"Football"
],
[
"Rabindranath_Tagore",
"profession",
"Composer"
],
[
"Rabindranath_Tagore",
"profession",
"Playwright-GB"
],
[
"Rupert_Holmes",
"profession",
"Composer"
],
[
"Rupert_Holmes",
"profession",
"Playwright-GB"
],
[
"Spike_Milligan",
"profession",
"Playwright-GB"
],
[
"Vince_Grella",
"profession",
"Football_player"
],
[
"Vince_Grella",
"team",
"Parma_F.C."
],
[
"Vinnie_Jones",
"profession",
"Composer"
],
[
"William_Shakespeare",
"profession",
"Playwright-GB"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
11214, Cartoonist
2017, Deep_Impact
10542, Elijah_Wood
10381, French_American
1061, Jon_Favreau
1159, Julie_Delpy
1936, Leelee_Sobieski
11133, Mike_Judge
6573, Richard_Linklater
13010, Roy_Thomas
13989, Spy_Kids
9905, Spy_Kids_3-D:_Game_Over
src, edge_attr, dst
10542, acted_in, 2017
10542, acted_in, 9905
10381, people, 1061
10381, people, 1159
10381, people, 1936
1061, acted_in, 2017
1159, award_nominee, 6573
1936, acted_in, 2017
11133, acted_in, 9905
11133, profession, 11214
6573, acted_in, 13989
6573, award_nominee, 1159
13010, profession, 11214
13989, prequel, 9905
9905, prequel, 13989
Question: How are Elijah_Wood, Julie_Delpy, and Roy_Thomas related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Elijah_Wood",
"Julie_Delpy",
"Roy_Thomas"
],
"valid_edges": [
[
"Elijah_Wood",
"acted_in",
"Deep_Impact"
],
[
"Elijah_Wood",
"acted_in",
"Spy_Kids_3-D:_Game_Over"
],
[
"French_American",
"people",
"Jon_Favreau"
],
[
"French_American",
"people",
"Julie_Delpy"
],
[
"French_American",
"people",
"Leelee_Sobieski"
],
[
"Jon_Favreau",
"acted_in",
"Deep_Impact"
],
[
"Julie_Delpy",
"award_nominee",
"Richard_Linklater"
],
[
"Leelee_Sobieski",
"acted_in",
"Deep_Impact"
],
[
"Mike_Judge",
"acted_in",
"Spy_Kids_3-D:_Game_Over"
],
[
"Mike_Judge",
"profession",
"Cartoonist"
],
[
"Richard_Linklater",
"acted_in",
"Spy_Kids"
],
[
"Richard_Linklater",
"award_nominee",
"Julie_Delpy"
],
[
"Roy_Thomas",
"profession",
"Cartoonist"
],
[
"Spy_Kids",
"prequel",
"Spy_Kids_3-D:_Game_Over"
],
[
"Spy_Kids_3-D:_Game_Over",
"prequel",
"Spy_Kids"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4344, Bayreuth
7766, David_Hemmings
6645, Dennis_Hopper
8700, Guildford
8347, Jimmy_Page
2539, National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor
2831, Richard_Wagner
11542, Surrey
5046, Venice
src, edge_attr, dst
7766, award, 2539
7766, place_of_birth, 8700
6645, award, 2539
6645, place_of_death, 5046
8347, location, 11542
2539, award_winner, 6645
2831, location, 4344
2831, location, 5046
11542, contains, 8700
Question: How are Bayreuth, Jimmy_Page, and National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bayreuth",
"Jimmy_Page",
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor"
],
"valid_edges": [
[
"David_Hemmings",
"award",
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor"
],
[
"David_Hemmings",
"place_of_birth",
"Guildford"
],
[
"Dennis_Hopper",
"award",
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor"
],
[
"Dennis_Hopper",
"place_of_death",
"Venice"
],
[
"Jimmy_Page",
"location",
"Surrey"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Supporting_Actor",
"award_winner",
"Dennis_Hopper"
],
[
"Richard_Wagner",
"location",
"Bayreuth"
],
[
"Richard_Wagner",
"location",
"Venice"
],
[
"Surrey",
"contains",
"Guildford"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1231, 13th_Screen_Actors_Guild_Awards
795, African_Union
5336, Angola
11624, Atlantic_Ocean
7352, Botswana
8308, Burkina_Faso
8211, Cameroon
11252, Chad
7947, Chandra_Wilson
1038, Christopher_Hitchens
7359, Commonwealth_of_Nations
12402, Cyprus
6955, CΓ΄te_dβIvoire
7976, El_Salvador
1607, Ellen_Pompeo
13243, Equatorial_Guinea
6460, Eric_Dane
4483, Eritrea
12903, Gabon
13841, Gambia
12368, Gene_Wolfe
13448, George_Orwell
2287, Ghana
3031, Guatemala
6702, Guinea
4410, Houston
10201, Isaiah_Washington
2937, James_Joyce
11691, James_Pickens_Jr.
4785, Jeff_Bennett
3044, Joseph_Haydn
13904, Justin_Chambers
1662, Kate_Walsh
10179, League_of_Nations
7449, Liberia
4150, Malawi
11586, Maldives
1030, Mali
11544, Michael_Nesmith
8271, Mozambique
3832, Myanmar
2168, Namibia
8020, Nicaragua
2322, Nigeria
6806, Presidential_system
13742, Rwanda
10271, Sara_Ramirez
1802, Senegal
4310, Seychelles
4989, Sierra_Leone
1509, South_Sudan
4601, Sudan
7023, T._R._Knight
31, Tanzania
10531, Tinker_Bell:_Secret_of_the_Wings
2030, Uganda
8096, United_States_Air_Force-GB
3457, University_of_Houston
8204, Vienna
13234, Vladimir_Vladimirovich_Nabokov
3087, W._H._Auden
6733, Zambia
6408, Zimbabwe
src, edge_attr, dst
1231, award_winner, 7947
1231, award_winner, 10201
5336, adjoins, 2168
5336, adjoins, 6733
5336, form_of_government, 6806
5336, organization, 795
11624, adjoins, 5336
11624, adjoins, 4989
7352, adjoins, 6733
8308, adjoins, 6955
8211, adjoins, 13243
11252, adjoins, 2322
11252, adjoins, 4601
11252, form_of_government, 6806
11252, organization, 795
7947, award_nominee, 1607
7947, award_nominee, 6460
7947, award_nominee, 10201
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7947, award_nominee, 7023
7947, award_winner, 1607
7947, award_winner, 6460
7947, award_winner, 10201
7947, award_winner, 11691
7947, award_winner, 13904
7947, award_winner, 1662
7947, award_winner, 10271
7947, award_winner, 7023
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7947, place_of_birth, 4410
1038, influenced_by, 13448
1038, influenced_by, 2937
1038, influenced_by, 13234
1038, influenced_by, 3087
1038, place_of_death, 4410
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12402, organization, 7359
6955, adjoins, 8308
6955, adjoins, 2287
6955, adjoins, 6702
6955, adjoins, 1030
6955, exported_to, 4989
6955, form_of_government, 6806
6955, organization, 795
7976, adjoins, 3031
7976, form_of_government, 6806
7976, organization, 10179
1607, award_nominee, 7947
1607, award_nominee, 10201
1607, award_winner, 7947
1607, award_winner, 10201
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13243, form_of_government, 6806
13243, organization, 795
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6460, award_winner, 7947
6460, award_winner, 10201
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4483, form_of_government, 6806
4483, organization, 795
12903, adjoins, 13243
12903, form_of_government, 6806
12903, organization, 795
13841, form_of_government, 6806
13841, organization, 795
13841, organization, 7359
12368, influenced_by, 13448
12368, influenced_by, 2937
12368, influenced_by, 13234
12368, location, 4410
13448, location, 3832
2287, adjoins, 8308
2287, adjoins, 6955
2287, form_of_government, 6806
2287, organization, 795
2287, organization, 7359
3031, adjoins, 7976
3031, form_of_government, 6806
3031, organization, 10179
6702, adjoins, 6955
6702, adjoins, 7449
6702, adjoins, 1030
6702, adjoins, 4989
6702, form_of_government, 6806
4410, place, 4410
10201, award_nominee, 7947
10201, award_nominee, 1607
10201, award_nominee, 6460
10201, award_nominee, 11691
10201, award_nominee, 13904
10201, award_nominee, 1662
10201, award_nominee, 10271
10201, award_nominee, 7023
10201, award_winner, 7947
10201, award_winner, 6460
10201, award_winner, 11691
10201, award_winner, 13904
10201, award_winner, 1662
10201, award_winner, 10271
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10201, company, 8096
10201, place_of_birth, 4410
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11691, award_winner, 10201
4785, acted_in, 10531
4785, place_of_birth, 4410
3044, place_of_death, 8204
13904, award_nominee, 7947
13904, award_nominee, 10201
13904, award_winner, 7947
1662, award_nominee, 7947
1662, award_nominee, 10201
1662, award_winner, 7947
1662, participant, 7947
7449, adjoins, 6955
7449, adjoins, 6702
7449, adjoins, 4989
7449, form_of_government, 6806
7449, organization, 795
7449, organization, 10179
4150, adjoins, 31
4150, adjoins, 6733
4150, form_of_government, 6806
4150, organization, 795
4150, organization, 7359
11586, form_of_government, 6806
11586, organization, 7359
1030, adjoins, 6955
11544, company, 8096
11544, location, 4410
11544, place_of_birth, 4410
8271, adjoins, 4150
8271, adjoins, 31
8271, form_of_government, 6806
8271, organization, 795
8271, organization, 7359
3832, form_of_government, 6806
2168, adjoins, 5336
2168, adjoins, 7352
2168, adjoins, 6733
2168, form_of_government, 6806
2168, organization, 795
2168, organization, 7359
8020, adjoins, 11624
8020, form_of_government, 6806
8020, organization, 10179
2322, adjoins, 8211
2322, form_of_government, 6806
2322, organization, 795
2322, organization, 7359
13742, adjoins, 2030
13742, form_of_government, 6806
13742, organization, 795
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10271, award_winner, 7947
10271, award_winner, 10201
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1802, adjoins, 6702
4310, form_of_government, 6806
4310, organization, 795
4310, organization, 7359
4989, adjoins, 11624
4989, adjoins, 6702
4989, adjoins, 7449
4989, form_of_government, 6806
4989, organization, 795
4989, organization, 7359
4989, vacationer, 10201
1509, form_of_government, 6806
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4601, adjoins, 11252
4601, adjoins, 1509
4601, adjoins, 2030
4601, form_of_government, 6806
4601, organization, 795
4601, split_to, 4601
7023, award_nominee, 7947
7023, award_winner, 7947
31, adjoins, 4150
31, adjoins, 8271
31, adjoins, 13742
31, adjoins, 2030
31, form_of_government, 6806
31, organization, 795
31, organization, 7359
10531, film_release_region, 7976
2030, adjoins, 13742
2030, adjoins, 31
2030, form_of_government, 6806
2030, organization, 795
2030, organization, 7359
3457, citytown, 4410
3457, student, 12368
3087, place_of_death, 8204
6733, adjoins, 5336
6733, adjoins, 7352
6733, adjoins, 2168
6733, adjoins, 31
6733, adjoins, 6408
6733, exported_to, 31
6733, form_of_government, 6806
6733, organization, 795
6733, organization, 7359
6408, adjoins, 8271
6408, adjoins, 6733
Question: For what reason are Houston, Joseph_Haydn, and Presidential_system associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Houston",
"Joseph_Haydn",
"Presidential_system"
],
"valid_edges": [
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"13th_Screen_Actors_Guild_Awards",
"award_winner",
"Chandra_Wilson"
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[
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"Isaiah_Washington"
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[
"Angola",
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"Namibia"
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[
"Angola",
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"Zambia"
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[
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[
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"African_Union"
],
[
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"Angola"
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[
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"Sierra_Leone"
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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"Guatemala"
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[
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[
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"Eric_Dane",
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"Isaiah_Washington",
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"T._R._Knight"
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"Isaiah_Washington",
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"Isaiah_Washington",
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"Tinker_Bell:_Secret_of_the_Wings"
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"Jeff_Bennett",
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"Houston"
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[
"Joseph_Haydn",
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"Vienna"
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"Justin_Chambers",
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"Justin_Chambers",
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"Kate_Walsh",
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"Chandra_Wilson"
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[
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"CΓ΄te_dβIvoire"
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"Liberia",
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"Tanzania"
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[
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[
"Malawi",
"form_of_government",
"Presidential_system"
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[
"Malawi",
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"African_Union"
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[
"Malawi",
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"Commonwealth_of_Nations"
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[
"Maldives",
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"Presidential_system"
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[
"Maldives",
"organization",
"Commonwealth_of_Nations"
],
[
"Mali",
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"CΓ΄te_dβIvoire"
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[
"Michael_Nesmith",
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"United_States_Air_Force-GB"
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"Michael_Nesmith",
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"Houston"
],
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"Michael_Nesmith",
"place_of_birth",
"Houston"
],
[
"Mozambique",
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"Malawi"
],
[
"Mozambique",
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"Tanzania"
],
[
"Mozambique",
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],
[
"Mozambique",
"organization",
"African_Union"
],
[
"Mozambique",
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"Commonwealth_of_Nations"
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[
"Myanmar",
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],
[
"Namibia",
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"Angola"
],
[
"Namibia",
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],
[
"Namibia",
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"Zambia"
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[
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"Atlantic_Ocean"
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],
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"Nicaragua",
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"Nigeria",
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"Rwanda",
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"Sara_Ramirez",
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"Seychelles",
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"Sierra_Leone",
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"Atlantic_Ocean"
],
[
"Sierra_Leone",
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"Guinea"
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"Sierra_Leone",
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"Liberia"
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"Sierra_Leone",
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"Sierra_Leone",
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"Sierra_Leone",
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"Sierra_Leone",
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"Isaiah_Washington"
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],
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"South_Sudan",
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"African_Union"
],
[
"Sudan",
"adjoins",
"Chad"
],
[
"Sudan",
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[
"Sudan",
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[
"Sudan",
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"African_Union"
],
[
"Sudan",
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"Sudan"
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[
"T._R._Knight",
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"Chandra_Wilson"
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"T._R._Knight",
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[
"Tanzania",
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"Malawi"
],
[
"Tanzania",
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"Mozambique"
],
[
"Tanzania",
"adjoins",
"Rwanda"
],
[
"Tanzania",
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"Tanzania",
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],
[
"Tanzania",
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"African_Union"
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[
"Tanzania",
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"Commonwealth_of_Nations"
],
[
"Tinker_Bell:_Secret_of_the_Wings",
"film_release_region",
"El_Salvador"
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[
"Uganda",
"adjoins",
"Rwanda"
],
[
"Uganda",
"adjoins",
"Tanzania"
],
[
"Uganda",
"form_of_government",
"Presidential_system"
],
[
"Uganda",
"organization",
"African_Union"
],
[
"Uganda",
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"Commonwealth_of_Nations"
],
[
"University_of_Houston",
"citytown",
"Houston"
],
[
"University_of_Houston",
"student",
"Gene_Wolfe"
],
[
"W._H._Auden",
"place_of_death",
"Vienna"
],
[
"Zambia",
"adjoins",
"Angola"
],
[
"Zambia",
"adjoins",
"Botswana"
],
[
"Zambia",
"adjoins",
"Namibia"
],
[
"Zambia",
"adjoins",
"Tanzania"
],
[
"Zambia",
"adjoins",
"Zimbabwe"
],
[
"Zambia",
"exported_to",
"Tanzania"
],
[
"Zambia",
"form_of_government",
"Presidential_system"
],
[
"Zambia",
"organization",
"African_Union"
],
[
"Zambia",
"organization",
"Commonwealth_of_Nations"
],
[
"Zimbabwe",
"adjoins",
"Mozambique"
],
[
"Zimbabwe",
"adjoins",
"Zambia"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
14128, Atonement
606, Classical_guitar
7191, Corinne_Bailey_Rae
8906, James_McAvoy
4233, Mark_Gatiss
13078, Rebecca_Eaton
14206, Starter_for_10
8359, University_of_Leeds
src, edge_attr, dst
14128, award_winner, 8906
7191, role, 606
8906, acted_in, 14128
8906, acted_in, 14206
8906, nominated_for, 14128
4233, acted_in, 14206
4233, award_nominee, 13078
13078, award_nominee, 4233
8359, student, 7191
8359, student, 4233
Question: For what reason are Atonement, Classical_guitar, and Rebecca_Eaton associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Atonement",
"Classical_guitar",
"Rebecca_Eaton"
],
"valid_edges": [
[
"Atonement",
"award_winner",
"James_McAvoy"
],
[
"Corinne_Bailey_Rae",
"role",
"Classical_guitar"
],
[
"James_McAvoy",
"acted_in",
"Atonement"
],
[
"James_McAvoy",
"acted_in",
"Starter_for_10"
],
[
"James_McAvoy",
"nominated_for",
"Atonement"
],
[
"Mark_Gatiss",
"acted_in",
"Starter_for_10"
],
[
"Mark_Gatiss",
"award_nominee",
"Rebecca_Eaton"
],
[
"Rebecca_Eaton",
"award_nominee",
"Mark_Gatiss"
],
[
"University_of_Leeds",
"student",
"Corinne_Bailey_Rae"
],
[
"University_of_Leeds",
"student",
"Mark_Gatiss"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3490, Abraham_Lincoln
12194, African_National_Congress
8656, Al_Gore
2415, Arnold_Schwarzenegger
13869, Austria-Hungary
965, Austrians
4788, Barack_Obama
1650, Bill_Clinton
726, Charlton_Heston
14176, Chiang_Kai-shek
13160, Colin_Powell
6146, Croatian_language
9867, Czech_Language
10196, Daniel_Inouye
1389, Fidel_Castro
3582, Franklin_D._Roosevelt
13463, Franz_Kafka
10576, Franz_Schubert
5032, Fred_Thompson
9795, George_H._W._Bush
9111, George_W._Bush
12266, Gerald_Ford
4557, Grover_Cleveland
10097, Hillary_Rodham_Clinton
2235, Hungarian_language
5351, J._G._Ballard
9241, Jacob_Zuma
2897, James_A._Garfield
1052, James_Buchanan
13986, James_K._Polk
12074, James_Madison
14218, James_Monroe
10240, Jimmy_Carter
11633, Joe_Biden
9475, John_Adams
10524, John_C._Calhoun
3635, John_Conyers
183, John_Dingell
8206, John_F._Kennedy
9020, John_Kerry
8533, John_Quincy_Adams
12442, Law
9073, Lawyer
5638, Lewis_Cass
6943, Ludwig_Wittgenstein
2066, Lyndon_B._Johnson
4761, Mahatma_Gandhi
1372, Margaret_Thatcher
6037, Martin_Luther_King,_Jr.
7662, Methodism
3425, Michael_Haneke
8273, Naomi_Campbell
3141, Nelson_Mandela
10987, Nobel_Peace_Prize
4586, Pier_Paolo_Pasolini
541, Pierre_Trudeau
9403, Politician-GB
6721, Pope
1980, Presidential_Medal_of_Freedom
10508, Prostate_cancer
368, Richard_Nixon
4028, Robert_F._Kennedy
14107, Rome
12571, Ronald_Reagan
8070, Shirley_Temple
10281, Ted_Kennedy
5220, The_Queen
10214, Theodore_Roosevelt
9736, Tony_Blair
6075, Ulysses_S._Grant
7495, University_of_London
8204, Vienna
1230, Vladimir_Lenin
7397, We_Have_a_Pope
8959, White_American
7725, William_McKinley
2439, Wolfgang_Amadeus_Mozart
14132, Woodrow_Wilson
8351, Yasser_Arafat
src, edge_attr, dst
3490, profession, 9073
3490, profession, 9403
12194, party_politician, 9241
12194, party_politician, 3141
8656, profession, 9403
2415, participant, 9111
2415, profession, 9403
13869, official_language, 6146
13869, official_language, 9867
13869, official_language, 2235
965, languages_spoken, 6146
965, languages_spoken, 9867
965, languages_spoken, 2235
965, people, 2415
965, people, 10576
965, people, 3425
965, people, 2439
4788, profession, 9073
4788, profession, 9403
1650, profession, 9073
1650, profession, 9403
14176, profession, 9403
14176, religion, 7662
13160, profession, 9403
10196, profession, 9403
10196, religion, 7662
1389, profession, 9073
1389, profession, 9403
3582, profession, 9073
3582, profession, 9403
13463, profession, 9073
10576, influenced_by, 2439
10576, place_of_death, 8204
5032, profession, 9073
5032, profession, 9403
9795, profession, 9403
9111, participant, 2415
9111, profession, 9403
12266, profession, 9073
12266, profession, 9403
4557, profession, 9073
4557, profession, 9403
10097, profession, 9073
10097, profession, 9403
10097, religion, 7662
9241, profession, 9403
2897, profession, 9073
2897, profession, 9403
1052, profession, 9073
1052, profession, 9403
13986, profession, 9073
13986, profession, 9403
13986, religion, 7662
12074, profession, 9073
12074, profession, 9403
14218, profession, 9073
14218, profession, 9403
10240, profession, 9403
11633, profession, 9073
11633, profession, 9403
9475, profession, 9073
9475, profession, 9403
10524, profession, 9073
10524, profession, 9403
3635, profession, 9073
3635, profession, 9403
183, profession, 9073
183, profession, 9403
8206, profession, 9403
9020, profession, 9073
9020, profession, 9403
8533, profession, 9073
8533, profession, 9403
12442, split_to, 9073
12442, student, 4761
5638, profession, 9073
5638, profession, 9403
2066, profession, 9403
4761, profession, 9073
4761, profession, 9403
1372, profession, 9073
1372, profession, 9403
1372, religion, 7662
6037, influenced_by, 4761
3425, influenced_by, 13463
3425, influenced_by, 6943
3425, influenced_by, 4586
8273, location, 14107
8273, participant, 3141
3141, award_winner, 8351
3141, influenced_by, 4761
3141, organizations_founded, 12194
3141, participant, 8273
3141, profession, 9073
3141, profession, 9403
3141, religion, 7662
10987, award_winner, 8656
10987, award_winner, 4788
10987, award_winner, 10240
10987, award_winner, 6037
10987, award_winner, 3141
10987, award_winner, 10214
10987, award_winner, 14132
10987, award_winner, 8351
4586, profession, 9403
541, profession, 9073
541, profession, 9403
6721, films, 7397
1980, award_winner, 726
1980, award_winner, 13160
1980, award_winner, 9795
1980, award_winner, 12266
1980, award_winner, 10240
1980, award_winner, 8206
1980, award_winner, 2066
1980, award_winner, 1372
1980, award_winner, 6037
1980, award_winner, 3141
1980, award_winner, 12571
1980, award_winner, 10281
1980, award_winner, 9736
10508, notable_people_with_this_condition, 9020
10508, notable_people_with_this_condition, 3141
10508, people, 726
10508, people, 5351
10508, people, 6943
10508, people, 541
368, profession, 9073
368, profession, 9403
4028, profession, 9073
4028, profession, 9403
12571, profession, 9403
8070, profession, 9403
8070, religion, 7662
10281, profession, 9073
10281, profession, 9403
5220, person, 1650
5220, person, 3141
10214, profession, 9403
9736, profession, 9073
9736, profession, 9403
6075, profession, 9403
6075, religion, 7662
7495, campuses, 7495
7495, major_field_of_study, 12442
7495, student, 5351
7495, student, 3141
1230, profession, 9073
1230, profession, 9403
7397, featured_film_locations, 14107
8959, languages_spoken, 6146
8959, languages_spoken, 9867
8959, languages_spoken, 2235
7725, profession, 9073
7725, profession, 9403
7725, religion, 7662
2439, location, 8204
2439, place_of_death, 8204
14132, profession, 9073
14132, profession, 9403
8351, award_winner, 3141
8351, profession, 9403
Question: In what context are Austrians, Nelson_Mandela, and Pope connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Austrians",
"Nelson_Mandela",
"Pope"
],
"valid_edges": [
[
"Abraham_Lincoln",
"profession",
"Lawyer"
],
[
"Abraham_Lincoln",
"profession",
"Politician-GB"
],
[
"African_National_Congress",
"party_politician",
"Jacob_Zuma"
],
[
"African_National_Congress",
"party_politician",
"Nelson_Mandela"
],
[
"Al_Gore",
"profession",
"Politician-GB"
],
[
"Arnold_Schwarzenegger",
"participant",
"George_W._Bush"
],
[
"Arnold_Schwarzenegger",
"profession",
"Politician-GB"
],
[
"Austria-Hungary",
"official_language",
"Croatian_language"
],
[
"Austria-Hungary",
"official_language",
"Czech_Language"
],
[
"Austria-Hungary",
"official_language",
"Hungarian_language"
],
[
"Austrians",
"languages_spoken",
"Croatian_language"
],
[
"Austrians",
"languages_spoken",
"Czech_Language"
],
[
"Austrians",
"languages_spoken",
"Hungarian_language"
],
[
"Austrians",
"people",
"Arnold_Schwarzenegger"
],
[
"Austrians",
"people",
"Franz_Schubert"
],
[
"Austrians",
"people",
"Michael_Haneke"
],
[
"Austrians",
"people",
"Wolfgang_Amadeus_Mozart"
],
[
"Barack_Obama",
"profession",
"Lawyer"
],
[
"Barack_Obama",
"profession",
"Politician-GB"
],
[
"Bill_Clinton",
"profession",
"Lawyer"
],
[
"Bill_Clinton",
"profession",
"Politician-GB"
],
[
"Chiang_Kai-shek",
"profession",
"Politician-GB"
],
[
"Chiang_Kai-shek",
"religion",
"Methodism"
],
[
"Colin_Powell",
"profession",
"Politician-GB"
],
[
"Daniel_Inouye",
"profession",
"Politician-GB"
],
[
"Daniel_Inouye",
"religion",
"Methodism"
],
[
"Fidel_Castro",
"profession",
"Lawyer"
],
[
"Fidel_Castro",
"profession",
"Politician-GB"
],
[
"Franklin_D._Roosevelt",
"profession",
"Lawyer"
],
[
"Franklin_D._Roosevelt",
"profession",
"Politician-GB"
],
[
"Franz_Kafka",
"profession",
"Lawyer"
],
[
"Franz_Schubert",
"influenced_by",
"Wolfgang_Amadeus_Mozart"
],
[
"Franz_Schubert",
"place_of_death",
"Vienna"
],
[
"Fred_Thompson",
"profession",
"Lawyer"
],
[
"Fred_Thompson",
"profession",
"Politician-GB"
],
[
"George_H._W._Bush",
"profession",
"Politician-GB"
],
[
"George_W._Bush",
"participant",
"Arnold_Schwarzenegger"
],
[
"George_W._Bush",
"profession",
"Politician-GB"
],
[
"Gerald_Ford",
"profession",
"Lawyer"
],
[
"Gerald_Ford",
"profession",
"Politician-GB"
],
[
"Grover_Cleveland",
"profession",
"Lawyer"
],
[
"Grover_Cleveland",
"profession",
"Politician-GB"
],
[
"Hillary_Rodham_Clinton",
"profession",
"Lawyer"
],
[
"Hillary_Rodham_Clinton",
"profession",
"Politician-GB"
],
[
"Hillary_Rodham_Clinton",
"religion",
"Methodism"
],
[
"Jacob_Zuma",
"profession",
"Politician-GB"
],
[
"James_A._Garfield",
"profession",
"Lawyer"
],
[
"James_A._Garfield",
"profession",
"Politician-GB"
],
[
"James_Buchanan",
"profession",
"Lawyer"
],
[
"James_Buchanan",
"profession",
"Politician-GB"
],
[
"James_K._Polk",
"profession",
"Lawyer"
],
[
"James_K._Polk",
"profession",
"Politician-GB"
],
[
"James_K._Polk",
"religion",
"Methodism"
],
[
"James_Madison",
"profession",
"Lawyer"
],
[
"James_Madison",
"profession",
"Politician-GB"
],
[
"James_Monroe",
"profession",
"Lawyer"
],
[
"James_Monroe",
"profession",
"Politician-GB"
],
[
"Jimmy_Carter",
"profession",
"Politician-GB"
],
[
"Joe_Biden",
"profession",
"Lawyer"
],
[
"Joe_Biden",
"profession",
"Politician-GB"
],
[
"John_Adams",
"profession",
"Lawyer"
],
[
"John_Adams",
"profession",
"Politician-GB"
],
[
"John_C._Calhoun",
"profession",
"Lawyer"
],
[
"John_C._Calhoun",
"profession",
"Politician-GB"
],
[
"John_Conyers",
"profession",
"Lawyer"
],
[
"John_Conyers",
"profession",
"Politician-GB"
],
[
"John_Dingell",
"profession",
"Lawyer"
],
[
"John_Dingell",
"profession",
"Politician-GB"
],
[
"John_F._Kennedy",
"profession",
"Politician-GB"
],
[
"John_Kerry",
"profession",
"Lawyer"
],
[
"John_Kerry",
"profession",
"Politician-GB"
],
[
"John_Quincy_Adams",
"profession",
"Lawyer"
],
[
"John_Quincy_Adams",
"profession",
"Politician-GB"
],
[
"Law",
"split_to",
"Lawyer"
],
[
"Law",
"student",
"Mahatma_Gandhi"
],
[
"Lewis_Cass",
"profession",
"Lawyer"
],
[
"Lewis_Cass",
"profession",
"Politician-GB"
],
[
"Lyndon_B._Johnson",
"profession",
"Politician-GB"
],
[
"Mahatma_Gandhi",
"profession",
"Lawyer"
],
[
"Mahatma_Gandhi",
"profession",
"Politician-GB"
],
[
"Margaret_Thatcher",
"profession",
"Lawyer"
],
[
"Margaret_Thatcher",
"profession",
"Politician-GB"
],
[
"Margaret_Thatcher",
"religion",
"Methodism"
],
[
"Martin_Luther_King,_Jr.",
"influenced_by",
"Mahatma_Gandhi"
],
[
"Michael_Haneke",
"influenced_by",
"Franz_Kafka"
],
[
"Michael_Haneke",
"influenced_by",
"Ludwig_Wittgenstein"
],
[
"Michael_Haneke",
"influenced_by",
"Pier_Paolo_Pasolini"
],
[
"Naomi_Campbell",
"location",
"Rome"
],
[
"Naomi_Campbell",
"participant",
"Nelson_Mandela"
],
[
"Nelson_Mandela",
"award_winner",
"Yasser_Arafat"
],
[
"Nelson_Mandela",
"influenced_by",
"Mahatma_Gandhi"
],
[
"Nelson_Mandela",
"organizations_founded",
"African_National_Congress"
],
[
"Nelson_Mandela",
"participant",
"Naomi_Campbell"
],
[
"Nelson_Mandela",
"profession",
"Lawyer"
],
[
"Nelson_Mandela",
"profession",
"Politician-GB"
],
[
"Nelson_Mandela",
"religion",
"Methodism"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Al_Gore"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Barack_Obama"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Jimmy_Carter"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Martin_Luther_King,_Jr."
],
[
"Nobel_Peace_Prize",
"award_winner",
"Nelson_Mandela"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Theodore_Roosevelt"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Woodrow_Wilson"
],
[
"Nobel_Peace_Prize",
"award_winner",
"Yasser_Arafat"
],
[
"Pier_Paolo_Pasolini",
"profession",
"Politician-GB"
],
[
"Pierre_Trudeau",
"profession",
"Lawyer"
],
[
"Pierre_Trudeau",
"profession",
"Politician-GB"
],
[
"Pope",
"films",
"We_Have_a_Pope"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Charlton_Heston"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Colin_Powell"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"George_H._W._Bush"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Gerald_Ford"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Jimmy_Carter"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"John_F._Kennedy"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Lyndon_B._Johnson"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Margaret_Thatcher"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Martin_Luther_King,_Jr."
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Nelson_Mandela"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Ronald_Reagan"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Ted_Kennedy"
],
[
"Presidential_Medal_of_Freedom",
"award_winner",
"Tony_Blair"
],
[
"Prostate_cancer",
"notable_people_with_this_condition",
"John_Kerry"
],
[
"Prostate_cancer",
"notable_people_with_this_condition",
"Nelson_Mandela"
],
[
"Prostate_cancer",
"people",
"Charlton_Heston"
],
[
"Prostate_cancer",
"people",
"J._G._Ballard"
],
[
"Prostate_cancer",
"people",
"Ludwig_Wittgenstein"
],
[
"Prostate_cancer",
"people",
"Pierre_Trudeau"
],
[
"Richard_Nixon",
"profession",
"Lawyer"
],
[
"Richard_Nixon",
"profession",
"Politician-GB"
],
[
"Robert_F._Kennedy",
"profession",
"Lawyer"
],
[
"Robert_F._Kennedy",
"profession",
"Politician-GB"
],
[
"Ronald_Reagan",
"profession",
"Politician-GB"
],
[
"Shirley_Temple",
"profession",
"Politician-GB"
],
[
"Shirley_Temple",
"religion",
"Methodism"
],
[
"Ted_Kennedy",
"profession",
"Lawyer"
],
[
"Ted_Kennedy",
"profession",
"Politician-GB"
],
[
"The_Queen",
"person",
"Bill_Clinton"
],
[
"The_Queen",
"person",
"Nelson_Mandela"
],
[
"Theodore_Roosevelt",
"profession",
"Politician-GB"
],
[
"Tony_Blair",
"profession",
"Lawyer"
],
[
"Tony_Blair",
"profession",
"Politician-GB"
],
[
"Ulysses_S._Grant",
"profession",
"Politician-GB"
],
[
"Ulysses_S._Grant",
"religion",
"Methodism"
],
[
"University_of_London",
"campuses",
"University_of_London"
],
[
"University_of_London",
"major_field_of_study",
"Law"
],
[
"University_of_London",
"student",
"J._G._Ballard"
],
[
"University_of_London",
"student",
"Nelson_Mandela"
],
[
"Vladimir_Lenin",
"profession",
"Lawyer"
],
[
"Vladimir_Lenin",
"profession",
"Politician-GB"
],
[
"We_Have_a_Pope",
"featured_film_locations",
"Rome"
],
[
"White_American",
"languages_spoken",
"Croatian_language"
],
[
"White_American",
"languages_spoken",
"Czech_Language"
],
[
"White_American",
"languages_spoken",
"Hungarian_language"
],
[
"William_McKinley",
"profession",
"Lawyer"
],
[
"William_McKinley",
"profession",
"Politician-GB"
],
[
"William_McKinley",
"religion",
"Methodism"
],
[
"Wolfgang_Amadeus_Mozart",
"location",
"Vienna"
],
[
"Wolfgang_Amadeus_Mozart",
"place_of_death",
"Vienna"
],
[
"Woodrow_Wilson",
"profession",
"Lawyer"
],
[
"Woodrow_Wilson",
"profession",
"Politician-GB"
],
[
"Yasser_Arafat",
"award_winner",
"Nelson_Mandela"
],
[
"Yasser_Arafat",
"profession",
"Politician-GB"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7226, A_Better_Tomorrow
7377, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography
1407, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design
3877, Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing
8528, American_Zoetrope
14101, An_Alan_Smithee_Film:_Burn_Hollywood_Burn
9616, Anchor_Bay_Entertainment
4691, Angelina_Jolie
1431, Assassins
2532, Bachelor_of_Fine_Arts
278, Being_There
2225, British_Independent_Film_Award_for_Best_British_Independent_Film
8008, Cantonese
2840, Carol_Spier
13081, Cliffhanger
2808, Cobra
8201, Columbus
3997, Columbus_Crew
12407, David_Cronenberg
516, Daylight
6360, Dead_Ringers
1123, Demolition_Man
1163, Eastern_Promises
7388, Film
10035, Focus_Features
9457, Genie_Award_for_Best_Achievement_in_Art_Direction/Production_Design
12240, Genie_Award_for_Best_Achievement_in_Overall_Sound
8217, Hong_Kong_Film_Award_for_Best_Cinematography
5936, Hong_Kong_Film_Award_for_Best_Director
6260, Hong_Kong_Film_Award_for_Best_Film
8501, Hong_Kong_Film_Award_for_Best_New_Performer
8997, Hong_Kong_Film_Award_for_Best_Supporting_Actor
13587, Howard_Shore
4578, James_G._Robinson
10245, Jonathan_Glickman
11749, Judge_Dredd
2758, Limitless
7497, Lock_Up
10606, Lorimar_Television
9954, Master_of_Fine_Arts
12675, Michigan
11171, Morgan_Creek_Productions
590, Ohio
4208, Oscar
3645, Over_the_Top
12495, Photography
7152, Political_drama
3978, Psychological_thriller
11758, Rambo:_First_Blood_Part_II
1580, Rambo_III
4175, Relativity_Media
4351, Rhinestone
8166, Rocky_IV
2263, Rocky_V
12492, Rogue
5453, Russian_Language
7522, Samuel_Goldwyn_Films
9211, Set_decorator-GB
1719, Sociology
9044, Stop!_Or_My_Mom_Will_Shoot
8378, StudioCanal
3540, Superman_IV:_The_Quest_For_Peace
9977, Sylvester_Stallone
4387, Tango_&_Cash
9489, Texas_Instruments
3534, The_Cannon_Group
4934, The_Good_Shepherd
11832, The_Specialist
9526, The_Tourist
12168, The_Whistleblower
2564, TriStar_Pictures
1924, United_Artists
1480, University_of_Michigan
src, edge_attr, dst
7226, award_honor_award, 6260
7226, language, 8008
7377, nominated_for, 6360
7377, nominated_for, 1163
1407, nominated_for, 6360
1407, nominated_for, 1163
3877, nominated_for, 6360
8528, industry, 7388
14101, honored_for, 1580
14101, honored_for, 8166
9616, film, 7226
9616, film, 6360
9616, industry, 7388
9616, state_province_region, 12675
4691, acted_in, 9526
4691, nominated_for, 9526
1431, honored_for, 8166
2532, institution, 1480
2532, major_field_of_study, 7388
278, language, 5453
278, production_companies, 10606
2225, disciplines_or_subjects, 7388
2225, nominated_for, 1163
2840, nominated_for, 6360
2840, nominated_for, 1163
13081, honored_for, 1580
13081, honored_for, 8166
2808, honored_for, 1580
2808, honored_for, 8166
2808, nominated_for, 1580
8201, place, 8201
8201, teams, 3997
12407, film, 6360
12407, film, 1163
12407, nominated_for, 6360
516, honored_for, 8166
6360, award_honor_award, 7377
6360, award_honor_award, 3877
6360, award_honor_award, 9457
6360, award_winner, 2840
6360, award_winner, 12407
6360, award_winner, 13587
6360, film_music, 13587
6360, film_production_design_by, 2840
6360, genre, 3978
6360, produced_by, 12407
6360, produced_by, 4578
6360, production_companies, 11171
6360, written_by, 12407
1123, honored_for, 1580
1123, honored_for, 8166
1163, award_honor_award, 3877
1163, award_honor_award, 12240
1163, award_winner, 13587
1163, film_music, 13587
1163, film_production_design_by, 2840
1163, language, 5453
1163, production_companies, 10035
7388, major_field_of_study, 1719
7388, student, 4691
10035, film, 1163
10035, industry, 7388
10035, nominated_for, 1163
9457, nominated_for, 1163
12240, nominated_for, 6360
12240, nominated_for, 1163
8217, disciplines_or_subjects, 7388
8217, nominated_for, 7226
5936, disciplines_or_subjects, 7388
5936, nominated_for, 7226
6260, disciplines_or_subjects, 7388
6260, nominated_for, 7226
8501, disciplines_or_subjects, 7388
8501, nominated_for, 7226
8997, disciplines_or_subjects, 7388
8997, nominated_for, 7226
13587, nominated_for, 6360
13587, nominated_for, 1163
10245, nominated_for, 9526
11749, honored_for, 1580
11749, honored_for, 8166
2758, genre, 3978
2758, language, 5453
2758, production_companies, 4175
2758, production_companies, 12492
7497, honored_for, 1580
7497, honored_for, 8166
10606, industry, 7388
9954, institution, 1480
9954, major_field_of_study, 7388
12675, contains, 1480
590, adjoins, 12675
590, capital, 8201
590, contains, 8201
4208, honored_for, 1580
3645, honored_for, 1580
3645, nominated_for, 1580
3645, nominated_for, 8166
12495, major_field_of_study, 7388
7152, titles, 8166
7152, titles, 4934
3978, titles, 6360
11758, honored_for, 1580
11758, honored_for, 8166
11758, nominated_for, 1580
11758, nominated_for, 8166
1580, award_winner, 9977
1580, honored_for, 14101
1580, honored_for, 1431
1580, honored_for, 13081
1580, honored_for, 2808
1580, honored_for, 516
1580, honored_for, 11749
1580, honored_for, 7497
1580, honored_for, 4208
1580, honored_for, 3645
1580, honored_for, 11758
1580, honored_for, 4351
1580, honored_for, 8166
1580, honored_for, 2263
1580, honored_for, 9044
1580, honored_for, 4387
1580, honored_for, 11832
1580, language, 5453
1580, nominated_for, 3645
1580, nominated_for, 11758
1580, nominated_for, 4351
1580, nominated_for, 4387
1580, prequel, 11758
1580, production_companies, 2564
1580, written_by, 9977
4175, film, 2758
4175, industry, 7388
4351, honored_for, 1580
4351, honored_for, 8166
4351, nominated_for, 1580
4351, nominated_for, 8166
8166, award_winner, 9977
8166, genre, 7152
8166, honored_for, 14101
8166, honored_for, 1431
8166, honored_for, 13081
8166, honored_for, 2808
8166, honored_for, 516
8166, honored_for, 11749
8166, honored_for, 4208
8166, honored_for, 3645
8166, honored_for, 11758
8166, honored_for, 1580
8166, honored_for, 2263
8166, honored_for, 11832
8166, language, 5453
8166, nominated_for, 2808
8166, nominated_for, 7497
8166, nominated_for, 3645
8166, nominated_for, 11758
8166, nominated_for, 1580
8166, nominated_for, 4351
8166, nominated_for, 2263
8166, production_companies, 1924
2263, honored_for, 1580
2263, honored_for, 8166
2263, nominated_for, 8166
2263, prequel, 8166
12492, film, 2758
12492, industry, 7388
7522, film, 12168
7522, industry, 7388
1719, major_field_of_study, 7388
9044, honored_for, 1580
9044, honored_for, 8166
8378, industry, 7388
3540, language, 5453
9977, acted_in, 1580
9977, acted_in, 8166
9977, film, 8166
9977, nominated_for, 1580
9977, nominated_for, 8166
4387, honored_for, 1580
4387, nominated_for, 1580
4387, nominated_for, 8166
9489, service_language, 8008
9489, service_language, 5453
3534, film, 3540
3534, industry, 7388
4934, award_winner, 4691
4934, genre, 7152
4934, language, 5453
4934, produced_by, 4578
4934, production_companies, 8528
4934, production_companies, 11171
11832, honored_for, 1580
11832, honored_for, 8166
9526, film_crew_role, 9211
9526, language, 5453
9526, produced_by, 10245
9526, production_companies, 4175
9526, production_companies, 8378
12168, film_crew_role, 9211
12168, language, 5453
2564, film, 1580
2564, industry, 7388
1924, film, 278
1480, educational_institution, 1480
1480, major_field_of_study, 12495
1480, major_field_of_study, 5453
1480, major_field_of_study, 1719
1480, student, 10245
Question: How are Anchor_Bay_Entertainment, Columbus_Crew, and Russian_Language related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Anchor_Bay_Entertainment",
"Columbus_Crew",
"Russian_Language"
],
"valid_edges": [
[
"A_Better_Tomorrow",
"award_honor_award",
"Hong_Kong_Film_Award_for_Best_Film"
],
[
"A_Better_Tomorrow",
"language",
"Cantonese"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Dead_Ringers"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography",
"nominated_for",
"Eastern_Promises"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design",
"nominated_for",
"Dead_Ringers"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Costume_Design",
"nominated_for",
"Eastern_Promises"
],
[
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing",
"nominated_for",
"Dead_Ringers"
],
[
"American_Zoetrope",
"industry",
"Film"
],
[
"An_Alan_Smithee_Film:_Burn_Hollywood_Burn",
"honored_for",
"Rambo_III"
],
[
"An_Alan_Smithee_Film:_Burn_Hollywood_Burn",
"honored_for",
"Rocky_IV"
],
[
"Anchor_Bay_Entertainment",
"film",
"A_Better_Tomorrow"
],
[
"Anchor_Bay_Entertainment",
"film",
"Dead_Ringers"
],
[
"Anchor_Bay_Entertainment",
"industry",
"Film"
],
[
"Anchor_Bay_Entertainment",
"state_province_region",
"Michigan"
],
[
"Angelina_Jolie",
"acted_in",
"The_Tourist"
],
[
"Angelina_Jolie",
"nominated_for",
"The_Tourist"
],
[
"Assassins",
"honored_for",
"Rocky_IV"
],
[
"Bachelor_of_Fine_Arts",
"institution",
"University_of_Michigan"
],
[
"Bachelor_of_Fine_Arts",
"major_field_of_study",
"Film"
],
[
"Being_There",
"language",
"Russian_Language"
],
[
"Being_There",
"production_companies",
"Lorimar_Television"
],
[
"British_Independent_Film_Award_for_Best_British_Independent_Film",
"disciplines_or_subjects",
"Film"
],
[
"British_Independent_Film_Award_for_Best_British_Independent_Film",
"nominated_for",
"Eastern_Promises"
],
[
"Carol_Spier",
"nominated_for",
"Dead_Ringers"
],
[
"Carol_Spier",
"nominated_for",
"Eastern_Promises"
],
[
"Cliffhanger",
"honored_for",
"Rambo_III"
],
[
"Cliffhanger",
"honored_for",
"Rocky_IV"
],
[
"Cobra",
"honored_for",
"Rambo_III"
],
[
"Cobra",
"honored_for",
"Rocky_IV"
],
[
"Cobra",
"nominated_for",
"Rambo_III"
],
[
"Columbus",
"place",
"Columbus"
],
[
"Columbus",
"teams",
"Columbus_Crew"
],
[
"David_Cronenberg",
"film",
"Dead_Ringers"
],
[
"David_Cronenberg",
"film",
"Eastern_Promises"
],
[
"David_Cronenberg",
"nominated_for",
"Dead_Ringers"
],
[
"Daylight",
"honored_for",
"Rocky_IV"
],
[
"Dead_Ringers",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Cinematography"
],
[
"Dead_Ringers",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing"
],
[
"Dead_Ringers",
"award_honor_award",
"Genie_Award_for_Best_Achievement_in_Art_Direction/Production_Design"
],
[
"Dead_Ringers",
"award_winner",
"Carol_Spier"
],
[
"Dead_Ringers",
"award_winner",
"David_Cronenberg"
],
[
"Dead_Ringers",
"award_winner",
"Howard_Shore"
],
[
"Dead_Ringers",
"film_music",
"Howard_Shore"
],
[
"Dead_Ringers",
"film_production_design_by",
"Carol_Spier"
],
[
"Dead_Ringers",
"genre",
"Psychological_thriller"
],
[
"Dead_Ringers",
"produced_by",
"David_Cronenberg"
],
[
"Dead_Ringers",
"produced_by",
"James_G._Robinson"
],
[
"Dead_Ringers",
"production_companies",
"Morgan_Creek_Productions"
],
[
"Dead_Ringers",
"written_by",
"David_Cronenberg"
],
[
"Demolition_Man",
"honored_for",
"Rambo_III"
],
[
"Demolition_Man",
"honored_for",
"Rocky_IV"
],
[
"Eastern_Promises",
"award_honor_award",
"Academy_of_Canadian_Cinema_and_Television_Award_for_Best_Achievement_in_Sound_Editing"
],
[
"Eastern_Promises",
"award_honor_award",
"Genie_Award_for_Best_Achievement_in_Overall_Sound"
],
[
"Eastern_Promises",
"award_winner",
"Howard_Shore"
],
[
"Eastern_Promises",
"film_music",
"Howard_Shore"
],
[
"Eastern_Promises",
"film_production_design_by",
"Carol_Spier"
],
[
"Eastern_Promises",
"language",
"Russian_Language"
],
[
"Eastern_Promises",
"production_companies",
"Focus_Features"
],
[
"Film",
"major_field_of_study",
"Sociology"
],
[
"Film",
"student",
"Angelina_Jolie"
],
[
"Focus_Features",
"film",
"Eastern_Promises"
],
[
"Focus_Features",
"industry",
"Film"
],
[
"Focus_Features",
"nominated_for",
"Eastern_Promises"
],
[
"Genie_Award_for_Best_Achievement_in_Art_Direction/Production_Design",
"nominated_for",
"Eastern_Promises"
],
[
"Genie_Award_for_Best_Achievement_in_Overall_Sound",
"nominated_for",
"Dead_Ringers"
],
[
"Genie_Award_for_Best_Achievement_in_Overall_Sound",
"nominated_for",
"Eastern_Promises"
],
[
"Hong_Kong_Film_Award_for_Best_Cinematography",
"disciplines_or_subjects",
"Film"
],
[
"Hong_Kong_Film_Award_for_Best_Cinematography",
"nominated_for",
"A_Better_Tomorrow"
],
[
"Hong_Kong_Film_Award_for_Best_Director",
"disciplines_or_subjects",
"Film"
],
[
"Hong_Kong_Film_Award_for_Best_Director",
"nominated_for",
"A_Better_Tomorrow"
],
[
"Hong_Kong_Film_Award_for_Best_Film",
"disciplines_or_subjects",
"Film"
],
[
"Hong_Kong_Film_Award_for_Best_Film",
"nominated_for",
"A_Better_Tomorrow"
],
[
"Hong_Kong_Film_Award_for_Best_New_Performer",
"disciplines_or_subjects",
"Film"
],
[
"Hong_Kong_Film_Award_for_Best_New_Performer",
"nominated_for",
"A_Better_Tomorrow"
],
[
"Hong_Kong_Film_Award_for_Best_Supporting_Actor",
"disciplines_or_subjects",
"Film"
],
[
"Hong_Kong_Film_Award_for_Best_Supporting_Actor",
"nominated_for",
"A_Better_Tomorrow"
],
[
"Howard_Shore",
"nominated_for",
"Dead_Ringers"
],
[
"Howard_Shore",
"nominated_for",
"Eastern_Promises"
],
[
"Jonathan_Glickman",
"nominated_for",
"The_Tourist"
],
[
"Judge_Dredd",
"honored_for",
"Rambo_III"
],
[
"Judge_Dredd",
"honored_for",
"Rocky_IV"
],
[
"Limitless",
"genre",
"Psychological_thriller"
],
[
"Limitless",
"language",
"Russian_Language"
],
[
"Limitless",
"production_companies",
"Relativity_Media"
],
[
"Limitless",
"production_companies",
"Rogue"
],
[
"Lock_Up",
"honored_for",
"Rambo_III"
],
[
"Lock_Up",
"honored_for",
"Rocky_IV"
],
[
"Lorimar_Television",
"industry",
"Film"
],
[
"Master_of_Fine_Arts",
"institution",
"University_of_Michigan"
],
[
"Master_of_Fine_Arts",
"major_field_of_study",
"Film"
],
[
"Michigan",
"contains",
"University_of_Michigan"
],
[
"Ohio",
"adjoins",
"Michigan"
],
[
"Ohio",
"capital",
"Columbus"
],
[
"Ohio",
"contains",
"Columbus"
],
[
"Oscar",
"honored_for",
"Rambo_III"
],
[
"Over_the_Top",
"honored_for",
"Rambo_III"
],
[
"Over_the_Top",
"nominated_for",
"Rambo_III"
],
[
"Over_the_Top",
"nominated_for",
"Rocky_IV"
],
[
"Photography",
"major_field_of_study",
"Film"
],
[
"Political_drama",
"titles",
"Rocky_IV"
],
[
"Political_drama",
"titles",
"The_Good_Shepherd"
],
[
"Psychological_thriller",
"titles",
"Dead_Ringers"
],
[
"Rambo:_First_Blood_Part_II",
"honored_for",
"Rambo_III"
],
[
"Rambo:_First_Blood_Part_II",
"honored_for",
"Rocky_IV"
],
[
"Rambo:_First_Blood_Part_II",
"nominated_for",
"Rambo_III"
],
[
"Rambo:_First_Blood_Part_II",
"nominated_for",
"Rocky_IV"
],
[
"Rambo_III",
"award_winner",
"Sylvester_Stallone"
],
[
"Rambo_III",
"honored_for",
"An_Alan_Smithee_Film:_Burn_Hollywood_Burn"
],
[
"Rambo_III",
"honored_for",
"Assassins"
],
[
"Rambo_III",
"honored_for",
"Cliffhanger"
],
[
"Rambo_III",
"honored_for",
"Cobra"
],
[
"Rambo_III",
"honored_for",
"Daylight"
],
[
"Rambo_III",
"honored_for",
"Judge_Dredd"
],
[
"Rambo_III",
"honored_for",
"Lock_Up"
],
[
"Rambo_III",
"honored_for",
"Oscar"
],
[
"Rambo_III",
"honored_for",
"Over_the_Top"
],
[
"Rambo_III",
"honored_for",
"Rambo:_First_Blood_Part_II"
],
[
"Rambo_III",
"honored_for",
"Rhinestone"
],
[
"Rambo_III",
"honored_for",
"Rocky_IV"
],
[
"Rambo_III",
"honored_for",
"Rocky_V"
],
[
"Rambo_III",
"honored_for",
"Stop!_Or_My_Mom_Will_Shoot"
],
[
"Rambo_III",
"honored_for",
"Tango_&_Cash"
],
[
"Rambo_III",
"honored_for",
"The_Specialist"
],
[
"Rambo_III",
"language",
"Russian_Language"
],
[
"Rambo_III",
"nominated_for",
"Over_the_Top"
],
[
"Rambo_III",
"nominated_for",
"Rambo:_First_Blood_Part_II"
],
[
"Rambo_III",
"nominated_for",
"Rhinestone"
],
[
"Rambo_III",
"nominated_for",
"Tango_&_Cash"
],
[
"Rambo_III",
"prequel",
"Rambo:_First_Blood_Part_II"
],
[
"Rambo_III",
"production_companies",
"TriStar_Pictures"
],
[
"Rambo_III",
"written_by",
"Sylvester_Stallone"
],
[
"Relativity_Media",
"film",
"Limitless"
],
[
"Relativity_Media",
"industry",
"Film"
],
[
"Rhinestone",
"honored_for",
"Rambo_III"
],
[
"Rhinestone",
"honored_for",
"Rocky_IV"
],
[
"Rhinestone",
"nominated_for",
"Rambo_III"
],
[
"Rhinestone",
"nominated_for",
"Rocky_IV"
],
[
"Rocky_IV",
"award_winner",
"Sylvester_Stallone"
],
[
"Rocky_IV",
"genre",
"Political_drama"
],
[
"Rocky_IV",
"honored_for",
"An_Alan_Smithee_Film:_Burn_Hollywood_Burn"
],
[
"Rocky_IV",
"honored_for",
"Assassins"
],
[
"Rocky_IV",
"honored_for",
"Cliffhanger"
],
[
"Rocky_IV",
"honored_for",
"Cobra"
],
[
"Rocky_IV",
"honored_for",
"Daylight"
],
[
"Rocky_IV",
"honored_for",
"Judge_Dredd"
],
[
"Rocky_IV",
"honored_for",
"Oscar"
],
[
"Rocky_IV",
"honored_for",
"Over_the_Top"
],
[
"Rocky_IV",
"honored_for",
"Rambo:_First_Blood_Part_II"
],
[
"Rocky_IV",
"honored_for",
"Rambo_III"
],
[
"Rocky_IV",
"honored_for",
"Rocky_V"
],
[
"Rocky_IV",
"honored_for",
"The_Specialist"
],
[
"Rocky_IV",
"language",
"Russian_Language"
],
[
"Rocky_IV",
"nominated_for",
"Cobra"
],
[
"Rocky_IV",
"nominated_for",
"Lock_Up"
],
[
"Rocky_IV",
"nominated_for",
"Over_the_Top"
],
[
"Rocky_IV",
"nominated_for",
"Rambo:_First_Blood_Part_II"
],
[
"Rocky_IV",
"nominated_for",
"Rambo_III"
],
[
"Rocky_IV",
"nominated_for",
"Rhinestone"
],
[
"Rocky_IV",
"nominated_for",
"Rocky_V"
],
[
"Rocky_IV",
"production_companies",
"United_Artists"
],
[
"Rocky_V",
"honored_for",
"Rambo_III"
],
[
"Rocky_V",
"honored_for",
"Rocky_IV"
],
[
"Rocky_V",
"nominated_for",
"Rocky_IV"
],
[
"Rocky_V",
"prequel",
"Rocky_IV"
],
[
"Rogue",
"film",
"Limitless"
],
[
"Rogue",
"industry",
"Film"
],
[
"Samuel_Goldwyn_Films",
"film",
"The_Whistleblower"
],
[
"Samuel_Goldwyn_Films",
"industry",
"Film"
],
[
"Sociology",
"major_field_of_study",
"Film"
],
[
"Stop!_Or_My_Mom_Will_Shoot",
"honored_for",
"Rambo_III"
],
[
"Stop!_Or_My_Mom_Will_Shoot",
"honored_for",
"Rocky_IV"
],
[
"StudioCanal",
"industry",
"Film"
],
[
"Superman_IV:_The_Quest_For_Peace",
"language",
"Russian_Language"
],
[
"Sylvester_Stallone",
"acted_in",
"Rambo_III"
],
[
"Sylvester_Stallone",
"acted_in",
"Rocky_IV"
],
[
"Sylvester_Stallone",
"film",
"Rocky_IV"
],
[
"Sylvester_Stallone",
"nominated_for",
"Rambo_III"
],
[
"Sylvester_Stallone",
"nominated_for",
"Rocky_IV"
],
[
"Tango_&_Cash",
"honored_for",
"Rambo_III"
],
[
"Tango_&_Cash",
"nominated_for",
"Rambo_III"
],
[
"Tango_&_Cash",
"nominated_for",
"Rocky_IV"
],
[
"Texas_Instruments",
"service_language",
"Cantonese"
],
[
"Texas_Instruments",
"service_language",
"Russian_Language"
],
[
"The_Cannon_Group",
"film",
"Superman_IV:_The_Quest_For_Peace"
],
[
"The_Cannon_Group",
"industry",
"Film"
],
[
"The_Good_Shepherd",
"award_winner",
"Angelina_Jolie"
],
[
"The_Good_Shepherd",
"genre",
"Political_drama"
],
[
"The_Good_Shepherd",
"language",
"Russian_Language"
],
[
"The_Good_Shepherd",
"produced_by",
"James_G._Robinson"
],
[
"The_Good_Shepherd",
"production_companies",
"American_Zoetrope"
],
[
"The_Good_Shepherd",
"production_companies",
"Morgan_Creek_Productions"
],
[
"The_Specialist",
"honored_for",
"Rambo_III"
],
[
"The_Specialist",
"honored_for",
"Rocky_IV"
],
[
"The_Tourist",
"film_crew_role",
"Set_decorator-GB"
],
[
"The_Tourist",
"language",
"Russian_Language"
],
[
"The_Tourist",
"produced_by",
"Jonathan_Glickman"
],
[
"The_Tourist",
"production_companies",
"Relativity_Media"
],
[
"The_Tourist",
"production_companies",
"StudioCanal"
],
[
"The_Whistleblower",
"film_crew_role",
"Set_decorator-GB"
],
[
"The_Whistleblower",
"language",
"Russian_Language"
],
[
"TriStar_Pictures",
"film",
"Rambo_III"
],
[
"TriStar_Pictures",
"industry",
"Film"
],
[
"United_Artists",
"film",
"Being_There"
],
[
"University_of_Michigan",
"educational_institution",
"University_of_Michigan"
],
[
"University_of_Michigan",
"major_field_of_study",
"Photography"
],
[
"University_of_Michigan",
"major_field_of_study",
"Russian_Language"
],
[
"University_of_Michigan",
"major_field_of_study",
"Sociology"
],
[
"University_of_Michigan",
"student",
"Jonathan_Glickman"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1775, Association_of_American_Universities
13543, Bachelor's_degree
309, Barnsley
12708, Barnsley_F.C.
6134, Biology
8484, Business
10961, Chemistry
11116, Computer_Science
2281, Customer_service
881, David_Grisman
10757, Doctorate
10882, Economics
11881, Electrical_engineering
3683, Golden_State_Warriors
179, Joseph_Heller
12117, Kurt_Vonnegut
7568, Master's_Degree
12081, Master_of_Science
10217, New_York_University
2248, Political_Science
8803, Rip_Torn
10907, Texas_A&M_University
12922, White
src, edge_attr, dst
13543, institution, 10217
13543, institution, 10907
309, teams, 12708
12708, colors, 12922
10961, student, 12117
10757, institution, 10217
10757, institution, 10907
3683, school, 10217
3683, school, 10907
12117, influenced_by, 179
7568, institution, 10217
7568, institution, 10907
7568, student, 12117
12081, institution, 10217
12081, institution, 10907
10217, campuses, 10217
10217, colors, 12922
10217, contact_category, 2281
10217, educational_institution, 10217
10217, major_field_of_study, 6134
10217, major_field_of_study, 8484
10217, major_field_of_study, 10961
10217, major_field_of_study, 11116
10217, major_field_of_study, 10882
10217, major_field_of_study, 11881
10217, major_field_of_study, 2248
10217, organization, 1775
10217, student, 881
10217, student, 179
8803, award_winner, 12117
10907, campuses, 10907
10907, colors, 12922
10907, contact_category, 2281
10907, educational_institution, 10907
10907, major_field_of_study, 6134
10907, major_field_of_study, 8484
10907, major_field_of_study, 11116
10907, major_field_of_study, 10882
10907, major_field_of_study, 11881
10907, major_field_of_study, 2248
10907, organization, 1775
10907, student, 8803
Question: In what context are Barnsley, David_Grisman, and Rip_Torn connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Barnsley",
"David_Grisman",
"Rip_Torn"
],
"valid_edges": [
[
"Bachelor's_degree",
"institution",
"New_York_University"
],
[
"Bachelor's_degree",
"institution",
"Texas_A&M_University"
],
[
"Barnsley",
"teams",
"Barnsley_F.C."
],
[
"Barnsley_F.C.",
"colors",
"White"
],
[
"Chemistry",
"student",
"Kurt_Vonnegut"
],
[
"Doctorate",
"institution",
"New_York_University"
],
[
"Doctorate",
"institution",
"Texas_A&M_University"
],
[
"Golden_State_Warriors",
"school",
"New_York_University"
],
[
"Golden_State_Warriors",
"school",
"Texas_A&M_University"
],
[
"Kurt_Vonnegut",
"influenced_by",
"Joseph_Heller"
],
[
"Master's_Degree",
"institution",
"New_York_University"
],
[
"Master's_Degree",
"institution",
"Texas_A&M_University"
],
[
"Master's_Degree",
"student",
"Kurt_Vonnegut"
],
[
"Master_of_Science",
"institution",
"New_York_University"
],
[
"Master_of_Science",
"institution",
"Texas_A&M_University"
],
[
"New_York_University",
"campuses",
"New_York_University"
],
[
"New_York_University",
"colors",
"White"
],
[
"New_York_University",
"contact_category",
"Customer_service"
],
[
"New_York_University",
"educational_institution",
"New_York_University"
],
[
"New_York_University",
"major_field_of_study",
"Biology"
],
[
"New_York_University",
"major_field_of_study",
"Business"
],
[
"New_York_University",
"major_field_of_study",
"Chemistry"
],
[
"New_York_University",
"major_field_of_study",
"Computer_Science"
],
[
"New_York_University",
"major_field_of_study",
"Economics"
],
[
"New_York_University",
"major_field_of_study",
"Electrical_engineering"
],
[
"New_York_University",
"major_field_of_study",
"Political_Science"
],
[
"New_York_University",
"organization",
"Association_of_American_Universities"
],
[
"New_York_University",
"student",
"David_Grisman"
],
[
"New_York_University",
"student",
"Joseph_Heller"
],
[
"Rip_Torn",
"award_winner",
"Kurt_Vonnegut"
],
[
"Texas_A&M_University",
"campuses",
"Texas_A&M_University"
],
[
"Texas_A&M_University",
"colors",
"White"
],
[
"Texas_A&M_University",
"contact_category",
"Customer_service"
],
[
"Texas_A&M_University",
"educational_institution",
"Texas_A&M_University"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Biology"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Business"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Computer_Science"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Economics"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Electrical_engineering"
],
[
"Texas_A&M_University",
"major_field_of_study",
"Political_Science"
],
[
"Texas_A&M_University",
"organization",
"Association_of_American_Universities"
],
[
"Texas_A&M_University",
"student",
"Rip_Torn"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12784, 45th_Academy_Awards
10259, 82nd_Academy_Awards
10430, Academy_Award_for_Best_Actress
5735, Academy_Award_for_Best_Actress_in_a_Supporting_Role
10204, Academy_Award_for_Best_Cinematography
7130, Academy_Award_for_Best_Costume_Design
3891, Academy_Award_for_Best_Film_Editing
9538, Academy_Award_for_Best_Original_Music_Score
6569, Academy_Award_for_Best_Original_Screenplay
13993, Academy_Award_for_Best_Production_Design
2359, Academy_Award_for_Best_Sound_Mixing
656, Academy_Award_for_Best_Writing_Adapted_Screenplay
9107, American_Graffiti
4127, Andrew_Stanton
2924, Annie_Hall
2096, Arthur_Laurents
13421, BAFTA_Award_for_Best_Film_Music
11852, Billy_Wilder
13653, Black_Swan
10443, Braveheart
9398, Bridesmaids
12687, Cate_Blanchett
840, Chicago
2885, Chris_Newman
863, Cornell_University
14134, Dog_Day_Afternoon
10308, Football
11664, Forrest_Gump
6132, Fran_Walsh
5353, Francis_Ford_Coppola
752, George_Clooney
11493, George_Lucas
10562, Golden_Globe_Award_for_Best_Director_-_Motion_Picture
2124, Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture
1318, Helena_Bonham_Carter
6222, Hungary
3308, Inception
883, Inglourious_Basterds
9136, James_L._Brooks
2327, Jodie_Foster
6367, John_Cleese
9505, John_Lasseter
3159, Judi_Dench
12117, Kurt_Vonnegut
6787, Lawrence_of_Arabia
8496, Mel_Brooks
13635, Melville_Shavelson
6583, Memento
3605, Mexico
10466, Natalie_Portman
3320, National_Society_of_Film_Critics_Award_for_Best_Director
13718, Paramount_Pictures
6469, Paul_Mazursky
5894, Paul_Thomas_Anderson
349, Peter_Jackson
12159, Poland_national_football_team
2673, Psycho
6247, Richard_Portman
7484, Skyfall
2750, South_Korea
13722, Star_Wars_Episode_IV:_A_New_Hope
9738, Sunset_Boulevard
13701, Terminator_2:_Judgment_Day
9256, The_Dark_Knight
7294, The_Descendants
1599, The_Godfather
8862, The_Godfather_Part_II
5178, The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring
11982, The_Lord_of_the_Rings:_The_Return_of_the_King
2425, The_Lord_of_the_Rings:_The_Two_Towers
1178, The_Shawshank_Redemption
2437, The_Silence_of_the_Lambs
1715, The_Social_Network
11139, Uruguay
5885, Vertigo
12676, Walter_Murch
src, edge_attr, dst
12784, award_winner, 5353
12784, honored_for, 1599
10430, award_winner, 2327
10430, award_winner, 10466
10430, ceremony, 12784
10430, ceremony, 10259
10430, nominated_for, 2924
10430, nominated_for, 13653
10430, nominated_for, 840
10430, nominated_for, 9738
10430, nominated_for, 2437
5735, award_winner, 12687
5735, award_winner, 3159
5735, ceremony, 12784
5735, ceremony, 10259
5735, nominated_for, 9107
5735, nominated_for, 9398
5735, nominated_for, 840
5735, nominated_for, 2673
5735, nominated_for, 9738
5735, nominated_for, 8862
10204, ceremony, 12784
10204, ceremony, 10259
10204, nominated_for, 13653
10204, nominated_for, 840
10204, nominated_for, 11664
10204, nominated_for, 883
10204, nominated_for, 2673
10204, nominated_for, 7484
10204, nominated_for, 9738
10204, nominated_for, 13701
10204, nominated_for, 9256
10204, nominated_for, 5178
10204, nominated_for, 1178
10204, nominated_for, 1715
7130, ceremony, 12784
7130, ceremony, 10259
7130, nominated_for, 10443
7130, nominated_for, 840
7130, nominated_for, 1599
7130, nominated_for, 8862
7130, nominated_for, 5178
7130, nominated_for, 11982
3891, ceremony, 12784
3891, ceremony, 10259
3891, nominated_for, 9107
3891, nominated_for, 13653
3891, nominated_for, 10443
3891, nominated_for, 840
3891, nominated_for, 14134
3891, nominated_for, 883
3891, nominated_for, 6787
3891, nominated_for, 6583
3891, nominated_for, 13722
3891, nominated_for, 9738
3891, nominated_for, 13701
3891, nominated_for, 9256
3891, nominated_for, 7294
3891, nominated_for, 1599
3891, nominated_for, 5178
3891, nominated_for, 11982
3891, nominated_for, 2425
3891, nominated_for, 1178
3891, nominated_for, 2437
3891, nominated_for, 1715
9538, ceremony, 12784
9538, ceremony, 10259
9538, nominated_for, 10443
9538, nominated_for, 11664
9538, nominated_for, 3308
9538, nominated_for, 6787
9538, nominated_for, 7484
9538, nominated_for, 13722
9538, nominated_for, 1599
9538, nominated_for, 8862
9538, nominated_for, 5178
9538, nominated_for, 11982
9538, nominated_for, 1178
9538, nominated_for, 1715
6569, award_winner, 11852
6569, award_winner, 5353
6569, award_winner, 8496
6569, ceremony, 12784
6569, ceremony, 10259
6569, nominated_for, 9107
6569, nominated_for, 2924
6569, nominated_for, 10443
6569, nominated_for, 9398
6569, nominated_for, 14134
6569, nominated_for, 3308
6569, nominated_for, 883
6569, nominated_for, 6583
6569, nominated_for, 13722
6569, nominated_for, 9738
13993, ceremony, 12784
13993, ceremony, 10259
13993, nominated_for, 840
13993, nominated_for, 11664
13993, nominated_for, 3308
13993, nominated_for, 6787
13993, nominated_for, 2673
13993, nominated_for, 13722
13993, nominated_for, 9738
13993, nominated_for, 9256
13993, nominated_for, 8862
13993, nominated_for, 5178
13993, nominated_for, 11982
13993, nominated_for, 2425
13993, nominated_for, 5885
2359, award_winner, 2885
2359, award_winner, 13718
2359, award_winner, 6247
2359, ceremony, 12784
2359, ceremony, 10259
2359, nominated_for, 10443
2359, nominated_for, 840
2359, nominated_for, 11664
2359, nominated_for, 883
2359, nominated_for, 6787
2359, nominated_for, 7484
2359, nominated_for, 13722
2359, nominated_for, 9256
2359, nominated_for, 1599
2359, nominated_for, 5178
2359, nominated_for, 11982
2359, nominated_for, 2425
2359, nominated_for, 1178
2359, nominated_for, 2437
2359, nominated_for, 1715
2359, nominated_for, 5885
656, award_winner, 11852
656, award_winner, 6132
656, award_winner, 5353
656, award_winner, 9136
656, award_winner, 349
656, ceremony, 12784
656, ceremony, 10259
656, nominated_for, 840
656, nominated_for, 11664
656, nominated_for, 6787
656, nominated_for, 7294
656, nominated_for, 1599
656, nominated_for, 8862
656, nominated_for, 5178
656, nominated_for, 11982
656, nominated_for, 1178
656, nominated_for, 2437
9107, award_winner, 5353
9107, produced_by, 5353
4127, award, 6569
4127, award, 656
2924, award_honor_award, 10430
2924, award_honor_award, 6569
2096, award, 6569
13421, nominated_for, 1599
11852, award, 6569
11852, award, 656
13653, award_honor_award, 10430
10443, award_honor_award, 10204
12687, award, 10430
12687, award, 5735
840, award_honor_award, 5735
840, award_honor_award, 7130
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863, student, 13635
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5353, nominated_for, 8862
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752, award, 656
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10466, award, 5735
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11982, award_honor_award, 9538
11982, award_honor_award, 13993
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12676, award, 3891
12676, award, 2359
Question: In what context are 45th_Academy_Awards, Kurt_Vonnegut, and Poland_national_football_team connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
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],
[
"Billy_Wilder",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Billy_Wilder",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Black_Swan",
"award_honor_award",
"Academy_Award_for_Best_Actress"
],
[
"Braveheart",
"award_honor_award",
"Academy_Award_for_Best_Cinematography"
],
[
"Cate_Blanchett",
"award",
"Academy_Award_for_Best_Actress"
],
[
"Cate_Blanchett",
"award",
"Academy_Award_for_Best_Actress_in_a_Supporting_Role"
],
[
"Chicago",
"award_honor_award",
"Academy_Award_for_Best_Actress_in_a_Supporting_Role"
],
[
"Chicago",
"award_honor_award",
"Academy_Award_for_Best_Costume_Design"
],
[
"Chicago",
"award_honor_award",
"Academy_Award_for_Best_Production_Design"
],
[
"Chicago",
"award_honor_award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"Chris_Newman",
"award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"Chris_Newman",
"nominated_for",
"The_Godfather"
],
[
"Cornell_University",
"student",
"Arthur_Laurents"
],
[
"Cornell_University",
"student",
"Kurt_Vonnegut"
],
[
"Cornell_University",
"student",
"Melville_Shavelson"
],
[
"Dog_Day_Afternoon",
"award_honor_award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Football",
"country",
"Hungary"
],
[
"Football",
"country",
"Mexico"
],
[
"Football",
"country",
"South_Korea"
],
[
"Football",
"country",
"Uruguay"
],
[
"Forrest_Gump",
"award_honor_award",
"Academy_Award_for_Best_Film_Editing"
],
[
"Forrest_Gump",
"award_honor_award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Fran_Walsh",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Fran_Walsh",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Francis_Ford_Coppola",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Francis_Ford_Coppola",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Francis_Ford_Coppola",
"award",
"BAFTA_Award_for_Best_Film_Music"
],
[
"Francis_Ford_Coppola",
"award",
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture"
],
[
"Francis_Ford_Coppola",
"award",
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture"
],
[
"Francis_Ford_Coppola",
"award",
"National_Society_of_Film_Critics_Award_for_Best_Director"
],
[
"Francis_Ford_Coppola",
"award_nominee",
"George_Lucas"
],
[
"Francis_Ford_Coppola",
"award_winner",
"George_Lucas"
],
[
"Francis_Ford_Coppola",
"film",
"The_Godfather"
],
[
"Francis_Ford_Coppola",
"film",
"The_Godfather_Part_II"
],
[
"Francis_Ford_Coppola",
"nominated_for",
"The_Godfather"
],
[
"Francis_Ford_Coppola",
"nominated_for",
"The_Godfather_Part_II"
],
[
"George_Clooney",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"George_Clooney",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"George_Lucas",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"George_Lucas",
"award_winner",
"Francis_Ford_Coppola"
],
[
"George_Lucas",
"influenced_by",
"Francis_Ford_Coppola"
],
[
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture",
"award_winner",
"Francis_Ford_Coppola"
],
[
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture",
"nominated_for",
"The_Godfather"
],
[
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture",
"award_winner",
"Francis_Ford_Coppola"
],
[
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture",
"nominated_for",
"The_Godfather"
],
[
"Helena_Bonham_Carter",
"award",
"Academy_Award_for_Best_Actress"
],
[
"Helena_Bonham_Carter",
"award",
"Academy_Award_for_Best_Actress_in_a_Supporting_Role"
],
[
"Inception",
"award_honor_award",
"Academy_Award_for_Best_Cinematography"
],
[
"Inception",
"award_honor_award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"James_L._Brooks",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"James_L._Brooks",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Jodie_Foster",
"award",
"Academy_Award_for_Best_Actress"
],
[
"Jodie_Foster",
"award",
"Academy_Award_for_Best_Actress_in_a_Supporting_Role"
],
[
"John_Cleese",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"John_Cleese",
"company",
"Cornell_University"
],
[
"John_Lasseter",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"John_Lasseter",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Judi_Dench",
"award",
"Academy_Award_for_Best_Actress"
],
[
"Lawrence_of_Arabia",
"award_honor_award",
"Academy_Award_for_Best_Film_Editing"
],
[
"Lawrence_of_Arabia",
"award_honor_award",
"Academy_Award_for_Best_Original_Music_Score"
],
[
"Lawrence_of_Arabia",
"award_honor_award",
"Academy_Award_for_Best_Production_Design"
],
[
"Lawrence_of_Arabia",
"award_honor_award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"Mel_Brooks",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Melville_Shavelson",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Natalie_Portman",
"award",
"Academy_Award_for_Best_Actress"
],
[
"Natalie_Portman",
"award",
"Academy_Award_for_Best_Actress_in_a_Supporting_Role"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"The_Godfather"
],
[
"Paramount_Pictures",
"award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"Paramount_Pictures",
"film",
"The_Godfather"
],
[
"Paul_Mazursky",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Paul_Mazursky",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Paul_Thomas_Anderson",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Paul_Thomas_Anderson",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Peter_Jackson",
"award",
"Academy_Award_for_Best_Original_Screenplay"
],
[
"Peter_Jackson",
"award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Poland_national_football_team",
"sport",
"Football"
],
[
"Richard_Portman",
"award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"Richard_Portman",
"nominated_for",
"The_Godfather"
],
[
"Star_Wars_Episode_IV:_A_New_Hope",
"award_honor_award",
"Academy_Award_for_Best_Costume_Design"
],
[
"Star_Wars_Episode_IV:_A_New_Hope",
"award_honor_award",
"Academy_Award_for_Best_Film_Editing"
],
[
"Star_Wars_Episode_IV:_A_New_Hope",
"award_honor_award",
"Academy_Award_for_Best_Production_Design"
],
[
"Terminator_2:_Judgment_Day",
"award_honor_award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"The_Descendants",
"award_honor_award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"The_Godfather",
"award_honor_award",
"BAFTA_Award_for_Best_Film_Music"
],
[
"The_Godfather",
"award_honor_award",
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture"
],
[
"The_Godfather",
"award_honor_award",
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture"
],
[
"The_Godfather",
"award_winner",
"Francis_Ford_Coppola"
],
[
"The_Godfather",
"crewmember",
"Chris_Newman"
],
[
"The_Godfather",
"film_release_region",
"Hungary"
],
[
"The_Godfather",
"film_release_region",
"Mexico"
],
[
"The_Godfather",
"film_release_region",
"South_Korea"
],
[
"The_Godfather",
"film_release_region",
"Uruguay"
],
[
"The_Godfather",
"honored_for",
"The_Godfather_Part_II"
],
[
"The_Godfather",
"nominated_for",
"The_Godfather_Part_II"
],
[
"The_Godfather",
"production_companies",
"Paramount_Pictures"
],
[
"The_Godfather",
"written_by",
"Francis_Ford_Coppola"
],
[
"The_Godfather_Part_II",
"award_honor_award",
"Academy_Award_for_Best_Original_Music_Score"
],
[
"The_Godfather_Part_II",
"award_honor_award",
"Academy_Award_for_Best_Production_Design"
],
[
"The_Godfather_Part_II",
"award_winner",
"Francis_Ford_Coppola"
],
[
"The_Godfather_Part_II",
"honored_for",
"The_Godfather"
],
[
"The_Godfather_Part_II",
"nominated_for",
"The_Godfather"
],
[
"The_Godfather_Part_II",
"prequel",
"The_Godfather"
],
[
"The_Godfather_Part_II",
"produced_by",
"Francis_Ford_Coppola"
],
[
"The_Godfather_Part_II",
"written_by",
"Francis_Ford_Coppola"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"award_honor_award",
"Academy_Award_for_Best_Cinematography"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"award_honor_award",
"Academy_Award_for_Best_Original_Music_Score"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"Academy_Award_for_Best_Costume_Design"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"Academy_Award_for_Best_Film_Editing"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"Academy_Award_for_Best_Original_Music_Score"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"Academy_Award_for_Best_Production_Design"
],
[
"The_Lord_of_the_Rings:_The_Return_of_the_King",
"award_honor_award",
"Academy_Award_for_Best_Sound_Mixing"
],
[
"The_Silence_of_the_Lambs",
"award_honor_award",
"Academy_Award_for_Best_Actress"
],
[
"The_Social_Network",
"award_honor_award",
"Academy_Award_for_Best_Film_Editing"
],
[
"The_Social_Network",
"award_honor_award",
"Academy_Award_for_Best_Original_Music_Score"
],
[
"The_Social_Network",
"award_honor_award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"Walter_Murch",
"award",
"Academy_Award_for_Best_Film_Editing"
],
[
"Walter_Murch",
"award",
"Academy_Award_for_Best_Sound_Mixing"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
11864, Amblin_Entertainment
3198, BFCA_Critics'_Choice_Award_for_Best_Composer
14123, Back_to_the_Future
12546, Back_to_the_Future_Part_II
2804, Back_to_the_Future_Part_III
4024, Broadcast_Film_Critics_Association_Award_for_Best_Actor
12116, Clint_Eastwood
9061, Dutch-American
12072, Frank_Marshall
5566, Gus_Van_Sant
4643, Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film
1125, Kathleen_Kennedy
13654, Los_Angeles_Film_Critics_Association_Award_for_Best_Actor
6449, Milk
13510, Paris,_je_t'aime
11626, Potassium
13413, Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture
10311, Star_Trek
13076, Time_travel
5227, Victor_Garber
src, edge_attr, dst
3198, nominated_for, 6449
14123, award_honor_award, 4643
14123, executive_produced_by, 12072
14123, executive_produced_by, 1125
14123, production_companies, 11864
12546, executive_produced_by, 12072
12546, executive_produced_by, 1125
12546, genre, 13076
12546, prequel, 14123
12546, production_companies, 11864
2804, executive_produced_by, 12072
2804, executive_produced_by, 1125
2804, prequel, 12546
2804, production_companies, 11864
4024, nominated_for, 6449
12116, award, 3198
12116, award, 4024
12116, award, 13413
9061, people, 12116
5566, film, 13510
5566, nominated_for, 6449
4643, award_winner, 12116
13654, award_winner, 12116
6449, award_honor_award, 4024
6449, award_honor_award, 13654
6449, award_winner, 5566
6449, food_nutrient, 11626
13510, genre, 13076
13413, nominated_for, 6449
13413, nominated_for, 10311
13076, films, 14123
13076, films, 12546
13076, films, 2804
13076, films, 10311
5227, acted_in, 6449
5227, acted_in, 10311
5227, nominated_for, 6449
Question: For what reason are Dutch-American, Potassium, and Time_travel associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Dutch-American",
"Potassium",
"Time_travel"
],
"valid_edges": [
[
"BFCA_Critics'_Choice_Award_for_Best_Composer",
"nominated_for",
"Milk"
],
[
"Back_to_the_Future",
"award_honor_award",
"Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film"
],
[
"Back_to_the_Future",
"executive_produced_by",
"Frank_Marshall"
],
[
"Back_to_the_Future",
"executive_produced_by",
"Kathleen_Kennedy"
],
[
"Back_to_the_Future",
"production_companies",
"Amblin_Entertainment"
],
[
"Back_to_the_Future_Part_II",
"executive_produced_by",
"Frank_Marshall"
],
[
"Back_to_the_Future_Part_II",
"executive_produced_by",
"Kathleen_Kennedy"
],
[
"Back_to_the_Future_Part_II",
"genre",
"Time_travel"
],
[
"Back_to_the_Future_Part_II",
"prequel",
"Back_to_the_Future"
],
[
"Back_to_the_Future_Part_II",
"production_companies",
"Amblin_Entertainment"
],
[
"Back_to_the_Future_Part_III",
"executive_produced_by",
"Frank_Marshall"
],
[
"Back_to_the_Future_Part_III",
"executive_produced_by",
"Kathleen_Kennedy"
],
[
"Back_to_the_Future_Part_III",
"prequel",
"Back_to_the_Future_Part_II"
],
[
"Back_to_the_Future_Part_III",
"production_companies",
"Amblin_Entertainment"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Actor",
"nominated_for",
"Milk"
],
[
"Clint_Eastwood",
"award",
"BFCA_Critics'_Choice_Award_for_Best_Composer"
],
[
"Clint_Eastwood",
"award",
"Broadcast_Film_Critics_Association_Award_for_Best_Actor"
],
[
"Clint_Eastwood",
"award",
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture"
],
[
"Dutch-American",
"people",
"Clint_Eastwood"
],
[
"Gus_Van_Sant",
"film",
"Paris,_je_t'aime"
],
[
"Gus_Van_Sant",
"nominated_for",
"Milk"
],
[
"Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film",
"award_winner",
"Clint_Eastwood"
],
[
"Los_Angeles_Film_Critics_Association_Award_for_Best_Actor",
"award_winner",
"Clint_Eastwood"
],
[
"Milk",
"award_honor_award",
"Broadcast_Film_Critics_Association_Award_for_Best_Actor"
],
[
"Milk",
"award_honor_award",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Actor"
],
[
"Milk",
"award_winner",
"Gus_Van_Sant"
],
[
"Milk",
"food_nutrient",
"Potassium"
],
[
"Paris,_je_t'aime",
"genre",
"Time_travel"
],
[
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture",
"nominated_for",
"Milk"
],
[
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture",
"nominated_for",
"Star_Trek"
],
[
"Time_travel",
"films",
"Back_to_the_Future"
],
[
"Time_travel",
"films",
"Back_to_the_Future_Part_II"
],
[
"Time_travel",
"films",
"Back_to_the_Future_Part_III"
],
[
"Time_travel",
"films",
"Star_Trek"
],
[
"Victor_Garber",
"acted_in",
"Milk"
],
[
"Victor_Garber",
"acted_in",
"Star_Trek"
],
[
"Victor_Garber",
"nominated_for",
"Milk"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2180, Indiana_University
14023, John_Mellencamp
6454, MCA_Records
8594, North_America-US
10933, Sierra_Nevada
10362, Spinal_Tap
6148, Sprint_Corporation
10111, Telecommunications
10412, Trinidad_and_Tobago
src, edge_attr, dst
2180, major_field_of_study, 10111
2180, student, 14023
6454, artist, 14023
6454, artist, 10362
8594, contains, 10933
8594, countries_within, 10412
6148, industry, 10111
6148, service_location, 10412
Question: For what reason are Sierra_Nevada, Spinal_Tap, and Telecommunications associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Sierra_Nevada",
"Spinal_Tap",
"Telecommunications"
],
"valid_edges": [
[
"Indiana_University",
"major_field_of_study",
"Telecommunications"
],
[
"Indiana_University",
"student",
"John_Mellencamp"
],
[
"MCA_Records",
"artist",
"John_Mellencamp"
],
[
"MCA_Records",
"artist",
"Spinal_Tap"
],
[
"North_America-US",
"contains",
"Sierra_Nevada"
],
[
"North_America-US",
"countries_within",
"Trinidad_and_Tobago"
],
[
"Sprint_Corporation",
"industry",
"Telecommunications"
],
[
"Sprint_Corporation",
"service_location",
"Trinidad_and_Tobago"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5947, Accountancy
2871, American_University
5344, Amherst_College
7504, Appalachian_State_University
1241, Arizona_State_University
5439, Ateneo_de_Manila_University
13543, Bachelor's_degree
7641, Ball_State_University
13765, Bavaria
9517, Baylor_University
3543, Binghamton_University
1549, Boston_College
3014, Boston_University
14138, Bowdoin_College
1494, Bowling_Green_State_University
1174, Bradley_University
10743, Brigham_Young_University
8484, Business
10748, Business_Administration
5199, California_Institute_of_Technology
10807, California_State_University
9495, California_State_University,_Northridge
7708, California_State_University,_Sacramento
10178, Claremont_McKenna_College
11566, Columbia_University
2681, Columbia_University_Graduate_School_of_Journalism
3941, Connecticut_College
6255, Davidson_College
13460, Diane_Sawyer
7229, Drake_University
12952, Drexel_University
11481, Eastern_Illinois_University
10882, Economics
9198, Fairleigh_Dickinson_University
9178, Finance
12360, Florida_International_University
6085, Fordham_University
10012, George_Washington_University
7472, Georgetown_University
7101, Hallmark_Hall_of_Fame
4543, Hamilton_College
1651, Harvard_Business_School
2921, Harvard_College
9868, Harvard_University
3129, Haverford_College
12054, Hobart_and_William_Smith_Colleges
2180, Indiana_University
12890, Information_technology
13214, Iowa_State_University
133, Ithaca_College
13298, John_F._Kennedy_School_of_Government
2580, Kellogg_School_of_Management
4888, Kingdom_of_France
2567, Knox_College,_Illinois
193, Lafayette_College
8158, Lehigh_University
12152, Louisiana_State_University
12955, Louisiana_Tech_University
12611, Loyola_University_Chicago
13909, Ludwig_Maximilian_University_of_Munich
3556, MIT_Sloan_School_of_Management
6457, Management
1093, Manhattan_School_of_Music
2261, Marketing-GB
1479, Massachusetts_Institute_of_Technology
7568, Master's_Degree
422, Master_of_Arts
12081, Master_of_Science
1192, Miami_University
4349, Michigan_State_University
13248, Mississippi_State_University
10217, New_York_University
1621, New_York_University_Stern_School_of_Business
817, Northeastern_University
10791, Northwestern_University
11019, Peabody_Award
8268, Pennsylvania_State_University
4341, Pepperdine_University
2248, Political_Science
5858, Pomona_College
8627, Portland_State_University
8941, Private_school
155, Purdue_University
1352, Reed_College
2470, Rensselaer_Polytechnic_Institute
13432, Saint_Joseph's_University
8960, San_Francisco_State_University
8066, San_JosΓ©_State_University
12816, Santa_Clara_University
10821, Sarah_Lawrence_College
10881, Skidmore_College
165, Smith_College
11891, Southern_Illinois_University_Carbondale
3070, St._Bonaventure_University
5766, St._Lawrence_University
1218, Stanford_Graduate_School_of_Business
5571, Stevens_Institute_of_Technology
8811, Swarthmore_College
6353, Syracuse_University
4371, Tel_Aviv_University
13312, Temple_University
1559, Texas_Tech_University
7386, The_College_of_Wooster
6875, Tufts_University
7433, Union_College
6515, University_of_Arizona
4436, University_of_Bristol
3848, University_of_California,_Berkeley
1640, University_of_California,_Los_Angeles
9077, University_of_Cape_Town
2418, University_of_Chicago
3871, University_of_Connecticut
1004, University_of_Delaware
10063, University_of_Denver
9348, University_of_Detroit_Mercy
221, University_of_Florida
6236, University_of_Georgia
3457, University_of_Houston
2680, University_of_Idaho
1645, University_of_Illinois_at_Chicago
595, University_of_Iowa
694, University_of_Kansas
5314, University_of_Maryland,_College_Park
3219, University_of_Memphis
12223, University_of_Miami
1480, University_of_Michigan
8082, University_of_Minnesota
1173, University_of_Mississippi
13487, University_of_MissouriβColumbia
13365, University_of_North_Carolina_at_Chapel_Hill
6056, University_of_North_Carolina_at_Charlotte
8689, University_of_Notre_Dame
12256, University_of_Oregon
1488, University_of_Pittsburgh
7723, University_of_Rhode_Island
10470, University_of_Richmond
8288, University_of_Rochester
7468, University_of_South_Carolina
6128, University_of_Southern_California
2688, University_of_Tennessee
1420, University_of_Texas_at_Arlington
5851, University_of_Texas_at_Austin
1590, University_of_Tulsa
9596, University_of_Virginia
4893, University_of_Wyoming
9275, Villanova_University
8207, Virginia_Commonwealth_University
6108, Washington_and_Lee_University
4564, Wellesley_College
112, Wesleyan_University
6094, Wharton_School_of_the_University_of_Pennsylvania
7995, Wheaton_College
12311, Williams_College
src, edge_attr, dst
5947, major_field_of_study, 8484
5947, major_field_of_study, 10748
5947, major_field_of_study, 10882
5947, major_field_of_study, 9178
5947, major_field_of_study, 12890
5947, major_field_of_study, 2261
5947, major_field_of_study, 2248
2871, major_field_of_study, 9178
5344, school_type, 8941
7504, major_field_of_study, 5947
1241, major_field_of_study, 5947
1241, major_field_of_study, 9178
5439, school_type, 8941
13543, institution, 2871
13543, institution, 5344
13543, institution, 7504
13543, institution, 1241
13543, institution, 5439
13543, institution, 7641
13543, institution, 9517
13543, institution, 3543
13543, institution, 1549
13543, institution, 3014
13543, institution, 14138
13543, institution, 1174
13543, institution, 10743
13543, institution, 5199
13543, institution, 10807
13543, institution, 9495
13543, institution, 7708
13543, institution, 10178
13543, institution, 11566
13543, institution, 3941
13543, institution, 6255
13543, institution, 7229
13543, institution, 11481
13543, institution, 9198
13543, institution, 12360
13543, institution, 6085
13543, institution, 10012
13543, institution, 7472
13543, institution, 4543
13543, institution, 2921
13543, institution, 9868
13543, institution, 3129
13543, institution, 12054
13543, institution, 2180
13543, institution, 13214
13543, institution, 133
13543, institution, 13298
13543, institution, 2567
13543, institution, 193
13543, institution, 8158
13543, institution, 12152
13543, institution, 12611
13543, institution, 13909
13543, institution, 1093
13543, institution, 1479
13543, institution, 1192
13543, institution, 4349
13543, institution, 13248
13543, institution, 10217
13543, institution, 817
13543, institution, 10791
13543, institution, 8268
13543, institution, 4341
13543, institution, 5858
13543, institution, 8627
13543, institution, 155
13543, institution, 1352
13543, institution, 2470
13543, institution, 8960
13543, institution, 8066
13543, institution, 12816
13543, institution, 10821
13543, institution, 10881
13543, institution, 165
13543, institution, 11891
13543, institution, 3070
13543, institution, 5766
13543, institution, 5571
13543, institution, 8811
13543, institution, 6353
13543, institution, 4371
13543, institution, 13312
13543, institution, 1559
13543, institution, 7386
13543, institution, 6875
13543, institution, 7433
13543, institution, 6515
13543, institution, 4436
13543, institution, 3848
13543, institution, 1640
13543, institution, 2418
13543, institution, 3871
13543, institution, 10063
13543, institution, 9348
13543, institution, 221
13543, institution, 6236
13543, institution, 3457
13543, institution, 2680
13543, institution, 1645
13543, institution, 595
13543, institution, 694
13543, institution, 5314
13543, institution, 3219
13543, institution, 1480
13543, institution, 8082
13543, institution, 1173
13543, institution, 13487
13543, institution, 13365
13543, institution, 6056
13543, institution, 8689
13543, institution, 12256
13543, institution, 1488
13543, institution, 7723
13543, institution, 10470
13543, institution, 8288
13543, institution, 7468
13543, institution, 6128
13543, institution, 2688
13543, institution, 1420
13543, institution, 5851
13543, institution, 9596
13543, institution, 4893
13543, institution, 9275
13543, institution, 8207
13543, institution, 6108
13543, institution, 4564
13543, institution, 112
13543, institution, 6094
13543, institution, 7995
13543, institution, 12311
13543, major_field_of_study, 5947
13543, major_field_of_study, 8484
13543, major_field_of_study, 10748
13543, major_field_of_study, 10882
13543, major_field_of_study, 9178
13543, major_field_of_study, 12890
13543, major_field_of_study, 6457
13543, major_field_of_study, 2261
13543, major_field_of_study, 2248
13543, student, 13460
7641, major_field_of_study, 5947
13765, combatants, 4888
13765, contains, 13909
9517, major_field_of_study, 5947
9517, school_type, 8941
3543, major_field_of_study, 5947
1549, major_field_of_study, 5947
3014, major_field_of_study, 9178
3014, school_type, 8941
14138, school_type, 8941
1494, major_field_of_study, 5947
1494, major_field_of_study, 9178
1174, major_field_of_study, 5947
1174, school_type, 8941
10743, major_field_of_study, 5947
10743, major_field_of_study, 9178
8484, major_field_of_study, 5947
10748, major_field_of_study, 5947
5199, school_type, 8941
10807, major_field_of_study, 5947
10807, major_field_of_study, 9178
9495, major_field_of_study, 5947
9495, major_field_of_study, 9178
7708, major_field_of_study, 5947
10178, school_type, 8941
11566, major_field_of_study, 9178
2681, school_type, 8941
3941, school_type, 8941
6255, school_type, 8941
7229, major_field_of_study, 5947
7229, school_type, 8941
12952, major_field_of_study, 9178
12952, school_type, 8941
11481, major_field_of_study, 9178
10882, major_field_of_study, 5947
10882, major_field_of_study, 9178
9198, major_field_of_study, 5947
9198, school_type, 8941
9178, major_field_of_study, 5947
9178, major_field_of_study, 10748
9178, major_field_of_study, 10882
9178, major_field_of_study, 6457
9178, major_field_of_study, 2261
12360, major_field_of_study, 5947
6085, major_field_of_study, 5947
6085, major_field_of_study, 9178
10012, major_field_of_study, 9178
7472, major_field_of_study, 9178
7101, award_honor_award, 11019
4543, school_type, 8941
1651, major_field_of_study, 9178
1651, school_type, 8941
2921, school_type, 8941
9868, major_field_of_study, 9178
3129, school_type, 8941
12054, school_type, 8941
2180, major_field_of_study, 9178
12890, major_field_of_study, 5947
13214, major_field_of_study, 5947
133, school_type, 8941
13298, school_type, 8941
2580, major_field_of_study, 9178
2580, school_type, 8941
4888, combatants, 13765
2567, school_type, 8941
193, school_type, 8941
8158, major_field_of_study, 5947
8158, school_type, 8941
12152, major_field_of_study, 9178
12955, major_field_of_study, 5947
12955, major_field_of_study, 9178
12611, major_field_of_study, 5947
12611, major_field_of_study, 9178
13909, state_province_region, 13765
3556, major_field_of_study, 9178
3556, school_type, 8941
6457, major_field_of_study, 9178
1093, school_type, 8941
2261, major_field_of_study, 5947
2261, major_field_of_study, 9178
1479, major_field_of_study, 9178
7568, major_field_of_study, 5947
7568, major_field_of_study, 9178
422, major_field_of_study, 5947
422, major_field_of_study, 9178
12081, major_field_of_study, 5947
12081, major_field_of_study, 9178
1192, major_field_of_study, 5947
4349, major_field_of_study, 5947
13248, major_field_of_study, 9178
10217, major_field_of_study, 9178
1621, major_field_of_study, 5947
1621, major_field_of_study, 9178
1621, school_type, 8941
817, major_field_of_study, 9178
817, school_type, 8941
10791, major_field_of_study, 9178
11019, award_winner, 10743
11019, award_winner, 2681
11019, award_winner, 13460
11019, award_winner, 7101
11019, award_winner, 5314
11019, award_winner, 3219
11019, award_winner, 6128
8268, major_field_of_study, 5947
8268, major_field_of_study, 9178
4341, school_type, 8941
2248, major_field_of_study, 5947
5858, school_type, 8941
8627, major_field_of_study, 9178
155, major_field_of_study, 5947
155, major_field_of_study, 9178
1352, school_type, 8941
2470, major_field_of_study, 9178
13432, major_field_of_study, 5947
13432, school_type, 8941
8960, major_field_of_study, 5947
8960, major_field_of_study, 9178
8066, major_field_of_study, 5947
8066, major_field_of_study, 9178
12816, major_field_of_study, 9178
12816, school_type, 8941
10821, school_type, 8941
10881, school_type, 8941
165, school_type, 8941
11891, major_field_of_study, 5947
3070, campuses, 3070
3070, educational_institution, 3070
3070, major_field_of_study, 5947
3070, major_field_of_study, 9178
3070, school_type, 8941
5766, school_type, 8941
1218, major_field_of_study, 9178
1218, school_type, 8941
5571, school_type, 8941
8811, school_type, 8941
6353, major_field_of_study, 5947
4371, major_field_of_study, 5947
13312, major_field_of_study, 9178
1559, major_field_of_study, 9178
7386, school_type, 8941
6875, school_type, 8941
7433, school_type, 8941
6515, major_field_of_study, 9178
4436, major_field_of_study, 5947
3848, major_field_of_study, 9178
1640, major_field_of_study, 5947
1640, major_field_of_study, 9178
9077, major_field_of_study, 5947
9077, major_field_of_study, 9178
2418, major_field_of_study, 9178
3871, major_field_of_study, 5947
1004, major_field_of_study, 5947
1004, major_field_of_study, 9178
1004, school_type, 8941
10063, school_type, 8941
9348, major_field_of_study, 5947
9348, major_field_of_study, 9178
221, major_field_of_study, 5947
6236, major_field_of_study, 5947
3457, major_field_of_study, 5947
3457, major_field_of_study, 9178
2680, major_field_of_study, 5947
1645, major_field_of_study, 5947
595, major_field_of_study, 9178
694, major_field_of_study, 9178
5314, major_field_of_study, 5947
3219, major_field_of_study, 9178
12223, major_field_of_study, 9178
12223, school_type, 8941
1480, major_field_of_study, 5947
1480, major_field_of_study, 9178
8082, major_field_of_study, 5947
1173, major_field_of_study, 5947
1173, major_field_of_study, 9178
13487, major_field_of_study, 9178
13365, major_field_of_study, 9178
6056, major_field_of_study, 5947
8689, major_field_of_study, 5947
8689, major_field_of_study, 9178
8689, school_type, 8941
12256, major_field_of_study, 5947
1488, major_field_of_study, 9178
7723, major_field_of_study, 5947
10470, school_type, 8941
8288, major_field_of_study, 9178
7468, major_field_of_study, 9178
6128, major_field_of_study, 5947
6128, major_field_of_study, 9178
2688, major_field_of_study, 5947
1420, major_field_of_study, 5947
1420, major_field_of_study, 9178
5851, major_field_of_study, 5947
5851, major_field_of_study, 9178
1590, major_field_of_study, 9178
1590, school_type, 8941
9596, major_field_of_study, 5947
9596, major_field_of_study, 9178
4893, major_field_of_study, 5947
4893, major_field_of_study, 9178
9275, major_field_of_study, 5947
9275, school_type, 8941
8207, major_field_of_study, 5947
8207, major_field_of_study, 9178
6108, school_type, 8941
4564, school_type, 8941
112, school_type, 8941
6094, major_field_of_study, 5947
6094, major_field_of_study, 9178
7995, school_type, 8941
12311, school_type, 8941
Question: How are Hallmark_Hall_of_Fame, Kingdom_of_France, and St._Bonaventure_University related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Hallmark_Hall_of_Fame",
"Kingdom_of_France",
"St._Bonaventure_University"
],
"valid_edges": [
[
"Accountancy",
"major_field_of_study",
"Business"
],
[
"Accountancy",
"major_field_of_study",
"Business_Administration"
],
[
"Accountancy",
"major_field_of_study",
"Economics"
],
[
"Accountancy",
"major_field_of_study",
"Finance"
],
[
"Accountancy",
"major_field_of_study",
"Information_technology"
],
[
"Accountancy",
"major_field_of_study",
"Marketing-GB"
],
[
"Accountancy",
"major_field_of_study",
"Political_Science"
],
[
"American_University",
"major_field_of_study",
"Finance"
],
[
"Amherst_College",
"school_type",
"Private_school"
],
[
"Appalachian_State_University",
"major_field_of_study",
"Accountancy"
],
[
"Arizona_State_University",
"major_field_of_study",
"Accountancy"
],
[
"Arizona_State_University",
"major_field_of_study",
"Finance"
],
[
"Ateneo_de_Manila_University",
"school_type",
"Private_school"
],
[
"Bachelor's_degree",
"institution",
"American_University"
],
[
"Bachelor's_degree",
"institution",
"Amherst_College"
],
[
"Bachelor's_degree",
"institution",
"Appalachian_State_University"
],
[
"Bachelor's_degree",
"institution",
"Arizona_State_University"
],
[
"Bachelor's_degree",
"institution",
"Ateneo_de_Manila_University"
],
[
"Bachelor's_degree",
"institution",
"Ball_State_University"
],
[
"Bachelor's_degree",
"institution",
"Baylor_University"
],
[
"Bachelor's_degree",
"institution",
"Binghamton_University"
],
[
"Bachelor's_degree",
"institution",
"Boston_College"
],
[
"Bachelor's_degree",
"institution",
"Boston_University"
],
[
"Bachelor's_degree",
"institution",
"Bowdoin_College"
],
[
"Bachelor's_degree",
"institution",
"Bradley_University"
],
[
"Bachelor's_degree",
"institution",
"Brigham_Young_University"
],
[
"Bachelor's_degree",
"institution",
"California_Institute_of_Technology"
],
[
"Bachelor's_degree",
"institution",
"California_State_University"
],
[
"Bachelor's_degree",
"institution",
"California_State_University,_Northridge"
],
[
"Bachelor's_degree",
"institution",
"California_State_University,_Sacramento"
],
[
"Bachelor's_degree",
"institution",
"Claremont_McKenna_College"
],
[
"Bachelor's_degree",
"institution",
"Columbia_University"
],
[
"Bachelor's_degree",
"institution",
"Connecticut_College"
],
[
"Bachelor's_degree",
"institution",
"Davidson_College"
],
[
"Bachelor's_degree",
"institution",
"Drake_University"
],
[
"Bachelor's_degree",
"institution",
"Eastern_Illinois_University"
],
[
"Bachelor's_degree",
"institution",
"Fairleigh_Dickinson_University"
],
[
"Bachelor's_degree",
"institution",
"Florida_International_University"
],
[
"Bachelor's_degree",
"institution",
"Fordham_University"
],
[
"Bachelor's_degree",
"institution",
"George_Washington_University"
],
[
"Bachelor's_degree",
"institution",
"Georgetown_University"
],
[
"Bachelor's_degree",
"institution",
"Hamilton_College"
],
[
"Bachelor's_degree",
"institution",
"Harvard_College"
],
[
"Bachelor's_degree",
"institution",
"Harvard_University"
],
[
"Bachelor's_degree",
"institution",
"Haverford_College"
],
[
"Bachelor's_degree",
"institution",
"Hobart_and_William_Smith_Colleges"
],
[
"Bachelor's_degree",
"institution",
"Indiana_University"
],
[
"Bachelor's_degree",
"institution",
"Iowa_State_University"
],
[
"Bachelor's_degree",
"institution",
"Ithaca_College"
],
[
"Bachelor's_degree",
"institution",
"John_F._Kennedy_School_of_Government"
],
[
"Bachelor's_degree",
"institution",
"Knox_College,_Illinois"
],
[
"Bachelor's_degree",
"institution",
"Lafayette_College"
],
[
"Bachelor's_degree",
"institution",
"Lehigh_University"
],
[
"Bachelor's_degree",
"institution",
"Louisiana_State_University"
],
[
"Bachelor's_degree",
"institution",
"Loyola_University_Chicago"
],
[
"Bachelor's_degree",
"institution",
"Ludwig_Maximilian_University_of_Munich"
],
[
"Bachelor's_degree",
"institution",
"Manhattan_School_of_Music"
],
[
"Bachelor's_degree",
"institution",
"Massachusetts_Institute_of_Technology"
],
[
"Bachelor's_degree",
"institution",
"Miami_University"
],
[
"Bachelor's_degree",
"institution",
"Michigan_State_University"
],
[
"Bachelor's_degree",
"institution",
"Mississippi_State_University"
],
[
"Bachelor's_degree",
"institution",
"New_York_University"
],
[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"Northwestern_University"
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[
"Bachelor's_degree",
"institution",
"Pennsylvania_State_University"
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[
"Bachelor's_degree",
"institution",
"Pepperdine_University"
],
[
"Bachelor's_degree",
"institution",
"Pomona_College"
],
[
"Bachelor's_degree",
"institution",
"Portland_State_University"
],
[
"Bachelor's_degree",
"institution",
"Purdue_University"
],
[
"Bachelor's_degree",
"institution",
"Reed_College"
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[
"Bachelor's_degree",
"institution",
"Rensselaer_Polytechnic_Institute"
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[
"Bachelor's_degree",
"institution",
"San_Francisco_State_University"
],
[
"Bachelor's_degree",
"institution",
"San_JosΓ©_State_University"
],
[
"Bachelor's_degree",
"institution",
"Santa_Clara_University"
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[
"Bachelor's_degree",
"institution",
"Sarah_Lawrence_College"
],
[
"Bachelor's_degree",
"institution",
"Skidmore_College"
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[
"Bachelor's_degree",
"institution",
"Smith_College"
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[
"Bachelor's_degree",
"institution",
"Southern_Illinois_University_Carbondale"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"Stevens_Institute_of_Technology"
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[
"Bachelor's_degree",
"institution",
"Swarthmore_College"
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[
"Bachelor's_degree",
"institution",
"Syracuse_University"
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[
"Bachelor's_degree",
"institution",
"Tel_Aviv_University"
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[
"Bachelor's_degree",
"institution",
"Temple_University"
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[
"Bachelor's_degree",
"institution",
"Texas_Tech_University"
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[
"Bachelor's_degree",
"institution",
"The_College_of_Wooster"
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[
"Bachelor's_degree",
"institution",
"Tufts_University"
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[
"Bachelor's_degree",
"institution",
"Union_College"
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[
"Bachelor's_degree",
"institution",
"University_of_Arizona"
],
[
"Bachelor's_degree",
"institution",
"University_of_Bristol"
],
[
"Bachelor's_degree",
"institution",
"University_of_California,_Berkeley"
],
[
"Bachelor's_degree",
"institution",
"University_of_California,_Los_Angeles"
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[
"Bachelor's_degree",
"institution",
"University_of_Chicago"
],
[
"Bachelor's_degree",
"institution",
"University_of_Connecticut"
],
[
"Bachelor's_degree",
"institution",
"University_of_Denver"
],
[
"Bachelor's_degree",
"institution",
"University_of_Detroit_Mercy"
],
[
"Bachelor's_degree",
"institution",
"University_of_Florida"
],
[
"Bachelor's_degree",
"institution",
"University_of_Georgia"
],
[
"Bachelor's_degree",
"institution",
"University_of_Houston"
],
[
"Bachelor's_degree",
"institution",
"University_of_Idaho"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"University_of_Iowa"
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[
"Bachelor's_degree",
"institution",
"University_of_Kansas"
],
[
"Bachelor's_degree",
"institution",
"University_of_Maryland,_College_Park"
],
[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"University_of_Michigan"
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[
"Bachelor's_degree",
"institution",
"University_of_Minnesota"
],
[
"Bachelor's_degree",
"institution",
"University_of_Mississippi"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
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"University_of_North_Carolina_at_Charlotte"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"University_of_Pittsburgh"
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[
"Bachelor's_degree",
"institution",
"University_of_Rhode_Island"
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[
"Bachelor's_degree",
"institution",
"University_of_Richmond"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"University_of_Tennessee"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"University_of_Wyoming"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
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],
[
"Bachelor's_degree",
"institution",
"Washington_and_Lee_University"
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[
"Bachelor's_degree",
"institution",
"Wellesley_College"
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[
"Bachelor's_degree",
"institution",
"Wesleyan_University"
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[
"Bachelor's_degree",
"institution",
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[
"Bachelor's_degree",
"institution",
"Wheaton_College"
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[
"Bachelor's_degree",
"institution",
"Williams_College"
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[
"Bachelor's_degree",
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[
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[
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[
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[
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[
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[
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[
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[
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[
"Bachelor's_degree",
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"Diane_Sawyer"
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[
"Ball_State_University",
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"Accountancy"
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[
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"combatants",
"Kingdom_of_France"
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[
"Bavaria",
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"Ludwig_Maximilian_University_of_Munich"
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[
"Baylor_University",
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"Accountancy"
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[
"Baylor_University",
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[
"Binghamton_University",
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[
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"Accountancy"
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[
"Boston_University",
"major_field_of_study",
"Finance"
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[
"Boston_University",
"school_type",
"Private_school"
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[
"Bowdoin_College",
"school_type",
"Private_school"
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[
"Bowling_Green_State_University",
"major_field_of_study",
"Accountancy"
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[
"Bowling_Green_State_University",
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"Finance"
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[
"Bradley_University",
"major_field_of_study",
"Accountancy"
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[
"Bradley_University",
"school_type",
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[
"Brigham_Young_University",
"major_field_of_study",
"Accountancy"
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[
"Brigham_Young_University",
"major_field_of_study",
"Finance"
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[
"Business",
"major_field_of_study",
"Accountancy"
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[
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"major_field_of_study",
"Accountancy"
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[
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"school_type",
"Private_school"
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[
"California_State_University",
"major_field_of_study",
"Accountancy"
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[
"California_State_University",
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"Finance"
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[
"California_State_University,_Northridge",
"major_field_of_study",
"Accountancy"
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[
"California_State_University,_Northridge",
"major_field_of_study",
"Finance"
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[
"California_State_University,_Sacramento",
"major_field_of_study",
"Accountancy"
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[
"Claremont_McKenna_College",
"school_type",
"Private_school"
],
[
"Columbia_University",
"major_field_of_study",
"Finance"
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[
"Columbia_University_Graduate_School_of_Journalism",
"school_type",
"Private_school"
],
[
"Connecticut_College",
"school_type",
"Private_school"
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[
"Davidson_College",
"school_type",
"Private_school"
],
[
"Drake_University",
"major_field_of_study",
"Accountancy"
],
[
"Drake_University",
"school_type",
"Private_school"
],
[
"Drexel_University",
"major_field_of_study",
"Finance"
],
[
"Drexel_University",
"school_type",
"Private_school"
],
[
"Eastern_Illinois_University",
"major_field_of_study",
"Finance"
],
[
"Economics",
"major_field_of_study",
"Accountancy"
],
[
"Economics",
"major_field_of_study",
"Finance"
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[
"Fairleigh_Dickinson_University",
"major_field_of_study",
"Accountancy"
],
[
"Fairleigh_Dickinson_University",
"school_type",
"Private_school"
],
[
"Finance",
"major_field_of_study",
"Accountancy"
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[
"Finance",
"major_field_of_study",
"Business_Administration"
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[
"Finance",
"major_field_of_study",
"Economics"
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[
"Finance",
"major_field_of_study",
"Management"
],
[
"Finance",
"major_field_of_study",
"Marketing-GB"
],
[
"Florida_International_University",
"major_field_of_study",
"Accountancy"
],
[
"Fordham_University",
"major_field_of_study",
"Accountancy"
],
[
"Fordham_University",
"major_field_of_study",
"Finance"
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[
"George_Washington_University",
"major_field_of_study",
"Finance"
],
[
"Georgetown_University",
"major_field_of_study",
"Finance"
],
[
"Hallmark_Hall_of_Fame",
"award_honor_award",
"Peabody_Award"
],
[
"Hamilton_College",
"school_type",
"Private_school"
],
[
"Harvard_Business_School",
"major_field_of_study",
"Finance"
],
[
"Harvard_Business_School",
"school_type",
"Private_school"
],
[
"Harvard_College",
"school_type",
"Private_school"
],
[
"Harvard_University",
"major_field_of_study",
"Finance"
],
[
"Haverford_College",
"school_type",
"Private_school"
],
[
"Hobart_and_William_Smith_Colleges",
"school_type",
"Private_school"
],
[
"Indiana_University",
"major_field_of_study",
"Finance"
],
[
"Information_technology",
"major_field_of_study",
"Accountancy"
],
[
"Iowa_State_University",
"major_field_of_study",
"Accountancy"
],
[
"Ithaca_College",
"school_type",
"Private_school"
],
[
"John_F._Kennedy_School_of_Government",
"school_type",
"Private_school"
],
[
"Kellogg_School_of_Management",
"major_field_of_study",
"Finance"
],
[
"Kellogg_School_of_Management",
"school_type",
"Private_school"
],
[
"Kingdom_of_France",
"combatants",
"Bavaria"
],
[
"Knox_College,_Illinois",
"school_type",
"Private_school"
],
[
"Lafayette_College",
"school_type",
"Private_school"
],
[
"Lehigh_University",
"major_field_of_study",
"Accountancy"
],
[
"Lehigh_University",
"school_type",
"Private_school"
],
[
"Louisiana_State_University",
"major_field_of_study",
"Finance"
],
[
"Louisiana_Tech_University",
"major_field_of_study",
"Accountancy"
],
[
"Louisiana_Tech_University",
"major_field_of_study",
"Finance"
],
[
"Loyola_University_Chicago",
"major_field_of_study",
"Accountancy"
],
[
"Loyola_University_Chicago",
"major_field_of_study",
"Finance"
],
[
"Ludwig_Maximilian_University_of_Munich",
"state_province_region",
"Bavaria"
],
[
"MIT_Sloan_School_of_Management",
"major_field_of_study",
"Finance"
],
[
"MIT_Sloan_School_of_Management",
"school_type",
"Private_school"
],
[
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"major_field_of_study",
"Finance"
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[
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"school_type",
"Private_school"
],
[
"Marketing-GB",
"major_field_of_study",
"Accountancy"
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[
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"major_field_of_study",
"Finance"
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[
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"major_field_of_study",
"Finance"
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[
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"Accountancy"
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[
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"Finance"
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[
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"Accountancy"
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[
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"Finance"
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[
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"major_field_of_study",
"Accountancy"
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[
"Master_of_Science",
"major_field_of_study",
"Finance"
],
[
"Miami_University",
"major_field_of_study",
"Accountancy"
],
[
"Michigan_State_University",
"major_field_of_study",
"Accountancy"
],
[
"Mississippi_State_University",
"major_field_of_study",
"Finance"
],
[
"New_York_University",
"major_field_of_study",
"Finance"
],
[
"New_York_University_Stern_School_of_Business",
"major_field_of_study",
"Accountancy"
],
[
"New_York_University_Stern_School_of_Business",
"major_field_of_study",
"Finance"
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[
"New_York_University_Stern_School_of_Business",
"school_type",
"Private_school"
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[
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"major_field_of_study",
"Finance"
],
[
"Northeastern_University",
"school_type",
"Private_school"
],
[
"Northwestern_University",
"major_field_of_study",
"Finance"
],
[
"Peabody_Award",
"award_winner",
"Brigham_Young_University"
],
[
"Peabody_Award",
"award_winner",
"Columbia_University_Graduate_School_of_Journalism"
],
[
"Peabody_Award",
"award_winner",
"Diane_Sawyer"
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[
"Peabody_Award",
"award_winner",
"Hallmark_Hall_of_Fame"
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[
"Peabody_Award",
"award_winner",
"University_of_Maryland,_College_Park"
],
[
"Peabody_Award",
"award_winner",
"University_of_Memphis"
],
[
"Peabody_Award",
"award_winner",
"University_of_Southern_California"
],
[
"Pennsylvania_State_University",
"major_field_of_study",
"Accountancy"
],
[
"Pennsylvania_State_University",
"major_field_of_study",
"Finance"
],
[
"Pepperdine_University",
"school_type",
"Private_school"
],
[
"Political_Science",
"major_field_of_study",
"Accountancy"
],
[
"Pomona_College",
"school_type",
"Private_school"
],
[
"Portland_State_University",
"major_field_of_study",
"Finance"
],
[
"Purdue_University",
"major_field_of_study",
"Accountancy"
],
[
"Purdue_University",
"major_field_of_study",
"Finance"
],
[
"Reed_College",
"school_type",
"Private_school"
],
[
"Rensselaer_Polytechnic_Institute",
"major_field_of_study",
"Finance"
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[
"Saint_Joseph's_University",
"major_field_of_study",
"Accountancy"
],
[
"Saint_Joseph's_University",
"school_type",
"Private_school"
],
[
"San_Francisco_State_University",
"major_field_of_study",
"Accountancy"
],
[
"San_Francisco_State_University",
"major_field_of_study",
"Finance"
],
[
"San_JosΓ©_State_University",
"major_field_of_study",
"Accountancy"
],
[
"San_JosΓ©_State_University",
"major_field_of_study",
"Finance"
],
[
"Santa_Clara_University",
"major_field_of_study",
"Finance"
],
[
"Santa_Clara_University",
"school_type",
"Private_school"
],
[
"Sarah_Lawrence_College",
"school_type",
"Private_school"
],
[
"Skidmore_College",
"school_type",
"Private_school"
],
[
"Smith_College",
"school_type",
"Private_school"
],
[
"Southern_Illinois_University_Carbondale",
"major_field_of_study",
"Accountancy"
],
[
"St._Bonaventure_University",
"campuses",
"St._Bonaventure_University"
],
[
"St._Bonaventure_University",
"educational_institution",
"St._Bonaventure_University"
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[
"St._Bonaventure_University",
"major_field_of_study",
"Accountancy"
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[
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"major_field_of_study",
"Finance"
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[
"St._Bonaventure_University",
"school_type",
"Private_school"
],
[
"St._Lawrence_University",
"school_type",
"Private_school"
],
[
"Stanford_Graduate_School_of_Business",
"major_field_of_study",
"Finance"
],
[
"Stanford_Graduate_School_of_Business",
"school_type",
"Private_school"
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[
"Stevens_Institute_of_Technology",
"school_type",
"Private_school"
],
[
"Swarthmore_College",
"school_type",
"Private_school"
],
[
"Syracuse_University",
"major_field_of_study",
"Accountancy"
],
[
"Tel_Aviv_University",
"major_field_of_study",
"Accountancy"
],
[
"Temple_University",
"major_field_of_study",
"Finance"
],
[
"Texas_Tech_University",
"major_field_of_study",
"Finance"
],
[
"The_College_of_Wooster",
"school_type",
"Private_school"
],
[
"Tufts_University",
"school_type",
"Private_school"
],
[
"Union_College",
"school_type",
"Private_school"
],
[
"University_of_Arizona",
"major_field_of_study",
"Finance"
],
[
"University_of_Bristol",
"major_field_of_study",
"Accountancy"
],
[
"University_of_California,_Berkeley",
"major_field_of_study",
"Finance"
],
[
"University_of_California,_Los_Angeles",
"major_field_of_study",
"Accountancy"
],
[
"University_of_California,_Los_Angeles",
"major_field_of_study",
"Finance"
],
[
"University_of_Cape_Town",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Cape_Town",
"major_field_of_study",
"Finance"
],
[
"University_of_Chicago",
"major_field_of_study",
"Finance"
],
[
"University_of_Connecticut",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Delaware",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Delaware",
"major_field_of_study",
"Finance"
],
[
"University_of_Delaware",
"school_type",
"Private_school"
],
[
"University_of_Denver",
"school_type",
"Private_school"
],
[
"University_of_Detroit_Mercy",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Detroit_Mercy",
"major_field_of_study",
"Finance"
],
[
"University_of_Florida",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Georgia",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Houston",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Houston",
"major_field_of_study",
"Finance"
],
[
"University_of_Idaho",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Illinois_at_Chicago",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Iowa",
"major_field_of_study",
"Finance"
],
[
"University_of_Kansas",
"major_field_of_study",
"Finance"
],
[
"University_of_Maryland,_College_Park",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Memphis",
"major_field_of_study",
"Finance"
],
[
"University_of_Miami",
"major_field_of_study",
"Finance"
],
[
"University_of_Miami",
"school_type",
"Private_school"
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[
"University_of_Michigan",
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"Accountancy"
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[
"University_of_Michigan",
"major_field_of_study",
"Finance"
],
[
"University_of_Minnesota",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Mississippi",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Mississippi",
"major_field_of_study",
"Finance"
],
[
"University_of_MissouriβColumbia",
"major_field_of_study",
"Finance"
],
[
"University_of_North_Carolina_at_Chapel_Hill",
"major_field_of_study",
"Finance"
],
[
"University_of_North_Carolina_at_Charlotte",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Notre_Dame",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Notre_Dame",
"major_field_of_study",
"Finance"
],
[
"University_of_Notre_Dame",
"school_type",
"Private_school"
],
[
"University_of_Oregon",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Pittsburgh",
"major_field_of_study",
"Finance"
],
[
"University_of_Rhode_Island",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Richmond",
"school_type",
"Private_school"
],
[
"University_of_Rochester",
"major_field_of_study",
"Finance"
],
[
"University_of_South_Carolina",
"major_field_of_study",
"Finance"
],
[
"University_of_Southern_California",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Southern_California",
"major_field_of_study",
"Finance"
],
[
"University_of_Tennessee",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Texas_at_Arlington",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Texas_at_Arlington",
"major_field_of_study",
"Finance"
],
[
"University_of_Texas_at_Austin",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Texas_at_Austin",
"major_field_of_study",
"Finance"
],
[
"University_of_Tulsa",
"major_field_of_study",
"Finance"
],
[
"University_of_Tulsa",
"school_type",
"Private_school"
],
[
"University_of_Virginia",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Virginia",
"major_field_of_study",
"Finance"
],
[
"University_of_Wyoming",
"major_field_of_study",
"Accountancy"
],
[
"University_of_Wyoming",
"major_field_of_study",
"Finance"
],
[
"Villanova_University",
"major_field_of_study",
"Accountancy"
],
[
"Villanova_University",
"school_type",
"Private_school"
],
[
"Virginia_Commonwealth_University",
"major_field_of_study",
"Accountancy"
],
[
"Virginia_Commonwealth_University",
"major_field_of_study",
"Finance"
],
[
"Washington_and_Lee_University",
"school_type",
"Private_school"
],
[
"Wellesley_College",
"school_type",
"Private_school"
],
[
"Wesleyan_University",
"school_type",
"Private_school"
],
[
"Wharton_School_of_the_University_of_Pennsylvania",
"major_field_of_study",
"Accountancy"
],
[
"Wharton_School_of_the_University_of_Pennsylvania",
"major_field_of_study",
"Finance"
],
[
"Wheaton_College",
"school_type",
"Private_school"
],
[
"Williams_College",
"school_type",
"Private_school"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12784, 45th_Academy_Awards
9490, 65th_Tony_Awards
6771, 66th_Tony_Awards
10351, Anthony_Newley
1261, Bob_Fosse
2548, Cabaret
9231, Colorado
2218, Evangelicalism
9601, Fred_Ebb
8365, Geoffrey_Unsworth
8179, Harvey_Fierstein
2810, Hebrew_Language
5685, Joel_Grey
7959, John_Kander
6017, Liza_Minnelli
12863, Martin_Short
3939, National_Board_of_Review_Award_for_Best_Director
2955, Richard_Burton
196, Robert_Redford
9181, Rupert_Holmes
2258, Stephen_Schwartz
10120, The_Bible
2270, The_Passion_of_the_Christ
1184, The_Prince_of_Egypt
1743, The_Robe
5675, Tony_Award_for_Best_Actor_in_a_Musical
5036, Tony_Award_for_Best_Book_of_a_Musical
10852, Utah
src, edge_attr, dst
12784, award_winner, 1261
12784, award_winner, 8365
12784, award_winner, 5685
12784, award_winner, 6017
12784, honored_for, 2548
10351, award, 5675
10351, award, 5036
1261, award, 5675
1261, award, 5036
1261, award_nominee, 9601
1261, film, 2548
1261, nominated_for, 2548
2548, award_honor_award, 3939
2548, award_winner, 1261
2548, award_winner, 8365
2548, award_winner, 5685
2548, award_winner, 6017
2548, cinematography, 8365
2548, film_music, 9601
2548, film_music, 7959
2548, language, 2810
2548, produced_by, 1261
9231, adjoins, 10852
9231, religion, 2218
9601, award, 5036
9601, award_nominee, 1261
9601, award_winner, 7959
8365, nominated_for, 2548
8179, award, 5675
8179, award, 5036
5685, award, 5675
5685, nominated_for, 2548
7959, award_nominee, 9601
6017, acted_in, 2548
6017, nominated_for, 2548
12863, acted_in, 1184
12863, award, 5675
3939, award_winner, 1261
3939, award_winner, 196
2955, award, 5675
2955, nominated_for, 1743
196, location, 10852
9181, award, 5036
9181, award_nominee, 9601
2258, award, 5036
2258, nominated_for, 1184
10120, films, 2270
10120, films, 1184
10120, films, 1743
2270, language, 2810
1184, language, 2810
5675, award_winner, 12863
5675, ceremony, 9490
5675, ceremony, 6771
5036, award_winner, 8179
5036, award_winner, 9181
5036, ceremony, 9490
5036, ceremony, 6771
10852, adjoins, 9231
10852, religion, 2218
Question: How are Bob_Fosse, Evangelicalism, and The_Bible related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bob_Fosse",
"Evangelicalism",
"The_Bible"
],
"valid_edges": [
[
"45th_Academy_Awards",
"award_winner",
"Bob_Fosse"
],
[
"45th_Academy_Awards",
"award_winner",
"Geoffrey_Unsworth"
],
[
"45th_Academy_Awards",
"award_winner",
"Joel_Grey"
],
[
"45th_Academy_Awards",
"award_winner",
"Liza_Minnelli"
],
[
"45th_Academy_Awards",
"honored_for",
"Cabaret"
],
[
"Anthony_Newley",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"Anthony_Newley",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Bob_Fosse",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"Bob_Fosse",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Bob_Fosse",
"award_nominee",
"Fred_Ebb"
],
[
"Bob_Fosse",
"film",
"Cabaret"
],
[
"Bob_Fosse",
"nominated_for",
"Cabaret"
],
[
"Cabaret",
"award_honor_award",
"National_Board_of_Review_Award_for_Best_Director"
],
[
"Cabaret",
"award_winner",
"Bob_Fosse"
],
[
"Cabaret",
"award_winner",
"Geoffrey_Unsworth"
],
[
"Cabaret",
"award_winner",
"Joel_Grey"
],
[
"Cabaret",
"award_winner",
"Liza_Minnelli"
],
[
"Cabaret",
"cinematography",
"Geoffrey_Unsworth"
],
[
"Cabaret",
"film_music",
"Fred_Ebb"
],
[
"Cabaret",
"film_music",
"John_Kander"
],
[
"Cabaret",
"language",
"Hebrew_Language"
],
[
"Cabaret",
"produced_by",
"Bob_Fosse"
],
[
"Colorado",
"adjoins",
"Utah"
],
[
"Colorado",
"religion",
"Evangelicalism"
],
[
"Fred_Ebb",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Fred_Ebb",
"award_nominee",
"Bob_Fosse"
],
[
"Fred_Ebb",
"award_winner",
"John_Kander"
],
[
"Geoffrey_Unsworth",
"nominated_for",
"Cabaret"
],
[
"Harvey_Fierstein",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"Harvey_Fierstein",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Joel_Grey",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"Joel_Grey",
"nominated_for",
"Cabaret"
],
[
"John_Kander",
"award_nominee",
"Fred_Ebb"
],
[
"Liza_Minnelli",
"acted_in",
"Cabaret"
],
[
"Liza_Minnelli",
"nominated_for",
"Cabaret"
],
[
"Martin_Short",
"acted_in",
"The_Prince_of_Egypt"
],
[
"Martin_Short",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"National_Board_of_Review_Award_for_Best_Director",
"award_winner",
"Bob_Fosse"
],
[
"National_Board_of_Review_Award_for_Best_Director",
"award_winner",
"Robert_Redford"
],
[
"Richard_Burton",
"award",
"Tony_Award_for_Best_Actor_in_a_Musical"
],
[
"Richard_Burton",
"nominated_for",
"The_Robe"
],
[
"Robert_Redford",
"location",
"Utah"
],
[
"Rupert_Holmes",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Rupert_Holmes",
"award_nominee",
"Fred_Ebb"
],
[
"Stephen_Schwartz",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Stephen_Schwartz",
"nominated_for",
"The_Prince_of_Egypt"
],
[
"The_Bible",
"films",
"The_Passion_of_the_Christ"
],
[
"The_Bible",
"films",
"The_Prince_of_Egypt"
],
[
"The_Bible",
"films",
"The_Robe"
],
[
"The_Passion_of_the_Christ",
"language",
"Hebrew_Language"
],
[
"The_Prince_of_Egypt",
"language",
"Hebrew_Language"
],
[
"Tony_Award_for_Best_Actor_in_a_Musical",
"award_winner",
"Martin_Short"
],
[
"Tony_Award_for_Best_Actor_in_a_Musical",
"ceremony",
"65th_Tony_Awards"
],
[
"Tony_Award_for_Best_Actor_in_a_Musical",
"ceremony",
"66th_Tony_Awards"
],
[
"Tony_Award_for_Best_Book_of_a_Musical",
"award_winner",
"Harvey_Fierstein"
],
[
"Tony_Award_for_Best_Book_of_a_Musical",
"award_winner",
"Rupert_Holmes"
],
[
"Tony_Award_for_Best_Book_of_a_Musical",
"ceremony",
"65th_Tony_Awards"
],
[
"Tony_Award_for_Best_Book_of_a_Musical",
"ceremony",
"66th_Tony_Awards"
],
[
"Utah",
"adjoins",
"Colorado"
],
[
"Utah",
"religion",
"Evangelicalism"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
10565, Australia
5282, Australia_national_association_football_team
10308, Football
5709, Ghana_national_football_team
4194, Goalkeeper
6953, Greater_Manchester
5527, Honduras_national_football_team
8038, K.S.C._Lokeren_Oost-Vlaanderen
6018, Manchester_United_F.C.
2182, Richard_Roxburgh
12271, Wigan
5097, Wigan_Athletic_F.C.
src, edge_attr, dst
10565, film_country, 10565
10565, teams, 5282
5282, football_roster_position, 4194
5282, position, 4194
10308, country, 10565
5709, current_club, 5097
5709, football_roster_position, 4194
4194, team, 5282
4194, team, 5709
4194, team, 5527
4194, team, 8038
4194, team, 6018
4194, team, 5097
6953, contains, 12271
5527, current_club, 5097
5527, football_roster_position, 4194
5527, position, 4194
6018, football_roster_position, 4194
6018, state_province_region, 6953
2182, nationality, 10565
12271, teams, 5097
5097, sport, 10308
Question: How are K.S.C._Lokeren_Oost-Vlaanderen, Richard_Roxburgh, and Wigan related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"K.S.C._Lokeren_Oost-Vlaanderen",
"Richard_Roxburgh",
"Wigan"
],
"valid_edges": [
[
"Australia",
"film_country",
"Australia"
],
[
"Australia",
"teams",
"Australia_national_association_football_team"
],
[
"Australia_national_association_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Australia_national_association_football_team",
"position",
"Goalkeeper"
],
[
"Football",
"country",
"Australia"
],
[
"Ghana_national_football_team",
"current_club",
"Wigan_Athletic_F.C."
],
[
"Ghana_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Goalkeeper",
"team",
"Australia_national_association_football_team"
],
[
"Goalkeeper",
"team",
"Ghana_national_football_team"
],
[
"Goalkeeper",
"team",
"Honduras_national_football_team"
],
[
"Goalkeeper",
"team",
"K.S.C._Lokeren_Oost-Vlaanderen"
],
[
"Goalkeeper",
"team",
"Manchester_United_F.C."
],
[
"Goalkeeper",
"team",
"Wigan_Athletic_F.C."
],
[
"Greater_Manchester",
"contains",
"Wigan"
],
[
"Honduras_national_football_team",
"current_club",
"Wigan_Athletic_F.C."
],
[
"Honduras_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Honduras_national_football_team",
"position",
"Goalkeeper"
],
[
"Manchester_United_F.C.",
"football_roster_position",
"Goalkeeper"
],
[
"Manchester_United_F.C.",
"state_province_region",
"Greater_Manchester"
],
[
"Richard_Roxburgh",
"nationality",
"Australia"
],
[
"Wigan",
"teams",
"Wigan_Athletic_F.C."
],
[
"Wigan_Athletic_F.C.",
"sport",
"Football"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9454, A_Pup_Named_Scooby-Doo
13845, Bobby_McFerrin
3211, Brian_Wilson
6977, Casey_Kasem
9775, Chris_Botti
13641, Chris_Thile
3846, Debbie_Harry
10492, Grammy_Award_for_Best_Classical_Crossover_Album
993, Joshua_Redman
6586, Nonesuch_Records
8170, Radio_personality-GB
4961, Reggae
4991, Sire_Records
4857, k.d._lang
src, edge_attr, dst
9454, actor, 6977
13845, award, 10492
6977, profession, 8170
9775, award, 10492
9775, award_nominee, 13641
9775, award_nominee, 993
9775, award_winner, 13641
9775, award_winner, 993
9775, profession, 8170
13641, award, 10492
13641, award_nominee, 9775
13641, award_nominee, 993
13641, award_winner, 9775
13641, award_winner, 993
10492, award_winner, 13641
10492, award_winner, 993
993, award, 10492
993, award_nominee, 9775
993, award_winner, 9775
993, award_winner, 13641
6586, artist, 3211
6586, artist, 13641
6586, artist, 993
6586, artist, 4857
4961, artists, 13845
4961, artists, 3846
4991, artist, 3211
4991, artist, 3846
4991, artist, 4857
Question: In what context are A_Pup_Named_Scooby-Doo, Chris_Thile, and Debbie_Harry connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"A_Pup_Named_Scooby-Doo",
"Chris_Thile",
"Debbie_Harry"
],
"valid_edges": [
[
"A_Pup_Named_Scooby-Doo",
"actor",
"Casey_Kasem"
],
[
"Bobby_McFerrin",
"award",
"Grammy_Award_for_Best_Classical_Crossover_Album"
],
[
"Casey_Kasem",
"profession",
"Radio_personality-GB"
],
[
"Chris_Botti",
"award",
"Grammy_Award_for_Best_Classical_Crossover_Album"
],
[
"Chris_Botti",
"award_nominee",
"Chris_Thile"
],
[
"Chris_Botti",
"award_nominee",
"Joshua_Redman"
],
[
"Chris_Botti",
"award_winner",
"Chris_Thile"
],
[
"Chris_Botti",
"award_winner",
"Joshua_Redman"
],
[
"Chris_Botti",
"profession",
"Radio_personality-GB"
],
[
"Chris_Thile",
"award",
"Grammy_Award_for_Best_Classical_Crossover_Album"
],
[
"Chris_Thile",
"award_nominee",
"Chris_Botti"
],
[
"Chris_Thile",
"award_nominee",
"Joshua_Redman"
],
[
"Chris_Thile",
"award_winner",
"Chris_Botti"
],
[
"Chris_Thile",
"award_winner",
"Joshua_Redman"
],
[
"Grammy_Award_for_Best_Classical_Crossover_Album",
"award_winner",
"Chris_Thile"
],
[
"Grammy_Award_for_Best_Classical_Crossover_Album",
"award_winner",
"Joshua_Redman"
],
[
"Joshua_Redman",
"award",
"Grammy_Award_for_Best_Classical_Crossover_Album"
],
[
"Joshua_Redman",
"award_nominee",
"Chris_Botti"
],
[
"Joshua_Redman",
"award_winner",
"Chris_Botti"
],
[
"Joshua_Redman",
"award_winner",
"Chris_Thile"
],
[
"Nonesuch_Records",
"artist",
"Brian_Wilson"
],
[
"Nonesuch_Records",
"artist",
"Chris_Thile"
],
[
"Nonesuch_Records",
"artist",
"Joshua_Redman"
],
[
"Nonesuch_Records",
"artist",
"k.d._lang"
],
[
"Reggae",
"artists",
"Bobby_McFerrin"
],
[
"Reggae",
"artists",
"Debbie_Harry"
],
[
"Sire_Records",
"artist",
"Brian_Wilson"
],
[
"Sire_Records",
"artist",
"Debbie_Harry"
],
[
"Sire_Records",
"artist",
"k.d._lang"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4929, Adam_Smith
3669, Alan_Moore
5836, Anglicanism
11007, Aristotle
3272, Atheism
12643, Ayn_Rand
5785, Balliol_College
8220, Baruch_Spinoza
11769, Bill_Finger
5139, C._S._Lewis
11214, Cartoonist
3022, Charles_Dickens
12992, Christ_Church,_Oxford
14198, Christchurch
1038, Christopher_Hitchens
7378, Classics
12614, Dante_Alighieri
260, Denver
7971, Dr._Seuss
14114, Edmund_Husserl
9145, English_Literature
3334, English_people
7907, Epistemology
3504, Ethics
7240, Friedrich_Nietzsche
12717, Fyodor_Dostoyevsky
294, Georg_Wilhelm_Friedrich_Hegel
11101, Gilles_Deleuze
5914, Gottfried_Wilhelm_von_Leibniz
2879, Hannah_Arendt
11956, Hermann_Hesse
10776, Hugh_Dancy
5391, Immanuel_Kant
3579, J._R._R._Tolkien
1119, Jacques_Derrida
5770, Jacques_Lacan
2937, James_Joyce
7857, Jane_Austen
11833, Jean-Paul_Sartre
3100, Johann_Wolfgang_von_Goethe
13645, John_Dewey
5006, John_Locke
1400, Jonathan_Swift
12994, Jorge_Luis_Borges
10808, Karl_Marx
1905, Kate_Beckinsale
9625, Leo_Tolstoy
3546, Lewis_Carroll
1372, Margaret_Thatcher
7413, Mark_Williams
11615, Martin_Heidegger
7957, Mathematics
3278, Mayor
12147, Michael_Palin
2478, Michael_Winterbottom
7062, Michael_York
927, Michel_Foucault
10455, Oscar_Wilde
1299, Oxford
13922, Oxfordshire
2752, Paris
716, PhD
9310, Philip_K._Dick
9376, Plato
7572, Playwright-GB
8121, Politics
263, Ralph_Waldo_Emerson
13120, Richard_Curtis
7324, Richard_Dawkins
2154, Richard_Rorty
8382, Samuel_R._Delany
534, South_Island
11228, Steve_Ditko
8475, T._S._Eliot
11240, Theodor_W._Adorno
5377, Thomas_Aquinas
6334, Thomas_Hobbes
2977, University_of_Oxford
8423, Victor_Hugo
5811, Voltaire
3087, W._H._Auden
5812, Walter_Benjamin
13284, William_Shakespeare
src, edge_attr, dst
4929, influenced_by, 11007
4929, influenced_by, 5006
4929, influenced_by, 6334
4929, interests, 3504
3669, profession, 11214
11007, influenced_by, 9376
11007, interests, 3504
11007, interests, 8121
12643, influenced_by, 4929
12643, influenced_by, 11007
12643, influenced_by, 7240
12643, influenced_by, 12717
12643, influenced_by, 5391
12643, influenced_by, 5006
12643, influenced_by, 5377
12643, influenced_by, 8423
12643, profession, 7572
12643, religion, 3272
5785, student, 4929
8220, influenced_by, 11007
8220, influenced_by, 9376
8220, influenced_by, 6334
8220, interests, 7907
8220, interests, 3504
8220, religion, 3272
11769, place_of_birth, 260
11769, profession, 11214
5139, influenced_by, 11007
5139, influenced_by, 9376
5139, religion, 5836
3022, religion, 5836
12992, campuses, 12992
12992, citytown, 1299
12992, educational_institution, 12992
12992, major_field_of_study, 7378
12992, major_field_of_study, 9145
12992, major_field_of_study, 7957
12992, state_province_region, 13922
12992, student, 5006
12992, student, 3546
12992, student, 13120
12992, student, 3087
1038, influenced_by, 8220
1038, influenced_by, 10808
1038, influenced_by, 6334
1038, influenced_by, 5811
12614, influenced_by, 11007
12614, influenced_by, 5377
260, county, 260
260, county_seat, 260
260, place, 260
7971, profession, 11214
14114, influenced_by, 5391
14114, influenced_by, 9376
14114, interests, 7907
3334, people, 3669
3334, people, 3022
3334, people, 10776
3334, people, 3579
3334, people, 7857
3334, people, 5006
3334, people, 1905
3334, people, 7413
3334, people, 12147
3334, people, 2478
3334, people, 7062
3334, people, 13120
3334, people, 7324
3334, people, 6334
3334, people, 3087
3334, people, 13284
3334, split_to, 9145
7240, influenced_by, 11007
7240, influenced_by, 8220
7240, influenced_by, 5391
7240, influenced_by, 9376
7240, influenced_by, 5811
12717, influenced_by, 5391
12717, influenced_by, 9376
294, influenced_by, 4929
294, influenced_by, 11007
294, influenced_by, 8220
294, influenced_by, 5391
294, influenced_by, 9376
294, interests, 7907
11101, influenced_by, 8220
11101, influenced_by, 5391
11101, influenced_by, 10808
5914, influenced_by, 11007
5914, influenced_by, 8220
5914, influenced_by, 9376
5914, influenced_by, 5377
5914, influenced_by, 6334
2879, influenced_by, 11007
2879, influenced_by, 5391
2879, influenced_by, 10808
2879, influenced_by, 9376
2879, interests, 7907
11956, influenced_by, 8220
11956, influenced_by, 9376
5391, influenced_by, 11007
5391, influenced_by, 8220
5391, influenced_by, 5914
5391, influenced_by, 5006
5391, influenced_by, 9376
5391, influenced_by, 5377
5391, interests, 7907
5391, interests, 3504
1119, influenced_by, 10808
1119, influenced_by, 9376
5770, influenced_by, 11007
5770, influenced_by, 8220
5770, influenced_by, 10808
5770, influenced_by, 9376
2937, influenced_by, 11007
2937, influenced_by, 5377
7857, religion, 5836
11833, influenced_by, 5391
11833, influenced_by, 10808
11833, influenced_by, 9376
11833, influenced_by, 5811
11833, interests, 7907
3100, influenced_by, 8220
3100, influenced_by, 5391
13645, influenced_by, 294
13645, influenced_by, 5391
13645, influenced_by, 5006
13645, influenced_by, 9376
13645, interests, 7907
13645, interests, 3504
5006, influenced_by, 11007
5006, influenced_by, 8220
5006, influenced_by, 9376
5006, influenced_by, 5377
5006, influenced_by, 6334
5006, interests, 7907
5006, religion, 5836
1400, religion, 5836
12994, influenced_by, 8220
12994, influenced_by, 9376
10808, influenced_by, 4929
10808, influenced_by, 11007
10808, influenced_by, 8220
10808, influenced_by, 3022
10808, influenced_by, 12614
10808, influenced_by, 294
10808, influenced_by, 5391
10808, influenced_by, 3100
10808, influenced_by, 5006
10808, influenced_by, 5811
10808, influenced_by, 13284
10808, interests, 8121
10808, religion, 3272
9625, influenced_by, 11007
9625, influenced_by, 9376
3546, company, 12992
3546, religion, 5836
1372, influenced_by, 12643
11615, influenced_by, 11007
11615, influenced_by, 5391
11615, influenced_by, 9376
3278, jurisdiction_of_office, 14198
3278, jurisdiction_of_office, 260
927, influenced_by, 5391
927, influenced_by, 10808
927, interests, 7907
10455, influenced_by, 11007
10455, influenced_by, 9376
1299, contains, 12992
1299, contains, 2977
13922, contains, 12992
716, institution, 2977
716, student, 13645
9310, influenced_by, 8220
9310, influenced_by, 5391
9376, interests, 7907
9376, interests, 8121
263, influenced_by, 5391
263, influenced_by, 9376
7324, company, 2977
2154, influenced_by, 13645
2154, influenced_by, 9376
2154, interests, 7907
8382, influenced_by, 9376
8382, profession, 11214
534, contains, 14198
11228, influenced_by, 12643
11228, profession, 11214
8475, influenced_by, 5391
8475, religion, 5836
11240, influenced_by, 5391
11240, influenced_by, 10808
11240, interests, 7907
5377, influenced_by, 11007
5377, influenced_by, 9376
5377, interests, 7907
5377, interests, 3504
6334, influenced_by, 11007
6334, influenced_by, 9376
6334, interests, 3504
6334, location, 2752
6334, religion, 5836
2977, campuses, 2977
2977, child, 5785
2977, educational_institution, 2977
2977, major_field_of_study, 7378
2977, major_field_of_study, 7957
2977, major_field_of_study, 8121
2977, state_province_region, 13922
2977, student, 4929
2977, student, 5139
2977, student, 1038
2977, student, 7971
2977, student, 10776
2977, student, 3579
2977, student, 5006
2977, student, 1400
2977, student, 1905
2977, student, 3546
2977, student, 1372
2977, student, 7413
2977, student, 12147
2977, student, 2478
2977, student, 7062
2977, student, 10455
2977, student, 13120
2977, student, 8475
2977, student, 3087
8423, influenced_by, 5811
5811, influenced_by, 5006
5811, influenced_by, 9376
5811, influenced_by, 13284
5811, location, 2752
5811, place_of_death, 2752
5811, profession, 7572
3087, religion, 5836
5812, influenced_by, 10808
5812, interests, 7907
Question: In what context are Bill_Finger, John_Locke, and South_Island connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bill_Finger",
"John_Locke",
"South_Island"
],
"valid_edges": [
[
"Adam_Smith",
"influenced_by",
"Aristotle"
],
[
"Adam_Smith",
"influenced_by",
"John_Locke"
],
[
"Adam_Smith",
"influenced_by",
"Thomas_Hobbes"
],
[
"Adam_Smith",
"interests",
"Ethics"
],
[
"Alan_Moore",
"profession",
"Cartoonist"
],
[
"Aristotle",
"influenced_by",
"Plato"
],
[
"Aristotle",
"interests",
"Ethics"
],
[
"Aristotle",
"interests",
"Politics"
],
[
"Ayn_Rand",
"influenced_by",
"Adam_Smith"
],
[
"Ayn_Rand",
"influenced_by",
"Aristotle"
],
[
"Ayn_Rand",
"influenced_by",
"Friedrich_Nietzsche"
],
[
"Ayn_Rand",
"influenced_by",
"Fyodor_Dostoyevsky"
],
[
"Ayn_Rand",
"influenced_by",
"Immanuel_Kant"
],
[
"Ayn_Rand",
"influenced_by",
"John_Locke"
],
[
"Ayn_Rand",
"influenced_by",
"Thomas_Aquinas"
],
[
"Ayn_Rand",
"influenced_by",
"Victor_Hugo"
],
[
"Ayn_Rand",
"profession",
"Playwright-GB"
],
[
"Ayn_Rand",
"religion",
"Atheism"
],
[
"Balliol_College",
"student",
"Adam_Smith"
],
[
"Baruch_Spinoza",
"influenced_by",
"Aristotle"
],
[
"Baruch_Spinoza",
"influenced_by",
"Plato"
],
[
"Baruch_Spinoza",
"influenced_by",
"Thomas_Hobbes"
],
[
"Baruch_Spinoza",
"interests",
"Epistemology"
],
[
"Baruch_Spinoza",
"interests",
"Ethics"
],
[
"Baruch_Spinoza",
"religion",
"Atheism"
],
[
"Bill_Finger",
"place_of_birth",
"Denver"
],
[
"Bill_Finger",
"profession",
"Cartoonist"
],
[
"C._S._Lewis",
"influenced_by",
"Aristotle"
],
[
"C._S._Lewis",
"influenced_by",
"Plato"
],
[
"C._S._Lewis",
"religion",
"Anglicanism"
],
[
"Charles_Dickens",
"religion",
"Anglicanism"
],
[
"Christ_Church,_Oxford",
"campuses",
"Christ_Church,_Oxford"
],
[
"Christ_Church,_Oxford",
"citytown",
"Oxford"
],
[
"Christ_Church,_Oxford",
"educational_institution",
"Christ_Church,_Oxford"
],
[
"Christ_Church,_Oxford",
"major_field_of_study",
"Classics"
],
[
"Christ_Church,_Oxford",
"major_field_of_study",
"English_Literature"
],
[
"Christ_Church,_Oxford",
"major_field_of_study",
"Mathematics"
],
[
"Christ_Church,_Oxford",
"state_province_region",
"Oxfordshire"
],
[
"Christ_Church,_Oxford",
"student",
"John_Locke"
],
[
"Christ_Church,_Oxford",
"student",
"Lewis_Carroll"
],
[
"Christ_Church,_Oxford",
"student",
"Richard_Curtis"
],
[
"Christ_Church,_Oxford",
"student",
"W._H._Auden"
],
[
"Christopher_Hitchens",
"influenced_by",
"Baruch_Spinoza"
],
[
"Christopher_Hitchens",
"influenced_by",
"Karl_Marx"
],
[
"Christopher_Hitchens",
"influenced_by",
"Thomas_Hobbes"
],
[
"Christopher_Hitchens",
"influenced_by",
"Voltaire"
],
[
"Dante_Alighieri",
"influenced_by",
"Aristotle"
],
[
"Dante_Alighieri",
"influenced_by",
"Thomas_Aquinas"
],
[
"Denver",
"county",
"Denver"
],
[
"Denver",
"county_seat",
"Denver"
],
[
"Denver",
"place",
"Denver"
],
[
"Dr._Seuss",
"profession",
"Cartoonist"
],
[
"Edmund_Husserl",
"influenced_by",
"Immanuel_Kant"
],
[
"Edmund_Husserl",
"influenced_by",
"Plato"
],
[
"Edmund_Husserl",
"interests",
"Epistemology"
],
[
"English_people",
"people",
"Alan_Moore"
],
[
"English_people",
"people",
"Charles_Dickens"
],
[
"English_people",
"people",
"Hugh_Dancy"
],
[
"English_people",
"people",
"J._R._R._Tolkien"
],
[
"English_people",
"people",
"Jane_Austen"
],
[
"English_people",
"people",
"John_Locke"
],
[
"English_people",
"people",
"Kate_Beckinsale"
],
[
"English_people",
"people",
"Mark_Williams"
],
[
"English_people",
"people",
"Michael_Palin"
],
[
"English_people",
"people",
"Michael_Winterbottom"
],
[
"English_people",
"people",
"Michael_York"
],
[
"English_people",
"people",
"Richard_Curtis"
],
[
"English_people",
"people",
"Richard_Dawkins"
],
[
"English_people",
"people",
"Thomas_Hobbes"
],
[
"English_people",
"people",
"W._H._Auden"
],
[
"English_people",
"people",
"William_Shakespeare"
],
[
"English_people",
"split_to",
"English_Literature"
],
[
"Friedrich_Nietzsche",
"influenced_by",
"Aristotle"
],
[
"Friedrich_Nietzsche",
"influenced_by",
"Baruch_Spinoza"
],
[
"Friedrich_Nietzsche",
"influenced_by",
"Immanuel_Kant"
],
[
"Friedrich_Nietzsche",
"influenced_by",
"Plato"
],
[
"Friedrich_Nietzsche",
"influenced_by",
"Voltaire"
],
[
"Fyodor_Dostoyevsky",
"influenced_by",
"Immanuel_Kant"
],
[
"Fyodor_Dostoyevsky",
"influenced_by",
"Plato"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"influenced_by",
"Adam_Smith"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"influenced_by",
"Aristotle"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"influenced_by",
"Baruch_Spinoza"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"influenced_by",
"Immanuel_Kant"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"influenced_by",
"Plato"
],
[
"Georg_Wilhelm_Friedrich_Hegel",
"interests",
"Epistemology"
],
[
"Gilles_Deleuze",
"influenced_by",
"Baruch_Spinoza"
],
[
"Gilles_Deleuze",
"influenced_by",
"Immanuel_Kant"
],
[
"Gilles_Deleuze",
"influenced_by",
"Karl_Marx"
],
[
"Gottfried_Wilhelm_von_Leibniz",
"influenced_by",
"Aristotle"
],
[
"Gottfried_Wilhelm_von_Leibniz",
"influenced_by",
"Baruch_Spinoza"
],
[
"Gottfried_Wilhelm_von_Leibniz",
"influenced_by",
"Plato"
],
[
"Gottfried_Wilhelm_von_Leibniz",
"influenced_by",
"Thomas_Aquinas"
],
[
"Gottfried_Wilhelm_von_Leibniz",
"influenced_by",
"Thomas_Hobbes"
],
[
"Hannah_Arendt",
"influenced_by",
"Aristotle"
],
[
"Hannah_Arendt",
"influenced_by",
"Immanuel_Kant"
],
[
"Hannah_Arendt",
"influenced_by",
"Karl_Marx"
],
[
"Hannah_Arendt",
"influenced_by",
"Plato"
],
[
"Hannah_Arendt",
"interests",
"Epistemology"
],
[
"Hermann_Hesse",
"influenced_by",
"Baruch_Spinoza"
],
[
"Hermann_Hesse",
"influenced_by",
"Plato"
],
[
"Immanuel_Kant",
"influenced_by",
"Aristotle"
],
[
"Immanuel_Kant",
"influenced_by",
"Baruch_Spinoza"
],
[
"Immanuel_Kant",
"influenced_by",
"Gottfried_Wilhelm_von_Leibniz"
],
[
"Immanuel_Kant",
"influenced_by",
"John_Locke"
],
[
"Immanuel_Kant",
"influenced_by",
"Plato"
],
[
"Immanuel_Kant",
"influenced_by",
"Thomas_Aquinas"
],
[
"Immanuel_Kant",
"interests",
"Epistemology"
],
[
"Immanuel_Kant",
"interests",
"Ethics"
],
[
"Jacques_Derrida",
"influenced_by",
"Karl_Marx"
],
[
"Jacques_Derrida",
"influenced_by",
"Plato"
],
[
"Jacques_Lacan",
"influenced_by",
"Aristotle"
],
[
"Jacques_Lacan",
"influenced_by",
"Baruch_Spinoza"
],
[
"Jacques_Lacan",
"influenced_by",
"Karl_Marx"
],
[
"Jacques_Lacan",
"influenced_by",
"Plato"
],
[
"James_Joyce",
"influenced_by",
"Aristotle"
],
[
"James_Joyce",
"influenced_by",
"Thomas_Aquinas"
],
[
"Jane_Austen",
"religion",
"Anglicanism"
],
[
"Jean-Paul_Sartre",
"influenced_by",
"Immanuel_Kant"
],
[
"Jean-Paul_Sartre",
"influenced_by",
"Karl_Marx"
],
[
"Jean-Paul_Sartre",
"influenced_by",
"Plato"
],
[
"Jean-Paul_Sartre",
"influenced_by",
"Voltaire"
],
[
"Jean-Paul_Sartre",
"interests",
"Epistemology"
],
[
"Johann_Wolfgang_von_Goethe",
"influenced_by",
"Baruch_Spinoza"
],
[
"Johann_Wolfgang_von_Goethe",
"influenced_by",
"Immanuel_Kant"
],
[
"John_Dewey",
"influenced_by",
"Georg_Wilhelm_Friedrich_Hegel"
],
[
"John_Dewey",
"influenced_by",
"Immanuel_Kant"
],
[
"John_Dewey",
"influenced_by",
"John_Locke"
],
[
"John_Dewey",
"influenced_by",
"Plato"
],
[
"John_Dewey",
"interests",
"Epistemology"
],
[
"John_Dewey",
"interests",
"Ethics"
],
[
"John_Locke",
"influenced_by",
"Aristotle"
],
[
"John_Locke",
"influenced_by",
"Baruch_Spinoza"
],
[
"John_Locke",
"influenced_by",
"Plato"
],
[
"John_Locke",
"influenced_by",
"Thomas_Aquinas"
],
[
"John_Locke",
"influenced_by",
"Thomas_Hobbes"
],
[
"John_Locke",
"interests",
"Epistemology"
],
[
"John_Locke",
"religion",
"Anglicanism"
],
[
"Jonathan_Swift",
"religion",
"Anglicanism"
],
[
"Jorge_Luis_Borges",
"influenced_by",
"Baruch_Spinoza"
],
[
"Jorge_Luis_Borges",
"influenced_by",
"Plato"
],
[
"Karl_Marx",
"influenced_by",
"Adam_Smith"
],
[
"Karl_Marx",
"influenced_by",
"Aristotle"
],
[
"Karl_Marx",
"influenced_by",
"Baruch_Spinoza"
],
[
"Karl_Marx",
"influenced_by",
"Charles_Dickens"
],
[
"Karl_Marx",
"influenced_by",
"Dante_Alighieri"
],
[
"Karl_Marx",
"influenced_by",
"Georg_Wilhelm_Friedrich_Hegel"
],
[
"Karl_Marx",
"influenced_by",
"Immanuel_Kant"
],
[
"Karl_Marx",
"influenced_by",
"Johann_Wolfgang_von_Goethe"
],
[
"Karl_Marx",
"influenced_by",
"John_Locke"
],
[
"Karl_Marx",
"influenced_by",
"Voltaire"
],
[
"Karl_Marx",
"influenced_by",
"William_Shakespeare"
],
[
"Karl_Marx",
"interests",
"Politics"
],
[
"Karl_Marx",
"religion",
"Atheism"
],
[
"Leo_Tolstoy",
"influenced_by",
"Aristotle"
],
[
"Leo_Tolstoy",
"influenced_by",
"Plato"
],
[
"Lewis_Carroll",
"company",
"Christ_Church,_Oxford"
],
[
"Lewis_Carroll",
"religion",
"Anglicanism"
],
[
"Margaret_Thatcher",
"influenced_by",
"Ayn_Rand"
],
[
"Martin_Heidegger",
"influenced_by",
"Aristotle"
],
[
"Martin_Heidegger",
"influenced_by",
"Immanuel_Kant"
],
[
"Martin_Heidegger",
"influenced_by",
"Plato"
],
[
"Mayor",
"jurisdiction_of_office",
"Christchurch"
],
[
"Mayor",
"jurisdiction_of_office",
"Denver"
],
[
"Michel_Foucault",
"influenced_by",
"Immanuel_Kant"
],
[
"Michel_Foucault",
"influenced_by",
"Karl_Marx"
],
[
"Michel_Foucault",
"interests",
"Epistemology"
],
[
"Oscar_Wilde",
"influenced_by",
"Aristotle"
],
[
"Oscar_Wilde",
"influenced_by",
"Plato"
],
[
"Oxford",
"contains",
"Christ_Church,_Oxford"
],
[
"Oxford",
"contains",
"University_of_Oxford"
],
[
"Oxfordshire",
"contains",
"Christ_Church,_Oxford"
],
[
"PhD",
"institution",
"University_of_Oxford"
],
[
"PhD",
"student",
"John_Dewey"
],
[
"Philip_K._Dick",
"influenced_by",
"Baruch_Spinoza"
],
[
"Philip_K._Dick",
"influenced_by",
"Immanuel_Kant"
],
[
"Plato",
"interests",
"Epistemology"
],
[
"Plato",
"interests",
"Politics"
],
[
"Ralph_Waldo_Emerson",
"influenced_by",
"Immanuel_Kant"
],
[
"Ralph_Waldo_Emerson",
"influenced_by",
"Plato"
],
[
"Richard_Dawkins",
"company",
"University_of_Oxford"
],
[
"Richard_Rorty",
"influenced_by",
"John_Dewey"
],
[
"Richard_Rorty",
"influenced_by",
"Plato"
],
[
"Richard_Rorty",
"interests",
"Epistemology"
],
[
"Samuel_R._Delany",
"influenced_by",
"Plato"
],
[
"Samuel_R._Delany",
"profession",
"Cartoonist"
],
[
"South_Island",
"contains",
"Christchurch"
],
[
"Steve_Ditko",
"influenced_by",
"Ayn_Rand"
],
[
"Steve_Ditko",
"profession",
"Cartoonist"
],
[
"T._S._Eliot",
"influenced_by",
"Immanuel_Kant"
],
[
"T._S._Eliot",
"religion",
"Anglicanism"
],
[
"Theodor_W._Adorno",
"influenced_by",
"Immanuel_Kant"
],
[
"Theodor_W._Adorno",
"influenced_by",
"Karl_Marx"
],
[
"Theodor_W._Adorno",
"interests",
"Epistemology"
],
[
"Thomas_Aquinas",
"influenced_by",
"Aristotle"
],
[
"Thomas_Aquinas",
"influenced_by",
"Plato"
],
[
"Thomas_Aquinas",
"interests",
"Epistemology"
],
[
"Thomas_Aquinas",
"interests",
"Ethics"
],
[
"Thomas_Hobbes",
"influenced_by",
"Aristotle"
],
[
"Thomas_Hobbes",
"influenced_by",
"Plato"
],
[
"Thomas_Hobbes",
"interests",
"Ethics"
],
[
"Thomas_Hobbes",
"location",
"Paris"
],
[
"Thomas_Hobbes",
"religion",
"Anglicanism"
],
[
"University_of_Oxford",
"campuses",
"University_of_Oxford"
],
[
"University_of_Oxford",
"child",
"Balliol_College"
],
[
"University_of_Oxford",
"educational_institution",
"University_of_Oxford"
],
[
"University_of_Oxford",
"major_field_of_study",
"Classics"
],
[
"University_of_Oxford",
"major_field_of_study",
"Mathematics"
],
[
"University_of_Oxford",
"major_field_of_study",
"Politics"
],
[
"University_of_Oxford",
"state_province_region",
"Oxfordshire"
],
[
"University_of_Oxford",
"student",
"Adam_Smith"
],
[
"University_of_Oxford",
"student",
"C._S._Lewis"
],
[
"University_of_Oxford",
"student",
"Christopher_Hitchens"
],
[
"University_of_Oxford",
"student",
"Dr._Seuss"
],
[
"University_of_Oxford",
"student",
"Hugh_Dancy"
],
[
"University_of_Oxford",
"student",
"J._R._R._Tolkien"
],
[
"University_of_Oxford",
"student",
"John_Locke"
],
[
"University_of_Oxford",
"student",
"Jonathan_Swift"
],
[
"University_of_Oxford",
"student",
"Kate_Beckinsale"
],
[
"University_of_Oxford",
"student",
"Lewis_Carroll"
],
[
"University_of_Oxford",
"student",
"Margaret_Thatcher"
],
[
"University_of_Oxford",
"student",
"Mark_Williams"
],
[
"University_of_Oxford",
"student",
"Michael_Palin"
],
[
"University_of_Oxford",
"student",
"Michael_Winterbottom"
],
[
"University_of_Oxford",
"student",
"Michael_York"
],
[
"University_of_Oxford",
"student",
"Oscar_Wilde"
],
[
"University_of_Oxford",
"student",
"Richard_Curtis"
],
[
"University_of_Oxford",
"student",
"T._S._Eliot"
],
[
"University_of_Oxford",
"student",
"W._H._Auden"
],
[
"Victor_Hugo",
"influenced_by",
"Voltaire"
],
[
"Voltaire",
"influenced_by",
"John_Locke"
],
[
"Voltaire",
"influenced_by",
"Plato"
],
[
"Voltaire",
"influenced_by",
"William_Shakespeare"
],
[
"Voltaire",
"location",
"Paris"
],
[
"Voltaire",
"place_of_death",
"Paris"
],
[
"Voltaire",
"profession",
"Playwright-GB"
],
[
"W._H._Auden",
"religion",
"Anglicanism"
],
[
"Walter_Benjamin",
"influenced_by",
"Karl_Marx"
],
[
"Walter_Benjamin",
"interests",
"Epistemology"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4213, 1988_NCAA_Men's_Division_I_Basketball_Tournament
815, Allen_County
12398, Alpha_Sigma_Phi
420, Anderson
13429, Atlanta
13543, Bachelor's_degree
2474, Bachelor_of_Science
6134, Biology
448, Bloomington
8868, Boston
10805, Cincinnati
3418, Cleveland
11116, Computer_Science
8527, Contiguous_United_States
10177, Cuyahoga_County
10757, Doctorate
10846, Eastern_Time_Zone
12198, Fort_Wayne
6942, Gary
6576, Greenwich
6105, Hartford
4806, History
8134, Indiana
2180, Indiana_University
3488, Indiana_University_Bloomington
5707, Indianapolis
5070, James_Walker
6048, Judaism-GB
12011, Kentucky
8074, Kokomo
12016, Lafayette
4287, Lake_County
1147, Lakewood
614, Library_of_Congress_Classification
7334, London
1521, Marion_County
9240, Massachusetts
422, Master_of_Arts
12081, Master_of_Science
9322, Medford
6622, Miami_Beach
12675, Michigan
6661, Muncie
590, Ohio
4866, Ontario
5772, Pontiac
3244, Richmond
9453, South_Bend
10600, Sydney_Pollack
11944, Terre_Haute
6641, Tracy_Chapman
6875, Tufts_University
9330, Vivica_A._Fox
src, edge_attr, dst
4213, locations, 13429
4213, locations, 10805
4213, locations, 6105
4213, locations, 5772
4213, locations, 9453
815, time_zones, 10846
12398, state_province_region, 8134
420, state, 8134
420, time_zones, 10846
13429, time_zones, 10846
13543, institution, 2180
13543, institution, 6875
2474, institution, 2180
2474, institution, 6875
448, state, 8134
448, time_zones, 10846
8868, contains, 6875
8868, time_zones, 10846
10805, time_zones, 10846
3418, adjoins, 1147
3418, county, 10177
3418, place, 3418
3418, time_zones, 10846
8527, contains, 8134
8527, time_zones, 10846
10177, contains, 3418
10177, county_seat, 3418
10177, time_zones, 10846
10757, institution, 2180
10757, institution, 6875
12198, time_zones, 10846
6576, time_zones, 10846
6105, time_zones, 10846
8134, adjoins, 590
8134, capital, 5707
8134, contains, 815
8134, contains, 420
8134, contains, 12198
8134, contains, 6942
8134, contains, 3488
8134, contains, 8074
8134, contains, 12016
8134, contains, 4287
8134, contains, 1521
8134, contains, 3244
8134, contains, 9453
8134, contains, 11944
8134, religion, 6048
8134, taxonomy, 614
8134, time_zones, 10846
2180, child, 3488
2180, major_field_of_study, 6134
2180, major_field_of_study, 11116
2180, major_field_of_study, 4806
2180, service_location, 448
2180, service_location, 12198
2180, service_location, 6942
2180, service_location, 5707
2180, service_location, 8074
2180, service_location, 3244
2180, service_location, 9453
5707, administrative_division, 8134
5707, time_zones, 10846
5070, place_of_birth, 7334
12011, adjoins, 8134
12011, time_zones, 10846
8074, time_zones, 10846
12016, state, 8134
12016, time_zones, 10846
4287, time_zones, 10846
1147, adjoins, 3418
1147, time_zones, 10846
7334, contains, 6576
7334, taxonomy, 614
7334, time_zones, 10846
1521, time_zones, 10846
9240, contains, 6875
9240, time_zones, 10846
422, institution, 2180
422, institution, 6875
12081, institution, 2180
12081, institution, 6875
9322, time_zones, 10846
6622, time_zones, 10846
6622, vacationer, 9330
12675, adjoins, 8134
12675, time_zones, 10846
6661, state, 8134
6661, time_zones, 10846
590, contains, 3418
590, time_zones, 10846
4866, contains, 7334
4866, time_zones, 10846
5772, time_zones, 10846
3244, time_zones, 10846
9453, place, 9453
9453, time_zones, 10846
10600, location, 12016
10600, location, 9453
10600, place_of_birth, 12016
10600, religion, 6048
11944, time_zones, 10846
6641, artist_origin, 3418
6641, location, 3418
6641, place_of_birth, 3418
6875, campuses, 6875
6875, citytown, 9322
6875, educational_institution, 6875
6875, fraternities_and_sororities, 12398
6875, major_field_of_study, 6134
6875, major_field_of_study, 11116
6875, major_field_of_study, 4806
6875, student, 6641
9330, location, 5707
9330, place_of_birth, 9453
Question: How are James_Walker, South_Bend, and Tracy_Chapman related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"James_Walker",
"South_Bend",
"Tracy_Chapman"
],
"valid_edges": [
[
"1988_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"Atlanta"
],
[
"1988_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"Cincinnati"
],
[
"1988_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"Hartford"
],
[
"1988_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"Pontiac"
],
[
"1988_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"South_Bend"
],
[
"Allen_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Alpha_Sigma_Phi",
"state_province_region",
"Indiana"
],
[
"Anderson",
"state",
"Indiana"
],
[
"Anderson",
"time_zones",
"Eastern_Time_Zone"
],
[
"Atlanta",
"time_zones",
"Eastern_Time_Zone"
],
[
"Bachelor's_degree",
"institution",
"Indiana_University"
],
[
"Bachelor's_degree",
"institution",
"Tufts_University"
],
[
"Bachelor_of_Science",
"institution",
"Indiana_University"
],
[
"Bachelor_of_Science",
"institution",
"Tufts_University"
],
[
"Bloomington",
"state",
"Indiana"
],
[
"Bloomington",
"time_zones",
"Eastern_Time_Zone"
],
[
"Boston",
"contains",
"Tufts_University"
],
[
"Boston",
"time_zones",
"Eastern_Time_Zone"
],
[
"Cincinnati",
"time_zones",
"Eastern_Time_Zone"
],
[
"Cleveland",
"adjoins",
"Lakewood"
],
[
"Cleveland",
"county",
"Cuyahoga_County"
],
[
"Cleveland",
"place",
"Cleveland"
],
[
"Cleveland",
"time_zones",
"Eastern_Time_Zone"
],
[
"Contiguous_United_States",
"contains",
"Indiana"
],
[
"Contiguous_United_States",
"time_zones",
"Eastern_Time_Zone"
],
[
"Cuyahoga_County",
"contains",
"Cleveland"
],
[
"Cuyahoga_County",
"county_seat",
"Cleveland"
],
[
"Cuyahoga_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Doctorate",
"institution",
"Indiana_University"
],
[
"Doctorate",
"institution",
"Tufts_University"
],
[
"Fort_Wayne",
"time_zones",
"Eastern_Time_Zone"
],
[
"Greenwich",
"time_zones",
"Eastern_Time_Zone"
],
[
"Hartford",
"time_zones",
"Eastern_Time_Zone"
],
[
"Indiana",
"adjoins",
"Ohio"
],
[
"Indiana",
"capital",
"Indianapolis"
],
[
"Indiana",
"contains",
"Allen_County"
],
[
"Indiana",
"contains",
"Anderson"
],
[
"Indiana",
"contains",
"Fort_Wayne"
],
[
"Indiana",
"contains",
"Gary"
],
[
"Indiana",
"contains",
"Indiana_University_Bloomington"
],
[
"Indiana",
"contains",
"Kokomo"
],
[
"Indiana",
"contains",
"Lafayette"
],
[
"Indiana",
"contains",
"Lake_County"
],
[
"Indiana",
"contains",
"Marion_County"
],
[
"Indiana",
"contains",
"Richmond"
],
[
"Indiana",
"contains",
"South_Bend"
],
[
"Indiana",
"contains",
"Terre_Haute"
],
[
"Indiana",
"religion",
"Judaism-GB"
],
[
"Indiana",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Indiana",
"time_zones",
"Eastern_Time_Zone"
],
[
"Indiana_University",
"child",
"Indiana_University_Bloomington"
],
[
"Indiana_University",
"major_field_of_study",
"Biology"
],
[
"Indiana_University",
"major_field_of_study",
"Computer_Science"
],
[
"Indiana_University",
"major_field_of_study",
"History"
],
[
"Indiana_University",
"service_location",
"Bloomington"
],
[
"Indiana_University",
"service_location",
"Fort_Wayne"
],
[
"Indiana_University",
"service_location",
"Gary"
],
[
"Indiana_University",
"service_location",
"Indianapolis"
],
[
"Indiana_University",
"service_location",
"Kokomo"
],
[
"Indiana_University",
"service_location",
"Richmond"
],
[
"Indiana_University",
"service_location",
"South_Bend"
],
[
"Indianapolis",
"administrative_division",
"Indiana"
],
[
"Indianapolis",
"time_zones",
"Eastern_Time_Zone"
],
[
"James_Walker",
"place_of_birth",
"London"
],
[
"Kentucky",
"adjoins",
"Indiana"
],
[
"Kentucky",
"time_zones",
"Eastern_Time_Zone"
],
[
"Kokomo",
"time_zones",
"Eastern_Time_Zone"
],
[
"Lafayette",
"state",
"Indiana"
],
[
"Lafayette",
"time_zones",
"Eastern_Time_Zone"
],
[
"Lake_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Lakewood",
"adjoins",
"Cleveland"
],
[
"Lakewood",
"time_zones",
"Eastern_Time_Zone"
],
[
"London",
"contains",
"Greenwich"
],
[
"London",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"London",
"time_zones",
"Eastern_Time_Zone"
],
[
"Marion_County",
"time_zones",
"Eastern_Time_Zone"
],
[
"Massachusetts",
"contains",
"Tufts_University"
],
[
"Massachusetts",
"time_zones",
"Eastern_Time_Zone"
],
[
"Master_of_Arts",
"institution",
"Indiana_University"
],
[
"Master_of_Arts",
"institution",
"Tufts_University"
],
[
"Master_of_Science",
"institution",
"Indiana_University"
],
[
"Master_of_Science",
"institution",
"Tufts_University"
],
[
"Medford",
"time_zones",
"Eastern_Time_Zone"
],
[
"Miami_Beach",
"time_zones",
"Eastern_Time_Zone"
],
[
"Miami_Beach",
"vacationer",
"Vivica_A._Fox"
],
[
"Michigan",
"adjoins",
"Indiana"
],
[
"Michigan",
"time_zones",
"Eastern_Time_Zone"
],
[
"Muncie",
"state",
"Indiana"
],
[
"Muncie",
"time_zones",
"Eastern_Time_Zone"
],
[
"Ohio",
"contains",
"Cleveland"
],
[
"Ohio",
"time_zones",
"Eastern_Time_Zone"
],
[
"Ontario",
"contains",
"London"
],
[
"Ontario",
"time_zones",
"Eastern_Time_Zone"
],
[
"Pontiac",
"time_zones",
"Eastern_Time_Zone"
],
[
"Richmond",
"time_zones",
"Eastern_Time_Zone"
],
[
"South_Bend",
"place",
"South_Bend"
],
[
"South_Bend",
"time_zones",
"Eastern_Time_Zone"
],
[
"Sydney_Pollack",
"location",
"Lafayette"
],
[
"Sydney_Pollack",
"location",
"South_Bend"
],
[
"Sydney_Pollack",
"place_of_birth",
"Lafayette"
],
[
"Sydney_Pollack",
"religion",
"Judaism-GB"
],
[
"Terre_Haute",
"time_zones",
"Eastern_Time_Zone"
],
[
"Tracy_Chapman",
"artist_origin",
"Cleveland"
],
[
"Tracy_Chapman",
"location",
"Cleveland"
],
[
"Tracy_Chapman",
"place_of_birth",
"Cleveland"
],
[
"Tufts_University",
"campuses",
"Tufts_University"
],
[
"Tufts_University",
"citytown",
"Medford"
],
[
"Tufts_University",
"educational_institution",
"Tufts_University"
],
[
"Tufts_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Tufts_University",
"major_field_of_study",
"Biology"
],
[
"Tufts_University",
"major_field_of_study",
"Computer_Science"
],
[
"Tufts_University",
"major_field_of_study",
"History"
],
[
"Tufts_University",
"student",
"Tracy_Chapman"
],
[
"Vivica_A._Fox",
"location",
"Indianapolis"
],
[
"Vivica_A._Fox",
"place_of_birth",
"South_Bend"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3531, Adelaide
3923, Architecture
6928, Auckland
1912, Australian_dollar
1535, Chairman
7359, Commonwealth_of_Nations
2854, Cook_Islands
9993, Elizabeth_II
5013, Federated_States_of_Micronesia
7318, Fiji
10012, George_Washington_University
12266, Gerald_Ford
10773, Governor-General
5513, Harvard_Law_School
10714, Howard_University
10024, James_Blunt
4562, Kiribati
11609, Law_degree
513, London_School_of_Economics_and_Political_Science
9560, Master_of_Laws
11306, McGill_University
1057, Monarch-GB
6025, Nauru
3247, New_Caledonia
8493, Oceania
10153, Papua_New_Guinea
3957, Rykodisc
3929, Samoa
2201, Solomon_Islands
11676, Tonga
10729, Tuvalu
4266, University_College_Dublin
6831, University_of_Adelaide
11108, University_of_Auckland
4436, University_of_Bristol
6936, University_of_Melbourne
8439, University_of_Michigan_Law_School
5881, University_of_Paris
7581, University_of_Virginia_School_of_Law
13118, University_of_Western_Australia
3843, Vanuatu
1230, Vladimir_Lenin
517, Warner_Music_Group
13168, William_Howard_Taft
9510, Yale_Law_School
src, edge_attr, dst
6928, contains, 11108
1535, company, 517
9993, basic_title, 1057
9993, jurisdiction_of_office, 2854
9993, jurisdiction_of_office, 10153
9993, jurisdiction_of_office, 2201
9993, jurisdiction_of_office, 10729
5013, adjoins, 2201
5013, country, 5013
7318, adjoins, 3843
10773, jurisdiction_of_office, 10153
10773, jurisdiction_of_office, 2201
10773, jurisdiction_of_office, 10729
5513, campuses, 5513
5513, educational_institution, 5513
10714, campuses, 10714
10714, educational_institution, 10714
10714, major_field_of_study, 3923
4562, organization, 7359
11609, institution, 10012
11609, institution, 5513
11609, institution, 10714
11609, institution, 513
11609, institution, 11306
11609, institution, 4266
11609, institution, 6831
11609, institution, 11108
11609, institution, 4436
11609, institution, 6936
11609, institution, 8439
11609, institution, 5881
11609, institution, 7581
11609, institution, 13118
11609, institution, 9510
11609, student, 1230
513, campuses, 513
513, educational_institution, 513
9560, institution, 10012
9560, institution, 5513
9560, institution, 513
9560, institution, 11108
9560, institution, 8439
9560, institution, 5881
9560, institution, 7581
9560, institution, 9510
11306, campuses, 11306
11306, educational_institution, 11306
11306, major_field_of_study, 3923
1057, jurisdiction_of_office, 2854
1057, jurisdiction_of_office, 10153
1057, jurisdiction_of_office, 2201
1057, jurisdiction_of_office, 11676
1057, jurisdiction_of_office, 10729
6025, organization, 7359
3247, adjoins, 3843
8493, contains, 3531
8493, contains, 6928
8493, contains, 2854
8493, contains, 5013
8493, contains, 7318
8493, contains, 4562
8493, contains, 6025
8493, contains, 3247
8493, contains, 10153
8493, contains, 3929
8493, contains, 2201
8493, contains, 11676
8493, contains, 10729
8493, contains, 11108
8493, contains, 3843
10153, organization, 7359
3929, organization, 7359
2201, adjoins, 5013
2201, adjoins, 10153
2201, adjoins, 3843
2201, organization, 7359
11676, organization, 7359
10729, organization, 7359
4266, major_field_of_study, 3923
6831, citytown, 3531
6831, international_tuition_currency, 1912
11108, campuses, 11108
11108, citytown, 6928
11108, currency, 1912
11108, educational_institution, 11108
11108, international_tuition_currency, 1912
11108, major_field_of_study, 3923
4436, campuses, 4436
4436, educational_institution, 4436
4436, student, 10024
6936, campuses, 6936
6936, currency, 1912
6936, educational_institution, 6936
6936, international_tuition_currency, 1912
8439, campuses, 8439
8439, educational_institution, 8439
8439, student, 12266
5881, campuses, 5881
5881, educational_institution, 5881
7581, campuses, 7581
7581, educational_institution, 7581
13118, campuses, 13118
13118, currency, 1912
13118, educational_institution, 13118
13118, international_tuition_currency, 1912
3843, adjoins, 7318
3843, adjoins, 3247
3843, adjoins, 2201
3843, country, 3843
3843, organization, 7359
1230, basic_title, 1535
517, artist, 10024
517, child, 3957
13168, basic_title, 10773
13168, company, 9510
9510, campuses, 9510
9510, educational_institution, 9510
9510, student, 12266
Question: How are Law_degree, Rykodisc, and Solomon_Islands related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Law_degree",
"Rykodisc",
"Solomon_Islands"
],
"valid_edges": [
[
"Auckland",
"contains",
"University_of_Auckland"
],
[
"Chairman",
"company",
"Warner_Music_Group"
],
[
"Elizabeth_II",
"basic_title",
"Monarch-GB"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Cook_Islands"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Papua_New_Guinea"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Solomon_Islands"
],
[
"Elizabeth_II",
"jurisdiction_of_office",
"Tuvalu"
],
[
"Federated_States_of_Micronesia",
"adjoins",
"Solomon_Islands"
],
[
"Federated_States_of_Micronesia",
"country",
"Federated_States_of_Micronesia"
],
[
"Fiji",
"adjoins",
"Vanuatu"
],
[
"Governor-General",
"jurisdiction_of_office",
"Papua_New_Guinea"
],
[
"Governor-General",
"jurisdiction_of_office",
"Solomon_Islands"
],
[
"Governor-General",
"jurisdiction_of_office",
"Tuvalu"
],
[
"Harvard_Law_School",
"campuses",
"Harvard_Law_School"
],
[
"Harvard_Law_School",
"educational_institution",
"Harvard_Law_School"
],
[
"Howard_University",
"campuses",
"Howard_University"
],
[
"Howard_University",
"educational_institution",
"Howard_University"
],
[
"Howard_University",
"major_field_of_study",
"Architecture"
],
[
"Kiribati",
"organization",
"Commonwealth_of_Nations"
],
[
"Law_degree",
"institution",
"George_Washington_University"
],
[
"Law_degree",
"institution",
"Harvard_Law_School"
],
[
"Law_degree",
"institution",
"Howard_University"
],
[
"Law_degree",
"institution",
"London_School_of_Economics_and_Political_Science"
],
[
"Law_degree",
"institution",
"McGill_University"
],
[
"Law_degree",
"institution",
"University_College_Dublin"
],
[
"Law_degree",
"institution",
"University_of_Adelaide"
],
[
"Law_degree",
"institution",
"University_of_Auckland"
],
[
"Law_degree",
"institution",
"University_of_Bristol"
],
[
"Law_degree",
"institution",
"University_of_Melbourne"
],
[
"Law_degree",
"institution",
"University_of_Michigan_Law_School"
],
[
"Law_degree",
"institution",
"University_of_Paris"
],
[
"Law_degree",
"institution",
"University_of_Virginia_School_of_Law"
],
[
"Law_degree",
"institution",
"University_of_Western_Australia"
],
[
"Law_degree",
"institution",
"Yale_Law_School"
],
[
"Law_degree",
"student",
"Vladimir_Lenin"
],
[
"London_School_of_Economics_and_Political_Science",
"campuses",
"London_School_of_Economics_and_Political_Science"
],
[
"London_School_of_Economics_and_Political_Science",
"educational_institution",
"London_School_of_Economics_and_Political_Science"
],
[
"Master_of_Laws",
"institution",
"George_Washington_University"
],
[
"Master_of_Laws",
"institution",
"Harvard_Law_School"
],
[
"Master_of_Laws",
"institution",
"London_School_of_Economics_and_Political_Science"
],
[
"Master_of_Laws",
"institution",
"University_of_Auckland"
],
[
"Master_of_Laws",
"institution",
"University_of_Michigan_Law_School"
],
[
"Master_of_Laws",
"institution",
"University_of_Paris"
],
[
"Master_of_Laws",
"institution",
"University_of_Virginia_School_of_Law"
],
[
"Master_of_Laws",
"institution",
"Yale_Law_School"
],
[
"McGill_University",
"campuses",
"McGill_University"
],
[
"McGill_University",
"educational_institution",
"McGill_University"
],
[
"McGill_University",
"major_field_of_study",
"Architecture"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Cook_Islands"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Papua_New_Guinea"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Solomon_Islands"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Tonga"
],
[
"Monarch-GB",
"jurisdiction_of_office",
"Tuvalu"
],
[
"Nauru",
"organization",
"Commonwealth_of_Nations"
],
[
"New_Caledonia",
"adjoins",
"Vanuatu"
],
[
"Oceania",
"contains",
"Adelaide"
],
[
"Oceania",
"contains",
"Auckland"
],
[
"Oceania",
"contains",
"Cook_Islands"
],
[
"Oceania",
"contains",
"Federated_States_of_Micronesia"
],
[
"Oceania",
"contains",
"Fiji"
],
[
"Oceania",
"contains",
"Kiribati"
],
[
"Oceania",
"contains",
"Nauru"
],
[
"Oceania",
"contains",
"New_Caledonia"
],
[
"Oceania",
"contains",
"Papua_New_Guinea"
],
[
"Oceania",
"contains",
"Samoa"
],
[
"Oceania",
"contains",
"Solomon_Islands"
],
[
"Oceania",
"contains",
"Tonga"
],
[
"Oceania",
"contains",
"Tuvalu"
],
[
"Oceania",
"contains",
"University_of_Auckland"
],
[
"Oceania",
"contains",
"Vanuatu"
],
[
"Papua_New_Guinea",
"organization",
"Commonwealth_of_Nations"
],
[
"Samoa",
"organization",
"Commonwealth_of_Nations"
],
[
"Solomon_Islands",
"adjoins",
"Federated_States_of_Micronesia"
],
[
"Solomon_Islands",
"adjoins",
"Papua_New_Guinea"
],
[
"Solomon_Islands",
"adjoins",
"Vanuatu"
],
[
"Solomon_Islands",
"organization",
"Commonwealth_of_Nations"
],
[
"Tonga",
"organization",
"Commonwealth_of_Nations"
],
[
"Tuvalu",
"organization",
"Commonwealth_of_Nations"
],
[
"University_College_Dublin",
"major_field_of_study",
"Architecture"
],
[
"University_of_Adelaide",
"citytown",
"Adelaide"
],
[
"University_of_Adelaide",
"international_tuition_currency",
"Australian_dollar"
],
[
"University_of_Auckland",
"campuses",
"University_of_Auckland"
],
[
"University_of_Auckland",
"citytown",
"Auckland"
],
[
"University_of_Auckland",
"currency",
"Australian_dollar"
],
[
"University_of_Auckland",
"educational_institution",
"University_of_Auckland"
],
[
"University_of_Auckland",
"international_tuition_currency",
"Australian_dollar"
],
[
"University_of_Auckland",
"major_field_of_study",
"Architecture"
],
[
"University_of_Bristol",
"campuses",
"University_of_Bristol"
],
[
"University_of_Bristol",
"educational_institution",
"University_of_Bristol"
],
[
"University_of_Bristol",
"student",
"James_Blunt"
],
[
"University_of_Melbourne",
"campuses",
"University_of_Melbourne"
],
[
"University_of_Melbourne",
"currency",
"Australian_dollar"
],
[
"University_of_Melbourne",
"educational_institution",
"University_of_Melbourne"
],
[
"University_of_Melbourne",
"international_tuition_currency",
"Australian_dollar"
],
[
"University_of_Michigan_Law_School",
"campuses",
"University_of_Michigan_Law_School"
],
[
"University_of_Michigan_Law_School",
"educational_institution",
"University_of_Michigan_Law_School"
],
[
"University_of_Michigan_Law_School",
"student",
"Gerald_Ford"
],
[
"University_of_Paris",
"campuses",
"University_of_Paris"
],
[
"University_of_Paris",
"educational_institution",
"University_of_Paris"
],
[
"University_of_Virginia_School_of_Law",
"campuses",
"University_of_Virginia_School_of_Law"
],
[
"University_of_Virginia_School_of_Law",
"educational_institution",
"University_of_Virginia_School_of_Law"
],
[
"University_of_Western_Australia",
"campuses",
"University_of_Western_Australia"
],
[
"University_of_Western_Australia",
"currency",
"Australian_dollar"
],
[
"University_of_Western_Australia",
"educational_institution",
"University_of_Western_Australia"
],
[
"University_of_Western_Australia",
"international_tuition_currency",
"Australian_dollar"
],
[
"Vanuatu",
"adjoins",
"Fiji"
],
[
"Vanuatu",
"adjoins",
"New_Caledonia"
],
[
"Vanuatu",
"adjoins",
"Solomon_Islands"
],
[
"Vanuatu",
"country",
"Vanuatu"
],
[
"Vanuatu",
"organization",
"Commonwealth_of_Nations"
],
[
"Vladimir_Lenin",
"basic_title",
"Chairman"
],
[
"Warner_Music_Group",
"artist",
"James_Blunt"
],
[
"Warner_Music_Group",
"child",
"Rykodisc"
],
[
"William_Howard_Taft",
"basic_title",
"Governor-General"
],
[
"William_Howard_Taft",
"company",
"Yale_Law_School"
],
[
"Yale_Law_School",
"campuses",
"Yale_Law_School"
],
[
"Yale_Law_School",
"educational_institution",
"Yale_Law_School"
],
[
"Yale_Law_School",
"student",
"Gerald_Ford"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2763, Chivas_USA
4193, Etta_James
4194, Goalkeeper
4196, James_Brolin
3415, Kavala_F.C.
13022, Los_Angeles
src, edge_attr, dst
2763, football_roster_position, 4194
2763, position, 4194
4193, location, 13022
4194, team, 2763
4194, team, 3415
4196, location, 13022
4196, place_of_birth, 13022
3415, football_roster_position, 4194
3415, position, 4194
13022, place, 13022
13022, teams, 2763
Question: For what reason are Etta_James, James_Brolin, and Kavala_F.C. associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Etta_James",
"James_Brolin",
"Kavala_F.C."
],
"valid_edges": [
[
"Chivas_USA",
"football_roster_position",
"Goalkeeper"
],
[
"Chivas_USA",
"position",
"Goalkeeper"
],
[
"Etta_James",
"location",
"Los_Angeles"
],
[
"Goalkeeper",
"team",
"Chivas_USA"
],
[
"Goalkeeper",
"team",
"Kavala_F.C."
],
[
"James_Brolin",
"location",
"Los_Angeles"
],
[
"James_Brolin",
"place_of_birth",
"Los_Angeles"
],
[
"Kavala_F.C.",
"football_roster_position",
"Goalkeeper"
],
[
"Kavala_F.C.",
"position",
"Goalkeeper"
],
[
"Los_Angeles",
"place",
"Los_Angeles"
],
[
"Los_Angeles",
"teams",
"Chivas_USA"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1346, Beverly_Hills
12844, Bob_Clampett
9099, Buster_Keaton
319, East_Java
8283, Errol_Flynn
14016, Forest_Lawn_Memorial_Park
7223, Fritz_Lang
6139, George_Burns
10046, Harold_Lloyd
6330, Indonesia
5549, Irving_Thalberg
5414, James_Stewart
13194, Robert_Z._Leonard
13916, Ryan_Reynolds
3764, Sammy_Davis,_Jr.
772, Spencer_Tracy
10397, Twilight
11315, Vancouver
2303, Vancouver_Canucks
5369, Wallace_Beery
13975, X-Men_Origins:_Wolverine
src, edge_attr, dst
1346, place, 1346
12844, influenced_by, 9099
12844, influenced_by, 10046
12844, place_of_burial, 14016
9099, influenced_by, 10046
9099, location, 1346
9099, place_of_burial, 14016
319, administrative_parent, 6330
8283, place_of_burial, 14016
8283, place_of_death, 11315
7223, place_of_burial, 14016
7223, place_of_death, 1346
6139, place_of_burial, 14016
6139, place_of_death, 1346
10046, place_of_burial, 14016
10046, place_of_death, 1346
6330, contains, 319
5549, location_of_ceremony, 1346
5549, place_of_burial, 14016
5414, place_of_burial, 14016
5414, place_of_death, 1346
13194, place_of_burial, 14016
13194, place_of_death, 1346
13916, location, 1346
13916, location, 11315
13916, place_of_birth, 11315
3764, place_of_burial, 14016
3764, place_of_death, 1346
772, place_of_burial, 14016
772, place_of_death, 1346
10397, featured_film_locations, 11315
10397, film_release_region, 6330
11315, place, 11315
11315, teams, 2303
5369, place_of_burial, 14016
5369, place_of_death, 1346
13975, featured_film_locations, 11315
13975, film_release_region, 6330
Question: In what context are East_Java, Harold_Lloyd, and Vancouver_Canucks connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"East_Java",
"Harold_Lloyd",
"Vancouver_Canucks"
],
"valid_edges": [
[
"Beverly_Hills",
"place",
"Beverly_Hills"
],
[
"Bob_Clampett",
"influenced_by",
"Buster_Keaton"
],
[
"Bob_Clampett",
"influenced_by",
"Harold_Lloyd"
],
[
"Bob_Clampett",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Buster_Keaton",
"influenced_by",
"Harold_Lloyd"
],
[
"Buster_Keaton",
"location",
"Beverly_Hills"
],
[
"Buster_Keaton",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"East_Java",
"administrative_parent",
"Indonesia"
],
[
"Errol_Flynn",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Errol_Flynn",
"place_of_death",
"Vancouver"
],
[
"Fritz_Lang",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Fritz_Lang",
"place_of_death",
"Beverly_Hills"
],
[
"George_Burns",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"George_Burns",
"place_of_death",
"Beverly_Hills"
],
[
"Harold_Lloyd",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Harold_Lloyd",
"place_of_death",
"Beverly_Hills"
],
[
"Indonesia",
"contains",
"East_Java"
],
[
"Irving_Thalberg",
"location_of_ceremony",
"Beverly_Hills"
],
[
"Irving_Thalberg",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"James_Stewart",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"James_Stewart",
"place_of_death",
"Beverly_Hills"
],
[
"Robert_Z._Leonard",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Robert_Z._Leonard",
"place_of_death",
"Beverly_Hills"
],
[
"Ryan_Reynolds",
"location",
"Beverly_Hills"
],
[
"Ryan_Reynolds",
"location",
"Vancouver"
],
[
"Ryan_Reynolds",
"place_of_birth",
"Vancouver"
],
[
"Sammy_Davis,_Jr.",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Sammy_Davis,_Jr.",
"place_of_death",
"Beverly_Hills"
],
[
"Spencer_Tracy",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Spencer_Tracy",
"place_of_death",
"Beverly_Hills"
],
[
"Twilight",
"featured_film_locations",
"Vancouver"
],
[
"Twilight",
"film_release_region",
"Indonesia"
],
[
"Vancouver",
"place",
"Vancouver"
],
[
"Vancouver",
"teams",
"Vancouver_Canucks"
],
[
"Wallace_Beery",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"Wallace_Beery",
"place_of_death",
"Beverly_Hills"
],
[
"X-Men_Origins:_Wolverine",
"featured_film_locations",
"Vancouver"
],
[
"X-Men_Origins:_Wolverine",
"film_release_region",
"Indonesia"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
13895, 49th_Annual_Grammy_Awards
7500, Anna_Faris
10677, Antonio_Banderas
5423, Artie_Lange
769, Ashton_Kutcher
10908, Bay_City
10137, Bill_Maher
3111, Bill_Murray
9614, Bill_Nighy
11463, Bob_Hope
4245, Bob_Newhart
13753, Bonnie_Hunt
1232, Bret_McKenzie
5979, Carroll_O'Connor
5375, Catherine_O'Hara
1325, Catherine_Tate
3303, Catholicism
171, Christopher_Guest
5128, Comedian
2746, Conan_O'Brien
5064, Connecticut
4047, Craig_Ferguson
17, Dane_Cook
2150, Danny_DeVito
12356, Dean_Martin
13163, Debra_Messing
10911, Denis_Leary
13741, Detroit
4304, Domestic_partnership
10846, Eastern_Time_Zone
13403, Enya
441, Fairfield
483, Florida_Keys
2708, Frank_Skinner
11496, George_Carlin
1655, George_Lopez
6059, Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media
11194, Gregory_Peck
2479, Guelph
8134, Indiana
8225, Jack_Black
5332, Jackie_Gleason
11731, Jamie_Kennedy
8539, Janeane_Garofalo
7125, Jay_Leno
8726, Jay_Mohr
8555, Jemaine_Clement
1981, Jenny_McCarthy
6053, Jim_Carrey
3178, Jimmy_Kimmel
2129, Joan_Cusack
7929, Joe_Pesci
8372, John_Cusack
9020, John_Kerry
4282, John_Mayer
9801, John_Wayne
1061, Jon_Favreau
5378, Kathy_Griffin
109, Kelsey_Grammer
2304, Kevin_Smith
11662, Kristen_Wiig
4592, Lady_Gaga
3499, Lucille_Ball
2622, Madonna
12863, Martin_Short
9621, Mary_Astor
9240, Massachusetts
908, Matt_Dillon
914, Meg_Ryan
8496, Mel_Brooks
10298, Mel_Gibson
4640, Michael_Keaton
7418, Michael_McKean
12675, Michigan
1451, Mickey_Rooney
3220, Neve_Campbell
3448, New_York
5787, Nicole_Sullivan
590, Ohio
4866, Ontario
5829, Patricia_Heaton
7193, Pennsylvania
4669, QuΓ©bec
1728, Ray_Liotta
1923, Ray_Romano
3248, Razzie_Award_for_Worst_Actress
9716, Rhode_Island
3131, Rob_Schneider
2458, Roscoe_Arbuckle
9898, Rupert_Everett
605, Sacha_Baron_Cohen
7570, Scottish_American
5386, Sean_Hayes
6872, Seth_Green
3509, Seth_MacFarlane
4039, Steve_Allen
7579, Steve_Carell
3357, Steve_Coogan
8782, Steve_McQueen
14231, Steven_Wright
898, Tina_Fey
10673, Tracey_Ullman
1480, University_of_Michigan
4536, Vince_Vaughn
src, edge_attr, dst
13895, award_winner, 2622
7500, profession, 5128
10677, participant, 2622
10677, religion, 3303
5423, profession, 5128
5423, religion, 3303
769, profession, 5128
769, religion, 3303
10908, time_zones, 10846
10137, profession, 5128
10137, religion, 3303
3111, profession, 5128
3111, religion, 3303
9614, profession, 5128
9614, religion, 3303
11463, profession, 5128
11463, religion, 3303
4245, profession, 5128
4245, religion, 3303
13753, profession, 5128
13753, religion, 3303
1232, award, 6059
1232, award_nominee, 8555
1232, profession, 5128
5979, profession, 5128
5979, religion, 3303
5375, profession, 5128
5375, religion, 3303
1325, profession, 5128
1325, religion, 3303
171, award, 6059
171, profession, 5128
2746, profession, 5128
2746, religion, 3303
5064, religion, 3303
5064, time_zones, 10846
4047, profession, 5128
17, profession, 5128
17, religion, 3303
2150, profession, 5128
2150, religion, 3303
12356, profession, 5128
12356, religion, 3303
13163, award_nominee, 914
13163, profession, 5128
10911, profession, 5128
10911, religion, 3303
13741, time_zones, 10846
13403, award, 6059
13403, religion, 3303
441, time_zones, 10846
483, time_zones, 10846
2708, profession, 5128
2708, religion, 3303
11496, profession, 5128
11496, religion, 3303
1655, profession, 5128
1655, religion, 3303
6059, award_winner, 171
6059, award_winner, 2622
6059, award_winner, 7418
6059, ceremony, 13895
11194, religion, 3303
2479, time_zones, 10846
8134, religion, 3303
8134, time_zones, 10846
8225, profession, 5128
5332, profession, 5128
5332, religion, 3303
11731, profession, 5128
11731, religion, 3303
8539, profession, 5128
8539, religion, 3303
7125, profession, 5128
8726, profession, 5128
8726, religion, 3303
8555, award_nominee, 1232
8555, profession, 5128
1981, profession, 5128
1981, religion, 3303
6053, profession, 5128
6053, religion, 3303
3178, profession, 5128
3178, religion, 3303
2129, profession, 5128
2129, religion, 3303
7929, profession, 5128
7929, religion, 3303
8372, participant, 914
8372, participant, 3220
8372, religion, 3303
9020, religion, 3303
4282, award, 6059
4282, profession, 5128
9801, religion, 3303
1061, profession, 5128
1061, religion, 3303
5378, profession, 5128
5378, religion, 3303
109, profession, 5128
109, religion, 3303
2304, profession, 5128
2304, religion, 3303
11662, profession, 5128
4592, influenced_by, 2622
4592, religion, 3303
3499, profession, 5128
2622, award, 6059
2622, award, 3248
2622, award_nominee, 9898
2622, location, 13741
2622, participant, 605
2622, place_of_birth, 10908
2622, religion, 3303
2622, type_of_union, 4304
12863, profession, 5128
12863, religion, 3303
9621, religion, 3303
9240, religion, 3303
9240, time_zones, 10846
908, award_nominee, 3220
908, participant, 2622
908, participant, 914
908, religion, 3303
914, award, 3248
914, award_nominee, 13163
914, location, 441
914, location, 3448
914, participant, 8372
914, participant, 908
914, participant, 6872
914, place_of_birth, 441
914, religion, 3303
8496, award, 6059
8496, profession, 5128
10298, religion, 3303
4640, profession, 5128
4640, religion, 3303
7418, profession, 5128
12675, religion, 3303
12675, time_zones, 10846
1451, profession, 5128
3220, award_nominee, 908
3220, location, 2479
3220, participant, 8372
3220, place_of_birth, 2479
3220, religion, 3303
3220, type_of_union, 4304
3448, religion, 3303
3448, time_zones, 10846
5787, profession, 5128
5787, religion, 3303
590, religion, 3303
590, time_zones, 10846
4866, religion, 3303
4866, time_zones, 10846
5829, profession, 5128
5829, religion, 3303
7193, religion, 3303
7193, time_zones, 10846
4669, religion, 3303
4669, time_zones, 10846
1728, religion, 3303
1923, profession, 5128
1923, religion, 3303
3248, award_winner, 2622
9716, religion, 3303
9716, time_zones, 10846
3131, profession, 5128
3131, religion, 3303
2458, profession, 5128
9898, award_nominee, 2622
9898, religion, 3303
605, participant, 2622
605, profession, 5128
7570, people, 7500
7570, people, 4047
7570, people, 11194
7570, people, 8225
7570, people, 7125
7570, people, 8726
7570, people, 9020
7570, people, 9801
7570, people, 11662
7570, people, 3499
7570, people, 9621
7570, people, 908
7570, people, 10298
7570, people, 4640
7570, people, 1451
7570, people, 1728
7570, people, 2458
7570, people, 8782
7570, people, 14231
7570, people, 898
5386, profession, 5128
5386, religion, 3303
6872, participant, 914
6872, profession, 5128
3509, award, 6059
3509, profession, 5128
4039, profession, 5128
4039, religion, 3303
7579, profession, 5128
7579, religion, 3303
3357, profession, 5128
3357, religion, 3303
8782, religion, 3303
14231, profession, 5128
898, profession, 5128
10673, profession, 5128
10673, religion, 3303
1480, student, 2622
1480, time_zones, 10846
4536, profession, 5128
4536, religion, 3303
Question: In what context are Bret_McKenzie, Florida_Keys, and Matt_Dillon connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bret_McKenzie",
"Florida_Keys",
"Matt_Dillon"
],
"valid_edges": [
[
"49th_Annual_Grammy_Awards",
"award_winner",
"Madonna"
],
[
"Anna_Faris",
"profession",
"Comedian"
],
[
"Antonio_Banderas",
"participant",
"Madonna"
],
[
"Antonio_Banderas",
"religion",
"Catholicism"
],
[
"Artie_Lange",
"profession",
"Comedian"
],
[
"Artie_Lange",
"religion",
"Catholicism"
],
[
"Ashton_Kutcher",
"profession",
"Comedian"
],
[
"Ashton_Kutcher",
"religion",
"Catholicism"
],
[
"Bay_City",
"time_zones",
"Eastern_Time_Zone"
],
[
"Bill_Maher",
"profession",
"Comedian"
],
[
"Bill_Maher",
"religion",
"Catholicism"
],
[
"Bill_Murray",
"profession",
"Comedian"
],
[
"Bill_Murray",
"religion",
"Catholicism"
],
[
"Bill_Nighy",
"profession",
"Comedian"
],
[
"Bill_Nighy",
"religion",
"Catholicism"
],
[
"Bob_Hope",
"profession",
"Comedian"
],
[
"Bob_Hope",
"religion",
"Catholicism"
],
[
"Bob_Newhart",
"profession",
"Comedian"
],
[
"Bob_Newhart",
"religion",
"Catholicism"
],
[
"Bonnie_Hunt",
"profession",
"Comedian"
],
[
"Bonnie_Hunt",
"religion",
"Catholicism"
],
[
"Bret_McKenzie",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Bret_McKenzie",
"award_nominee",
"Jemaine_Clement"
],
[
"Bret_McKenzie",
"profession",
"Comedian"
],
[
"Carroll_O'Connor",
"profession",
"Comedian"
],
[
"Carroll_O'Connor",
"religion",
"Catholicism"
],
[
"Catherine_O'Hara",
"profession",
"Comedian"
],
[
"Catherine_O'Hara",
"religion",
"Catholicism"
],
[
"Catherine_Tate",
"profession",
"Comedian"
],
[
"Catherine_Tate",
"religion",
"Catholicism"
],
[
"Christopher_Guest",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Christopher_Guest",
"profession",
"Comedian"
],
[
"Conan_O'Brien",
"profession",
"Comedian"
],
[
"Conan_O'Brien",
"religion",
"Catholicism"
],
[
"Connecticut",
"religion",
"Catholicism"
],
[
"Connecticut",
"time_zones",
"Eastern_Time_Zone"
],
[
"Craig_Ferguson",
"profession",
"Comedian"
],
[
"Dane_Cook",
"profession",
"Comedian"
],
[
"Dane_Cook",
"religion",
"Catholicism"
],
[
"Danny_DeVito",
"profession",
"Comedian"
],
[
"Danny_DeVito",
"religion",
"Catholicism"
],
[
"Dean_Martin",
"profession",
"Comedian"
],
[
"Dean_Martin",
"religion",
"Catholicism"
],
[
"Debra_Messing",
"award_nominee",
"Meg_Ryan"
],
[
"Debra_Messing",
"profession",
"Comedian"
],
[
"Denis_Leary",
"profession",
"Comedian"
],
[
"Denis_Leary",
"religion",
"Catholicism"
],
[
"Detroit",
"time_zones",
"Eastern_Time_Zone"
],
[
"Enya",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Enya",
"religion",
"Catholicism"
],
[
"Fairfield",
"time_zones",
"Eastern_Time_Zone"
],
[
"Florida_Keys",
"time_zones",
"Eastern_Time_Zone"
],
[
"Frank_Skinner",
"profession",
"Comedian"
],
[
"Frank_Skinner",
"religion",
"Catholicism"
],
[
"George_Carlin",
"profession",
"Comedian"
],
[
"George_Carlin",
"religion",
"Catholicism"
],
[
"George_Lopez",
"profession",
"Comedian"
],
[
"George_Lopez",
"religion",
"Catholicism"
],
[
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media",
"award_winner",
"Christopher_Guest"
],
[
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media",
"award_winner",
"Madonna"
],
[
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media",
"award_winner",
"Michael_McKean"
],
[
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media",
"ceremony",
"49th_Annual_Grammy_Awards"
],
[
"Gregory_Peck",
"religion",
"Catholicism"
],
[
"Guelph",
"time_zones",
"Eastern_Time_Zone"
],
[
"Indiana",
"religion",
"Catholicism"
],
[
"Indiana",
"time_zones",
"Eastern_Time_Zone"
],
[
"Jack_Black",
"profession",
"Comedian"
],
[
"Jackie_Gleason",
"profession",
"Comedian"
],
[
"Jackie_Gleason",
"religion",
"Catholicism"
],
[
"Jamie_Kennedy",
"profession",
"Comedian"
],
[
"Jamie_Kennedy",
"religion",
"Catholicism"
],
[
"Janeane_Garofalo",
"profession",
"Comedian"
],
[
"Janeane_Garofalo",
"religion",
"Catholicism"
],
[
"Jay_Leno",
"profession",
"Comedian"
],
[
"Jay_Mohr",
"profession",
"Comedian"
],
[
"Jay_Mohr",
"religion",
"Catholicism"
],
[
"Jemaine_Clement",
"award_nominee",
"Bret_McKenzie"
],
[
"Jemaine_Clement",
"profession",
"Comedian"
],
[
"Jenny_McCarthy",
"profession",
"Comedian"
],
[
"Jenny_McCarthy",
"religion",
"Catholicism"
],
[
"Jim_Carrey",
"profession",
"Comedian"
],
[
"Jim_Carrey",
"religion",
"Catholicism"
],
[
"Jimmy_Kimmel",
"profession",
"Comedian"
],
[
"Jimmy_Kimmel",
"religion",
"Catholicism"
],
[
"Joan_Cusack",
"profession",
"Comedian"
],
[
"Joan_Cusack",
"religion",
"Catholicism"
],
[
"Joe_Pesci",
"profession",
"Comedian"
],
[
"Joe_Pesci",
"religion",
"Catholicism"
],
[
"John_Cusack",
"participant",
"Meg_Ryan"
],
[
"John_Cusack",
"participant",
"Neve_Campbell"
],
[
"John_Cusack",
"religion",
"Catholicism"
],
[
"John_Kerry",
"religion",
"Catholicism"
],
[
"John_Mayer",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"John_Mayer",
"profession",
"Comedian"
],
[
"John_Wayne",
"religion",
"Catholicism"
],
[
"Jon_Favreau",
"profession",
"Comedian"
],
[
"Jon_Favreau",
"religion",
"Catholicism"
],
[
"Kathy_Griffin",
"profession",
"Comedian"
],
[
"Kathy_Griffin",
"religion",
"Catholicism"
],
[
"Kelsey_Grammer",
"profession",
"Comedian"
],
[
"Kelsey_Grammer",
"religion",
"Catholicism"
],
[
"Kevin_Smith",
"profession",
"Comedian"
],
[
"Kevin_Smith",
"religion",
"Catholicism"
],
[
"Kristen_Wiig",
"profession",
"Comedian"
],
[
"Lady_Gaga",
"influenced_by",
"Madonna"
],
[
"Lady_Gaga",
"religion",
"Catholicism"
],
[
"Lucille_Ball",
"profession",
"Comedian"
],
[
"Madonna",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Madonna",
"award",
"Razzie_Award_for_Worst_Actress"
],
[
"Madonna",
"award_nominee",
"Rupert_Everett"
],
[
"Madonna",
"location",
"Detroit"
],
[
"Madonna",
"participant",
"Sacha_Baron_Cohen"
],
[
"Madonna",
"place_of_birth",
"Bay_City"
],
[
"Madonna",
"religion",
"Catholicism"
],
[
"Madonna",
"type_of_union",
"Domestic_partnership"
],
[
"Martin_Short",
"profession",
"Comedian"
],
[
"Martin_Short",
"religion",
"Catholicism"
],
[
"Mary_Astor",
"religion",
"Catholicism"
],
[
"Massachusetts",
"religion",
"Catholicism"
],
[
"Massachusetts",
"time_zones",
"Eastern_Time_Zone"
],
[
"Matt_Dillon",
"award_nominee",
"Neve_Campbell"
],
[
"Matt_Dillon",
"participant",
"Madonna"
],
[
"Matt_Dillon",
"participant",
"Meg_Ryan"
],
[
"Matt_Dillon",
"religion",
"Catholicism"
],
[
"Meg_Ryan",
"award",
"Razzie_Award_for_Worst_Actress"
],
[
"Meg_Ryan",
"award_nominee",
"Debra_Messing"
],
[
"Meg_Ryan",
"location",
"Fairfield"
],
[
"Meg_Ryan",
"location",
"New_York"
],
[
"Meg_Ryan",
"participant",
"John_Cusack"
],
[
"Meg_Ryan",
"participant",
"Matt_Dillon"
],
[
"Meg_Ryan",
"participant",
"Seth_Green"
],
[
"Meg_Ryan",
"place_of_birth",
"Fairfield"
],
[
"Meg_Ryan",
"religion",
"Catholicism"
],
[
"Mel_Brooks",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Mel_Brooks",
"profession",
"Comedian"
],
[
"Mel_Gibson",
"religion",
"Catholicism"
],
[
"Michael_Keaton",
"profession",
"Comedian"
],
[
"Michael_Keaton",
"religion",
"Catholicism"
],
[
"Michael_McKean",
"profession",
"Comedian"
],
[
"Michigan",
"religion",
"Catholicism"
],
[
"Michigan",
"time_zones",
"Eastern_Time_Zone"
],
[
"Mickey_Rooney",
"profession",
"Comedian"
],
[
"Neve_Campbell",
"award_nominee",
"Matt_Dillon"
],
[
"Neve_Campbell",
"location",
"Guelph"
],
[
"Neve_Campbell",
"participant",
"John_Cusack"
],
[
"Neve_Campbell",
"place_of_birth",
"Guelph"
],
[
"Neve_Campbell",
"religion",
"Catholicism"
],
[
"Neve_Campbell",
"type_of_union",
"Domestic_partnership"
],
[
"New_York",
"religion",
"Catholicism"
],
[
"New_York",
"time_zones",
"Eastern_Time_Zone"
],
[
"Nicole_Sullivan",
"profession",
"Comedian"
],
[
"Nicole_Sullivan",
"religion",
"Catholicism"
],
[
"Ohio",
"religion",
"Catholicism"
],
[
"Ohio",
"time_zones",
"Eastern_Time_Zone"
],
[
"Ontario",
"religion",
"Catholicism"
],
[
"Ontario",
"time_zones",
"Eastern_Time_Zone"
],
[
"Patricia_Heaton",
"profession",
"Comedian"
],
[
"Patricia_Heaton",
"religion",
"Catholicism"
],
[
"Pennsylvania",
"religion",
"Catholicism"
],
[
"Pennsylvania",
"time_zones",
"Eastern_Time_Zone"
],
[
"QuΓ©bec",
"religion",
"Catholicism"
],
[
"QuΓ©bec",
"time_zones",
"Eastern_Time_Zone"
],
[
"Ray_Liotta",
"religion",
"Catholicism"
],
[
"Ray_Romano",
"profession",
"Comedian"
],
[
"Ray_Romano",
"religion",
"Catholicism"
],
[
"Razzie_Award_for_Worst_Actress",
"award_winner",
"Madonna"
],
[
"Rhode_Island",
"religion",
"Catholicism"
],
[
"Rhode_Island",
"time_zones",
"Eastern_Time_Zone"
],
[
"Rob_Schneider",
"profession",
"Comedian"
],
[
"Rob_Schneider",
"religion",
"Catholicism"
],
[
"Roscoe_Arbuckle",
"profession",
"Comedian"
],
[
"Rupert_Everett",
"award_nominee",
"Madonna"
],
[
"Rupert_Everett",
"religion",
"Catholicism"
],
[
"Sacha_Baron_Cohen",
"participant",
"Madonna"
],
[
"Sacha_Baron_Cohen",
"profession",
"Comedian"
],
[
"Scottish_American",
"people",
"Anna_Faris"
],
[
"Scottish_American",
"people",
"Craig_Ferguson"
],
[
"Scottish_American",
"people",
"Gregory_Peck"
],
[
"Scottish_American",
"people",
"Jack_Black"
],
[
"Scottish_American",
"people",
"Jay_Leno"
],
[
"Scottish_American",
"people",
"Jay_Mohr"
],
[
"Scottish_American",
"people",
"John_Kerry"
],
[
"Scottish_American",
"people",
"John_Wayne"
],
[
"Scottish_American",
"people",
"Kristen_Wiig"
],
[
"Scottish_American",
"people",
"Lucille_Ball"
],
[
"Scottish_American",
"people",
"Mary_Astor"
],
[
"Scottish_American",
"people",
"Matt_Dillon"
],
[
"Scottish_American",
"people",
"Mel_Gibson"
],
[
"Scottish_American",
"people",
"Michael_Keaton"
],
[
"Scottish_American",
"people",
"Mickey_Rooney"
],
[
"Scottish_American",
"people",
"Ray_Liotta"
],
[
"Scottish_American",
"people",
"Roscoe_Arbuckle"
],
[
"Scottish_American",
"people",
"Steve_McQueen"
],
[
"Scottish_American",
"people",
"Steven_Wright"
],
[
"Scottish_American",
"people",
"Tina_Fey"
],
[
"Sean_Hayes",
"profession",
"Comedian"
],
[
"Sean_Hayes",
"religion",
"Catholicism"
],
[
"Seth_Green",
"participant",
"Meg_Ryan"
],
[
"Seth_Green",
"profession",
"Comedian"
],
[
"Seth_MacFarlane",
"award",
"Grammy_Award_for_Best_Song_Written_for_a_Motion_Picture,_Television_or_Other_Visual_Media"
],
[
"Seth_MacFarlane",
"profession",
"Comedian"
],
[
"Steve_Allen",
"profession",
"Comedian"
],
[
"Steve_Allen",
"religion",
"Catholicism"
],
[
"Steve_Carell",
"profession",
"Comedian"
],
[
"Steve_Carell",
"religion",
"Catholicism"
],
[
"Steve_Coogan",
"profession",
"Comedian"
],
[
"Steve_Coogan",
"religion",
"Catholicism"
],
[
"Steve_McQueen",
"religion",
"Catholicism"
],
[
"Steven_Wright",
"profession",
"Comedian"
],
[
"Tina_Fey",
"profession",
"Comedian"
],
[
"Tracey_Ullman",
"profession",
"Comedian"
],
[
"Tracey_Ullman",
"religion",
"Catholicism"
],
[
"University_of_Michigan",
"student",
"Madonna"
],
[
"University_of_Michigan",
"time_zones",
"Eastern_Time_Zone"
],
[
"Vince_Vaughn",
"profession",
"Comedian"
],
[
"Vince_Vaughn",
"religion",
"Catholicism"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9434, Apache
6151, Apache_Wars
2940, Casey_Affleck
3336, Confederate_States_of_America
3496, English_Language
638, French_Language
10755, Ice_Age
3339, Ocean's_Thirteen
8807, Ocean's_Twelve
3130, Sioux
src, edge_attr, dst
6151, combatants, 9434
6151, combatants, 3336
6151, entity_involved, 3336
6151, entity_involved, 3130
2940, acted_in, 3339
2940, acted_in, 8807
2940, languages, 3496
2940, nominated_for, 8807
3336, official_language, 3496
3496, major_field_of_study, 638
10755, language, 3496
3339, language, 3496
3339, language, 638
3339, prequel, 8807
8807, language, 3496
8807, language, 638
3130, languages_spoken, 3496
Question: How are Apache, Casey_Affleck, and Ice_Age related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Apache",
"Casey_Affleck",
"Ice_Age"
],
"valid_edges": [
[
"Apache_Wars",
"combatants",
"Apache"
],
[
"Apache_Wars",
"combatants",
"Confederate_States_of_America"
],
[
"Apache_Wars",
"entity_involved",
"Confederate_States_of_America"
],
[
"Apache_Wars",
"entity_involved",
"Sioux"
],
[
"Casey_Affleck",
"acted_in",
"Ocean's_Thirteen"
],
[
"Casey_Affleck",
"acted_in",
"Ocean's_Twelve"
],
[
"Casey_Affleck",
"languages",
"English_Language"
],
[
"Casey_Affleck",
"nominated_for",
"Ocean's_Twelve"
],
[
"Confederate_States_of_America",
"official_language",
"English_Language"
],
[
"English_Language",
"major_field_of_study",
"French_Language"
],
[
"Ice_Age",
"language",
"English_Language"
],
[
"Ocean's_Thirteen",
"language",
"English_Language"
],
[
"Ocean's_Thirteen",
"language",
"French_Language"
],
[
"Ocean's_Thirteen",
"prequel",
"Ocean's_Twelve"
],
[
"Ocean's_Twelve",
"language",
"English_Language"
],
[
"Ocean's_Twelve",
"language",
"French_Language"
],
[
"Sioux",
"languages_spoken",
"English_Language"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2476, 48th_Academy_Awards
3967, Dana_Carvey
6139, George_Burns
9111, George_W._Bush
12968, Peter_Morgan
8237, Primetime_Emmy_Award_for_Outstanding_Television_Movie
10441, Recount
2903, United_Methodist_Church
src, edge_attr, dst
2476, award_winner, 6139
3967, celebrities_impersonated, 6139
3967, celebrities_impersonated, 9111
9111, religion, 2903
12968, award, 8237
10441, award_honor_award, 8237
10441, person, 9111
Question: How are 48th_Academy_Awards, Peter_Morgan, and United_Methodist_Church related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"48th_Academy_Awards",
"Peter_Morgan",
"United_Methodist_Church"
],
"valid_edges": [
[
"48th_Academy_Awards",
"award_winner",
"George_Burns"
],
[
"Dana_Carvey",
"celebrities_impersonated",
"George_Burns"
],
[
"Dana_Carvey",
"celebrities_impersonated",
"George_W._Bush"
],
[
"George_W._Bush",
"religion",
"United_Methodist_Church"
],
[
"Peter_Morgan",
"award",
"Primetime_Emmy_Award_for_Outstanding_Television_Movie"
],
[
"Recount",
"award_honor_award",
"Primetime_Emmy_Award_for_Outstanding_Television_Movie"
],
[
"Recount",
"person",
"George_W._Bush"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
13993, Academy_Award_for_Best_Production_Design
10726, African_American
12061, Frank_R._McKelvy
11732, French_Revolution
571, Henry_Bumstead
3456, Jackie_Robinson
614, Library_of_Congress_Classification
5652, Pasadena
1686, UCLA_Bruins_football
src, edge_attr, dst
13993, award_winner, 571
10726, people, 3456
10726, taxonomy, 614
12061, award, 13993
11732, taxonomy, 614
571, award_nominee, 12061
571, place_of_death, 5652
3456, location, 5652
3456, team, 1686
Question: In what context are Frank_R._McKelvy, French_Revolution, and UCLA_Bruins_football connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Frank_R._McKelvy",
"French_Revolution",
"UCLA_Bruins_football"
],
"valid_edges": [
[
"Academy_Award_for_Best_Production_Design",
"award_winner",
"Henry_Bumstead"
],
[
"African_American",
"people",
"Jackie_Robinson"
],
[
"African_American",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Frank_R._McKelvy",
"award",
"Academy_Award_for_Best_Production_Design"
],
[
"French_Revolution",
"taxonomy",
"Library_of_Congress_Classification"
],
[
"Henry_Bumstead",
"award_nominee",
"Frank_R._McKelvy"
],
[
"Henry_Bumstead",
"place_of_death",
"Pasadena"
],
[
"Jackie_Robinson",
"location",
"Pasadena"
],
[
"Jackie_Robinson",
"team",
"UCLA_Bruins_football"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12573, Adolf_Hitler
8918, Aleksandr_Pushkin
9919, Baku
3022, Charles_Dickens
4200, Communist_Party_of_the_Soviet_Union
10192, David_Mills
10710, Dmitri_Shostakovich
6507, Eastern_Front
12915, FC_Dynamo_Moscow
12717, Fyodor_Dostoyevsky
5123, George_Bernard_Shaw
14212, Georgy_Zhukov
157, Henrik_Ibsen
11441, Joseph_Stalin
10808, Karl_Marx
4883, Kingdom_of_Italy
5290, Kingdom_of_Romania
13071, Leon_Trotsky
3326, Moscow
6827, Mstislav_Rostropovich
9105, Nazi_Germany
7593, Nicholas_II_of_Russia
11632, Operation_Barbarossa
13366, Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special
6678, Red_Army
3778, Robert_Bolt
4705, Russian_Civil_War
6057, Russian_Empire
6503, Russian_Soviet_Federative_Socialist_Republic
4522, Saint_Petersburg
208, Second_Polish_Republic
5137, Stroke
1230, Vladimir_Lenin
src, edge_attr, dst
8918, location, 3326
8918, place_of_birth, 3326
8918, place_of_death, 4522
4200, party_politician, 14212
4200, party_politician, 11441
4200, party_politician, 13071
4200, party_politician, 1230
10192, award, 13366
10710, location, 4522
10710, place_of_birth, 4522
10710, place_of_death, 3326
6507, combatants, 4883
6507, combatants, 5290
6507, combatants, 9105
6507, entity_involved, 12573
6507, entity_involved, 14212
6507, entity_involved, 11441
12717, place_of_birth, 3326
12717, place_of_death, 4522
5123, influenced_by, 3022
5123, influenced_by, 157
5123, influenced_by, 11441
5123, influenced_by, 10808
14212, place_of_death, 3326
11441, influenced_by, 10808
11441, location, 9919
11441, location, 4522
11441, organizations_founded, 6678
10808, influenced_by, 3022
13071, influenced_by, 10808
13071, organizations_founded, 6678
3326, place, 3326
3326, teams, 12915
6827, place_of_birth, 9919
6827, place_of_death, 3326
7593, location, 3326
7593, location, 4522
7593, place_of_birth, 4522
11632, combatants, 4883
11632, combatants, 5290
11632, entity_involved, 12573
11632, entity_involved, 14212
11632, entity_involved, 11441
11632, entity_involved, 5290
11632, entity_involved, 9105
11632, locations, 208
3778, award, 13366
4705, combatants, 4883
4705, combatants, 5290
4705, combatants, 6057
4705, combatants, 208
4705, entity_involved, 11441
4705, entity_involved, 13071
4705, entity_involved, 208
4705, entity_involved, 1230
4705, locations, 6057
4705, locations, 6503
6057, capital, 3326
6057, capital, 4522
6503, capital, 3326
6503, contains, 3326
5137, people, 3022
5137, people, 157
5137, people, 11441
5137, people, 3778
1230, influenced_by, 10808
1230, organizations_founded, 6678
Question: In what context are David_Mills, FC_Dynamo_Moscow, and Joseph_Stalin connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"David_Mills",
"FC_Dynamo_Moscow",
"Joseph_Stalin"
],
"valid_edges": [
[
"Aleksandr_Pushkin",
"location",
"Moscow"
],
[
"Aleksandr_Pushkin",
"place_of_birth",
"Moscow"
],
[
"Aleksandr_Pushkin",
"place_of_death",
"Saint_Petersburg"
],
[
"Communist_Party_of_the_Soviet_Union",
"party_politician",
"Georgy_Zhukov"
],
[
"Communist_Party_of_the_Soviet_Union",
"party_politician",
"Joseph_Stalin"
],
[
"Communist_Party_of_the_Soviet_Union",
"party_politician",
"Leon_Trotsky"
],
[
"Communist_Party_of_the_Soviet_Union",
"party_politician",
"Vladimir_Lenin"
],
[
"David_Mills",
"award",
"Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special"
],
[
"Dmitri_Shostakovich",
"location",
"Saint_Petersburg"
],
[
"Dmitri_Shostakovich",
"place_of_birth",
"Saint_Petersburg"
],
[
"Dmitri_Shostakovich",
"place_of_death",
"Moscow"
],
[
"Eastern_Front",
"combatants",
"Kingdom_of_Italy"
],
[
"Eastern_Front",
"combatants",
"Kingdom_of_Romania"
],
[
"Eastern_Front",
"combatants",
"Nazi_Germany"
],
[
"Eastern_Front",
"entity_involved",
"Adolf_Hitler"
],
[
"Eastern_Front",
"entity_involved",
"Georgy_Zhukov"
],
[
"Eastern_Front",
"entity_involved",
"Joseph_Stalin"
],
[
"Fyodor_Dostoyevsky",
"place_of_birth",
"Moscow"
],
[
"Fyodor_Dostoyevsky",
"place_of_death",
"Saint_Petersburg"
],
[
"George_Bernard_Shaw",
"influenced_by",
"Charles_Dickens"
],
[
"George_Bernard_Shaw",
"influenced_by",
"Henrik_Ibsen"
],
[
"George_Bernard_Shaw",
"influenced_by",
"Joseph_Stalin"
],
[
"George_Bernard_Shaw",
"influenced_by",
"Karl_Marx"
],
[
"Georgy_Zhukov",
"place_of_death",
"Moscow"
],
[
"Joseph_Stalin",
"influenced_by",
"Karl_Marx"
],
[
"Joseph_Stalin",
"location",
"Baku"
],
[
"Joseph_Stalin",
"location",
"Saint_Petersburg"
],
[
"Joseph_Stalin",
"organizations_founded",
"Red_Army"
],
[
"Karl_Marx",
"influenced_by",
"Charles_Dickens"
],
[
"Leon_Trotsky",
"influenced_by",
"Karl_Marx"
],
[
"Leon_Trotsky",
"organizations_founded",
"Red_Army"
],
[
"Moscow",
"place",
"Moscow"
],
[
"Moscow",
"teams",
"FC_Dynamo_Moscow"
],
[
"Mstislav_Rostropovich",
"place_of_birth",
"Baku"
],
[
"Mstislav_Rostropovich",
"place_of_death",
"Moscow"
],
[
"Nicholas_II_of_Russia",
"location",
"Moscow"
],
[
"Nicholas_II_of_Russia",
"location",
"Saint_Petersburg"
],
[
"Nicholas_II_of_Russia",
"place_of_birth",
"Saint_Petersburg"
],
[
"Operation_Barbarossa",
"combatants",
"Kingdom_of_Italy"
],
[
"Operation_Barbarossa",
"combatants",
"Kingdom_of_Romania"
],
[
"Operation_Barbarossa",
"entity_involved",
"Adolf_Hitler"
],
[
"Operation_Barbarossa",
"entity_involved",
"Georgy_Zhukov"
],
[
"Operation_Barbarossa",
"entity_involved",
"Joseph_Stalin"
],
[
"Operation_Barbarossa",
"entity_involved",
"Kingdom_of_Romania"
],
[
"Operation_Barbarossa",
"entity_involved",
"Nazi_Germany"
],
[
"Operation_Barbarossa",
"locations",
"Second_Polish_Republic"
],
[
"Robert_Bolt",
"award",
"Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special"
],
[
"Russian_Civil_War",
"combatants",
"Kingdom_of_Italy"
],
[
"Russian_Civil_War",
"combatants",
"Kingdom_of_Romania"
],
[
"Russian_Civil_War",
"combatants",
"Russian_Empire"
],
[
"Russian_Civil_War",
"combatants",
"Second_Polish_Republic"
],
[
"Russian_Civil_War",
"entity_involved",
"Joseph_Stalin"
],
[
"Russian_Civil_War",
"entity_involved",
"Leon_Trotsky"
],
[
"Russian_Civil_War",
"entity_involved",
"Second_Polish_Republic"
],
[
"Russian_Civil_War",
"entity_involved",
"Vladimir_Lenin"
],
[
"Russian_Civil_War",
"locations",
"Russian_Empire"
],
[
"Russian_Civil_War",
"locations",
"Russian_Soviet_Federative_Socialist_Republic"
],
[
"Russian_Empire",
"capital",
"Moscow"
],
[
"Russian_Empire",
"capital",
"Saint_Petersburg"
],
[
"Russian_Soviet_Federative_Socialist_Republic",
"capital",
"Moscow"
],
[
"Russian_Soviet_Federative_Socialist_Republic",
"contains",
"Moscow"
],
[
"Stroke",
"people",
"Charles_Dickens"
],
[
"Stroke",
"people",
"Henrik_Ibsen"
],
[
"Stroke",
"people",
"Joseph_Stalin"
],
[
"Stroke",
"people",
"Robert_Bolt"
],
[
"Vladimir_Lenin",
"influenced_by",
"Karl_Marx"
],
[
"Vladimir_Lenin",
"organizations_founded",
"Red_Army"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
13534, 41st_Academy_Awards
13133, Alan_Rickman
6823, Alexandre_Trauner
3923, Architecture
930, Art_Students_League_of_New_York
5761, Astrid_Lindgren_Memorial_Award
856, Boris_Leven
10443, Braveheart
10903, Brendan_Gleeson
13572, Cedric_Gibbons
1090, Costume_Designer-GB
9428, Danilo_Donati
12167, Designer
1540, Diamonds_Are_Forever
7936, Fiddler_on_the_Roof
9484, Flash_Gordon
11929, Franco_Zeffirelli
8393, From_Hell
466, Galaxy_Quest
10197, Garage_punk
11066, GoldenEye
5084, Graphic_Designer-GB
2442, Greystoke:_The_Legend_of_Tarzan,_Lord_of_the_Apes
8583, Gwen_Stefani
13331, Harry_Potter_and_the_Chamber_of_Secrets
8058, Harry_Potter_and_the_Goblet_of_Fire
10188, Harry_Potter_and_the_Half-Blood_Prince
9497, Harry_Potter_and_the_Order_of_the_Phoenix
8887, Harry_Potter_and_the_Philosopher's_Stone
2822, Harry_Potter_and_the_Prisoner_of_Azkaban
13175, Into_the_Storm
8319, J._K._Rowling
6907, John_Box
11845, Ken_Adam
3209, Kingdom_of_Heaven
5463, Lindy_Hemming
757, Maurice_Sendak
2981, Michael_Collins
5355, Minority_Report
3350, Natural_causes
7146, Peter_Lamont
615, Production_Designer
8139, Psychobilly
8703, Punk_rock
2880, Richard_Griffiths
4993, Ridley_Scott
674, Robbie_Coltrane
5213, Robert_F._Boyle
662, Robin_Hood:_Prince_of_Thieves
6922, Romeo_+_Juliet
725, Romeo_and_Juliet
13885, Royal_Academy_of_Dramatic_Art
2155, Royal_College_of_Art
12008, Santo_Loquasto
13584, Saturn_Award_for_Best_Costume
6778, Sleepy_Hollow
10878, Stuart_Craig
1930, Sweeney_Todd:_The_Demon_Barber_of_Fleet_Street
10113, The_Hitchhiker's_Guide_to_the_Galaxy
894, The_Spy_Who_Loved_Me
11904, The_White_Stripes
13319, The_Wiz
1979, The_World_Is_Not_Enough
9952, Thunderball
3421, Tony_Award_for_Best_Actor_in_a_Play
4336, Tony_Award_for_Best_Costume_Design
4575, Tony_Walton
5888, Van_Helsing
1142, William_Chang
src, edge_attr, dst
13534, award_winner, 9428
13534, award_winner, 6907
13133, acted_in, 466
13133, acted_in, 13331
13133, acted_in, 8058
13133, acted_in, 10188
13133, acted_in, 9497
13133, acted_in, 8887
13133, acted_in, 2822
13133, acted_in, 2981
13133, acted_in, 662
13133, acted_in, 1930
13133, acted_in, 10113
13133, award, 3421
13133, nominated_for, 466
13133, nominated_for, 2981
13133, nominated_for, 662
6823, profession, 615
3923, student, 856
3923, student, 6907
3923, student, 5213
930, student, 13572
930, student, 757
5761, award_winner, 757
856, profession, 615
10903, acted_in, 10443
10903, acted_in, 8058
10903, acted_in, 9497
10903, acted_in, 13175
10903, acted_in, 3209
10903, acted_in, 2981
13572, nominated_for, 725
13572, profession, 615
1090, specialization_of, 12167
9428, award, 13584
9428, film_sets_designed, 9484
9428, nominated_for, 9484
9428, nominated_for, 725
9428, profession, 1090
9428, profession, 615
1540, film_production_design_by, 11845
7936, film_production_design_by, 5213
9484, costume_design_by, 9428
9484, film_production_design_by, 9428
11929, film, 725
11929, nominated_for, 6922
11929, profession, 615
10197, artists, 11904
10197, parent_genre, 8139
10197, parent_genre, 8703
11066, film_production_design_by, 7146
5084, specialization_of, 12167
8583, profession, 12167
13331, costume_design_by, 5463
13331, film_production_design_by, 10878
13331, honored_for, 5355
13331, nominated_for, 8058
13331, nominated_for, 10188
13331, nominated_for, 9497
13331, nominated_for, 8887
13331, nominated_for, 2822
13331, nominated_for, 5355
13331, prequel, 8887
13331, story_by, 8319
8058, award_winner, 10878
8058, film_production_design_by, 10878
8058, nominated_for, 13331
8058, nominated_for, 10188
8058, nominated_for, 9497
8058, nominated_for, 8887
8058, prequel, 2822
8058, story_by, 8319
10188, film_crew_role, 5084
10188, film_production_design_by, 10878
10188, nominated_for, 13331
10188, nominated_for, 8058
10188, nominated_for, 9497
10188, nominated_for, 8887
10188, nominated_for, 2822
10188, prequel, 9497
10188, story_by, 8319
9497, nominated_for, 8058
9497, nominated_for, 8887
9497, nominated_for, 2822
9497, prequel, 8058
9497, story_by, 8319
8887, award_winner, 10878
8887, film_production_design_by, 10878
8887, nominated_for, 13331
8887, nominated_for, 8058
8887, nominated_for, 10188
8887, story_by, 8319
2822, film_production_design_by, 10878
2822, nominated_for, 13331
2822, nominated_for, 8058
2822, nominated_for, 10188
2822, nominated_for, 9497
2822, nominated_for, 8887
2822, prequel, 13331
2822, story_by, 8319
13175, award_winner, 10903
13175, executive_produced_by, 4993
8319, award, 5761
6907, profession, 615
11845, award_nominee, 7146
11845, nominated_for, 894
11845, nominated_for, 9952
11845, profession, 615
5463, award, 13584
5463, nominated_for, 13331
757, profession, 615
5355, honored_for, 13331
5355, nominated_for, 13331
3350, people, 6823
3350, people, 9428
3350, people, 5213
7146, award_nominee, 11845
7146, film_sets_designed, 1540
7146, film_sets_designed, 7936
7146, film_sets_designed, 9952
7146, nominated_for, 7936
7146, nominated_for, 894
7146, profession, 615
615, specialization_of, 12167
8139, parent_genre, 8703
8703, artists, 8583
8703, artists, 11904
2880, acted_in, 2442
2880, acted_in, 13331
2880, acted_in, 9497
2880, acted_in, 8887
2880, acted_in, 2822
2880, acted_in, 6778
2880, acted_in, 10113
2880, award, 3421
4993, film, 3209
4993, nominated_for, 13175
4993, profession, 615
674, acted_in, 9484
674, acted_in, 8393
674, acted_in, 11066
674, acted_in, 13331
674, acted_in, 8058
674, acted_in, 10188
674, acted_in, 9497
674, acted_in, 8887
674, acted_in, 2822
674, acted_in, 1979
674, acted_in, 5888
674, nominated_for, 8887
5213, award_nominee, 7146
5213, profession, 615
6922, produced_by, 4993
725, award_winner, 11929
725, costume_design_by, 9428
725, edited_by, 9428
725, written_by, 11929
13885, student, 13133
13885, student, 10903
2155, student, 13133
2155, student, 4993
12008, award, 4336
12008, profession, 1090
12008, profession, 615
13584, nominated_for, 10443
13584, nominated_for, 9484
13584, nominated_for, 8393
13584, nominated_for, 466
13584, nominated_for, 2442
13584, nominated_for, 13331
13584, nominated_for, 8058
13584, nominated_for, 10188
13584, nominated_for, 9497
13584, nominated_for, 8887
13584, nominated_for, 2822
13584, nominated_for, 5355
13584, nominated_for, 662
13584, nominated_for, 6922
13584, nominated_for, 6778
13584, nominated_for, 1930
13584, nominated_for, 13319
13584, nominated_for, 5888
10878, nominated_for, 2442
10878, nominated_for, 13331
10878, nominated_for, 8058
10878, nominated_for, 10188
10878, nominated_for, 9497
10878, nominated_for, 8887
10878, nominated_for, 2822
10878, profession, 615
1930, award_honor_award, 13584
894, film_art_direction_by, 7146
894, film_production_design_by, 11845
13319, costume_design_by, 4575
13319, film_production_design_by, 4575
1979, film_production_design_by, 7146
4336, award_winner, 12008
4575, award, 13584
4575, award, 4336
4575, profession, 1090
4575, profession, 615
1142, profession, 1090
1142, profession, 615
Question: For what reason are Garage_punk, Harry_Potter_and_the_Order_of_the_Phoenix, and Production_Designer associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Garage_punk",
"Harry_Potter_and_the_Order_of_the_Phoenix",
"Production_Designer"
],
"valid_edges": [
[
"41st_Academy_Awards",
"award_winner",
"Danilo_Donati"
],
[
"41st_Academy_Awards",
"award_winner",
"John_Box"
],
[
"Alan_Rickman",
"acted_in",
"Galaxy_Quest"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Alan_Rickman",
"acted_in",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Alan_Rickman",
"acted_in",
"Michael_Collins"
],
[
"Alan_Rickman",
"acted_in",
"Robin_Hood:_Prince_of_Thieves"
],
[
"Alan_Rickman",
"acted_in",
"Sweeney_Todd:_The_Demon_Barber_of_Fleet_Street"
],
[
"Alan_Rickman",
"acted_in",
"The_Hitchhiker's_Guide_to_the_Galaxy"
],
[
"Alan_Rickman",
"award",
"Tony_Award_for_Best_Actor_in_a_Play"
],
[
"Alan_Rickman",
"nominated_for",
"Galaxy_Quest"
],
[
"Alan_Rickman",
"nominated_for",
"Michael_Collins"
],
[
"Alan_Rickman",
"nominated_for",
"Robin_Hood:_Prince_of_Thieves"
],
[
"Alexandre_Trauner",
"profession",
"Production_Designer"
],
[
"Architecture",
"student",
"Boris_Leven"
],
[
"Architecture",
"student",
"John_Box"
],
[
"Architecture",
"student",
"Robert_F._Boyle"
],
[
"Art_Students_League_of_New_York",
"student",
"Cedric_Gibbons"
],
[
"Art_Students_League_of_New_York",
"student",
"Maurice_Sendak"
],
[
"Astrid_Lindgren_Memorial_Award",
"award_winner",
"Maurice_Sendak"
],
[
"Boris_Leven",
"profession",
"Production_Designer"
],
[
"Brendan_Gleeson",
"acted_in",
"Braveheart"
],
[
"Brendan_Gleeson",
"acted_in",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Brendan_Gleeson",
"acted_in",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Brendan_Gleeson",
"acted_in",
"Into_the_Storm"
],
[
"Brendan_Gleeson",
"acted_in",
"Kingdom_of_Heaven"
],
[
"Brendan_Gleeson",
"acted_in",
"Michael_Collins"
],
[
"Cedric_Gibbons",
"nominated_for",
"Romeo_and_Juliet"
],
[
"Cedric_Gibbons",
"profession",
"Production_Designer"
],
[
"Costume_Designer-GB",
"specialization_of",
"Designer"
],
[
"Danilo_Donati",
"award",
"Saturn_Award_for_Best_Costume"
],
[
"Danilo_Donati",
"film_sets_designed",
"Flash_Gordon"
],
[
"Danilo_Donati",
"nominated_for",
"Flash_Gordon"
],
[
"Danilo_Donati",
"nominated_for",
"Romeo_and_Juliet"
],
[
"Danilo_Donati",
"profession",
"Costume_Designer-GB"
],
[
"Danilo_Donati",
"profession",
"Production_Designer"
],
[
"Diamonds_Are_Forever",
"film_production_design_by",
"Ken_Adam"
],
[
"Fiddler_on_the_Roof",
"film_production_design_by",
"Robert_F._Boyle"
],
[
"Flash_Gordon",
"costume_design_by",
"Danilo_Donati"
],
[
"Flash_Gordon",
"film_production_design_by",
"Danilo_Donati"
],
[
"Franco_Zeffirelli",
"film",
"Romeo_and_Juliet"
],
[
"Franco_Zeffirelli",
"nominated_for",
"Romeo_+_Juliet"
],
[
"Franco_Zeffirelli",
"profession",
"Production_Designer"
],
[
"Garage_punk",
"artists",
"The_White_Stripes"
],
[
"Garage_punk",
"parent_genre",
"Psychobilly"
],
[
"Garage_punk",
"parent_genre",
"Punk_rock"
],
[
"GoldenEye",
"film_production_design_by",
"Peter_Lamont"
],
[
"Graphic_Designer-GB",
"specialization_of",
"Designer"
],
[
"Gwen_Stefani",
"profession",
"Designer"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"costume_design_by",
"Lindy_Hemming"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"film_production_design_by",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"honored_for",
"Minority_Report"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"nominated_for",
"Minority_Report"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"prequel",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Chamber_of_Secrets",
"story_by",
"J._K._Rowling"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"award_winner",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"film_production_design_by",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"prequel",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Harry_Potter_and_the_Goblet_of_Fire",
"story_by",
"J._K._Rowling"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"film_crew_role",
"Graphic_Designer-GB"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"film_production_design_by",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"prequel",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Harry_Potter_and_the_Half-Blood_Prince",
"story_by",
"J._K._Rowling"
],
[
"Harry_Potter_and_the_Order_of_the_Phoenix",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Order_of_the_Phoenix",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Order_of_the_Phoenix",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Harry_Potter_and_the_Order_of_the_Phoenix",
"prequel",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Order_of_the_Phoenix",
"story_by",
"J._K._Rowling"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"award_winner",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"film_production_design_by",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Harry_Potter_and_the_Philosopher's_Stone",
"story_by",
"J._K._Rowling"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"film_production_design_by",
"Stuart_Craig"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"prequel",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Harry_Potter_and_the_Prisoner_of_Azkaban",
"story_by",
"J._K._Rowling"
],
[
"Into_the_Storm",
"award_winner",
"Brendan_Gleeson"
],
[
"Into_the_Storm",
"executive_produced_by",
"Ridley_Scott"
],
[
"J._K._Rowling",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"John_Box",
"profession",
"Production_Designer"
],
[
"Ken_Adam",
"award_nominee",
"Peter_Lamont"
],
[
"Ken_Adam",
"nominated_for",
"The_Spy_Who_Loved_Me"
],
[
"Ken_Adam",
"nominated_for",
"Thunderball"
],
[
"Ken_Adam",
"profession",
"Production_Designer"
],
[
"Lindy_Hemming",
"award",
"Saturn_Award_for_Best_Costume"
],
[
"Lindy_Hemming",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Maurice_Sendak",
"profession",
"Production_Designer"
],
[
"Minority_Report",
"honored_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Minority_Report",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Natural_causes",
"people",
"Alexandre_Trauner"
],
[
"Natural_causes",
"people",
"Danilo_Donati"
],
[
"Natural_causes",
"people",
"Robert_F._Boyle"
],
[
"Peter_Lamont",
"award_nominee",
"Ken_Adam"
],
[
"Peter_Lamont",
"film_sets_designed",
"Diamonds_Are_Forever"
],
[
"Peter_Lamont",
"film_sets_designed",
"Fiddler_on_the_Roof"
],
[
"Peter_Lamont",
"film_sets_designed",
"Thunderball"
],
[
"Peter_Lamont",
"nominated_for",
"Fiddler_on_the_Roof"
],
[
"Peter_Lamont",
"nominated_for",
"The_Spy_Who_Loved_Me"
],
[
"Peter_Lamont",
"profession",
"Production_Designer"
],
[
"Production_Designer",
"specialization_of",
"Designer"
],
[
"Psychobilly",
"parent_genre",
"Punk_rock"
],
[
"Punk_rock",
"artists",
"Gwen_Stefani"
],
[
"Punk_rock",
"artists",
"The_White_Stripes"
],
[
"Richard_Griffiths",
"acted_in",
"Greystoke:_The_Legend_of_Tarzan,_Lord_of_the_Apes"
],
[
"Richard_Griffiths",
"acted_in",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Richard_Griffiths",
"acted_in",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Richard_Griffiths",
"acted_in",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Richard_Griffiths",
"acted_in",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Richard_Griffiths",
"acted_in",
"Sleepy_Hollow"
],
[
"Richard_Griffiths",
"acted_in",
"The_Hitchhiker's_Guide_to_the_Galaxy"
],
[
"Richard_Griffiths",
"award",
"Tony_Award_for_Best_Actor_in_a_Play"
],
[
"Ridley_Scott",
"film",
"Kingdom_of_Heaven"
],
[
"Ridley_Scott",
"nominated_for",
"Into_the_Storm"
],
[
"Ridley_Scott",
"profession",
"Production_Designer"
],
[
"Robbie_Coltrane",
"acted_in",
"Flash_Gordon"
],
[
"Robbie_Coltrane",
"acted_in",
"From_Hell"
],
[
"Robbie_Coltrane",
"acted_in",
"GoldenEye"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Robbie_Coltrane",
"acted_in",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Robbie_Coltrane",
"acted_in",
"The_World_Is_Not_Enough"
],
[
"Robbie_Coltrane",
"acted_in",
"Van_Helsing"
],
[
"Robbie_Coltrane",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Robert_F._Boyle",
"award_nominee",
"Peter_Lamont"
],
[
"Robert_F._Boyle",
"profession",
"Production_Designer"
],
[
"Romeo_+_Juliet",
"produced_by",
"Ridley_Scott"
],
[
"Romeo_and_Juliet",
"award_winner",
"Franco_Zeffirelli"
],
[
"Romeo_and_Juliet",
"costume_design_by",
"Danilo_Donati"
],
[
"Romeo_and_Juliet",
"edited_by",
"Danilo_Donati"
],
[
"Romeo_and_Juliet",
"written_by",
"Franco_Zeffirelli"
],
[
"Royal_Academy_of_Dramatic_Art",
"student",
"Alan_Rickman"
],
[
"Royal_Academy_of_Dramatic_Art",
"student",
"Brendan_Gleeson"
],
[
"Royal_College_of_Art",
"student",
"Alan_Rickman"
],
[
"Royal_College_of_Art",
"student",
"Ridley_Scott"
],
[
"Santo_Loquasto",
"award",
"Tony_Award_for_Best_Costume_Design"
],
[
"Santo_Loquasto",
"profession",
"Costume_Designer-GB"
],
[
"Santo_Loquasto",
"profession",
"Production_Designer"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Braveheart"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Flash_Gordon"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"From_Hell"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Galaxy_Quest"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Greystoke:_The_Legend_of_Tarzan,_Lord_of_the_Apes"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Minority_Report"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Robin_Hood:_Prince_of_Thieves"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Romeo_+_Juliet"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Sleepy_Hollow"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Sweeney_Todd:_The_Demon_Barber_of_Fleet_Street"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Wiz"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Van_Helsing"
],
[
"Stuart_Craig",
"nominated_for",
"Greystoke:_The_Legend_of_Tarzan,_Lord_of_the_Apes"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Chamber_of_Secrets"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Goblet_of_Fire"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Half-Blood_Prince"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Stuart_Craig",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Stuart_Craig",
"profession",
"Production_Designer"
],
[
"Sweeney_Todd:_The_Demon_Barber_of_Fleet_Street",
"award_honor_award",
"Saturn_Award_for_Best_Costume"
],
[
"The_Spy_Who_Loved_Me",
"film_art_direction_by",
"Peter_Lamont"
],
[
"The_Spy_Who_Loved_Me",
"film_production_design_by",
"Ken_Adam"
],
[
"The_Wiz",
"costume_design_by",
"Tony_Walton"
],
[
"The_Wiz",
"film_production_design_by",
"Tony_Walton"
],
[
"The_World_Is_Not_Enough",
"film_production_design_by",
"Peter_Lamont"
],
[
"Tony_Award_for_Best_Costume_Design",
"award_winner",
"Santo_Loquasto"
],
[
"Tony_Walton",
"award",
"Saturn_Award_for_Best_Costume"
],
[
"Tony_Walton",
"award",
"Tony_Award_for_Best_Costume_Design"
],
[
"Tony_Walton",
"profession",
"Costume_Designer-GB"
],
[
"Tony_Walton",
"profession",
"Production_Designer"
],
[
"William_Chang",
"profession",
"Costume_Designer-GB"
],
[
"William_Chang",
"profession",
"Production_Designer"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3906, Burlington
3987, College_of_William_and_Mary
14177, Grinnell_College
3129, Haverford_College
9558, Paul_Robeson
3223, Princeton
2748, Religion
13376, Rutgers_University
10954, Scarlet
11910, Trey_Anastasio
src, edge_attr, dst
3906, place, 3906
3987, campuses, 3987
3987, educational_institution, 3987
3987, major_field_of_study, 2748
14177, colors, 10954
14177, major_field_of_study, 2748
3129, colors, 10954
3129, major_field_of_study, 2748
9558, location, 3223
9558, place_of_birth, 3223
13376, colors, 10954
13376, student, 9558
11910, artist_origin, 3906
11910, location, 3223
Question: For what reason are Burlington, College_of_William_and_Mary, and Rutgers_University associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Burlington",
"College_of_William_and_Mary",
"Rutgers_University"
],
"valid_edges": [
[
"Burlington",
"place",
"Burlington"
],
[
"College_of_William_and_Mary",
"campuses",
"College_of_William_and_Mary"
],
[
"College_of_William_and_Mary",
"educational_institution",
"College_of_William_and_Mary"
],
[
"College_of_William_and_Mary",
"major_field_of_study",
"Religion"
],
[
"Grinnell_College",
"colors",
"Scarlet"
],
[
"Grinnell_College",
"major_field_of_study",
"Religion"
],
[
"Haverford_College",
"colors",
"Scarlet"
],
[
"Haverford_College",
"major_field_of_study",
"Religion"
],
[
"Paul_Robeson",
"location",
"Princeton"
],
[
"Paul_Robeson",
"place_of_birth",
"Princeton"
],
[
"Rutgers_University",
"colors",
"Scarlet"
],
[
"Rutgers_University",
"student",
"Paul_Robeson"
],
[
"Trey_Anastasio",
"artist_origin",
"Burlington"
],
[
"Trey_Anastasio",
"location",
"Princeton"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
11768, 107th_United_States_Congress
1113, 108th_United_States_Congress
13445, 109th_United_States_Congress
362, 110th_United_States_Congress
7637, 111th_United_States_Congress
10634, 112th_United_States_Congress
6673, 113th_United_States_Congress
8795, 30th_United_States_Congress
10644, 31st_United_States_Congress
994, 32nd_United_States_Congress
8188, Arkansas
8356, Attorney_general
11478, Baptists
717, Boca_Raton
3014, Boston_University
5379, Christianity
4041, Churches_of_Christ
8527, Contiguous_United_States
4140, Donnie_Yen
1311, Florida
4944, Florida_Atlantic_University
7749, Governor-GB
12982, Lutheranism
8705, Mechanical_Engineering
7662, Methodism
13057, Nondenominational_Christianity
9830, Pentecostalism
9332, Pine_Bluff
5986, Presbyterianism
2244, Protestantism
8889, Secretary_of_state
12042, Theatre
src, edge_attr, dst
11768, district_represented, 8188
11768, district_represented, 1311
1113, district_represented, 8188
1113, district_represented, 1311
13445, district_represented, 8188
13445, district_represented, 1311
362, district_represented, 8188
362, district_represented, 1311
7637, district_represented, 8188
7637, district_represented, 1311
10634, district_represented, 8188
10634, district_represented, 1311
6673, district_represented, 8188
6673, district_represented, 1311
8795, district_represented, 8188
8795, district_represented, 1311
10644, district_represented, 8188
10644, district_represented, 1311
994, district_represented, 8188
994, district_represented, 1311
8188, contains, 9332
8188, religion, 11478
8188, religion, 5379
8188, religion, 4041
8188, religion, 12982
8188, religion, 7662
8188, religion, 13057
8188, religion, 9830
8188, religion, 5986
8188, religion, 2244
8356, jurisdiction_of_office, 8188
8356, jurisdiction_of_office, 1311
717, contains, 4944
717, place, 717
3014, major_field_of_study, 8705
3014, major_field_of_study, 12042
3014, student, 4140
8527, contains, 8188
8527, contains, 1311
1311, contains, 717
1311, contains, 4944
1311, religion, 11478
1311, religion, 5379
1311, religion, 4041
1311, religion, 12982
1311, religion, 7662
1311, religion, 13057
1311, religion, 9830
1311, religion, 5986
1311, religion, 2244
4944, campuses, 4944
4944, citytown, 717
4944, educational_institution, 4944
4944, major_field_of_study, 8705
4944, major_field_of_study, 12042
4944, state_province_region, 1311
7749, jurisdiction_of_office, 8188
7749, jurisdiction_of_office, 1311
9332, place, 9332
8889, jurisdiction_of_office, 8188
8889, jurisdiction_of_office, 1311
Question: In what context are Boca_Raton, Donnie_Yen, and Pine_Bluff connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Boca_Raton",
"Donnie_Yen",
"Pine_Bluff"
],
"valid_edges": [
[
"107th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"107th_United_States_Congress",
"district_represented",
"Florida"
],
[
"108th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"108th_United_States_Congress",
"district_represented",
"Florida"
],
[
"109th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"109th_United_States_Congress",
"district_represented",
"Florida"
],
[
"110th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"110th_United_States_Congress",
"district_represented",
"Florida"
],
[
"111th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"111th_United_States_Congress",
"district_represented",
"Florida"
],
[
"112th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"112th_United_States_Congress",
"district_represented",
"Florida"
],
[
"113th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"113th_United_States_Congress",
"district_represented",
"Florida"
],
[
"30th_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"30th_United_States_Congress",
"district_represented",
"Florida"
],
[
"31st_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"31st_United_States_Congress",
"district_represented",
"Florida"
],
[
"32nd_United_States_Congress",
"district_represented",
"Arkansas"
],
[
"32nd_United_States_Congress",
"district_represented",
"Florida"
],
[
"Arkansas",
"contains",
"Pine_Bluff"
],
[
"Arkansas",
"religion",
"Baptists"
],
[
"Arkansas",
"religion",
"Christianity"
],
[
"Arkansas",
"religion",
"Churches_of_Christ"
],
[
"Arkansas",
"religion",
"Lutheranism"
],
[
"Arkansas",
"religion",
"Methodism"
],
[
"Arkansas",
"religion",
"Nondenominational_Christianity"
],
[
"Arkansas",
"religion",
"Pentecostalism"
],
[
"Arkansas",
"religion",
"Presbyterianism"
],
[
"Arkansas",
"religion",
"Protestantism"
],
[
"Attorney_general",
"jurisdiction_of_office",
"Arkansas"
],
[
"Attorney_general",
"jurisdiction_of_office",
"Florida"
],
[
"Boca_Raton",
"contains",
"Florida_Atlantic_University"
],
[
"Boca_Raton",
"place",
"Boca_Raton"
],
[
"Boston_University",
"major_field_of_study",
"Mechanical_Engineering"
],
[
"Boston_University",
"major_field_of_study",
"Theatre"
],
[
"Boston_University",
"student",
"Donnie_Yen"
],
[
"Contiguous_United_States",
"contains",
"Arkansas"
],
[
"Contiguous_United_States",
"contains",
"Florida"
],
[
"Florida",
"contains",
"Boca_Raton"
],
[
"Florida",
"contains",
"Florida_Atlantic_University"
],
[
"Florida",
"religion",
"Baptists"
],
[
"Florida",
"religion",
"Christianity"
],
[
"Florida",
"religion",
"Churches_of_Christ"
],
[
"Florida",
"religion",
"Lutheranism"
],
[
"Florida",
"religion",
"Methodism"
],
[
"Florida",
"religion",
"Nondenominational_Christianity"
],
[
"Florida",
"religion",
"Pentecostalism"
],
[
"Florida",
"religion",
"Presbyterianism"
],
[
"Florida",
"religion",
"Protestantism"
],
[
"Florida_Atlantic_University",
"campuses",
"Florida_Atlantic_University"
],
[
"Florida_Atlantic_University",
"citytown",
"Boca_Raton"
],
[
"Florida_Atlantic_University",
"educational_institution",
"Florida_Atlantic_University"
],
[
"Florida_Atlantic_University",
"major_field_of_study",
"Mechanical_Engineering"
],
[
"Florida_Atlantic_University",
"major_field_of_study",
"Theatre"
],
[
"Florida_Atlantic_University",
"state_province_region",
"Florida"
],
[
"Governor-GB",
"jurisdiction_of_office",
"Arkansas"
],
[
"Governor-GB",
"jurisdiction_of_office",
"Florida"
],
[
"Pine_Bluff",
"place",
"Pine_Bluff"
],
[
"Secretary_of_state",
"jurisdiction_of_office",
"Arkansas"
],
[
"Secretary_of_state",
"jurisdiction_of_office",
"Florida"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9437, Alex_Rodriguez
3698, Athlete
3342, Avril_Lavigne-US
4783, Derek_Jeter
13640, Fast_Food_Nation
10345, Las_Vegas
11180, Modern_rock
4440, Strongman-GB
13434, The_Hangover
11139, Uruguay
src, edge_attr, dst
9437, profession, 3698
3342, acted_in, 13640
4783, profession, 3698
13640, film_release_region, 11139
10345, place, 10345
10345, vacationer, 9437
10345, vacationer, 4783
11180, artists, 3342
4440, specialization_of, 3698
13434, featured_film_locations, 10345
13434, film_release_region, 11139
Question: How are Modern_rock, Strongman-GB, and The_Hangover related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Modern_rock",
"Strongman-GB",
"The_Hangover"
],
"valid_edges": [
[
"Alex_Rodriguez",
"profession",
"Athlete"
],
[
"Avril_Lavigne-US",
"acted_in",
"Fast_Food_Nation"
],
[
"Derek_Jeter",
"profession",
"Athlete"
],
[
"Fast_Food_Nation",
"film_release_region",
"Uruguay"
],
[
"Las_Vegas",
"place",
"Las_Vegas"
],
[
"Las_Vegas",
"vacationer",
"Alex_Rodriguez"
],
[
"Las_Vegas",
"vacationer",
"Derek_Jeter"
],
[
"Modern_rock",
"artists",
"Avril_Lavigne-US"
],
[
"Strongman-GB",
"specialization_of",
"Athlete"
],
[
"The_Hangover",
"featured_film_locations",
"Las_Vegas"
],
[
"The_Hangover",
"film_release_region",
"Uruguay"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1770, 13_Assassins
8740, 2012_British_Academy_Film_Awards
8428, 24
6005, 300
2463, 30_Rock
8920, 59th_Primetime_Emmy_Awards
4152, 60th_Primetime_Emmy_Awards
12443, 61st_Primetime_Emmy_Awards
7226, A_Better_Tomorrow
14241, A_Serious_Man
990, About_a_Boy
2027, Alec_Baldwin
9466, American_Idol
7911, American_Masters
10174, Anna_Karenina
14128, Atonement
9562, Battlestar_Galactica-GB
11584, Ben_Silverman
7273, Big_Miracle
8838, Bodyguards_and_Assassins
2967, Breaking_Bad
2089, Brian_Grazer
4439, Bridget_Jones's_Diary
7518, Brothers_&_Sisters
9401, Bryan_Cranston
8925, Burn_After_Reading
12490, Bury_My_Heart_at_Wounded_Knee
5405, CSI:_Crime_Scene_Investigation
14117, Captain_Corelli's_Mandolin
6199, China
3569, Christopher_Hampton
1702, Chuck
13102, Contraband
14197, Damages
1610, Dancing_with_the_Stars
9794, David_Javerbaum
2022, David_Miner
8084, Dead_Man_Walking
3649, Deadwood
2094, Desperate_Housewives
504, Dexter
5005, Don_Scardino
292, Elizabeth
8098, Elizabeth:_The_Golden_Age
3334, English_people
497, Entourage
7394, Eragon
5930, Eric_Fellner
9405, Fargo
4805, Four_Weddings_and_a_Funeral
10160, Friday_Night_Lights
3008, Frost/Nixon
11488, Glenn_Close
9800, Green_Zone
10370, Heroes
12590, Historical_fiction
9870, Hot_Fuzz
2197, House
2498, How_I_Met_Your_Mother
13175, Into_the_Storm
6035, Ip_Man
6123, Jeremy_Piven
9475, John_Adams
352, Johnny_English_Reborn
553, Jon_Stewart
3560, Joss_Stone
11701, Kettering
4319, Laura_Linney
14071, Law_&_Order:_Special_Victims_Unit
1602, Lorne_Michaels
5152, Lost
573, Love_Actually
1946, Mad_Men
6457, Management
11340, Marci_Klein
2855, Matthew_Weiner
3685, Monk
11125, My_Week_with_Marilyn
5596, Ned_Kelly
402, Notting_Hill
3052, Nurse_Jackie
9364, Paul
3998, Pride_&_Prejudice
9232, Primetime_Emmy_Award
12009, Primetime_Emmy_Award_for_Outstanding_Comedy_Series
6570, Primetime_Emmy_Award_for_Outstanding_Continued_Performance_by_an_Actress_in_a_Leading_Role_in_a_Dramatic_Series
8330, Primetime_Emmy_Award_for_Outstanding_Costumes_for_a_Miniseries,_Movie_or_a_Special
11727, Primetime_Emmy_Award_for_Outstanding_Directing_-_Comedy_Series
2390, Primetime_Emmy_Award_for_Outstanding_Drama_Series
340, Primetime_Emmy_Award_for_Outstanding_Guest_Actor_-_Drama_Series
4663, Primetime_Emmy_Award_for_Outstanding_Guest_Actress_-_Comedy_Series
1862, Primetime_Emmy_Award_for_Outstanding_Guest_Actress_-_Drama_Series
14195, Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Comedy_Series
4770, Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Drama_Series
137, Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie
11556, Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Comedy_Series
7775, Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Miniseries_or_a_Movie
10010, Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Comedy_Series
10280, Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie
327, Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Comedy_Series
2504, Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Drama_Series
11025, Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie
4017, Primetime_Emmy_Award_for_Outstanding_Variety_Series
13366, Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special
13413, Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture
2603, Pushing_Daisies
11687, Qingdao
9086, Quiz_Show
7119, Resident_Evil:_Retribution
13120, Richard_Curtis
12620, Robert_Carlock
4988, Robert_De_Niro
2346, Ron_Howard
546, Saturday_Night_Live
2923, Senna
6703, Shaun_of_the_Dead
2900, Sheila_Nevins
4071, Showtime
12602, Sienna_Guillory
7798, Smallville
6259, Smokin'_Aces
8948, Spartacus
12229, State_of_Play
9103, Television
5253, The_Big_Lebowski
13289, The_Boat_That_Rocked
9697, The_Daily_Show
2893, The_Flowers_of_War
8441, The_Interpreter
6287, The_Office
6666, The_Outer_Limits
7607, The_Soloist
9749, The_Tudors-GB
4558, Thirteen
13337, Tim_Bevan
12409, Tin_Man
898, Tina_Fey
13016, Tinker,_Tailor,_Soldier,_Spy
9350, Tom_Stoppard
6735, Tony_Award_for_Best_Musical
321, Trey_Parker
205, True_Blood
6712, Ugly_Betty
12900, United_93
13924, Weeds
6204, Working_Title_Films
src, edge_attr, dst
1770, film_release_distribution_medium, 9103
1770, genre, 12590
8740, award_winner, 5930
8740, award_winner, 13337
6005, film_release_region, 6199
6005, genre, 12590
8920, award_winner, 9794
8920, award_winner, 2022
8920, award_winner, 6123
8920, award_winner, 553
8920, award_winner, 1602
8920, award_winner, 11340
8920, award_winner, 2855
8920, award_winner, 12620
8920, award_winner, 2900
8920, award_winner, 898
8920, award_winner, 321
8920, honored_for, 8428
8920, honored_for, 2463
8920, honored_for, 9466
8920, honored_for, 7911
8920, honored_for, 9562
8920, honored_for, 7518
8920, honored_for, 12490
8920, honored_for, 5405
8920, honored_for, 504
8920, honored_for, 497
8920, honored_for, 10160
8920, honored_for, 2498
8920, honored_for, 14071
8920, honored_for, 3685
8920, honored_for, 546
8920, honored_for, 9697
8920, honored_for, 6287
8920, honored_for, 9749
8920, honored_for, 6712
8920, instance_of_recurring_event, 9232
4152, award_winner, 2027
4152, award_winner, 9401
4152, award_winner, 9794
4152, award_winner, 2022
4152, award_winner, 5005
4152, award_winner, 11488
4152, award_winner, 6123
4152, award_winner, 553
4152, award_winner, 4319
4152, award_winner, 1602
4152, award_winner, 11340
4152, award_winner, 2855
4152, award_winner, 12620
4152, award_winner, 2900
4152, award_winner, 898
4152, award_winner, 321
4152, honored_for, 2463
4152, honored_for, 9466
4152, honored_for, 7911
4152, honored_for, 9562
4152, honored_for, 2967
4152, honored_for, 1702
4152, honored_for, 14197
4152, honored_for, 1610
4152, honored_for, 2094
4152, honored_for, 497
4152, honored_for, 2498
4152, honored_for, 9475
4152, honored_for, 14071
4152, honored_for, 5152
4152, honored_for, 1946
4152, honored_for, 2603
4152, honored_for, 546
4152, honored_for, 7798
4152, honored_for, 9697
4152, honored_for, 9749
4152, honored_for, 12409
4152, instance_of_recurring_event, 9232
12443, award_winner, 2027
12443, award_winner, 9401
12443, award_winner, 9794
12443, award_winner, 2022
12443, award_winner, 5005
12443, award_winner, 11488
12443, award_winner, 553
12443, award_winner, 1602
12443, award_winner, 11340
12443, award_winner, 2855
12443, award_winner, 12620
12443, award_winner, 2900
12443, award_winner, 898
12443, award_winner, 321
12443, honored_for, 8428
12443, honored_for, 2463
12443, honored_for, 9466
12443, honored_for, 7911
12443, honored_for, 9562
12443, honored_for, 2967
12443, honored_for, 1702
12443, honored_for, 14197
12443, honored_for, 1610
12443, honored_for, 497
12443, honored_for, 10370
12443, honored_for, 2197
12443, honored_for, 2498
12443, honored_for, 13175
12443, honored_for, 14071
12443, honored_for, 5152
12443, honored_for, 1946
12443, honored_for, 2603
12443, honored_for, 546
12443, honored_for, 9697
12443, honored_for, 6287
12443, honored_for, 9749
12443, honored_for, 205
12443, honored_for, 13924
12443, instance_of_recurring_event, 9232
7226, film_country, 6199
7226, film_release_distribution_medium, 9103
14241, executive_produced_by, 5930
14241, executive_produced_by, 13337
990, produced_by, 5930
990, produced_by, 13337
10174, produced_by, 13337
14128, award_winner, 5930
14128, award_winner, 13337
14128, produced_by, 5930
11584, award, 12009
11584, award_nominee, 5930
11584, award_nominee, 13337
11584, nominated_for, 6287
11584, nominated_for, 9749
11584, nominated_for, 6712
11584, program, 6287
11584, program, 9749
11584, program, 6712
7273, film_release_region, 6199
7273, produced_by, 5930
7273, produced_by, 13337
8838, film_country, 6199
8838, genre, 12590
2089, award_nominee, 5930
2089, award_nominee, 13337
4439, produced_by, 5930
4439, produced_by, 13337
8925, executive_produced_by, 5930
8925, executive_produced_by, 13337
12490, genre, 12590
14117, produced_by, 5930
14117, produced_by, 13337
6199, contains, 11687
3569, award_nominee, 13337
13102, film_release_region, 6199
13102, produced_by, 5930
13102, produced_by, 13337
8084, executive_produced_by, 5930
8084, executive_produced_by, 13337
3649, genre, 12590
504, award_winner, 4071
292, award_winner, 5930
292, award_winner, 13337
292, produced_by, 5930
292, produced_by, 13337
8098, genre, 12590
8098, produced_by, 5930
8098, produced_by, 13337
3334, people, 5930
3334, people, 3560
5930, award, 13413
5930, award, 6735
5930, award_nominee, 11584
5930, award_nominee, 2089
5930, award_nominee, 3569
5930, award_nominee, 13120
5930, award_nominee, 4988
5930, award_nominee, 2346
5930, award_nominee, 13337
5930, award_nominee, 9350
5930, award_nominee, 6204
5930, award_winner, 13337
5930, award_winner, 6204
5930, nominated_for, 990
5930, nominated_for, 10174
5930, nominated_for, 14128
5930, nominated_for, 4439
5930, nominated_for, 292
5930, nominated_for, 3008
5930, nominated_for, 573
5930, nominated_for, 3998
5930, nominated_for, 2923
5930, nominated_for, 9749
9405, executive_produced_by, 5930
9405, executive_produced_by, 13337
4805, executive_produced_by, 5930
4805, executive_produced_by, 13337
10160, film_release_distribution_medium, 9103
3008, produced_by, 5930
3008, produced_by, 13337
9800, produced_by, 5930
9800, produced_by, 13337
9870, produced_by, 5930
9870, produced_by, 13337
13175, genre, 12590
6035, film_country, 6199
6035, genre, 12590
9475, genre, 12590
352, produced_by, 5930
352, produced_by, 13337
3560, acted_in, 7394
573, produced_by, 5930
573, produced_by, 13337
6457, produced_by, 5930
6457, produced_by, 13337
11125, film_release_region, 6199
11125, genre, 12590
5596, executive_produced_by, 5930
5596, executive_produced_by, 13337
402, executive_produced_by, 5930
402, executive_produced_by, 13337
9364, produced_by, 5930
9364, produced_by, 13337
3998, produced_by, 5930
3998, produced_by, 13337
12009, award_winner, 11584
12009, ceremony, 8920
12009, ceremony, 4152
12009, ceremony, 12443
6570, ceremony, 8920
6570, ceremony, 4152
6570, ceremony, 12443
8330, ceremony, 4152
8330, ceremony, 12443
11727, ceremony, 8920
11727, ceremony, 4152
11727, ceremony, 12443
2390, ceremony, 8920
2390, ceremony, 4152
2390, ceremony, 12443
340, ceremony, 8920
340, ceremony, 4152
340, ceremony, 12443
4663, ceremony, 8920
4663, ceremony, 4152
4663, ceremony, 12443
1862, ceremony, 8920
1862, ceremony, 4152
1862, ceremony, 12443
14195, ceremony, 8920
14195, ceremony, 4152
14195, ceremony, 12443
4770, ceremony, 8920
4770, ceremony, 4152
4770, ceremony, 12443
137, ceremony, 8920
137, ceremony, 4152
137, ceremony, 12443
11556, ceremony, 8920
11556, ceremony, 4152
11556, ceremony, 12443
7775, ceremony, 8920
7775, ceremony, 4152
7775, ceremony, 12443
10010, ceremony, 8920
10010, ceremony, 4152
10010, ceremony, 12443
10280, ceremony, 8920
10280, ceremony, 4152
10280, ceremony, 12443
327, ceremony, 8920
327, ceremony, 4152
327, ceremony, 12443
2504, ceremony, 8920
2504, ceremony, 4152
2504, ceremony, 12443
11025, ceremony, 8920
11025, ceremony, 4152
11025, ceremony, 12443
4017, ceremony, 8920
4017, ceremony, 4152
4017, ceremony, 12443
13366, ceremony, 8920
13366, ceremony, 4152
13366, ceremony, 12443
9086, genre, 12590
7119, genre, 12590
13120, award_nominee, 5930
13120, award_nominee, 13337
4988, acted_in, 4071
4988, award_nominee, 5930
4988, award_nominee, 13337
4988, nominated_for, 4071
2346, award_nominee, 5930
2923, award_winner, 5930
2923, produced_by, 5930
2923, produced_by, 13337
6703, executive_produced_by, 5930
6703, executive_produced_by, 13337
4071, nominated_for, 504
4071, nominated_for, 9749
4071, nominated_for, 13924
4071, program, 504
4071, program, 3052
4071, program, 6666
4071, program, 9749
4071, program, 13924
4071, titles, 504
4071, titles, 3052
4071, titles, 6666
4071, titles, 9749
4071, titles, 13924
12602, acted_in, 7394
12602, acted_in, 573
12602, acted_in, 7119
12602, award_nominee, 4319
12602, location, 11701
12602, nominated_for, 573
6259, produced_by, 5930
6259, produced_by, 13337
8948, film_release_distribution_medium, 9103
8948, genre, 12590
12229, produced_by, 5930
12229, produced_by, 13337
9103, films, 9086
9103, films, 4071
9103, titles, 8428
9103, titles, 2463
9103, titles, 2967
9103, titles, 7518
9103, titles, 5405
9103, titles, 1702
9103, titles, 14197
9103, titles, 3649
9103, titles, 2094
9103, titles, 504
9103, titles, 497
9103, titles, 10160
9103, titles, 10370
9103, titles, 2197
9103, titles, 2498
9103, titles, 14071
9103, titles, 5152
9103, titles, 1946
9103, titles, 3685
9103, titles, 3052
9103, titles, 2603
9103, titles, 546
9103, titles, 7798
9103, titles, 6287
9103, titles, 6666
9103, titles, 9749
9103, titles, 205
9103, titles, 6712
9103, titles, 13924
5253, executive_produced_by, 5930
5253, executive_produced_by, 13337
13289, produced_by, 5930
13289, produced_by, 13337
2893, film_country, 6199
2893, film_release_region, 6199
2893, genre, 12590
8441, produced_by, 5930
8441, produced_by, 13337
6287, award_winner, 11584
7607, executive_produced_by, 5930
7607, executive_produced_by, 13337
9749, actor, 3560
9749, genre, 12590
4558, executive_produced_by, 5930
4558, executive_produced_by, 13337
13337, award, 13413
13337, award_nominee, 2089
13337, award_nominee, 3569
13337, award_nominee, 5930
13337, award_nominee, 13120
13337, award_nominee, 4988
13337, award_nominee, 2346
13337, award_nominee, 9350
13337, award_nominee, 6204
13337, award_winner, 5930
13337, award_winner, 6204
13337, company, 6204
13337, nominated_for, 14128
13337, nominated_for, 4439
13337, nominated_for, 3008
13337, nominated_for, 3998
13337, nominated_for, 9749
13337, nominated_for, 13016
13337, nominated_for, 12900
12409, film_release_distribution_medium, 9103
13016, award_winner, 5930
13016, award_winner, 13337
13016, produced_by, 13337
6735, award_winner, 13337
12900, produced_by, 5930
12900, produced_by, 13337
6204, award_nominee, 5930
6204, award_winner, 13337
Question: In what context are Kettering, Qingdao, and The_Tudors-GB connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Kettering",
"Qingdao",
"The_Tudors-GB"
],
"valid_edges": [
[
"13_Assassins",
"film_release_distribution_medium",
"Television"
],
[
"13_Assassins",
"genre",
"Historical_fiction"
],
[
"2012_British_Academy_Film_Awards",
"award_winner",
"Eric_Fellner"
],
[
"2012_British_Academy_Film_Awards",
"award_winner",
"Tim_Bevan"
],
[
"300",
"film_release_region",
"China"
],
[
"300",
"genre",
"Historical_fiction"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"David_Javerbaum"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"David_Miner"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Jeremy_Piven"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Jon_Stewart"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Lorne_Michaels"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Marci_Klein"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Matthew_Weiner"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Robert_Carlock"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Sheila_Nevins"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Tina_Fey"
],
[
"59th_Primetime_Emmy_Awards",
"award_winner",
"Trey_Parker"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"24"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"30_Rock"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"American_Idol"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"American_Masters"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Battlestar_Galactica-GB"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Brothers_&_Sisters"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Bury_My_Heart_at_Wounded_Knee"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"CSI:_Crime_Scene_Investigation"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Dexter"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Entourage"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Friday_Night_Lights"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"How_I_Met_Your_Mother"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Law_&_Order:_Special_Victims_Unit"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Monk"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Saturday_Night_Live"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"The_Daily_Show"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"The_Office"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"The_Tudors-GB"
],
[
"59th_Primetime_Emmy_Awards",
"honored_for",
"Ugly_Betty"
],
[
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"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Comedy_Series",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Comedy_Series",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Comedy_Series",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Comedy_Series",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Comedy_Series",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Comedy_Series",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Comedy_Series",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Comedy_Series",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Comedy_Series",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Drama_Series",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Drama_Series",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Drama_Series",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Variety_Series",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Variety_Series",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Variety_Series",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special",
"ceremony",
"59th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special",
"ceremony",
"60th_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Writing_-_Miniseries,_Movie_or_Dramatic_Special",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Quiz_Show",
"genre",
"Historical_fiction"
],
[
"Resident_Evil:_Retribution",
"genre",
"Historical_fiction"
],
[
"Richard_Curtis",
"award_nominee",
"Eric_Fellner"
],
[
"Richard_Curtis",
"award_nominee",
"Tim_Bevan"
],
[
"Robert_De_Niro",
"acted_in",
"Showtime"
],
[
"Robert_De_Niro",
"award_nominee",
"Eric_Fellner"
],
[
"Robert_De_Niro",
"award_nominee",
"Tim_Bevan"
],
[
"Robert_De_Niro",
"nominated_for",
"Showtime"
],
[
"Ron_Howard",
"award_nominee",
"Eric_Fellner"
],
[
"Senna",
"award_winner",
"Eric_Fellner"
],
[
"Senna",
"produced_by",
"Eric_Fellner"
],
[
"Senna",
"produced_by",
"Tim_Bevan"
],
[
"Shaun_of_the_Dead",
"executive_produced_by",
"Eric_Fellner"
],
[
"Shaun_of_the_Dead",
"executive_produced_by",
"Tim_Bevan"
],
[
"Showtime",
"nominated_for",
"Dexter"
],
[
"Showtime",
"nominated_for",
"The_Tudors-GB"
],
[
"Showtime",
"nominated_for",
"Weeds"
],
[
"Showtime",
"program",
"Dexter"
],
[
"Showtime",
"program",
"Nurse_Jackie"
],
[
"Showtime",
"program",
"The_Outer_Limits"
],
[
"Showtime",
"program",
"The_Tudors-GB"
],
[
"Showtime",
"program",
"Weeds"
],
[
"Showtime",
"titles",
"Dexter"
],
[
"Showtime",
"titles",
"Nurse_Jackie"
],
[
"Showtime",
"titles",
"The_Outer_Limits"
],
[
"Showtime",
"titles",
"The_Tudors-GB"
],
[
"Showtime",
"titles",
"Weeds"
],
[
"Sienna_Guillory",
"acted_in",
"Eragon"
],
[
"Sienna_Guillory",
"acted_in",
"Love_Actually"
],
[
"Sienna_Guillory",
"acted_in",
"Resident_Evil:_Retribution"
],
[
"Sienna_Guillory",
"award_nominee",
"Laura_Linney"
],
[
"Sienna_Guillory",
"location",
"Kettering"
],
[
"Sienna_Guillory",
"nominated_for",
"Love_Actually"
],
[
"Smokin'_Aces",
"produced_by",
"Eric_Fellner"
],
[
"Smokin'_Aces",
"produced_by",
"Tim_Bevan"
],
[
"Spartacus",
"film_release_distribution_medium",
"Television"
],
[
"Spartacus",
"genre",
"Historical_fiction"
],
[
"State_of_Play",
"produced_by",
"Eric_Fellner"
],
[
"State_of_Play",
"produced_by",
"Tim_Bevan"
],
[
"Television",
"films",
"Quiz_Show"
],
[
"Television",
"films",
"Showtime"
],
[
"Television",
"titles",
"24"
],
[
"Television",
"titles",
"30_Rock"
],
[
"Television",
"titles",
"Breaking_Bad"
],
[
"Television",
"titles",
"Brothers_&_Sisters"
],
[
"Television",
"titles",
"CSI:_Crime_Scene_Investigation"
],
[
"Television",
"titles",
"Chuck"
],
[
"Television",
"titles",
"Damages"
],
[
"Television",
"titles",
"Deadwood"
],
[
"Television",
"titles",
"Desperate_Housewives"
],
[
"Television",
"titles",
"Dexter"
],
[
"Television",
"titles",
"Entourage"
],
[
"Television",
"titles",
"Friday_Night_Lights"
],
[
"Television",
"titles",
"Heroes"
],
[
"Television",
"titles",
"House"
],
[
"Television",
"titles",
"How_I_Met_Your_Mother"
],
[
"Television",
"titles",
"Law_&_Order:_Special_Victims_Unit"
],
[
"Television",
"titles",
"Lost"
],
[
"Television",
"titles",
"Mad_Men"
],
[
"Television",
"titles",
"Monk"
],
[
"Television",
"titles",
"Nurse_Jackie"
],
[
"Television",
"titles",
"Pushing_Daisies"
],
[
"Television",
"titles",
"Saturday_Night_Live"
],
[
"Television",
"titles",
"Smallville"
],
[
"Television",
"titles",
"The_Office"
],
[
"Television",
"titles",
"The_Outer_Limits"
],
[
"Television",
"titles",
"The_Tudors-GB"
],
[
"Television",
"titles",
"True_Blood"
],
[
"Television",
"titles",
"Ugly_Betty"
],
[
"Television",
"titles",
"Weeds"
],
[
"The_Big_Lebowski",
"executive_produced_by",
"Eric_Fellner"
],
[
"The_Big_Lebowski",
"executive_produced_by",
"Tim_Bevan"
],
[
"The_Boat_That_Rocked",
"produced_by",
"Eric_Fellner"
],
[
"The_Boat_That_Rocked",
"produced_by",
"Tim_Bevan"
],
[
"The_Flowers_of_War",
"film_country",
"China"
],
[
"The_Flowers_of_War",
"film_release_region",
"China"
],
[
"The_Flowers_of_War",
"genre",
"Historical_fiction"
],
[
"The_Interpreter",
"produced_by",
"Eric_Fellner"
],
[
"The_Interpreter",
"produced_by",
"Tim_Bevan"
],
[
"The_Office",
"award_winner",
"Ben_Silverman"
],
[
"The_Soloist",
"executive_produced_by",
"Eric_Fellner"
],
[
"The_Soloist",
"executive_produced_by",
"Tim_Bevan"
],
[
"The_Tudors-GB",
"actor",
"Joss_Stone"
],
[
"The_Tudors-GB",
"genre",
"Historical_fiction"
],
[
"Thirteen",
"executive_produced_by",
"Eric_Fellner"
],
[
"Thirteen",
"executive_produced_by",
"Tim_Bevan"
],
[
"Tim_Bevan",
"award",
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture"
],
[
"Tim_Bevan",
"award_nominee",
"Brian_Grazer"
],
[
"Tim_Bevan",
"award_nominee",
"Christopher_Hampton"
],
[
"Tim_Bevan",
"award_nominee",
"Eric_Fellner"
],
[
"Tim_Bevan",
"award_nominee",
"Richard_Curtis"
],
[
"Tim_Bevan",
"award_nominee",
"Robert_De_Niro"
],
[
"Tim_Bevan",
"award_nominee",
"Ron_Howard"
],
[
"Tim_Bevan",
"award_nominee",
"Tom_Stoppard"
],
[
"Tim_Bevan",
"award_nominee",
"Working_Title_Films"
],
[
"Tim_Bevan",
"award_winner",
"Eric_Fellner"
],
[
"Tim_Bevan",
"award_winner",
"Working_Title_Films"
],
[
"Tim_Bevan",
"company",
"Working_Title_Films"
],
[
"Tim_Bevan",
"nominated_for",
"Atonement"
],
[
"Tim_Bevan",
"nominated_for",
"Bridget_Jones's_Diary"
],
[
"Tim_Bevan",
"nominated_for",
"Frost/Nixon"
],
[
"Tim_Bevan",
"nominated_for",
"Pride_&_Prejudice"
],
[
"Tim_Bevan",
"nominated_for",
"The_Tudors-GB"
],
[
"Tim_Bevan",
"nominated_for",
"Tinker,_Tailor,_Soldier,_Spy"
],
[
"Tim_Bevan",
"nominated_for",
"United_93"
],
[
"Tin_Man",
"film_release_distribution_medium",
"Television"
],
[
"Tinker,_Tailor,_Soldier,_Spy",
"award_winner",
"Eric_Fellner"
],
[
"Tinker,_Tailor,_Soldier,_Spy",
"award_winner",
"Tim_Bevan"
],
[
"Tinker,_Tailor,_Soldier,_Spy",
"produced_by",
"Tim_Bevan"
],
[
"Tony_Award_for_Best_Musical",
"award_winner",
"Tim_Bevan"
],
[
"United_93",
"produced_by",
"Eric_Fellner"
],
[
"United_93",
"produced_by",
"Tim_Bevan"
],
[
"Working_Title_Films",
"award_nominee",
"Eric_Fellner"
],
[
"Working_Title_Films",
"award_winner",
"Tim_Bevan"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
172, Animaniacs
3756, Animated_cartoon
5423, Artie_Lange
744, Batman:_The_Animated_Series
8381, Batman_Beyond
3301, Cartoon
6297, Freakazoid!
6676, George_Takei
4320, Justice_League
8650, King_of_the_Hill
7654, Ludacris
8170, Radio_personality-GB
12470, Rango
13422, Star_Trek:_The_Animated_Series
414, Stephen_Root
6802, The_Fairly_OddParents
12561, Tiny_Toon_Adventures
src, edge_attr, dst
172, genre, 3756
5423, participant, 6676
5423, profession, 8170
744, genre, 3756
8381, genre, 3756
3301, titles, 172
3301, titles, 744
3301, titles, 8381
3301, titles, 6297
3301, titles, 4320
3301, titles, 13422
3301, titles, 6802
3301, titles, 12561
6297, genre, 3756
6676, participant, 5423
4320, genre, 3756
8650, actor, 414
8650, genre, 3756
8650, genre, 3301
7654, profession, 8170
13422, actor, 6676
13422, genre, 3756
414, acted_in, 12470
6802, genre, 3756
12561, genre, 3756
Question: How are Ludacris, Rango, and Star_Trek:_The_Animated_Series related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Ludacris",
"Rango",
"Star_Trek:_The_Animated_Series"
],
"valid_edges": [
[
"Animaniacs",
"genre",
"Animated_cartoon"
],
[
"Artie_Lange",
"participant",
"George_Takei"
],
[
"Artie_Lange",
"profession",
"Radio_personality-GB"
],
[
"Batman:_The_Animated_Series",
"genre",
"Animated_cartoon"
],
[
"Batman_Beyond",
"genre",
"Animated_cartoon"
],
[
"Cartoon",
"titles",
"Animaniacs"
],
[
"Cartoon",
"titles",
"Batman:_The_Animated_Series"
],
[
"Cartoon",
"titles",
"Batman_Beyond"
],
[
"Cartoon",
"titles",
"Freakazoid!"
],
[
"Cartoon",
"titles",
"Justice_League"
],
[
"Cartoon",
"titles",
"Star_Trek:_The_Animated_Series"
],
[
"Cartoon",
"titles",
"The_Fairly_OddParents"
],
[
"Cartoon",
"titles",
"Tiny_Toon_Adventures"
],
[
"Freakazoid!",
"genre",
"Animated_cartoon"
],
[
"George_Takei",
"participant",
"Artie_Lange"
],
[
"Justice_League",
"genre",
"Animated_cartoon"
],
[
"King_of_the_Hill",
"actor",
"Stephen_Root"
],
[
"King_of_the_Hill",
"genre",
"Animated_cartoon"
],
[
"King_of_the_Hill",
"genre",
"Cartoon"
],
[
"Ludacris",
"profession",
"Radio_personality-GB"
],
[
"Star_Trek:_The_Animated_Series",
"actor",
"George_Takei"
],
[
"Star_Trek:_The_Animated_Series",
"genre",
"Animated_cartoon"
],
[
"Stephen_Root",
"acted_in",
"Rango"
],
[
"The_Fairly_OddParents",
"genre",
"Animated_cartoon"
],
[
"Tiny_Toon_Adventures",
"genre",
"Animated_cartoon"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1435, Berkshire
2384, Cancer
1529, Carl_Sagan
13933, Dan_Stevens
4199, Dance_music
9812, Donna_Summer
1200, Douglas_Adams
12028, Dr._Dre
13995, Emmanuel_College,_Cambridge
10901, Eric_Idle
7988, Graham_Chapman
13478, Hugo_Award_for_Best_Dramatic_Presentation
317, Jim_Jonsin
6367, John_Cleese
11609, Law_degree
1804, Major_depression
12291, Master
6897, Missy_Elliott
9310, Philip_K._Dick
11846, Reading
4113, Robert_Morley
12021, Sam_Mendes
5137, Stroke
2301, Terry_Gilliam
6357, The_Neptunes
7144, Tobacco_smoking
6240, University_of_Cambridge
9421, Wellington_College,_Berkshire
src, edge_attr, dst
1435, contains, 11846
2384, people, 1529
2384, people, 9812
2384, people, 7988
2384, risk_factors, 7144
1529, award, 13478
4199, artists, 9812
4199, artists, 317
4199, artists, 6897
4199, artists, 6357
1200, award, 13478
12028, award_nominee, 317
12028, award_nominee, 6897
13995, educational_institution, 13995
13995, student, 13933
13995, student, 7988
10901, award, 13478
10901, award_nominee, 7988
10901, award_nominee, 6367
10901, award_nominee, 2301
7988, award, 13478
7988, award_nominee, 10901
7988, award_nominee, 6367
7988, award_nominee, 2301
13478, award_winner, 1529
317, award_nominee, 12028
6367, award, 13478
6367, award_nominee, 10901
6367, award_nominee, 7988
6367, award_nominee, 2301
11609, institution, 6240
11609, student, 6367
1804, risk_factors, 2384
1804, risk_factors, 5137
12291, organization, 13995
12291, organization, 9421
6897, award_nominee, 12028
11846, administrative_parent, 1435
11846, place, 11846
11846, state, 1435
4113, place_of_death, 11846
12021, location, 11846
12021, place_of_birth, 11846
5137, people, 9310
5137, people, 4113
5137, risk_factors, 7144
2301, award, 13478
2301, award_nominee, 6367
2301, influenced_by, 9310
6357, award_nominee, 12028
6240, educational_institution, 6240
6240, student, 13933
6240, student, 1200
6240, student, 10901
6240, student, 7988
6240, student, 6367
6240, student, 12021
9421, campuses, 9421
9421, state_province_region, 1435
9421, student, 4113
Question: In what context are Graham_Chapman, Jim_Jonsin, and Robert_Morley connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Graham_Chapman",
"Jim_Jonsin",
"Robert_Morley"
],
"valid_edges": [
[
"Berkshire",
"contains",
"Reading"
],
[
"Cancer",
"people",
"Carl_Sagan"
],
[
"Cancer",
"people",
"Donna_Summer"
],
[
"Cancer",
"people",
"Graham_Chapman"
],
[
"Cancer",
"risk_factors",
"Tobacco_smoking"
],
[
"Carl_Sagan",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Dance_music",
"artists",
"Donna_Summer"
],
[
"Dance_music",
"artists",
"Jim_Jonsin"
],
[
"Dance_music",
"artists",
"Missy_Elliott"
],
[
"Dance_music",
"artists",
"The_Neptunes"
],
[
"Douglas_Adams",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Dr._Dre",
"award_nominee",
"Jim_Jonsin"
],
[
"Dr._Dre",
"award_nominee",
"Missy_Elliott"
],
[
"Emmanuel_College,_Cambridge",
"educational_institution",
"Emmanuel_College,_Cambridge"
],
[
"Emmanuel_College,_Cambridge",
"student",
"Dan_Stevens"
],
[
"Emmanuel_College,_Cambridge",
"student",
"Graham_Chapman"
],
[
"Eric_Idle",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Eric_Idle",
"award_nominee",
"Graham_Chapman"
],
[
"Eric_Idle",
"award_nominee",
"John_Cleese"
],
[
"Eric_Idle",
"award_nominee",
"Terry_Gilliam"
],
[
"Graham_Chapman",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Graham_Chapman",
"award_nominee",
"Eric_Idle"
],
[
"Graham_Chapman",
"award_nominee",
"John_Cleese"
],
[
"Graham_Chapman",
"award_nominee",
"Terry_Gilliam"
],
[
"Hugo_Award_for_Best_Dramatic_Presentation",
"award_winner",
"Carl_Sagan"
],
[
"Jim_Jonsin",
"award_nominee",
"Dr._Dre"
],
[
"John_Cleese",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"John_Cleese",
"award_nominee",
"Eric_Idle"
],
[
"John_Cleese",
"award_nominee",
"Graham_Chapman"
],
[
"John_Cleese",
"award_nominee",
"Terry_Gilliam"
],
[
"Law_degree",
"institution",
"University_of_Cambridge"
],
[
"Law_degree",
"student",
"John_Cleese"
],
[
"Major_depression",
"risk_factors",
"Cancer"
],
[
"Major_depression",
"risk_factors",
"Stroke"
],
[
"Master",
"organization",
"Emmanuel_College,_Cambridge"
],
[
"Master",
"organization",
"Wellington_College,_Berkshire"
],
[
"Missy_Elliott",
"award_nominee",
"Dr._Dre"
],
[
"Reading",
"administrative_parent",
"Berkshire"
],
[
"Reading",
"place",
"Reading"
],
[
"Reading",
"state",
"Berkshire"
],
[
"Robert_Morley",
"place_of_death",
"Reading"
],
[
"Sam_Mendes",
"location",
"Reading"
],
[
"Sam_Mendes",
"place_of_birth",
"Reading"
],
[
"Stroke",
"people",
"Philip_K._Dick"
],
[
"Stroke",
"people",
"Robert_Morley"
],
[
"Stroke",
"risk_factors",
"Tobacco_smoking"
],
[
"Terry_Gilliam",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Terry_Gilliam",
"award_nominee",
"John_Cleese"
],
[
"Terry_Gilliam",
"influenced_by",
"Philip_K._Dick"
],
[
"The_Neptunes",
"award_nominee",
"Dr._Dre"
],
[
"University_of_Cambridge",
"educational_institution",
"University_of_Cambridge"
],
[
"University_of_Cambridge",
"student",
"Dan_Stevens"
],
[
"University_of_Cambridge",
"student",
"Douglas_Adams"
],
[
"University_of_Cambridge",
"student",
"Eric_Idle"
],
[
"University_of_Cambridge",
"student",
"Graham_Chapman"
],
[
"University_of_Cambridge",
"student",
"John_Cleese"
],
[
"University_of_Cambridge",
"student",
"Sam_Mendes"
],
[
"Wellington_College,_Berkshire",
"campuses",
"Wellington_College,_Berkshire"
],
[
"Wellington_College,_Berkshire",
"state_province_region",
"Berkshire"
],
[
"Wellington_College,_Berkshire",
"student",
"Robert_Morley"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
10275, 75th_Academy_Awards
4123, 9th_Golden_Satellite_Awards
6331, Anthony_Adverse
7235, Black-and-white
2139, Eminem
11433, Gena_Rowlands
1298, La_Dolce_Vita
2279, Talk_to_Her
src, edge_attr, dst
10275, award_winner, 2139
10275, honored_for, 2279
4123, award_winner, 11433
4123, honored_for, 1298
6331, genre, 7235
1298, genre, 7235
2279, genre, 7235
Question: For what reason are Anthony_Adverse, Eminem, and Gena_Rowlands associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Anthony_Adverse",
"Eminem",
"Gena_Rowlands"
],
"valid_edges": [
[
"75th_Academy_Awards",
"award_winner",
"Eminem"
],
[
"75th_Academy_Awards",
"honored_for",
"Talk_to_Her"
],
[
"9th_Golden_Satellite_Awards",
"award_winner",
"Gena_Rowlands"
],
[
"9th_Golden_Satellite_Awards",
"honored_for",
"La_Dolce_Vita"
],
[
"Anthony_Adverse",
"genre",
"Black-and-white"
],
[
"La_Dolce_Vita",
"genre",
"Black-and-white"
],
[
"Talk_to_Her",
"genre",
"Black-and-white"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
8374, 2012_Sundance_Film_Festival
800, Alanine
8278, Alpha-Tocopherol
9303, Arginine
1490, Ash
7210, Aspartic_acid
2426, Avocado
10495, Beasts_of_the_Southern_Wild
3573, Beta-carotene
838, Betaine
7465, Broccoli
9206, Cabbage
8833, Calcium
2953, Capsicum
5891, Carbohydrate
3735, Carrot
5662, Chicken_meat
384, Choline
2730, Copper
2803, Cryptoxanthin
6657, Cystine
3951, D-Glucose
11892, Dietary_fiber
11093, Fluoride
7613, Fructose
6175, Glutamic_acid
1069, Glycine
7643, Histidine
1584, Iron
5396, Isoleucine
8809, Leucine
5472, Linoleic_acid
11767, Lipid
3719, Lysine
3864, Magnesium
1867, Manganese
2494, Methionine
6449, Milk
7987, Monounsaturated_fat
8465, Myristic_acid
12981, Niacin
10861, Oleic_acid
11936, Palmitic_acid
8578, Palmitoleic_acid
9120, Pantothenic_acid
10992, Phenylalanine
6197, Phosphorus
13486, Phytonadione
5951, Polyunsaturated_fat
11626, Potassium
13413, Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture
1990, Proline
467, Protein
12265, Riboflavin
6081, Saturated_fat
11507, Sean_Penn
6492, Selenium
14207, Serine
5757, Sodium
2341, Stearic_acid
2641, Sugar
8056, Table_sugar
2650, Thiamine
13846, This_Must_Be_the_Place
12734, Threonine
8836, Tryptophan
598, Tyrosine
10056, Valine
4258, Vitamin_A
11857, Vitamin_B-6
335, Vitamin_C
11776, Water
11772, Zinc
8673, alpha-Carotene
5165, gamma-Tocopherol
src, edge_attr, dst
2426, food_nutrient, 800
2426, food_nutrient, 8278
2426, food_nutrient, 9303
2426, food_nutrient, 1490
2426, food_nutrient, 7210
2426, food_nutrient, 3573
2426, food_nutrient, 838
2426, food_nutrient, 8833
2426, food_nutrient, 5891
2426, food_nutrient, 384
2426, food_nutrient, 2730
2426, food_nutrient, 2803
2426, food_nutrient, 6657
2426, food_nutrient, 3951
2426, food_nutrient, 11892
2426, food_nutrient, 11093
2426, food_nutrient, 7613
2426, food_nutrient, 6175
2426, food_nutrient, 1069
2426, food_nutrient, 7643
2426, food_nutrient, 1584
2426, food_nutrient, 5396
2426, food_nutrient, 8809
2426, food_nutrient, 5472
2426, food_nutrient, 11767
2426, food_nutrient, 3719
2426, food_nutrient, 3864
2426, food_nutrient, 1867
2426, food_nutrient, 2494
2426, food_nutrient, 7987
2426, food_nutrient, 12981
2426, food_nutrient, 10861
2426, food_nutrient, 11936
2426, food_nutrient, 8578
2426, food_nutrient, 9120
2426, food_nutrient, 10992
2426, food_nutrient, 6197
2426, food_nutrient, 13486
2426, food_nutrient, 5951
2426, food_nutrient, 11626
2426, food_nutrient, 1990
2426, food_nutrient, 467
2426, food_nutrient, 12265
2426, food_nutrient, 6081
2426, food_nutrient, 6492
2426, food_nutrient, 14207
2426, food_nutrient, 5757
2426, food_nutrient, 2341
2426, food_nutrient, 2641
2426, food_nutrient, 8056
2426, food_nutrient, 2650
2426, food_nutrient, 12734
2426, food_nutrient, 8836
2426, food_nutrient, 598
2426, food_nutrient, 10056
2426, food_nutrient, 4258
2426, food_nutrient, 11857
2426, food_nutrient, 335
2426, food_nutrient, 11776
2426, food_nutrient, 11772
2426, food_nutrient, 8673
2426, food_nutrient, 5165
10495, film_festivals, 8374
10495, film_regional_debut_venue, 8374
7465, food_nutrient, 800
7465, food_nutrient, 8278
7465, food_nutrient, 9303
7465, food_nutrient, 1490
7465, food_nutrient, 7210
7465, food_nutrient, 3573
7465, food_nutrient, 838
7465, food_nutrient, 8833
7465, food_nutrient, 5891
7465, food_nutrient, 384
7465, food_nutrient, 2730
7465, food_nutrient, 2803
7465, food_nutrient, 6657
7465, food_nutrient, 3951
7465, food_nutrient, 11892
7465, food_nutrient, 7613
7465, food_nutrient, 6175
7465, food_nutrient, 1069
7465, food_nutrient, 7643
7465, food_nutrient, 1584
7465, food_nutrient, 5396
7465, food_nutrient, 8809
7465, food_nutrient, 5472
7465, food_nutrient, 11767
7465, food_nutrient, 3719
7465, food_nutrient, 3864
7465, food_nutrient, 1867
7465, food_nutrient, 2494
7465, food_nutrient, 7987
7465, food_nutrient, 8465
7465, food_nutrient, 12981
7465, food_nutrient, 10861
7465, food_nutrient, 11936
7465, food_nutrient, 9120
7465, food_nutrient, 10992
7465, food_nutrient, 6197
7465, food_nutrient, 13486
7465, food_nutrient, 5951
7465, food_nutrient, 11626
7465, food_nutrient, 1990
7465, food_nutrient, 467
7465, food_nutrient, 12265
7465, food_nutrient, 6081
7465, food_nutrient, 6492
7465, food_nutrient, 14207
7465, food_nutrient, 5757
7465, food_nutrient, 2341
7465, food_nutrient, 2641
7465, food_nutrient, 8056
7465, food_nutrient, 2650
7465, food_nutrient, 12734
7465, food_nutrient, 8836
7465, food_nutrient, 598
7465, food_nutrient, 10056
7465, food_nutrient, 4258
7465, food_nutrient, 11857
7465, food_nutrient, 335
7465, food_nutrient, 11776
7465, food_nutrient, 11772
7465, food_nutrient, 8673
7465, food_nutrient, 5165
9206, food_nutrient, 800
9206, food_nutrient, 8278
9206, food_nutrient, 9303
9206, food_nutrient, 1490
9206, food_nutrient, 7210
9206, food_nutrient, 3573
9206, food_nutrient, 838
9206, food_nutrient, 8833
9206, food_nutrient, 5891
9206, food_nutrient, 384
9206, food_nutrient, 2730
9206, food_nutrient, 6657
9206, food_nutrient, 3951
9206, food_nutrient, 11892
9206, food_nutrient, 11093
9206, food_nutrient, 7613
9206, food_nutrient, 6175
9206, food_nutrient, 1069
9206, food_nutrient, 7643
9206, food_nutrient, 1584
9206, food_nutrient, 5396
9206, food_nutrient, 8809
9206, food_nutrient, 5472
9206, food_nutrient, 11767
9206, food_nutrient, 3719
9206, food_nutrient, 3864
9206, food_nutrient, 1867
9206, food_nutrient, 2494
9206, food_nutrient, 7987
9206, food_nutrient, 12981
9206, food_nutrient, 10861
9206, food_nutrient, 11936
9206, food_nutrient, 9120
9206, food_nutrient, 10992
9206, food_nutrient, 6197
9206, food_nutrient, 13486
9206, food_nutrient, 5951
9206, food_nutrient, 11626
9206, food_nutrient, 1990
9206, food_nutrient, 467
9206, food_nutrient, 12265
9206, food_nutrient, 6081
9206, food_nutrient, 6492
9206, food_nutrient, 14207
9206, food_nutrient, 5757
9206, food_nutrient, 2641
9206, food_nutrient, 8056
9206, food_nutrient, 2650
9206, food_nutrient, 12734
9206, food_nutrient, 8836
9206, food_nutrient, 598
9206, food_nutrient, 10056
9206, food_nutrient, 4258
9206, food_nutrient, 11857
9206, food_nutrient, 335
9206, food_nutrient, 11776
9206, food_nutrient, 11772
9206, food_nutrient, 8673
2953, food_nutrient, 800
2953, food_nutrient, 8278
2953, food_nutrient, 9303
2953, food_nutrient, 1490
2953, food_nutrient, 7210
2953, food_nutrient, 3573
2953, food_nutrient, 838
2953, food_nutrient, 8833
2953, food_nutrient, 5891
2953, food_nutrient, 384
2953, food_nutrient, 2730
2953, food_nutrient, 2803
2953, food_nutrient, 6657
2953, food_nutrient, 3951
2953, food_nutrient, 11892
2953, food_nutrient, 7613
2953, food_nutrient, 6175
2953, food_nutrient, 1069
2953, food_nutrient, 7643
2953, food_nutrient, 1584
2953, food_nutrient, 5396
2953, food_nutrient, 8809
2953, food_nutrient, 5472
2953, food_nutrient, 11767
2953, food_nutrient, 3719
2953, food_nutrient, 3864
2953, food_nutrient, 1867
2953, food_nutrient, 2494
2953, food_nutrient, 7987
2953, food_nutrient, 12981
2953, food_nutrient, 10861
2953, food_nutrient, 11936
2953, food_nutrient, 8578
2953, food_nutrient, 9120
2953, food_nutrient, 10992
2953, food_nutrient, 6197
2953, food_nutrient, 13486
2953, food_nutrient, 5951
2953, food_nutrient, 11626
2953, food_nutrient, 1990
2953, food_nutrient, 467
2953, food_nutrient, 12265
2953, food_nutrient, 6081
2953, food_nutrient, 6492
2953, food_nutrient, 14207
2953, food_nutrient, 5757
2953, food_nutrient, 2341
2953, food_nutrient, 2641
2953, food_nutrient, 2650
2953, food_nutrient, 12734
2953, food_nutrient, 8836
2953, food_nutrient, 598
2953, food_nutrient, 10056
2953, food_nutrient, 4258
2953, food_nutrient, 11857
2953, food_nutrient, 335
2953, food_nutrient, 11776
2953, food_nutrient, 11772
2953, food_nutrient, 8673
2953, food_nutrient, 5165
3735, food_nutrient, 800
3735, food_nutrient, 8278
3735, food_nutrient, 9303
3735, food_nutrient, 1490
3735, food_nutrient, 7210
3735, food_nutrient, 3573
3735, food_nutrient, 838
3735, food_nutrient, 8833
3735, food_nutrient, 5891
3735, food_nutrient, 384
3735, food_nutrient, 2730
3735, food_nutrient, 6657
3735, food_nutrient, 3951
3735, food_nutrient, 11892
3735, food_nutrient, 11093
3735, food_nutrient, 7613
3735, food_nutrient, 6175
3735, food_nutrient, 1069
3735, food_nutrient, 7643
3735, food_nutrient, 1584
3735, food_nutrient, 5396
3735, food_nutrient, 8809
3735, food_nutrient, 5472
3735, food_nutrient, 11767
3735, food_nutrient, 3719
3735, food_nutrient, 3864
3735, food_nutrient, 1867
3735, food_nutrient, 2494
3735, food_nutrient, 7987
3735, food_nutrient, 12981
3735, food_nutrient, 10861
3735, food_nutrient, 11936
3735, food_nutrient, 8578
3735, food_nutrient, 9120
3735, food_nutrient, 10992
3735, food_nutrient, 6197
3735, food_nutrient, 13486
3735, food_nutrient, 5951
3735, food_nutrient, 11626
3735, food_nutrient, 1990
3735, food_nutrient, 467
3735, food_nutrient, 12265
3735, food_nutrient, 6081
3735, food_nutrient, 6492
3735, food_nutrient, 14207
3735, food_nutrient, 5757
3735, food_nutrient, 2341
3735, food_nutrient, 2641
3735, food_nutrient, 8056
3735, food_nutrient, 2650
3735, food_nutrient, 12734
3735, food_nutrient, 8836
3735, food_nutrient, 598
3735, food_nutrient, 10056
3735, food_nutrient, 4258
3735, food_nutrient, 11857
3735, food_nutrient, 335
3735, food_nutrient, 11776
3735, food_nutrient, 11772
3735, food_nutrient, 8673
5662, food_nutrient, 800
5662, food_nutrient, 8278
5662, food_nutrient, 9303
5662, food_nutrient, 1490
5662, food_nutrient, 7210
5662, food_nutrient, 838
5662, food_nutrient, 8833
5662, food_nutrient, 384
5662, food_nutrient, 2730
5662, food_nutrient, 6657
5662, food_nutrient, 6175
5662, food_nutrient, 1069
5662, food_nutrient, 7643
5662, food_nutrient, 1584
5662, food_nutrient, 5396
5662, food_nutrient, 8809
5662, food_nutrient, 5472
5662, food_nutrient, 11767
5662, food_nutrient, 3719
5662, food_nutrient, 3864
5662, food_nutrient, 1867
5662, food_nutrient, 2494
5662, food_nutrient, 7987
5662, food_nutrient, 8465
5662, food_nutrient, 12981
5662, food_nutrient, 10861
5662, food_nutrient, 11936
5662, food_nutrient, 8578
5662, food_nutrient, 9120
5662, food_nutrient, 10992
5662, food_nutrient, 6197
5662, food_nutrient, 13486
5662, food_nutrient, 5951
5662, food_nutrient, 11626
5662, food_nutrient, 1990
5662, food_nutrient, 467
5662, food_nutrient, 12265
5662, food_nutrient, 6081
5662, food_nutrient, 6492
5662, food_nutrient, 14207
5662, food_nutrient, 5757
5662, food_nutrient, 2341
5662, food_nutrient, 2650
5662, food_nutrient, 12734
5662, food_nutrient, 8836
5662, food_nutrient, 598
5662, food_nutrient, 10056
5662, food_nutrient, 4258
5662, food_nutrient, 11857
5662, food_nutrient, 335
5662, food_nutrient, 11776
5662, food_nutrient, 11772
6449, award_winner, 11507
6449, food_nutrient, 800
6449, food_nutrient, 8278
6449, food_nutrient, 9303
6449, food_nutrient, 1490
6449, food_nutrient, 7210
6449, food_nutrient, 3573
6449, food_nutrient, 838
6449, food_nutrient, 8833
6449, food_nutrient, 5891
6449, food_nutrient, 384
6449, food_nutrient, 2730
6449, food_nutrient, 6657
6449, food_nutrient, 6175
6449, food_nutrient, 1069
6449, food_nutrient, 7643
6449, food_nutrient, 1584
6449, food_nutrient, 5396
6449, food_nutrient, 8809
6449, food_nutrient, 5472
6449, food_nutrient, 11767
6449, food_nutrient, 3719
6449, food_nutrient, 3864
6449, food_nutrient, 1867
6449, food_nutrient, 2494
6449, food_nutrient, 7987
6449, food_nutrient, 8465
6449, food_nutrient, 12981
6449, food_nutrient, 10861
6449, food_nutrient, 11936
6449, food_nutrient, 9120
6449, food_nutrient, 10992
6449, food_nutrient, 6197
6449, food_nutrient, 13486
6449, food_nutrient, 5951
6449, food_nutrient, 11626
6449, food_nutrient, 1990
6449, food_nutrient, 467
6449, food_nutrient, 12265
6449, food_nutrient, 6081
6449, food_nutrient, 6492
6449, food_nutrient, 14207
6449, food_nutrient, 5757
6449, food_nutrient, 2341
6449, food_nutrient, 2641
6449, food_nutrient, 2650
6449, food_nutrient, 12734
6449, food_nutrient, 8836
6449, food_nutrient, 598
6449, food_nutrient, 10056
6449, food_nutrient, 4258
6449, food_nutrient, 11857
6449, food_nutrient, 11776
6449, food_nutrient, 11772
6449, food_nutrient, 5165
13413, nominated_for, 10495
13413, nominated_for, 6449
11507, acted_in, 6449
11507, acted_in, 13846
11507, nominated_for, 6449
13846, film_festivals, 8374
Question: For what reason are 2012_Sundance_Film_Festival, Glycine, and Vitamin_C associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"2012_Sundance_Film_Festival",
"Glycine",
"Vitamin_C"
],
"valid_edges": [
[
"Avocado",
"food_nutrient",
"Alanine"
],
[
"Avocado",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Avocado",
"food_nutrient",
"Arginine"
],
[
"Avocado",
"food_nutrient",
"Ash"
],
[
"Avocado",
"food_nutrient",
"Aspartic_acid"
],
[
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"food_nutrient",
"Beta-carotene"
],
[
"Avocado",
"food_nutrient",
"Betaine"
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[
"Avocado",
"food_nutrient",
"Calcium"
],
[
"Avocado",
"food_nutrient",
"Carbohydrate"
],
[
"Avocado",
"food_nutrient",
"Choline"
],
[
"Avocado",
"food_nutrient",
"Copper"
],
[
"Avocado",
"food_nutrient",
"Cryptoxanthin"
],
[
"Avocado",
"food_nutrient",
"Cystine"
],
[
"Avocado",
"food_nutrient",
"D-Glucose"
],
[
"Avocado",
"food_nutrient",
"Dietary_fiber"
],
[
"Avocado",
"food_nutrient",
"Fluoride"
],
[
"Avocado",
"food_nutrient",
"Fructose"
],
[
"Avocado",
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"Glutamic_acid"
],
[
"Avocado",
"food_nutrient",
"Glycine"
],
[
"Avocado",
"food_nutrient",
"Histidine"
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[
"Avocado",
"food_nutrient",
"Iron"
],
[
"Avocado",
"food_nutrient",
"Isoleucine"
],
[
"Avocado",
"food_nutrient",
"Leucine"
],
[
"Avocado",
"food_nutrient",
"Linoleic_acid"
],
[
"Avocado",
"food_nutrient",
"Lipid"
],
[
"Avocado",
"food_nutrient",
"Lysine"
],
[
"Avocado",
"food_nutrient",
"Magnesium"
],
[
"Avocado",
"food_nutrient",
"Manganese"
],
[
"Avocado",
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"Methionine"
],
[
"Avocado",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Avocado",
"food_nutrient",
"Niacin"
],
[
"Avocado",
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"Oleic_acid"
],
[
"Avocado",
"food_nutrient",
"Palmitic_acid"
],
[
"Avocado",
"food_nutrient",
"Palmitoleic_acid"
],
[
"Avocado",
"food_nutrient",
"Pantothenic_acid"
],
[
"Avocado",
"food_nutrient",
"Phenylalanine"
],
[
"Avocado",
"food_nutrient",
"Phosphorus"
],
[
"Avocado",
"food_nutrient",
"Phytonadione"
],
[
"Avocado",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Avocado",
"food_nutrient",
"Potassium"
],
[
"Avocado",
"food_nutrient",
"Proline"
],
[
"Avocado",
"food_nutrient",
"Protein"
],
[
"Avocado",
"food_nutrient",
"Riboflavin"
],
[
"Avocado",
"food_nutrient",
"Saturated_fat"
],
[
"Avocado",
"food_nutrient",
"Selenium"
],
[
"Avocado",
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"Serine"
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[
"Avocado",
"food_nutrient",
"Sodium"
],
[
"Avocado",
"food_nutrient",
"Stearic_acid"
],
[
"Avocado",
"food_nutrient",
"Sugar"
],
[
"Avocado",
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"Table_sugar"
],
[
"Avocado",
"food_nutrient",
"Thiamine"
],
[
"Avocado",
"food_nutrient",
"Threonine"
],
[
"Avocado",
"food_nutrient",
"Tryptophan"
],
[
"Avocado",
"food_nutrient",
"Tyrosine"
],
[
"Avocado",
"food_nutrient",
"Valine"
],
[
"Avocado",
"food_nutrient",
"Vitamin_A"
],
[
"Avocado",
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"Vitamin_B-6"
],
[
"Avocado",
"food_nutrient",
"Vitamin_C"
],
[
"Avocado",
"food_nutrient",
"Water"
],
[
"Avocado",
"food_nutrient",
"Zinc"
],
[
"Avocado",
"food_nutrient",
"alpha-Carotene"
],
[
"Avocado",
"food_nutrient",
"gamma-Tocopherol"
],
[
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"film_festivals",
"2012_Sundance_Film_Festival"
],
[
"Beasts_of_the_Southern_Wild",
"film_regional_debut_venue",
"2012_Sundance_Film_Festival"
],
[
"Broccoli",
"food_nutrient",
"Alanine"
],
[
"Broccoli",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Broccoli",
"food_nutrient",
"Arginine"
],
[
"Broccoli",
"food_nutrient",
"Ash"
],
[
"Broccoli",
"food_nutrient",
"Aspartic_acid"
],
[
"Broccoli",
"food_nutrient",
"Beta-carotene"
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[
"Broccoli",
"food_nutrient",
"Betaine"
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[
"Broccoli",
"food_nutrient",
"Calcium"
],
[
"Broccoli",
"food_nutrient",
"Carbohydrate"
],
[
"Broccoli",
"food_nutrient",
"Choline"
],
[
"Broccoli",
"food_nutrient",
"Copper"
],
[
"Broccoli",
"food_nutrient",
"Cryptoxanthin"
],
[
"Broccoli",
"food_nutrient",
"Cystine"
],
[
"Broccoli",
"food_nutrient",
"D-Glucose"
],
[
"Broccoli",
"food_nutrient",
"Dietary_fiber"
],
[
"Broccoli",
"food_nutrient",
"Fructose"
],
[
"Broccoli",
"food_nutrient",
"Glutamic_acid"
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[
"Broccoli",
"food_nutrient",
"Glycine"
],
[
"Broccoli",
"food_nutrient",
"Histidine"
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[
"Broccoli",
"food_nutrient",
"Iron"
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[
"Broccoli",
"food_nutrient",
"Isoleucine"
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[
"Broccoli",
"food_nutrient",
"Leucine"
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"Broccoli",
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"Linoleic_acid"
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"Broccoli",
"food_nutrient",
"Lipid"
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[
"Broccoli",
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"Lysine"
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"Broccoli",
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"Magnesium"
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[
"Broccoli",
"food_nutrient",
"Manganese"
],
[
"Broccoli",
"food_nutrient",
"Methionine"
],
[
"Broccoli",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Broccoli",
"food_nutrient",
"Myristic_acid"
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[
"Broccoli",
"food_nutrient",
"Niacin"
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[
"Broccoli",
"food_nutrient",
"Oleic_acid"
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[
"Broccoli",
"food_nutrient",
"Palmitic_acid"
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[
"Broccoli",
"food_nutrient",
"Pantothenic_acid"
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[
"Broccoli",
"food_nutrient",
"Phenylalanine"
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[
"Broccoli",
"food_nutrient",
"Phosphorus"
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[
"Broccoli",
"food_nutrient",
"Phytonadione"
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[
"Broccoli",
"food_nutrient",
"Polyunsaturated_fat"
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[
"Broccoli",
"food_nutrient",
"Potassium"
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[
"Broccoli",
"food_nutrient",
"Proline"
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[
"Broccoli",
"food_nutrient",
"Protein"
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[
"Broccoli",
"food_nutrient",
"Riboflavin"
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[
"Broccoli",
"food_nutrient",
"Saturated_fat"
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[
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"food_nutrient",
"Selenium"
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[
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"Serine"
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[
"Broccoli",
"food_nutrient",
"Sodium"
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[
"Broccoli",
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"Stearic_acid"
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[
"Broccoli",
"food_nutrient",
"Sugar"
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[
"Broccoli",
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"Broccoli",
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"Thiamine"
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"Broccoli",
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"Threonine"
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"Broccoli",
"food_nutrient",
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"Broccoli",
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"Tyrosine"
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"Broccoli",
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"Broccoli",
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"Vitamin_A"
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"Broccoli",
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"Vitamin_B-6"
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"Broccoli",
"food_nutrient",
"Vitamin_C"
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[
"Broccoli",
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[
"Broccoli",
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"Broccoli",
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"Broccoli",
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"food_nutrient",
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"Cabbage",
"food_nutrient",
"Copper"
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"Cabbage",
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"Cabbage",
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"food_nutrient",
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"Cabbage",
"food_nutrient",
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"food_nutrient",
"Isoleucine"
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"Cabbage",
"food_nutrient",
"Leucine"
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"food_nutrient",
"Linoleic_acid"
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"Cabbage",
"food_nutrient",
"Lipid"
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"Cabbage",
"food_nutrient",
"Lysine"
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"Cabbage",
"food_nutrient",
"Magnesium"
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"Cabbage",
"food_nutrient",
"Manganese"
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[
"Cabbage",
"food_nutrient",
"Methionine"
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"food_nutrient",
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"Cabbage",
"food_nutrient",
"Niacin"
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"Cabbage",
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"Oleic_acid"
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"Cabbage",
"food_nutrient",
"Palmitic_acid"
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"Cabbage",
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"Pantothenic_acid"
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"Cabbage",
"food_nutrient",
"Phenylalanine"
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"Cabbage",
"food_nutrient",
"Phosphorus"
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[
"Cabbage",
"food_nutrient",
"Phytonadione"
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"Cabbage",
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"Cabbage",
"food_nutrient",
"Potassium"
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"Cabbage",
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"Cabbage",
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"Cabbage",
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"Serine"
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"Cabbage",
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"Sodium"
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"Cabbage",
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"Thiamine"
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"Cabbage",
"food_nutrient",
"Threonine"
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"Cabbage",
"food_nutrient",
"Tryptophan"
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"Cabbage",
"food_nutrient",
"Tyrosine"
],
[
"Cabbage",
"food_nutrient",
"Valine"
],
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"Cabbage",
"food_nutrient",
"Vitamin_A"
],
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"Cabbage",
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"Vitamin_B-6"
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"Cabbage",
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"Vitamin_C"
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"Cabbage",
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[
"Cabbage",
"food_nutrient",
"Zinc"
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"Cabbage",
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"Arginine"
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"Ash"
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"Betaine"
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"Capsicum",
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"Capsicum",
"food_nutrient",
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"Copper"
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"Cryptoxanthin"
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"Cystine"
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"Capsicum",
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"Capsicum",
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],
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"Capsicum",
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],
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"Capsicum",
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],
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"Capsicum",
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"Tryptophan"
],
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"Capsicum",
"food_nutrient",
"Tyrosine"
],
[
"Capsicum",
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"Valine"
],
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"Vitamin_A"
],
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"Vitamin_B-6"
],
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"Capsicum",
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"Vitamin_C"
],
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"Capsicum",
"food_nutrient",
"Water"
],
[
"Capsicum",
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"Zinc"
],
[
"Capsicum",
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"alpha-Carotene"
],
[
"Capsicum",
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"gamma-Tocopherol"
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[
"Carrot",
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"Alanine"
],
[
"Carrot",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Carrot",
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"Arginine"
],
[
"Carrot",
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"Ash"
],
[
"Carrot",
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"Aspartic_acid"
],
[
"Carrot",
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"Beta-carotene"
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"Carrot",
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"Betaine"
],
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"Carrot",
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"Calcium"
],
[
"Carrot",
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"Carbohydrate"
],
[
"Carrot",
"food_nutrient",
"Choline"
],
[
"Carrot",
"food_nutrient",
"Copper"
],
[
"Carrot",
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],
[
"Carrot",
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],
[
"Carrot",
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"Dietary_fiber"
],
[
"Carrot",
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],
[
"Carrot",
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],
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"Carrot",
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],
[
"Carrot",
"food_nutrient",
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],
[
"Carrot",
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"Histidine"
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[
"Carrot",
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"Iron"
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"Carrot",
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"Isoleucine"
],
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"Carrot",
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"Leucine"
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"Carrot",
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"Carrot",
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"Lipid"
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"Carrot",
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"Carrot",
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"Carrot",
"food_nutrient",
"Manganese"
],
[
"Carrot",
"food_nutrient",
"Methionine"
],
[
"Carrot",
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"Monounsaturated_fat"
],
[
"Carrot",
"food_nutrient",
"Niacin"
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[
"Carrot",
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"Palmitic_acid"
],
[
"Carrot",
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"Palmitoleic_acid"
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[
"Carrot",
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[
"Carrot",
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[
"Carrot",
"food_nutrient",
"Phosphorus"
],
[
"Carrot",
"food_nutrient",
"Phytonadione"
],
[
"Carrot",
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"Polyunsaturated_fat"
],
[
"Carrot",
"food_nutrient",
"Potassium"
],
[
"Carrot",
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"Proline"
],
[
"Carrot",
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"Protein"
],
[
"Carrot",
"food_nutrient",
"Riboflavin"
],
[
"Carrot",
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"Saturated_fat"
],
[
"Carrot",
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"Selenium"
],
[
"Carrot",
"food_nutrient",
"Serine"
],
[
"Carrot",
"food_nutrient",
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],
[
"Carrot",
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],
[
"Carrot",
"food_nutrient",
"Sugar"
],
[
"Carrot",
"food_nutrient",
"Table_sugar"
],
[
"Carrot",
"food_nutrient",
"Thiamine"
],
[
"Carrot",
"food_nutrient",
"Threonine"
],
[
"Carrot",
"food_nutrient",
"Tryptophan"
],
[
"Carrot",
"food_nutrient",
"Tyrosine"
],
[
"Carrot",
"food_nutrient",
"Valine"
],
[
"Carrot",
"food_nutrient",
"Vitamin_A"
],
[
"Carrot",
"food_nutrient",
"Vitamin_B-6"
],
[
"Carrot",
"food_nutrient",
"Vitamin_C"
],
[
"Carrot",
"food_nutrient",
"Water"
],
[
"Carrot",
"food_nutrient",
"Zinc"
],
[
"Carrot",
"food_nutrient",
"alpha-Carotene"
],
[
"Chicken_meat",
"food_nutrient",
"Alanine"
],
[
"Chicken_meat",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Chicken_meat",
"food_nutrient",
"Arginine"
],
[
"Chicken_meat",
"food_nutrient",
"Ash"
],
[
"Chicken_meat",
"food_nutrient",
"Aspartic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Betaine"
],
[
"Chicken_meat",
"food_nutrient",
"Calcium"
],
[
"Chicken_meat",
"food_nutrient",
"Choline"
],
[
"Chicken_meat",
"food_nutrient",
"Copper"
],
[
"Chicken_meat",
"food_nutrient",
"Cystine"
],
[
"Chicken_meat",
"food_nutrient",
"Glutamic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Glycine"
],
[
"Chicken_meat",
"food_nutrient",
"Histidine"
],
[
"Chicken_meat",
"food_nutrient",
"Iron"
],
[
"Chicken_meat",
"food_nutrient",
"Isoleucine"
],
[
"Chicken_meat",
"food_nutrient",
"Leucine"
],
[
"Chicken_meat",
"food_nutrient",
"Linoleic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Lipid"
],
[
"Chicken_meat",
"food_nutrient",
"Lysine"
],
[
"Chicken_meat",
"food_nutrient",
"Magnesium"
],
[
"Chicken_meat",
"food_nutrient",
"Manganese"
],
[
"Chicken_meat",
"food_nutrient",
"Methionine"
],
[
"Chicken_meat",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Chicken_meat",
"food_nutrient",
"Myristic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Niacin"
],
[
"Chicken_meat",
"food_nutrient",
"Oleic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Palmitic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Palmitoleic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Pantothenic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Phenylalanine"
],
[
"Chicken_meat",
"food_nutrient",
"Phosphorus"
],
[
"Chicken_meat",
"food_nutrient",
"Phytonadione"
],
[
"Chicken_meat",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Chicken_meat",
"food_nutrient",
"Potassium"
],
[
"Chicken_meat",
"food_nutrient",
"Proline"
],
[
"Chicken_meat",
"food_nutrient",
"Protein"
],
[
"Chicken_meat",
"food_nutrient",
"Riboflavin"
],
[
"Chicken_meat",
"food_nutrient",
"Saturated_fat"
],
[
"Chicken_meat",
"food_nutrient",
"Selenium"
],
[
"Chicken_meat",
"food_nutrient",
"Serine"
],
[
"Chicken_meat",
"food_nutrient",
"Sodium"
],
[
"Chicken_meat",
"food_nutrient",
"Stearic_acid"
],
[
"Chicken_meat",
"food_nutrient",
"Thiamine"
],
[
"Chicken_meat",
"food_nutrient",
"Threonine"
],
[
"Chicken_meat",
"food_nutrient",
"Tryptophan"
],
[
"Chicken_meat",
"food_nutrient",
"Tyrosine"
],
[
"Chicken_meat",
"food_nutrient",
"Valine"
],
[
"Chicken_meat",
"food_nutrient",
"Vitamin_A"
],
[
"Chicken_meat",
"food_nutrient",
"Vitamin_B-6"
],
[
"Chicken_meat",
"food_nutrient",
"Vitamin_C"
],
[
"Chicken_meat",
"food_nutrient",
"Water"
],
[
"Chicken_meat",
"food_nutrient",
"Zinc"
],
[
"Milk",
"award_winner",
"Sean_Penn"
],
[
"Milk",
"food_nutrient",
"Alanine"
],
[
"Milk",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Milk",
"food_nutrient",
"Arginine"
],
[
"Milk",
"food_nutrient",
"Ash"
],
[
"Milk",
"food_nutrient",
"Aspartic_acid"
],
[
"Milk",
"food_nutrient",
"Beta-carotene"
],
[
"Milk",
"food_nutrient",
"Betaine"
],
[
"Milk",
"food_nutrient",
"Calcium"
],
[
"Milk",
"food_nutrient",
"Carbohydrate"
],
[
"Milk",
"food_nutrient",
"Choline"
],
[
"Milk",
"food_nutrient",
"Copper"
],
[
"Milk",
"food_nutrient",
"Cystine"
],
[
"Milk",
"food_nutrient",
"Glutamic_acid"
],
[
"Milk",
"food_nutrient",
"Glycine"
],
[
"Milk",
"food_nutrient",
"Histidine"
],
[
"Milk",
"food_nutrient",
"Iron"
],
[
"Milk",
"food_nutrient",
"Isoleucine"
],
[
"Milk",
"food_nutrient",
"Leucine"
],
[
"Milk",
"food_nutrient",
"Linoleic_acid"
],
[
"Milk",
"food_nutrient",
"Lipid"
],
[
"Milk",
"food_nutrient",
"Lysine"
],
[
"Milk",
"food_nutrient",
"Magnesium"
],
[
"Milk",
"food_nutrient",
"Manganese"
],
[
"Milk",
"food_nutrient",
"Methionine"
],
[
"Milk",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Milk",
"food_nutrient",
"Myristic_acid"
],
[
"Milk",
"food_nutrient",
"Niacin"
],
[
"Milk",
"food_nutrient",
"Oleic_acid"
],
[
"Milk",
"food_nutrient",
"Palmitic_acid"
],
[
"Milk",
"food_nutrient",
"Pantothenic_acid"
],
[
"Milk",
"food_nutrient",
"Phenylalanine"
],
[
"Milk",
"food_nutrient",
"Phosphorus"
],
[
"Milk",
"food_nutrient",
"Phytonadione"
],
[
"Milk",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Milk",
"food_nutrient",
"Potassium"
],
[
"Milk",
"food_nutrient",
"Proline"
],
[
"Milk",
"food_nutrient",
"Protein"
],
[
"Milk",
"food_nutrient",
"Riboflavin"
],
[
"Milk",
"food_nutrient",
"Saturated_fat"
],
[
"Milk",
"food_nutrient",
"Selenium"
],
[
"Milk",
"food_nutrient",
"Serine"
],
[
"Milk",
"food_nutrient",
"Sodium"
],
[
"Milk",
"food_nutrient",
"Stearic_acid"
],
[
"Milk",
"food_nutrient",
"Sugar"
],
[
"Milk",
"food_nutrient",
"Thiamine"
],
[
"Milk",
"food_nutrient",
"Threonine"
],
[
"Milk",
"food_nutrient",
"Tryptophan"
],
[
"Milk",
"food_nutrient",
"Tyrosine"
],
[
"Milk",
"food_nutrient",
"Valine"
],
[
"Milk",
"food_nutrient",
"Vitamin_A"
],
[
"Milk",
"food_nutrient",
"Vitamin_B-6"
],
[
"Milk",
"food_nutrient",
"Water"
],
[
"Milk",
"food_nutrient",
"Zinc"
],
[
"Milk",
"food_nutrient",
"gamma-Tocopherol"
],
[
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture",
"nominated_for",
"Beasts_of_the_Southern_Wild"
],
[
"Producers_Guild_of_America_Award_for_Best_Theatrical_Motion_Picture",
"nominated_for",
"Milk"
],
[
"Sean_Penn",
"acted_in",
"Milk"
],
[
"Sean_Penn",
"acted_in",
"This_Must_Be_the_Place"
],
[
"Sean_Penn",
"nominated_for",
"Milk"
],
[
"This_Must_Be_the_Place",
"film_festivals",
"2012_Sundance_Film_Festival"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2642, Akira_Kurosawa
10229, Coach_Carter
12664, Docudrama
4338, Epic_film
13686, Japanese
4469, MTV
281, Ran
12709, Richard_III
725, Romeo_and_Juliet
12187, Thirteen_Days
7054, Tragedy
src, edge_attr, dst
2642, film, 281
10229, genre, 12664
10229, production_companies, 4469
4338, titles, 12709
4338, titles, 725
4338, titles, 12187
13686, people, 2642
281, edited_by, 2642
281, genre, 4338
281, written_by, 2642
12709, genre, 4338
725, genre, 4338
12187, genre, 12664
12187, genre, 4338
7054, films, 281
7054, films, 12709
7054, films, 725
Question: How are Epic_film, Japanese, and MTV related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Epic_film",
"Japanese",
"MTV"
],
"valid_edges": [
[
"Akira_Kurosawa",
"film",
"Ran"
],
[
"Coach_Carter",
"genre",
"Docudrama"
],
[
"Coach_Carter",
"production_companies",
"MTV"
],
[
"Epic_film",
"titles",
"Richard_III"
],
[
"Epic_film",
"titles",
"Romeo_and_Juliet"
],
[
"Epic_film",
"titles",
"Thirteen_Days"
],
[
"Japanese",
"people",
"Akira_Kurosawa"
],
[
"Ran",
"edited_by",
"Akira_Kurosawa"
],
[
"Ran",
"genre",
"Epic_film"
],
[
"Ran",
"written_by",
"Akira_Kurosawa"
],
[
"Richard_III",
"genre",
"Epic_film"
],
[
"Romeo_and_Juliet",
"genre",
"Epic_film"
],
[
"Thirteen_Days",
"genre",
"Docudrama"
],
[
"Thirteen_Days",
"genre",
"Epic_film"
],
[
"Tragedy",
"films",
"Ran"
],
[
"Tragedy",
"films",
"Richard_III"
],
[
"Tragedy",
"films",
"Romeo_and_Juliet"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
10464, 2008_NBA_draft
12398, Alpha_Sigma_Phi
12737, Associate_degree
11365, Auburn_University
7992, Burbank
8484, Business
14090, California_Polytechnic_State_University
9495, California_State_University,_Northridge
7708, California_State_University,_Sacramento
1535, Chairman
1044, Clemson_University
863, Cornell_University
5542, E._W._Scripps_Company
3085, Engineering-GB
13178, Entercom
5252, Gannett_Company
12947, General_Dynamics
8249, Google
3488, Indiana_University_Bloomington
13214, Iowa_State_University
9611, JPMorgan_Chase
6305, Johnson_&_Johnson
8061, Kansas_State_University
14166, Land-grant_university
8158, Lehigh_University
581, Lockheed_Corporation
12152, Louisiana_State_University
12611, Loyola_University_Chicago
6215, Macy's_Inc.
332, Marriott_International
8736, Marshall_University
1479, Massachusetts_Institute_of_Technology
1192, Miami_University
4349, Michigan_State_University
10340, Nike
2160, North_Carolina_State_University
1212, Ohio_State_University
697, Oregon_State_University
8268, Pennsylvania_State_University
5872, PepsiCo
155, Purdue_University
13376, Rutgers_University
2968, Sean_McNamara
3878, Soul_Surfer
5571, Stevens_Institute_of_Technology
4601, Sudan
13538, Symantec_Corporation
6353, Syracuse_University
7739, The_Coca-Cola_Company
11318, The_Graham_Holdings_Company
7743, The_McClatchy_Company
2564, TriStar_Pictures
2919, Tribune_Company
4863, University_of_Alabama
6515, University_of_Arizona
7609, University_of_California,_Irvine
11425, University_of_Colorado_Boulder
3871, University_of_Connecticut
1004, University_of_Delaware
221, University_of_Florida
2680, University_of_Idaho
694, University_of_Kansas
10254, University_of_Kentucky
5314, University_of_Maryland,_College_Park
10310, University_of_Massachusetts_Amherst
1480, University_of_Michigan
8082, University_of_Minnesota
13487, University_of_MissouriβColumbia
3190, University_of_Nevada,_Reno
6688, University_of_New_Hampshire
7587, University_of_Pennsylvania
1488, University_of_Pittsburgh
2838, Vice_President-GB
8831, Virginia_Polytechnic_Institute_and_State_University
4132, Washington_University_in_St._Louis
125, Wayne_State_University
13818, West_Virginia_University
7475, Yahoo!
src, edge_attr, dst
10464, school, 8061
10464, school, 12152
10464, school, 2160
10464, school, 6353
10464, school, 4863
10464, school, 6515
10464, school, 221
10464, school, 694
10464, school, 10254
10464, school, 3190
10464, school, 13818
12737, major_field_of_study, 8484
12737, major_field_of_study, 3085
11365, major_field_of_study, 3085
11365, school_type, 14166
7992, place, 7992
14090, major_field_of_study, 3085
14090, school_type, 14166
9495, major_field_of_study, 8484
9495, major_field_of_study, 3085
7708, fraternities_and_sororities, 12398
7708, school_type, 14166
1535, company, 5542
1535, company, 13178
1535, company, 5252
1535, company, 12947
1535, company, 8249
1535, company, 9611
1535, company, 6305
1535, company, 6215
1535, company, 332
1535, company, 10340
1535, company, 5872
1535, company, 13538
1535, company, 7739
1535, company, 11318
1535, company, 7743
1535, company, 2919
1535, company, 11425
1535, company, 7475
1535, jurisdiction_of_office, 4601
1044, fraternities_and_sororities, 12398
1044, school_type, 14166
863, fraternities_and_sororities, 12398
863, major_field_of_study, 8484
863, major_field_of_study, 3085
863, school_type, 14166
3488, fraternities_and_sororities, 12398
3488, major_field_of_study, 8484
13214, fraternities_and_sororities, 12398
13214, major_field_of_study, 3085
13214, school_type, 14166
8061, school_type, 14166
8158, fraternities_and_sororities, 12398
8158, major_field_of_study, 3085
581, citytown, 7992
12152, school_type, 14166
12611, fraternities_and_sororities, 12398
12611, major_field_of_study, 8484
8736, fraternities_and_sororities, 12398
8736, major_field_of_study, 3085
1479, fraternities_and_sororities, 12398
1479, major_field_of_study, 3085
1479, school_type, 14166
1192, fraternities_and_sororities, 12398
1192, major_field_of_study, 8484
4349, fraternities_and_sororities, 12398
4349, major_field_of_study, 8484
4349, school_type, 14166
2160, fraternities_and_sororities, 12398
2160, school_type, 14166
1212, fraternities_and_sororities, 12398
1212, school_type, 14166
697, fraternities_and_sororities, 12398
697, major_field_of_study, 8484
8268, fraternities_and_sororities, 12398
8268, major_field_of_study, 3085
8268, school_type, 14166
155, fraternities_and_sororities, 12398
155, major_field_of_study, 3085
155, school_type, 14166
13376, fraternities_and_sororities, 12398
13376, school_type, 14166
2968, acted_in, 3878
2968, film, 3878
2968, place_of_birth, 7992
3878, produced_by, 2968
3878, written_by, 2968
5571, fraternities_and_sororities, 12398
5571, major_field_of_study, 3085
6353, fraternities_and_sororities, 12398
2564, film, 3878
4863, fraternities_and_sororities, 12398
6515, fraternities_and_sororities, 12398
6515, major_field_of_study, 8484
6515, school_type, 14166
7609, major_field_of_study, 3085
7609, school_type, 14166
11425, fraternities_and_sororities, 12398
11425, school_type, 14166
3871, fraternities_and_sororities, 12398
3871, school_type, 14166
1004, fraternities_and_sororities, 12398
1004, school_type, 14166
221, major_field_of_study, 3085
221, school_type, 14166
2680, major_field_of_study, 8484
2680, school_type, 14166
694, major_field_of_study, 8484
694, school_type, 14166
10254, fraternities_and_sororities, 12398
10254, school_type, 14166
5314, fraternities_and_sororities, 12398
5314, major_field_of_study, 8484
5314, school_type, 14166
10310, fraternities_and_sororities, 12398
10310, major_field_of_study, 3085
10310, school_type, 14166
1480, fraternities_and_sororities, 12398
1480, major_field_of_study, 3085
8082, fraternities_and_sororities, 12398
8082, major_field_of_study, 8484
8082, school_type, 14166
13487, fraternities_and_sororities, 12398
13487, major_field_of_study, 8484
3190, major_field_of_study, 3085
3190, school_type, 14166
6688, fraternities_and_sororities, 12398
6688, school_type, 14166
7587, fraternities_and_sororities, 12398
7587, major_field_of_study, 3085
1488, major_field_of_study, 8484
1488, major_field_of_study, 3085
2838, company, 863
2838, company, 5542
2838, company, 13178
2838, company, 5252
2838, company, 12947
2838, company, 8249
2838, company, 9611
2838, company, 6305
2838, company, 581
2838, company, 6215
2838, company, 332
2838, company, 10340
2838, company, 5872
2838, company, 13538
2838, company, 7739
2838, company, 11318
2838, company, 7743
2838, company, 2564
2838, company, 2919
2838, company, 7475
2838, jurisdiction_of_office, 4601
8831, fraternities_and_sororities, 12398
8831, major_field_of_study, 3085
8831, school_type, 14166
4132, fraternities_and_sororities, 12398
4132, major_field_of_study, 3085
125, fraternities_and_sororities, 12398
125, major_field_of_study, 3085
13818, campuses, 13818
13818, educational_institution, 13818
13818, fraternities_and_sororities, 12398
13818, major_field_of_study, 8484
13818, major_field_of_study, 3085
13818, school_type, 14166
Question: For what reason are General_Dynamics, Sean_McNamara, and West_Virginia_University associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"General_Dynamics",
"Sean_McNamara",
"West_Virginia_University"
],
"valid_edges": [
[
"2008_NBA_draft",
"school",
"Kansas_State_University"
],
[
"2008_NBA_draft",
"school",
"Louisiana_State_University"
],
[
"2008_NBA_draft",
"school",
"North_Carolina_State_University"
],
[
"2008_NBA_draft",
"school",
"Syracuse_University"
],
[
"2008_NBA_draft",
"school",
"University_of_Alabama"
],
[
"2008_NBA_draft",
"school",
"University_of_Arizona"
],
[
"2008_NBA_draft",
"school",
"University_of_Florida"
],
[
"2008_NBA_draft",
"school",
"University_of_Kansas"
],
[
"2008_NBA_draft",
"school",
"University_of_Kentucky"
],
[
"2008_NBA_draft",
"school",
"University_of_Nevada,_Reno"
],
[
"2008_NBA_draft",
"school",
"West_Virginia_University"
],
[
"Associate_degree",
"major_field_of_study",
"Business"
],
[
"Associate_degree",
"major_field_of_study",
"Engineering-GB"
],
[
"Auburn_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Auburn_University",
"school_type",
"Land-grant_university"
],
[
"Burbank",
"place",
"Burbank"
],
[
"California_Polytechnic_State_University",
"major_field_of_study",
"Engineering-GB"
],
[
"California_Polytechnic_State_University",
"school_type",
"Land-grant_university"
],
[
"California_State_University,_Northridge",
"major_field_of_study",
"Business"
],
[
"California_State_University,_Northridge",
"major_field_of_study",
"Engineering-GB"
],
[
"California_State_University,_Sacramento",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"California_State_University,_Sacramento",
"school_type",
"Land-grant_university"
],
[
"Chairman",
"company",
"E._W._Scripps_Company"
],
[
"Chairman",
"company",
"Entercom"
],
[
"Chairman",
"company",
"Gannett_Company"
],
[
"Chairman",
"company",
"General_Dynamics"
],
[
"Chairman",
"company",
"Google"
],
[
"Chairman",
"company",
"JPMorgan_Chase"
],
[
"Chairman",
"company",
"Johnson_&_Johnson"
],
[
"Chairman",
"company",
"Macy's_Inc."
],
[
"Chairman",
"company",
"Marriott_International"
],
[
"Chairman",
"company",
"Nike"
],
[
"Chairman",
"company",
"PepsiCo"
],
[
"Chairman",
"company",
"Symantec_Corporation"
],
[
"Chairman",
"company",
"The_Coca-Cola_Company"
],
[
"Chairman",
"company",
"The_Graham_Holdings_Company"
],
[
"Chairman",
"company",
"The_McClatchy_Company"
],
[
"Chairman",
"company",
"Tribune_Company"
],
[
"Chairman",
"company",
"University_of_Colorado_Boulder"
],
[
"Chairman",
"company",
"Yahoo!"
],
[
"Chairman",
"jurisdiction_of_office",
"Sudan"
],
[
"Clemson_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Clemson_University",
"school_type",
"Land-grant_university"
],
[
"Cornell_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Cornell_University",
"major_field_of_study",
"Business"
],
[
"Cornell_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Cornell_University",
"school_type",
"Land-grant_university"
],
[
"Indiana_University_Bloomington",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Indiana_University_Bloomington",
"major_field_of_study",
"Business"
],
[
"Iowa_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Iowa_State_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Iowa_State_University",
"school_type",
"Land-grant_university"
],
[
"Kansas_State_University",
"school_type",
"Land-grant_university"
],
[
"Lehigh_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Lehigh_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Lockheed_Corporation",
"citytown",
"Burbank"
],
[
"Louisiana_State_University",
"school_type",
"Land-grant_university"
],
[
"Loyola_University_Chicago",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Loyola_University_Chicago",
"major_field_of_study",
"Business"
],
[
"Marshall_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Marshall_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Massachusetts_Institute_of_Technology",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Massachusetts_Institute_of_Technology",
"major_field_of_study",
"Engineering-GB"
],
[
"Massachusetts_Institute_of_Technology",
"school_type",
"Land-grant_university"
],
[
"Miami_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Miami_University",
"major_field_of_study",
"Business"
],
[
"Michigan_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Michigan_State_University",
"major_field_of_study",
"Business"
],
[
"Michigan_State_University",
"school_type",
"Land-grant_university"
],
[
"North_Carolina_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"North_Carolina_State_University",
"school_type",
"Land-grant_university"
],
[
"Ohio_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Ohio_State_University",
"school_type",
"Land-grant_university"
],
[
"Oregon_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Oregon_State_University",
"major_field_of_study",
"Business"
],
[
"Pennsylvania_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Pennsylvania_State_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Pennsylvania_State_University",
"school_type",
"Land-grant_university"
],
[
"Purdue_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Purdue_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Purdue_University",
"school_type",
"Land-grant_university"
],
[
"Rutgers_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Rutgers_University",
"school_type",
"Land-grant_university"
],
[
"Sean_McNamara",
"acted_in",
"Soul_Surfer"
],
[
"Sean_McNamara",
"film",
"Soul_Surfer"
],
[
"Sean_McNamara",
"place_of_birth",
"Burbank"
],
[
"Soul_Surfer",
"produced_by",
"Sean_McNamara"
],
[
"Soul_Surfer",
"written_by",
"Sean_McNamara"
],
[
"Stevens_Institute_of_Technology",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Stevens_Institute_of_Technology",
"major_field_of_study",
"Engineering-GB"
],
[
"Syracuse_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"TriStar_Pictures",
"film",
"Soul_Surfer"
],
[
"University_of_Alabama",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Arizona",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Arizona",
"major_field_of_study",
"Business"
],
[
"University_of_Arizona",
"school_type",
"Land-grant_university"
],
[
"University_of_California,_Irvine",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_California,_Irvine",
"school_type",
"Land-grant_university"
],
[
"University_of_Colorado_Boulder",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Colorado_Boulder",
"school_type",
"Land-grant_university"
],
[
"University_of_Connecticut",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Connecticut",
"school_type",
"Land-grant_university"
],
[
"University_of_Delaware",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Delaware",
"school_type",
"Land-grant_university"
],
[
"University_of_Florida",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_Florida",
"school_type",
"Land-grant_university"
],
[
"University_of_Idaho",
"major_field_of_study",
"Business"
],
[
"University_of_Idaho",
"school_type",
"Land-grant_university"
],
[
"University_of_Kansas",
"major_field_of_study",
"Business"
],
[
"University_of_Kansas",
"school_type",
"Land-grant_university"
],
[
"University_of_Kentucky",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Kentucky",
"school_type",
"Land-grant_university"
],
[
"University_of_Maryland,_College_Park",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Maryland,_College_Park",
"major_field_of_study",
"Business"
],
[
"University_of_Maryland,_College_Park",
"school_type",
"Land-grant_university"
],
[
"University_of_Massachusetts_Amherst",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Massachusetts_Amherst",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_Massachusetts_Amherst",
"school_type",
"Land-grant_university"
],
[
"University_of_Michigan",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Michigan",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_Minnesota",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Minnesota",
"major_field_of_study",
"Business"
],
[
"University_of_Minnesota",
"school_type",
"Land-grant_university"
],
[
"University_of_MissouriβColumbia",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_MissouriβColumbia",
"major_field_of_study",
"Business"
],
[
"University_of_Nevada,_Reno",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_Nevada,_Reno",
"school_type",
"Land-grant_university"
],
[
"University_of_New_Hampshire",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_New_Hampshire",
"school_type",
"Land-grant_university"
],
[
"University_of_Pennsylvania",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Pennsylvania",
"major_field_of_study",
"Engineering-GB"
],
[
"University_of_Pittsburgh",
"major_field_of_study",
"Business"
],
[
"University_of_Pittsburgh",
"major_field_of_study",
"Engineering-GB"
],
[
"Vice_President-GB",
"company",
"Cornell_University"
],
[
"Vice_President-GB",
"company",
"E._W._Scripps_Company"
],
[
"Vice_President-GB",
"company",
"Entercom"
],
[
"Vice_President-GB",
"company",
"Gannett_Company"
],
[
"Vice_President-GB",
"company",
"General_Dynamics"
],
[
"Vice_President-GB",
"company",
"Google"
],
[
"Vice_President-GB",
"company",
"JPMorgan_Chase"
],
[
"Vice_President-GB",
"company",
"Johnson_&_Johnson"
],
[
"Vice_President-GB",
"company",
"Lockheed_Corporation"
],
[
"Vice_President-GB",
"company",
"Macy's_Inc."
],
[
"Vice_President-GB",
"company",
"Marriott_International"
],
[
"Vice_President-GB",
"company",
"Nike"
],
[
"Vice_President-GB",
"company",
"PepsiCo"
],
[
"Vice_President-GB",
"company",
"Symantec_Corporation"
],
[
"Vice_President-GB",
"company",
"The_Coca-Cola_Company"
],
[
"Vice_President-GB",
"company",
"The_Graham_Holdings_Company"
],
[
"Vice_President-GB",
"company",
"The_McClatchy_Company"
],
[
"Vice_President-GB",
"company",
"TriStar_Pictures"
],
[
"Vice_President-GB",
"company",
"Tribune_Company"
],
[
"Vice_President-GB",
"company",
"Yahoo!"
],
[
"Vice_President-GB",
"jurisdiction_of_office",
"Sudan"
],
[
"Virginia_Polytechnic_Institute_and_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Virginia_Polytechnic_Institute_and_State_University",
"major_field_of_study",
"Engineering-GB"
],
[
"Virginia_Polytechnic_Institute_and_State_University",
"school_type",
"Land-grant_university"
],
[
"Washington_University_in_St._Louis",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Washington_University_in_St._Louis",
"major_field_of_study",
"Engineering-GB"
],
[
"Wayne_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Wayne_State_University",
"major_field_of_study",
"Engineering-GB"
],
[
"West_Virginia_University",
"campuses",
"West_Virginia_University"
],
[
"West_Virginia_University",
"educational_institution",
"West_Virginia_University"
],
[
"West_Virginia_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"West_Virginia_University",
"major_field_of_study",
"Business"
],
[
"West_Virginia_University",
"major_field_of_study",
"Engineering-GB"
],
[
"West_Virginia_University",
"school_type",
"Land-grant_university"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4704, Akiva_Goldsman
11268, DC_Comics
54, David_Schwimmer
8106, Ellen_DeGeneres
5200, I,_Robot
5850, Jonah_Hex
6184, Lost_in_Space
5616, Marco_Beltrami
2464, Matt_LeBlanc
10541, Portia_de_Rossi
10494, The_Losers
3976, University_of_New_Orleans
2163, Will_Arnett
src, edge_attr, dst
54, award_nominee, 2464
54, award_winner, 2464
8106, spouse, 10541
5200, film_music, 5616
5200, written_by, 4704
5850, executive_produced_by, 2464
5850, film_music, 5616
5850, produced_by, 4704
5850, production_companies, 11268
6184, produced_by, 4704
6184, written_by, 4704
2464, acted_in, 6184
2464, award_nominee, 54
2464, award_winner, 54
10541, award_nominee, 2163
10541, participant, 8106
10541, spouse, 8106
10494, produced_by, 4704
10494, production_companies, 11268
3976, campuses, 3976
3976, student, 8106
2163, acted_in, 5850
2163, award_nominee, 10541
Question: For what reason are David_Schwimmer, Jonah_Hex, and University_of_New_Orleans associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"David_Schwimmer",
"Jonah_Hex",
"University_of_New_Orleans"
],
"valid_edges": [
[
"David_Schwimmer",
"award_nominee",
"Matt_LeBlanc"
],
[
"David_Schwimmer",
"award_winner",
"Matt_LeBlanc"
],
[
"Ellen_DeGeneres",
"spouse",
"Portia_de_Rossi"
],
[
"I,_Robot",
"film_music",
"Marco_Beltrami"
],
[
"I,_Robot",
"written_by",
"Akiva_Goldsman"
],
[
"Jonah_Hex",
"executive_produced_by",
"Matt_LeBlanc"
],
[
"Jonah_Hex",
"film_music",
"Marco_Beltrami"
],
[
"Jonah_Hex",
"produced_by",
"Akiva_Goldsman"
],
[
"Jonah_Hex",
"production_companies",
"DC_Comics"
],
[
"Lost_in_Space",
"produced_by",
"Akiva_Goldsman"
],
[
"Lost_in_Space",
"written_by",
"Akiva_Goldsman"
],
[
"Matt_LeBlanc",
"acted_in",
"Lost_in_Space"
],
[
"Matt_LeBlanc",
"award_nominee",
"David_Schwimmer"
],
[
"Matt_LeBlanc",
"award_winner",
"David_Schwimmer"
],
[
"Portia_de_Rossi",
"award_nominee",
"Will_Arnett"
],
[
"Portia_de_Rossi",
"participant",
"Ellen_DeGeneres"
],
[
"Portia_de_Rossi",
"spouse",
"Ellen_DeGeneres"
],
[
"The_Losers",
"produced_by",
"Akiva_Goldsman"
],
[
"The_Losers",
"production_companies",
"DC_Comics"
],
[
"University_of_New_Orleans",
"campuses",
"University_of_New_Orleans"
],
[
"University_of_New_Orleans",
"student",
"Ellen_DeGeneres"
],
[
"Will_Arnett",
"acted_in",
"Jonah_Hex"
],
[
"Will_Arnett",
"award_nominee",
"Portia_de_Rossi"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12268, 57th_Academy_Awards
11203, Acting
9423, All_the_President's_Men
9839, Amadeus
11681, Carnegie_Institute_of_Technology
2627, Constantin_Film
12126, Dean-GB
3567, F._Murray_Abraham
9537, FC_Anzhi_Makhachkala
13493, Filmmaking
5696, Gods_and_Monsters
3704, Hal_Holbrook
8258, Julie_Benz
3067, Latin_Language
13654, Los_Angeles_Film_Critics_Association_Award_for_Best_Actor
4340, Los_Angeles_Film_Critics_Association_Award_for_Best_Director
12027, Marcia_Gay_Harden
8223, Mark_Berger
13554, Parsons_The_New_School_for_Design
796, Pittsburgh
12966, Spike_Lee
4687, The_Name_of_the_Rose-US
1478, The_New_School
13637, Tisch_School_of_the_Arts
6644, University_of_California,_San_Diego
12277, University_of_California,_Santa_Cruz
11518, Virginia_Military_Institute
7080, Yellow
src, edge_attr, dst
12268, award_winner, 3567
12268, award_winner, 8223
12268, honored_for, 9839
11203, student, 8258
9839, award_honor_award, 13654
9839, award_honor_award, 4340
9839, award_winner, 8223
9839, language, 3067
11681, citytown, 796
2627, film, 4687
2627, industry, 13493
12126, company, 12277
12126, organization, 11681
12126, organization, 13554
12126, organization, 13637
12126, organization, 11518
3567, acted_in, 9423
3567, acted_in, 4687
3567, nominated_for, 9839
3567, place_of_birth, 796
9537, colors, 7080
13493, films, 5696
5696, award_honor_award, 13654
3704, acted_in, 9423
3704, award_nominee, 12027
8258, location, 796
8258, place_of_birth, 796
13654, award_winner, 3567
4340, award_winner, 12966
12027, award_nominee, 3704
8223, nominated_for, 9839
13554, colors, 7080
796, contains, 11681
796, place, 796
4687, language, 3067
4687, production_companies, 2627
1478, colors, 7080
1478, major_field_of_study, 11203
13637, campuses, 13637
13637, educational_institution, 13637
13637, major_field_of_study, 11203
13637, major_field_of_study, 13493
13637, student, 12027
13637, student, 12966
6644, major_field_of_study, 11203
6644, major_field_of_study, 13493
12277, major_field_of_study, 11203
11518, colors, 7080
Question: How are F._Murray_Abraham, FC_Anzhi_Makhachkala, and Tisch_School_of_the_Arts related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"F._Murray_Abraham",
"FC_Anzhi_Makhachkala",
"Tisch_School_of_the_Arts"
],
"valid_edges": [
[
"57th_Academy_Awards",
"award_winner",
"F._Murray_Abraham"
],
[
"57th_Academy_Awards",
"award_winner",
"Mark_Berger"
],
[
"57th_Academy_Awards",
"honored_for",
"Amadeus"
],
[
"Acting",
"student",
"Julie_Benz"
],
[
"Amadeus",
"award_honor_award",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Actor"
],
[
"Amadeus",
"award_honor_award",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Director"
],
[
"Amadeus",
"award_winner",
"Mark_Berger"
],
[
"Amadeus",
"language",
"Latin_Language"
],
[
"Carnegie_Institute_of_Technology",
"citytown",
"Pittsburgh"
],
[
"Constantin_Film",
"film",
"The_Name_of_the_Rose-US"
],
[
"Constantin_Film",
"industry",
"Filmmaking"
],
[
"Dean-GB",
"company",
"University_of_California,_Santa_Cruz"
],
[
"Dean-GB",
"organization",
"Carnegie_Institute_of_Technology"
],
[
"Dean-GB",
"organization",
"Parsons_The_New_School_for_Design"
],
[
"Dean-GB",
"organization",
"Tisch_School_of_the_Arts"
],
[
"Dean-GB",
"organization",
"Virginia_Military_Institute"
],
[
"F._Murray_Abraham",
"acted_in",
"All_the_President's_Men"
],
[
"F._Murray_Abraham",
"acted_in",
"The_Name_of_the_Rose-US"
],
[
"F._Murray_Abraham",
"nominated_for",
"Amadeus"
],
[
"F._Murray_Abraham",
"place_of_birth",
"Pittsburgh"
],
[
"FC_Anzhi_Makhachkala",
"colors",
"Yellow"
],
[
"Filmmaking",
"films",
"Gods_and_Monsters"
],
[
"Gods_and_Monsters",
"award_honor_award",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Actor"
],
[
"Hal_Holbrook",
"acted_in",
"All_the_President's_Men"
],
[
"Hal_Holbrook",
"award_nominee",
"Marcia_Gay_Harden"
],
[
"Julie_Benz",
"location",
"Pittsburgh"
],
[
"Julie_Benz",
"place_of_birth",
"Pittsburgh"
],
[
"Los_Angeles_Film_Critics_Association_Award_for_Best_Actor",
"award_winner",
"F._Murray_Abraham"
],
[
"Los_Angeles_Film_Critics_Association_Award_for_Best_Director",
"award_winner",
"Spike_Lee"
],
[
"Marcia_Gay_Harden",
"award_nominee",
"Hal_Holbrook"
],
[
"Mark_Berger",
"nominated_for",
"Amadeus"
],
[
"Parsons_The_New_School_for_Design",
"colors",
"Yellow"
],
[
"Pittsburgh",
"contains",
"Carnegie_Institute_of_Technology"
],
[
"Pittsburgh",
"place",
"Pittsburgh"
],
[
"The_Name_of_the_Rose-US",
"language",
"Latin_Language"
],
[
"The_Name_of_the_Rose-US",
"production_companies",
"Constantin_Film"
],
[
"The_New_School",
"colors",
"Yellow"
],
[
"The_New_School",
"major_field_of_study",
"Acting"
],
[
"Tisch_School_of_the_Arts",
"campuses",
"Tisch_School_of_the_Arts"
],
[
"Tisch_School_of_the_Arts",
"educational_institution",
"Tisch_School_of_the_Arts"
],
[
"Tisch_School_of_the_Arts",
"major_field_of_study",
"Acting"
],
[
"Tisch_School_of_the_Arts",
"major_field_of_study",
"Filmmaking"
],
[
"Tisch_School_of_the_Arts",
"student",
"Marcia_Gay_Harden"
],
[
"Tisch_School_of_the_Arts",
"student",
"Spike_Lee"
],
[
"University_of_California,_San_Diego",
"major_field_of_study",
"Acting"
],
[
"University_of_California,_San_Diego",
"major_field_of_study",
"Filmmaking"
],
[
"University_of_California,_Santa_Cruz",
"major_field_of_study",
"Acting"
],
[
"Virginia_Military_Institute",
"colors",
"Yellow"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4123, 9th_Golden_Satellite_Awards
3263, ANTIβ
9379, A_Prairie_Home_Companion
5126, Alanis_Morissette
7955, Buck_Henry
10036, City_of_Angels
3481, Cookie's_Fortune
1670, De-Lovely
6387, Elliott_Smith
3313, Epitaph_Records
1622, Even_Cowgirls_Get_the_Blues
2578, Experimental_music
11702, Fine_Line_Features
2422, Golden_Lion
12823, Grammy_Award_for_Best_Female_Rock_Vocal_Performance
5566, Gus_Van_Sant
2434, Island_Records
13941, Jay_and_Silent_Bob_Strike_Back
1219, Kim_Carnes
5835, Lo-fi_music
11281, Lyle_Lovett
6454, MCA_Records
12653, Mrs._Parker_and_the_Vicious_Circle
547, Portishead
11532, Post-grunge
12848, Robert_Altman
6924, Short_Cuts
11030, Sound_Re-Recording_Mixer-GB
397, The_Devil_Wears_Prada
6604, The_Sea_Inside
13851, Tom_Waits
8479, Tommy_Lee
7724, Vera_Drake
973, Wim_Wenders
src, edge_attr, dst
4123, award_winner, 11702
4123, honored_for, 1670
3263, artist, 6387
3263, artist, 13851
9379, award_winner, 12848
9379, honored_for, 397
9379, nominated_for, 397
5126, acted_in, 1670
5126, acted_in, 13941
5126, award, 12823
5126, nominated_for, 10036
5126, nominated_for, 397
7955, acted_in, 1622
7955, acted_in, 6924
10036, award_winner, 5126
10036, story_by, 973
3481, award_winner, 12848
3481, produced_by, 12848
1670, film_crew_role, 11030
3313, artist, 6387
3313, artist, 13851
2578, artists, 547
2578, artists, 13851
11702, film, 1622
11702, film, 12653
11702, film, 6924
11702, film, 7724
11702, nominated_for, 6604
11702, nominated_for, 7724
2422, award_winner, 12848
2422, award_winner, 973
2422, nominated_for, 6604
12823, award_winner, 5126
5566, acted_in, 13941
5566, award, 2422
2434, artist, 547
2434, artist, 13851
1219, award, 12823
5835, artists, 6387
5835, artists, 547
11281, acted_in, 3481
11281, acted_in, 6924
6454, artist, 5126
6454, artist, 1219
6454, artist, 11281
6454, artist, 8479
12653, produced_by, 12848
11532, artists, 5126
11532, artists, 8479
12848, film, 9379
12848, film, 3481
12848, film, 6924
12848, nominated_for, 9379
12848, nominated_for, 12653
12848, nominated_for, 6924
6924, award_honor_award, 2422
6924, award_winner, 12848
6924, production_companies, 11702
6924, written_by, 12848
397, film_crew_role, 11030
397, honored_for, 9379
397, nominated_for, 9379
6604, award_winner, 11702
13851, acted_in, 6924
7724, award_honor_award, 2422
Question: How are Alanis_Morissette, Lo-fi_music, and Short_Cuts related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Alanis_Morissette",
"Lo-fi_music",
"Short_Cuts"
],
"valid_edges": [
[
"9th_Golden_Satellite_Awards",
"award_winner",
"Fine_Line_Features"
],
[
"9th_Golden_Satellite_Awards",
"honored_for",
"De-Lovely"
],
[
"ANTIβ",
"artist",
"Elliott_Smith"
],
[
"ANTIβ",
"artist",
"Tom_Waits"
],
[
"A_Prairie_Home_Companion",
"award_winner",
"Robert_Altman"
],
[
"A_Prairie_Home_Companion",
"honored_for",
"The_Devil_Wears_Prada"
],
[
"A_Prairie_Home_Companion",
"nominated_for",
"The_Devil_Wears_Prada"
],
[
"Alanis_Morissette",
"acted_in",
"De-Lovely"
],
[
"Alanis_Morissette",
"acted_in",
"Jay_and_Silent_Bob_Strike_Back"
],
[
"Alanis_Morissette",
"award",
"Grammy_Award_for_Best_Female_Rock_Vocal_Performance"
],
[
"Alanis_Morissette",
"nominated_for",
"City_of_Angels"
],
[
"Alanis_Morissette",
"nominated_for",
"The_Devil_Wears_Prada"
],
[
"Buck_Henry",
"acted_in",
"Even_Cowgirls_Get_the_Blues"
],
[
"Buck_Henry",
"acted_in",
"Short_Cuts"
],
[
"City_of_Angels",
"award_winner",
"Alanis_Morissette"
],
[
"City_of_Angels",
"story_by",
"Wim_Wenders"
],
[
"Cookie's_Fortune",
"award_winner",
"Robert_Altman"
],
[
"Cookie's_Fortune",
"produced_by",
"Robert_Altman"
],
[
"De-Lovely",
"film_crew_role",
"Sound_Re-Recording_Mixer-GB"
],
[
"Epitaph_Records",
"artist",
"Elliott_Smith"
],
[
"Epitaph_Records",
"artist",
"Tom_Waits"
],
[
"Experimental_music",
"artists",
"Portishead"
],
[
"Experimental_music",
"artists",
"Tom_Waits"
],
[
"Fine_Line_Features",
"film",
"Even_Cowgirls_Get_the_Blues"
],
[
"Fine_Line_Features",
"film",
"Mrs._Parker_and_the_Vicious_Circle"
],
[
"Fine_Line_Features",
"film",
"Short_Cuts"
],
[
"Fine_Line_Features",
"film",
"Vera_Drake"
],
[
"Fine_Line_Features",
"nominated_for",
"The_Sea_Inside"
],
[
"Fine_Line_Features",
"nominated_for",
"Vera_Drake"
],
[
"Golden_Lion",
"award_winner",
"Robert_Altman"
],
[
"Golden_Lion",
"award_winner",
"Wim_Wenders"
],
[
"Golden_Lion",
"nominated_for",
"The_Sea_Inside"
],
[
"Grammy_Award_for_Best_Female_Rock_Vocal_Performance",
"award_winner",
"Alanis_Morissette"
],
[
"Gus_Van_Sant",
"acted_in",
"Jay_and_Silent_Bob_Strike_Back"
],
[
"Gus_Van_Sant",
"award",
"Golden_Lion"
],
[
"Island_Records",
"artist",
"Portishead"
],
[
"Island_Records",
"artist",
"Tom_Waits"
],
[
"Kim_Carnes",
"award",
"Grammy_Award_for_Best_Female_Rock_Vocal_Performance"
],
[
"Lo-fi_music",
"artists",
"Elliott_Smith"
],
[
"Lo-fi_music",
"artists",
"Portishead"
],
[
"Lyle_Lovett",
"acted_in",
"Cookie's_Fortune"
],
[
"Lyle_Lovett",
"acted_in",
"Short_Cuts"
],
[
"MCA_Records",
"artist",
"Alanis_Morissette"
],
[
"MCA_Records",
"artist",
"Kim_Carnes"
],
[
"MCA_Records",
"artist",
"Lyle_Lovett"
],
[
"MCA_Records",
"artist",
"Tommy_Lee"
],
[
"Mrs._Parker_and_the_Vicious_Circle",
"produced_by",
"Robert_Altman"
],
[
"Post-grunge",
"artists",
"Alanis_Morissette"
],
[
"Post-grunge",
"artists",
"Tommy_Lee"
],
[
"Robert_Altman",
"film",
"A_Prairie_Home_Companion"
],
[
"Robert_Altman",
"film",
"Cookie's_Fortune"
],
[
"Robert_Altman",
"film",
"Short_Cuts"
],
[
"Robert_Altman",
"nominated_for",
"A_Prairie_Home_Companion"
],
[
"Robert_Altman",
"nominated_for",
"Mrs._Parker_and_the_Vicious_Circle"
],
[
"Robert_Altman",
"nominated_for",
"Short_Cuts"
],
[
"Short_Cuts",
"award_honor_award",
"Golden_Lion"
],
[
"Short_Cuts",
"award_winner",
"Robert_Altman"
],
[
"Short_Cuts",
"production_companies",
"Fine_Line_Features"
],
[
"Short_Cuts",
"written_by",
"Robert_Altman"
],
[
"The_Devil_Wears_Prada",
"film_crew_role",
"Sound_Re-Recording_Mixer-GB"
],
[
"The_Devil_Wears_Prada",
"honored_for",
"A_Prairie_Home_Companion"
],
[
"The_Devil_Wears_Prada",
"nominated_for",
"A_Prairie_Home_Companion"
],
[
"The_Sea_Inside",
"award_winner",
"Fine_Line_Features"
],
[
"Tom_Waits",
"acted_in",
"Short_Cuts"
],
[
"Vera_Drake",
"award_honor_award",
"Golden_Lion"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3821, Aldous_Huxley
70, Anne_Rice
5761, Astrid_Lindgren_Memorial_Award
5139, C._S._Lewis
14111, Cardiovascular_disease
3986, Clive_Barker
619, Dan_Simmons
12614, Dante_Alighieri
11484, Diabetes_mellitus
10902, Diana_Wynne_Jones
9262, Donald_Crisp
12432, Epilepsy
2074, Fiction
5446, Fritz_Leiber
12368, Gene_Wolfe
1947, George_R._R._Martin
7749, Governor-GB
4838, Headache
4655, Hypertension
8319, J._K._Rowling
3579, J._R._R._Tolkien
6009, Jack_Vance
11806, John_Milton
12994, Jorge_Luis_Borges
417, Librarian
9252, Literature
220, Lloyd_Alexander
12139, Locus_Award_for_Best_Fantasy_Novel
3921, Lois_McMaster_Bujold
757, Maurice_Sendak
924, Mel_Blanc
3109, Michael_Moorcock
10186, Michael_Swanwick
1972, Neil_Gaiman
8541, Novel
3893, Obesity
9542, Okinawa_Prefecture
7561, Old_age
9310, Philip_K._Dick
1935, Philip_Pullman
9985, Poet
8877, Ray_Bradbury
5802, Robert_A._Heinlein
6829, Stephen_King
5137, Stroke
8475, T._S._Eliot
1598, Terry_Pratchett
10214, Theodore_Roosevelt
7144, Tobacco_smoking
2977, University_of_Oxford
4882, Ursula_K._Le_Guin
10728, William_Blake
13168, William_Howard_Taft
14132, Woodrow_Wilson
6951, World_Fantasy_Award_for_Best_Novel
src, edge_attr, dst
3821, influenced_by, 10728
70, award, 12139
70, influenced_by, 11806
5761, award_winner, 757
5761, category_of, 5761
5761, disciplines_or_subjects, 9252
5139, influenced_by, 11806
5139, influenced_by, 10728
14111, people, 924
14111, people, 5802
14111, people, 10214
14111, people, 13168
14111, risk_factors, 11484
14111, risk_factors, 4655
14111, risk_factors, 3893
14111, risk_factors, 7561
14111, risk_factors, 7144
3986, award, 12139
3986, influenced_by, 10728
619, award, 12139
11484, risk_factors, 7561
10902, award, 5761
10902, award, 12139
12432, risk_factors, 7561
12432, risk_factors, 5137
5446, award, 12139
12368, award, 6951
1947, award, 6951
7749, jurisdiction_of_office, 9542
4838, symptom_of, 14111
4838, symptom_of, 5137
8319, award, 5761
8319, award, 12139
3579, award, 12139
6009, award, 12139
6009, award, 6951
11806, influenced_by, 12614
11806, profession, 9985
12994, influenced_by, 10728
12994, profession, 417
220, award, 5761
220, award, 12139
12139, award_winner, 12368
12139, award_winner, 1947
12139, award_winner, 8319
12139, award_winner, 3579
12139, award_winner, 3921
12139, award_winner, 1972
12139, award_winner, 5802
12139, award_winner, 1598
12139, award_winner, 4882
12139, disciplines_or_subjects, 2074
12139, disciplines_or_subjects, 9252
12139, disciplines_or_subjects, 8541
3921, award, 12139
3921, award, 6951
757, influenced_by, 10728
3109, award, 12139
10186, award, 12139
10186, award, 6951
1972, award, 5761
1972, award, 12139
1972, award, 6951
3893, risk_factors, 7561
9310, award, 12139
1935, award, 5761
1935, award, 12139
1935, award, 6951
1935, influenced_by, 11806
1935, influenced_by, 10728
1935, profession, 417
8877, award, 12139
8877, award, 6951
5802, award, 12139
6829, award, 12139
6829, award, 6951
5137, people, 9262
5137, people, 757
5137, people, 924
5137, people, 9310
5137, people, 14132
5137, risk_factors, 11484
5137, risk_factors, 4655
5137, risk_factors, 3893
5137, risk_factors, 7561
5137, risk_factors, 7144
8475, influenced_by, 11806
1598, award, 12139
1598, award, 6951
10214, basic_title, 7749
2977, campuses, 2977
2977, educational_institution, 2977
2977, major_field_of_study, 9252
2977, student, 3821
2977, student, 5139
2977, student, 10902
2977, student, 9262
2977, student, 3579
2977, student, 1935
2977, student, 8475
4882, award, 5761
4882, award, 6951
10728, influenced_by, 12614
10728, influenced_by, 11806
10728, profession, 9985
13168, basic_title, 7749
14132, basic_title, 7749
6951, award_winner, 619
6951, award_winner, 5446
6951, award_winner, 12368
6951, award_winner, 6009
6951, award_winner, 3109
6951, award_winner, 4882
6951, disciplines_or_subjects, 2074
6951, disciplines_or_subjects, 9252
6951, disciplines_or_subjects, 8541
Question: For what reason are Obesity, Okinawa_Prefecture, and Philip_Pullman associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Obesity",
"Okinawa_Prefecture",
"Philip_Pullman"
],
"valid_edges": [
[
"Aldous_Huxley",
"influenced_by",
"William_Blake"
],
[
"Anne_Rice",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Anne_Rice",
"influenced_by",
"John_Milton"
],
[
"Astrid_Lindgren_Memorial_Award",
"award_winner",
"Maurice_Sendak"
],
[
"Astrid_Lindgren_Memorial_Award",
"category_of",
"Astrid_Lindgren_Memorial_Award"
],
[
"Astrid_Lindgren_Memorial_Award",
"disciplines_or_subjects",
"Literature"
],
[
"C._S._Lewis",
"influenced_by",
"John_Milton"
],
[
"C._S._Lewis",
"influenced_by",
"William_Blake"
],
[
"Cardiovascular_disease",
"people",
"Mel_Blanc"
],
[
"Cardiovascular_disease",
"people",
"Robert_A._Heinlein"
],
[
"Cardiovascular_disease",
"people",
"Theodore_Roosevelt"
],
[
"Cardiovascular_disease",
"people",
"William_Howard_Taft"
],
[
"Cardiovascular_disease",
"risk_factors",
"Diabetes_mellitus"
],
[
"Cardiovascular_disease",
"risk_factors",
"Hypertension"
],
[
"Cardiovascular_disease",
"risk_factors",
"Obesity"
],
[
"Cardiovascular_disease",
"risk_factors",
"Old_age"
],
[
"Cardiovascular_disease",
"risk_factors",
"Tobacco_smoking"
],
[
"Clive_Barker",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Clive_Barker",
"influenced_by",
"William_Blake"
],
[
"Dan_Simmons",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Diabetes_mellitus",
"risk_factors",
"Old_age"
],
[
"Diana_Wynne_Jones",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Diana_Wynne_Jones",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Epilepsy",
"risk_factors",
"Old_age"
],
[
"Epilepsy",
"risk_factors",
"Stroke"
],
[
"Fritz_Leiber",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Gene_Wolfe",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"George_R._R._Martin",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Governor-GB",
"jurisdiction_of_office",
"Okinawa_Prefecture"
],
[
"Headache",
"symptom_of",
"Cardiovascular_disease"
],
[
"Headache",
"symptom_of",
"Stroke"
],
[
"J._K._Rowling",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"J._K._Rowling",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"J._R._R._Tolkien",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Jack_Vance",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Jack_Vance",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"John_Milton",
"influenced_by",
"Dante_Alighieri"
],
[
"John_Milton",
"profession",
"Poet"
],
[
"Jorge_Luis_Borges",
"influenced_by",
"William_Blake"
],
[
"Jorge_Luis_Borges",
"profession",
"Librarian"
],
[
"Lloyd_Alexander",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Lloyd_Alexander",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Gene_Wolfe"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"George_R._R._Martin"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"J._K._Rowling"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"J._R._R._Tolkien"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Lois_McMaster_Bujold"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Neil_Gaiman"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Robert_A._Heinlein"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Terry_Pratchett"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"award_winner",
"Ursula_K._Le_Guin"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"disciplines_or_subjects",
"Fiction"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"disciplines_or_subjects",
"Literature"
],
[
"Locus_Award_for_Best_Fantasy_Novel",
"disciplines_or_subjects",
"Novel"
],
[
"Lois_McMaster_Bujold",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Lois_McMaster_Bujold",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Maurice_Sendak",
"influenced_by",
"William_Blake"
],
[
"Michael_Moorcock",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Michael_Swanwick",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Michael_Swanwick",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Neil_Gaiman",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Neil_Gaiman",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Neil_Gaiman",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Obesity",
"risk_factors",
"Old_age"
],
[
"Philip_K._Dick",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Philip_Pullman",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Philip_Pullman",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Philip_Pullman",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Philip_Pullman",
"influenced_by",
"John_Milton"
],
[
"Philip_Pullman",
"influenced_by",
"William_Blake"
],
[
"Philip_Pullman",
"profession",
"Librarian"
],
[
"Ray_Bradbury",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Ray_Bradbury",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Robert_A._Heinlein",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Stephen_King",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Stephen_King",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Stroke",
"people",
"Donald_Crisp"
],
[
"Stroke",
"people",
"Maurice_Sendak"
],
[
"Stroke",
"people",
"Mel_Blanc"
],
[
"Stroke",
"people",
"Philip_K._Dick"
],
[
"Stroke",
"people",
"Woodrow_Wilson"
],
[
"Stroke",
"risk_factors",
"Diabetes_mellitus"
],
[
"Stroke",
"risk_factors",
"Hypertension"
],
[
"Stroke",
"risk_factors",
"Obesity"
],
[
"Stroke",
"risk_factors",
"Old_age"
],
[
"Stroke",
"risk_factors",
"Tobacco_smoking"
],
[
"T._S._Eliot",
"influenced_by",
"John_Milton"
],
[
"Terry_Pratchett",
"award",
"Locus_Award_for_Best_Fantasy_Novel"
],
[
"Terry_Pratchett",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"Theodore_Roosevelt",
"basic_title",
"Governor-GB"
],
[
"University_of_Oxford",
"campuses",
"University_of_Oxford"
],
[
"University_of_Oxford",
"educational_institution",
"University_of_Oxford"
],
[
"University_of_Oxford",
"major_field_of_study",
"Literature"
],
[
"University_of_Oxford",
"student",
"Aldous_Huxley"
],
[
"University_of_Oxford",
"student",
"C._S._Lewis"
],
[
"University_of_Oxford",
"student",
"Diana_Wynne_Jones"
],
[
"University_of_Oxford",
"student",
"Donald_Crisp"
],
[
"University_of_Oxford",
"student",
"J._R._R._Tolkien"
],
[
"University_of_Oxford",
"student",
"Philip_Pullman"
],
[
"University_of_Oxford",
"student",
"T._S._Eliot"
],
[
"Ursula_K._Le_Guin",
"award",
"Astrid_Lindgren_Memorial_Award"
],
[
"Ursula_K._Le_Guin",
"award",
"World_Fantasy_Award_for_Best_Novel"
],
[
"William_Blake",
"influenced_by",
"Dante_Alighieri"
],
[
"William_Blake",
"influenced_by",
"John_Milton"
],
[
"William_Blake",
"profession",
"Poet"
],
[
"William_Howard_Taft",
"basic_title",
"Governor-GB"
],
[
"Woodrow_Wilson",
"basic_title",
"Governor-GB"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Dan_Simmons"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Fritz_Leiber"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Gene_Wolfe"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Jack_Vance"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Michael_Moorcock"
],
[
"World_Fantasy_Award_for_Best_Novel",
"award_winner",
"Ursula_K._Le_Guin"
],
[
"World_Fantasy_Award_for_Best_Novel",
"disciplines_or_subjects",
"Fiction"
],
[
"World_Fantasy_Award_for_Best_Novel",
"disciplines_or_subjects",
"Literature"
],
[
"World_Fantasy_Award_for_Best_Novel",
"disciplines_or_subjects",
"Novel"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2190, Albert_Wolsky
2056, Ali
2691, Anaconda
13805, Arcadia
5480, Congo
13287, Danny_Trejo
11142, Dumb_&_Dumber
7633, Enemy_of_the_State
6750, Final_Destination
9257, Freddy_vs._Jason
466, Galaxy_Quest
7882, Grease
11033, Grindhouse
8120, Halloween
288, Heat
12651, Holes
3364, Indian_people
2699, Jon_Voight
2892, Lucky_Numbers
3467, Michael_Biehn
8455, Raj_Babbar
6544, Randy_Edelman
9843, Razzie_Award_for_Worst_New_Star
7515, Saturn_Award_for_Best_Actress
201, Scary_Movie_2
5050, Scream_2
7242, Splash
10218, Striptease
13606, Teen_film
13701, Terminator_2:_Judgment_Day
1713, The_Goonies
6435, The_Manchurian_Candidate
5599, The_Mask
6557, The_Mask_of_Zorro
6083, VHS
4554, xXx
src, edge_attr, dst
2190, nominated_for, 466
2056, award_winner, 2699
2691, featured_film_locations, 13805
2691, film_music, 6544
13805, place, 13805
5480, featured_film_locations, 13805
13287, acted_in, 2691
13287, acted_in, 11033
13287, acted_in, 8120
13287, acted_in, 288
13287, acted_in, 4554
11142, film_distribution_medium, 6083
7633, film_distribution_medium, 6083
6750, film_distribution_medium, 6083
6750, genre, 13606
9257, film_distribution_medium, 6083
9257, genre, 13606
466, costume_design_by, 2190
7882, costume_design_by, 2190
7882, film_distribution_medium, 6083
7882, genre, 13606
8120, genre, 13606
12651, genre, 13606
3364, people, 2056
3364, people, 8455
2699, acted_in, 2056
2699, acted_in, 2691
2699, acted_in, 7633
2699, acted_in, 288
2699, acted_in, 12651
2699, acted_in, 6435
2699, nominated_for, 2056
2892, costume_design_by, 2190
2892, featured_film_locations, 13805
3467, acted_in, 7882
3467, acted_in, 11033
3467, acted_in, 13701
6544, nominated_for, 2691
9843, nominated_for, 2691
9843, nominated_for, 5480
9843, nominated_for, 11142
9843, nominated_for, 5050
9843, nominated_for, 5599
7515, nominated_for, 2691
7515, nominated_for, 466
7515, nominated_for, 11033
7515, nominated_for, 7242
7515, nominated_for, 6557
201, film_distribution_medium, 6083
201, genre, 13606
5050, genre, 13606
7242, award_honor_award, 7515
7242, film_distribution_medium, 6083
10218, costume_design_by, 2190
10218, film_distribution_medium, 6083
13701, featured_film_locations, 13805
1713, film_distribution_medium, 6083
1713, genre, 13606
6435, costume_design_by, 2190
5599, film_distribution_medium, 6083
5599, film_music, 6544
6557, film_distribution_medium, 6083
4554, film_music, 6544
Question: How are Anaconda, Grease, and Raj_Babbar related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Anaconda",
"Grease",
"Raj_Babbar"
],
"valid_edges": [
[
"Albert_Wolsky",
"nominated_for",
"Galaxy_Quest"
],
[
"Ali",
"award_winner",
"Jon_Voight"
],
[
"Anaconda",
"featured_film_locations",
"Arcadia"
],
[
"Anaconda",
"film_music",
"Randy_Edelman"
],
[
"Arcadia",
"place",
"Arcadia"
],
[
"Congo",
"featured_film_locations",
"Arcadia"
],
[
"Danny_Trejo",
"acted_in",
"Anaconda"
],
[
"Danny_Trejo",
"acted_in",
"Grindhouse"
],
[
"Danny_Trejo",
"acted_in",
"Halloween"
],
[
"Danny_Trejo",
"acted_in",
"Heat"
],
[
"Danny_Trejo",
"acted_in",
"xXx"
],
[
"Dumb_&_Dumber",
"film_distribution_medium",
"VHS"
],
[
"Enemy_of_the_State",
"film_distribution_medium",
"VHS"
],
[
"Final_Destination",
"film_distribution_medium",
"VHS"
],
[
"Final_Destination",
"genre",
"Teen_film"
],
[
"Freddy_vs._Jason",
"film_distribution_medium",
"VHS"
],
[
"Freddy_vs._Jason",
"genre",
"Teen_film"
],
[
"Galaxy_Quest",
"costume_design_by",
"Albert_Wolsky"
],
[
"Grease",
"costume_design_by",
"Albert_Wolsky"
],
[
"Grease",
"film_distribution_medium",
"VHS"
],
[
"Grease",
"genre",
"Teen_film"
],
[
"Halloween",
"genre",
"Teen_film"
],
[
"Holes",
"genre",
"Teen_film"
],
[
"Indian_people",
"people",
"Ali"
],
[
"Indian_people",
"people",
"Raj_Babbar"
],
[
"Jon_Voight",
"acted_in",
"Ali"
],
[
"Jon_Voight",
"acted_in",
"Anaconda"
],
[
"Jon_Voight",
"acted_in",
"Enemy_of_the_State"
],
[
"Jon_Voight",
"acted_in",
"Heat"
],
[
"Jon_Voight",
"acted_in",
"Holes"
],
[
"Jon_Voight",
"acted_in",
"The_Manchurian_Candidate"
],
[
"Jon_Voight",
"nominated_for",
"Ali"
],
[
"Lucky_Numbers",
"costume_design_by",
"Albert_Wolsky"
],
[
"Lucky_Numbers",
"featured_film_locations",
"Arcadia"
],
[
"Michael_Biehn",
"acted_in",
"Grease"
],
[
"Michael_Biehn",
"acted_in",
"Grindhouse"
],
[
"Michael_Biehn",
"acted_in",
"Terminator_2:_Judgment_Day"
],
[
"Randy_Edelman",
"nominated_for",
"Anaconda"
],
[
"Razzie_Award_for_Worst_New_Star",
"nominated_for",
"Anaconda"
],
[
"Razzie_Award_for_Worst_New_Star",
"nominated_for",
"Congo"
],
[
"Razzie_Award_for_Worst_New_Star",
"nominated_for",
"Dumb_&_Dumber"
],
[
"Razzie_Award_for_Worst_New_Star",
"nominated_for",
"Scream_2"
],
[
"Razzie_Award_for_Worst_New_Star",
"nominated_for",
"The_Mask"
],
[
"Saturn_Award_for_Best_Actress",
"nominated_for",
"Anaconda"
],
[
"Saturn_Award_for_Best_Actress",
"nominated_for",
"Galaxy_Quest"
],
[
"Saturn_Award_for_Best_Actress",
"nominated_for",
"Grindhouse"
],
[
"Saturn_Award_for_Best_Actress",
"nominated_for",
"Splash"
],
[
"Saturn_Award_for_Best_Actress",
"nominated_for",
"The_Mask_of_Zorro"
],
[
"Scary_Movie_2",
"film_distribution_medium",
"VHS"
],
[
"Scary_Movie_2",
"genre",
"Teen_film"
],
[
"Scream_2",
"genre",
"Teen_film"
],
[
"Splash",
"award_honor_award",
"Saturn_Award_for_Best_Actress"
],
[
"Splash",
"film_distribution_medium",
"VHS"
],
[
"Striptease",
"costume_design_by",
"Albert_Wolsky"
],
[
"Striptease",
"film_distribution_medium",
"VHS"
],
[
"Terminator_2:_Judgment_Day",
"featured_film_locations",
"Arcadia"
],
[
"The_Goonies",
"film_distribution_medium",
"VHS"
],
[
"The_Goonies",
"genre",
"Teen_film"
],
[
"The_Manchurian_Candidate",
"costume_design_by",
"Albert_Wolsky"
],
[
"The_Mask",
"film_distribution_medium",
"VHS"
],
[
"The_Mask",
"film_music",
"Randy_Edelman"
],
[
"The_Mask_of_Zorro",
"film_distribution_medium",
"VHS"
],
[
"xXx",
"film_music",
"Randy_Edelman"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7488, 20th-century_classical_music
10127, 54th_Annual_Grammy_Awards-US
4579, 60th_Academy_Awards
4936, A._R._Rahman
12182, Adolph_Deutsch
8844, All_the_King's_Men
9839, Amadeus
3389, Andrea_Bocelli
11394, Arabic_Language
2878, Aretha_Franklin
1459, Arnold_Schoenberg
1371, Avant-garde
13912, Ballet
6997, Barry_Manilow
6588, Benjamin_Britten
9603, Billy_Joel
13845, Bobby_McFerrin
13589, Brian_Tyler
3261, Bugsy
3711, Carl_Davis
10770, Chamber_music
13745, Chick_Corea
6261, Cinema_Paradiso
5008, Classical_music
12232, Claude_Debussy
797, Conductor
920, Contemporary_classical_music
8709, Daniel_Barenboim
8584, Dave_Grusin
10125, Dimitri_Tiomkin
10710, Dmitri_Shostakovich
1854, Edward_Elgar
14170, Elmer_Bernstein
2633, Ennio_Morricone
3221, Erich_Wolfgang_Korngold
975, Felix_Mendelssohn-Bartholdy
8426, Filipino
714, Frank_Sinatra
12096, Frank_Zappa
9053, Franz_Liszt
10576, Franz_Schubert
1392, Georg_Solti
2944, George_Frideric_Handel
10364, George_Gershwin
4656, Gioacchino_Rossini
5957, Giuseppe_Verdi
13323, Grammy_Award_for_Best_Classical_Album
1270, Grammy_Award_for_Best_Classical_Contemporary_Composition
5909, Grammy_Award_for_Best_Orchestral_Performance
11545, Grammy_Lifetime_Achievement_Award
13169, Heart_failure
13532, Igor_Stravinsky
1799, Isaac_Stern
10224, Itzhak_Perlman
4275, James_Levine
12140, Jamie_Foxx
5823, Jerry_Goldsmith
10477, Jerry_Lee_Lewis
5465, Jessye_Norman
10544, Johannes_Brahms
6989, John_Barrowman
5966, John_Cage
3740, Jon_Lord
3044, Joseph_Haydn
7738, Lalo_Schifrin
4957, Leonard_Bernstein
11195, London_Film_Critics_Circle_Award_for_Actor_of_the_Year
8427, Looney_Tunes:_Back_in_Action
3511, Lorenzo_Ferrero
6764, Ludwig_van_Beethoven
2408, Malcolm_Arnold
9272, Marvin_Hamlisch
4707, Michael_Nyman
12997, Michel_Colombier
1848, Michel_Legrand
6827, Mstislav_Rostropovich
7543, Music_Director
5276, Nikolai_Rimsky-Korsakov
3225, Nino_Rota
2621, Once_Upon_a_Time_in_America
5503, Opera
12029, Patricia_Clarkson
10299, Patrizia_von_Brandenstein
10713, Patton
4003, Philip_Glass
9725, Pianist-GB
2609, Pierre_Boulez
7108, Pyotr_Ilyich_Tchaikovsky
10581, Ralph_Vaughan_Williams
3932, Razzie_Award_for_Worst_Original_Song
11107, Richard_Rodgers
12891, Richard_Strauss
2831, Richard_Wagner
3835, Robert_Alexander_Schumann
12864, Russian
13391, Russian_American
2403, Ryuichi_Sakamoto
4522, Saint_Petersburg
896, Saint_Petersburg_Conservatory
11436, San_Diego
7026, Scott_Bradley
11095, Sean_Connery
10389, Sergei_Prokofiev
11086, Sergei_Rachmaninoff
12001, Sicilian_Mafia
13669, Six_Degrees_of_Separation
4824, The_Mothers_of_Invention
2679, The_Mummy
4218, The_Sum_of_All_Fears
6956, The_Untouchables
3779, Vladimir_Horowitz
2439, Wolfgang_Amadeus_Mozart
12242, Yo-Yo_Ma
src, edge_attr, dst
7488, artists, 1459
7488, artists, 6588
7488, artists, 3711
7488, artists, 12232
7488, artists, 10710
7488, artists, 3221
7488, artists, 10364
7488, artists, 13532
7488, artists, 5966
7488, artists, 3740
7488, artists, 4957
7488, artists, 4707
7488, artists, 3225
7488, artists, 2609
7488, artists, 10581
7488, artists, 10389
7488, parent_genre, 5008
4579, award_winner, 2403
4579, award_winner, 11095
4579, honored_for, 6956
4936, profession, 797
12182, profession, 797
8844, film_production_design_by, 10299
9839, film_production_design_by, 10299
1459, profession, 797
1371, artists, 12096
1371, parent_genre, 7488
13912, artists, 6588
13912, artists, 3711
13912, artists, 12232
13912, artists, 10710
13912, artists, 1854
13912, artists, 13532
13912, artists, 5966
13912, artists, 4957
13912, artists, 3511
13912, artists, 2408
13912, artists, 4707
13912, artists, 12997
13912, artists, 7108
13912, artists, 10581
13912, artists, 11107
13912, artists, 12891
13912, artists, 10389
13912, artists, 2439
6997, profession, 797
6997, profession, 9725
6588, award, 13323
6588, award, 1270
6588, profession, 797
6588, profession, 9725
9603, profession, 9725
13845, profession, 797
13589, profession, 797
3261, film_music, 2633
3711, profession, 797
10770, artists, 1459
10770, artists, 6588
10770, artists, 1854
10770, artists, 975
10770, artists, 9053
10770, artists, 10576
10770, artists, 13532
10770, artists, 3044
10770, artists, 3511
10770, artists, 5276
10770, artists, 10581
10770, artists, 12891
10770, artists, 11086
10770, artists, 2439
10770, parent_genre, 5008
13745, profession, 9725
6261, award_honor_award, 11195
6261, award_winner, 2633
5008, artists, 4936
5008, artists, 3389
5008, artists, 2878
5008, artists, 1459
5008, artists, 9603
5008, artists, 13845
5008, artists, 13589
5008, artists, 13745
5008, artists, 12232
5008, artists, 8709
5008, artists, 10710
5008, artists, 1854
5008, artists, 2633
5008, artists, 975
5008, artists, 9053
5008, artists, 10576
5008, artists, 1392
5008, artists, 2944
5008, artists, 4656
5008, artists, 5957
5008, artists, 13532
5008, artists, 1799
5008, artists, 10224
5008, artists, 5465
5008, artists, 10544
5008, artists, 3044
5008, artists, 6764
5008, artists, 5276
5008, artists, 4003
5008, artists, 7108
5008, artists, 10581
5008, artists, 12891
5008, artists, 2831
5008, artists, 3835
5008, artists, 2403
5008, artists, 10389
5008, artists, 11086
5008, artists, 4824
5008, artists, 3779
5008, artists, 2439
5008, artists, 12242
5008, titles, 9839
12232, profession, 9725
920, artists, 5823
920, parent_genre, 5008
8709, award, 13323
8709, award, 5909
8709, profession, 797
8709, profession, 9725
8584, profession, 797
8584, profession, 9725
10125, profession, 797
10710, company, 896
10710, location, 4522
10710, place_of_birth, 4522
10710, profession, 797
10710, profession, 9725
1854, profession, 797
14170, profession, 797
14170, profession, 9725
2633, award, 3932
2633, nominated_for, 3261
2633, nominated_for, 6261
2633, nominated_for, 2621
2633, nominated_for, 6956
2633, profession, 797
2633, profession, 7543
2633, profession, 9725
3221, profession, 797
975, profession, 797
975, profession, 9725
8426, languages_spoken, 11394
714, profession, 797
12096, group, 4824
12096, influenced_by, 13532
12096, location, 11436
12096, profession, 797
9053, profession, 9725
10576, profession, 9725
1392, award, 5909
1392, profession, 797
10364, profession, 9725
13323, award_winner, 6588
13323, award_winner, 8709
13323, award_winner, 1392
13323, award_winner, 13532
13323, award_winner, 1799
13323, award_winner, 4957
13323, award_winner, 6827
13323, award_winner, 3779
13323, award_winner, 12242
1270, award_winner, 6588
1270, award_winner, 13532
1270, award_winner, 4957
1270, award_winner, 2609
1270, ceremony, 10127
5909, award_winner, 8709
5909, award_winner, 1392
5909, award_winner, 13532
5909, award_winner, 4957
5909, award_winner, 2609
5909, ceremony, 10127
11545, award_winner, 2878
11545, award_winner, 714
11545, award_winner, 13532
11545, award_winner, 10477
11545, award_winner, 5465
11545, award_winner, 4957
11545, award_winner, 3779
13169, people, 12182
13169, people, 13532
13532, award, 13323
13532, award, 1270
13532, award, 5909
13532, award_winner, 1799
13532, location, 4522
13532, profession, 797
13532, profession, 9725
1799, award, 13323
1799, award_nominee, 10224
1799, award_nominee, 6827
1799, award_nominee, 3779
1799, award_nominee, 12242
1799, award_winner, 10224
1799, award_winner, 6827
1799, award_winner, 3779
1799, award_winner, 12242
1799, profession, 797
10224, award, 13323
10224, award_nominee, 1799
10224, award_winner, 1799
10224, profession, 797
4275, award, 13323
4275, award, 5909
4275, profession, 797
4275, profession, 9725
12140, profession, 9725
5823, influenced_by, 13532
5823, nominated_for, 10713
5823, nominated_for, 4218
5823, profession, 797
10477, profession, 9725
10544, profession, 9725
6989, acted_in, 6956
6989, location, 11436
3740, profession, 9725
7738, profession, 797
7738, profession, 9725
4957, award, 13323
4957, award, 1270
4957, award, 5909
4957, award_nominee, 1799
4957, award_winner, 1799
4957, profession, 797
4957, profession, 9725
11195, award_winner, 12140
11195, award_winner, 11095
8427, film_music, 5823
8427, produced_by, 11095
6764, profession, 9725
2408, profession, 797
9272, profession, 797
9272, profession, 9725
4707, profession, 9725
12997, profession, 797
1848, profession, 797
1848, profession, 9725
6827, award, 13323
6827, award_nominee, 1799
6827, award_winner, 1799
6827, profession, 797
7543, specialization_of, 797
5276, place_of_death, 4522
5276, profession, 797
3225, profession, 797
2621, award_winner, 2633
5503, artists, 3389
5503, artists, 6588
5503, artists, 10710
5503, artists, 3221
5503, artists, 975
5503, artists, 9053
5503, artists, 10576
5503, artists, 2944
5503, artists, 10364
5503, artists, 4656
5503, artists, 5957
5503, artists, 13532
5503, artists, 5465
5503, artists, 5966
5503, artists, 3044
5503, artists, 4957
5503, artists, 3511
5503, artists, 6764
5503, artists, 4707
5503, artists, 5276
5503, artists, 3225
5503, artists, 4003
5503, artists, 7108
5503, artists, 10581
5503, artists, 12891
5503, artists, 2831
5503, artists, 3835
5503, artists, 10389
5503, artists, 11086
5503, artists, 2439
12029, acted_in, 8844
12029, acted_in, 6956
10299, nominated_for, 9839
10299, nominated_for, 6956
10713, film_music, 5823
10713, language, 11394
4003, profession, 9725
2609, award, 13323
2609, award, 1270
2609, profession, 797
2609, profession, 9725
7108, place_of_death, 4522
3932, award_winner, 5823
11107, profession, 797
12891, profession, 797
2831, profession, 797
3835, profession, 9725
12864, people, 10710
12864, people, 13532
12864, people, 7108
12864, people, 10389
12864, people, 11086
13391, people, 13532
13391, people, 11086
2403, profession, 9725
4522, contains, 896
896, campuses, 896
896, citytown, 4522
896, educational_institution, 896
896, state_province_region, 4522
896, student, 10125
896, student, 10710
896, student, 13532
896, student, 7108
896, student, 10389
896, student, 11086
7026, profession, 797
7026, profession, 9725
11095, acted_in, 6956
11095, nominated_for, 6956
10389, profession, 797
10389, profession, 9725
11086, profession, 797
11086, profession, 9725
12001, films, 3261
12001, films, 2621
12001, films, 6956
13669, film_music, 5823
13669, film_production_design_by, 10299
2679, film_music, 5823
2679, language, 11394
4218, film_music, 5823
4218, language, 11394
6956, award_honor_award, 11195
6956, award_winner, 2633
6956, film_music, 2633
3779, award_nominee, 1799
3779, award_winner, 1799
3779, profession, 9725
2439, profession, 9725
12242, award, 13323
12242, award_nominee, 1799
Question: How are Filipino, Igor_Stravinsky, and The_Untouchables related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Filipino",
"Igor_Stravinsky",
"The_Untouchables"
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"valid_edges": [
[
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"Arnold_Schoenberg"
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[
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],
[
"20th-century_classical_music",
"artists",
"Carl_Davis"
],
[
"20th-century_classical_music",
"artists",
"Claude_Debussy"
],
[
"20th-century_classical_music",
"artists",
"Dmitri_Shostakovich"
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[
"20th-century_classical_music",
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[
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],
[
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],
[
"20th-century_classical_music",
"artists",
"John_Cage"
],
[
"20th-century_classical_music",
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[
"20th-century_classical_music",
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[
"20th-century_classical_music",
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[
"20th-century_classical_music",
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
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[
"Arnold_Schoenberg",
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[
"Avant-garde",
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[
"Avant-garde",
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"20th-century_classical_music"
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[
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[
"Ballet",
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[
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[
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[
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[
"Ballet",
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[
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[
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[
"Ballet",
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[
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[
"Ballet",
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[
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[
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[
"Ballet",
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[
"Ballet",
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[
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[
"Ballet",
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[
"Ballet",
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"Wolfgang_Amadeus_Mozart"
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[
"Barry_Manilow",
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[
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[
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[
"Carl_Davis",
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[
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[
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[
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[
"Classical_music",
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[
"Classical_music",
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"Classical_music",
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"Brian_Tyler"
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[
"Classical_music",
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"Chick_Corea"
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[
"Classical_music",
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[
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[
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"Classical_music",
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[
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"Felix_Mendelssohn-Bartholdy"
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[
"Classical_music",
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[
"Classical_music",
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[
"Classical_music",
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[
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"Classical_music",
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[
"Classical_music",
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"Isaac_Stern"
],
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[
"Classical_music",
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"Jessye_Norman"
],
[
"Classical_music",
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[
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[
"Classical_music",
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[
"Classical_music",
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[
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[
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[
"Classical_music",
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"Richard_Strauss"
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[
"Classical_music",
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[
"Classical_music",
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[
"Classical_music",
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[
"Classical_music",
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],
[
"Classical_music",
"artists",
"Sergei_Rachmaninoff"
],
[
"Classical_music",
"artists",
"The_Mothers_of_Invention"
],
[
"Classical_music",
"artists",
"Vladimir_Horowitz"
],
[
"Classical_music",
"artists",
"Wolfgang_Amadeus_Mozart"
],
[
"Classical_music",
"artists",
"Yo-Yo_Ma"
],
[
"Classical_music",
"titles",
"Amadeus"
],
[
"Claude_Debussy",
"profession",
"Pianist-GB"
],
[
"Contemporary_classical_music",
"artists",
"Jerry_Goldsmith"
],
[
"Contemporary_classical_music",
"parent_genre",
"Classical_music"
],
[
"Daniel_Barenboim",
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"Grammy_Award_for_Best_Classical_Album"
],
[
"Daniel_Barenboim",
"award",
"Grammy_Award_for_Best_Orchestral_Performance"
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[
"Daniel_Barenboim",
"profession",
"Conductor"
],
[
"Daniel_Barenboim",
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[
"Dave_Grusin",
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"Conductor"
],
[
"Dave_Grusin",
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[
"Dimitri_Tiomkin",
"profession",
"Conductor"
],
[
"Dmitri_Shostakovich",
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"Saint_Petersburg_Conservatory"
],
[
"Dmitri_Shostakovich",
"location",
"Saint_Petersburg"
],
[
"Dmitri_Shostakovich",
"place_of_birth",
"Saint_Petersburg"
],
[
"Dmitri_Shostakovich",
"profession",
"Conductor"
],
[
"Dmitri_Shostakovich",
"profession",
"Pianist-GB"
],
[
"Edward_Elgar",
"profession",
"Conductor"
],
[
"Elmer_Bernstein",
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"Conductor"
],
[
"Elmer_Bernstein",
"profession",
"Pianist-GB"
],
[
"Ennio_Morricone",
"award",
"Razzie_Award_for_Worst_Original_Song"
],
[
"Ennio_Morricone",
"nominated_for",
"Bugsy"
],
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"Ennio_Morricone",
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"Cinema_Paradiso"
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[
"Ennio_Morricone",
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[
"Ennio_Morricone",
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"The_Untouchables"
],
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],
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"Conductor"
],
[
"Felix_Mendelssohn-Bartholdy",
"profession",
"Pianist-GB"
],
[
"Filipino",
"languages_spoken",
"Arabic_Language"
],
[
"Frank_Sinatra",
"profession",
"Conductor"
],
[
"Frank_Zappa",
"group",
"The_Mothers_of_Invention"
],
[
"Frank_Zappa",
"influenced_by",
"Igor_Stravinsky"
],
[
"Frank_Zappa",
"location",
"San_Diego"
],
[
"Frank_Zappa",
"profession",
"Conductor"
],
[
"Franz_Liszt",
"profession",
"Pianist-GB"
],
[
"Franz_Schubert",
"profession",
"Pianist-GB"
],
[
"Georg_Solti",
"award",
"Grammy_Award_for_Best_Orchestral_Performance"
],
[
"Georg_Solti",
"profession",
"Conductor"
],
[
"George_Gershwin",
"profession",
"Pianist-GB"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Benjamin_Britten"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Daniel_Barenboim"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Georg_Solti"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Igor_Stravinsky"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Isaac_Stern"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Leonard_Bernstein"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Mstislav_Rostropovich"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Vladimir_Horowitz"
],
[
"Grammy_Award_for_Best_Classical_Album",
"award_winner",
"Yo-Yo_Ma"
],
[
"Grammy_Award_for_Best_Classical_Contemporary_Composition",
"award_winner",
"Benjamin_Britten"
],
[
"Grammy_Award_for_Best_Classical_Contemporary_Composition",
"award_winner",
"Igor_Stravinsky"
],
[
"Grammy_Award_for_Best_Classical_Contemporary_Composition",
"award_winner",
"Leonard_Bernstein"
],
[
"Grammy_Award_for_Best_Classical_Contemporary_Composition",
"award_winner",
"Pierre_Boulez"
],
[
"Grammy_Award_for_Best_Classical_Contemporary_Composition",
"ceremony",
"54th_Annual_Grammy_Awards-US"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"award_winner",
"Daniel_Barenboim"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"award_winner",
"Georg_Solti"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"award_winner",
"Igor_Stravinsky"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"award_winner",
"Leonard_Bernstein"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"award_winner",
"Pierre_Boulez"
],
[
"Grammy_Award_for_Best_Orchestral_Performance",
"ceremony",
"54th_Annual_Grammy_Awards-US"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Aretha_Franklin"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Frank_Sinatra"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Igor_Stravinsky"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Jerry_Lee_Lewis"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Jessye_Norman"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Leonard_Bernstein"
],
[
"Grammy_Lifetime_Achievement_Award",
"award_winner",
"Vladimir_Horowitz"
],
[
"Heart_failure",
"people",
"Adolph_Deutsch"
],
[
"Heart_failure",
"people",
"Igor_Stravinsky"
],
[
"Igor_Stravinsky",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Igor_Stravinsky",
"award",
"Grammy_Award_for_Best_Classical_Contemporary_Composition"
],
[
"Igor_Stravinsky",
"award",
"Grammy_Award_for_Best_Orchestral_Performance"
],
[
"Igor_Stravinsky",
"award_winner",
"Isaac_Stern"
],
[
"Igor_Stravinsky",
"location",
"Saint_Petersburg"
],
[
"Igor_Stravinsky",
"profession",
"Conductor"
],
[
"Igor_Stravinsky",
"profession",
"Pianist-GB"
],
[
"Isaac_Stern",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Isaac_Stern",
"award_nominee",
"Itzhak_Perlman"
],
[
"Isaac_Stern",
"award_nominee",
"Mstislav_Rostropovich"
],
[
"Isaac_Stern",
"award_nominee",
"Vladimir_Horowitz"
],
[
"Isaac_Stern",
"award_nominee",
"Yo-Yo_Ma"
],
[
"Isaac_Stern",
"award_winner",
"Itzhak_Perlman"
],
[
"Isaac_Stern",
"award_winner",
"Mstislav_Rostropovich"
],
[
"Isaac_Stern",
"award_winner",
"Vladimir_Horowitz"
],
[
"Isaac_Stern",
"award_winner",
"Yo-Yo_Ma"
],
[
"Isaac_Stern",
"profession",
"Conductor"
],
[
"Itzhak_Perlman",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Itzhak_Perlman",
"award_nominee",
"Isaac_Stern"
],
[
"Itzhak_Perlman",
"award_winner",
"Isaac_Stern"
],
[
"Itzhak_Perlman",
"profession",
"Conductor"
],
[
"James_Levine",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"James_Levine",
"award",
"Grammy_Award_for_Best_Orchestral_Performance"
],
[
"James_Levine",
"profession",
"Conductor"
],
[
"James_Levine",
"profession",
"Pianist-GB"
],
[
"Jamie_Foxx",
"profession",
"Pianist-GB"
],
[
"Jerry_Goldsmith",
"influenced_by",
"Igor_Stravinsky"
],
[
"Jerry_Goldsmith",
"nominated_for",
"Patton"
],
[
"Jerry_Goldsmith",
"nominated_for",
"The_Sum_of_All_Fears"
],
[
"Jerry_Goldsmith",
"profession",
"Conductor"
],
[
"Jerry_Lee_Lewis",
"profession",
"Pianist-GB"
],
[
"Johannes_Brahms",
"profession",
"Pianist-GB"
],
[
"John_Barrowman",
"acted_in",
"The_Untouchables"
],
[
"John_Barrowman",
"location",
"San_Diego"
],
[
"Jon_Lord",
"profession",
"Pianist-GB"
],
[
"Lalo_Schifrin",
"profession",
"Conductor"
],
[
"Lalo_Schifrin",
"profession",
"Pianist-GB"
],
[
"Leonard_Bernstein",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Leonard_Bernstein",
"award",
"Grammy_Award_for_Best_Classical_Contemporary_Composition"
],
[
"Leonard_Bernstein",
"award",
"Grammy_Award_for_Best_Orchestral_Performance"
],
[
"Leonard_Bernstein",
"award_nominee",
"Isaac_Stern"
],
[
"Leonard_Bernstein",
"award_winner",
"Isaac_Stern"
],
[
"Leonard_Bernstein",
"profession",
"Conductor"
],
[
"Leonard_Bernstein",
"profession",
"Pianist-GB"
],
[
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year",
"award_winner",
"Jamie_Foxx"
],
[
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year",
"award_winner",
"Sean_Connery"
],
[
"Looney_Tunes:_Back_in_Action",
"film_music",
"Jerry_Goldsmith"
],
[
"Looney_Tunes:_Back_in_Action",
"produced_by",
"Sean_Connery"
],
[
"Ludwig_van_Beethoven",
"profession",
"Pianist-GB"
],
[
"Malcolm_Arnold",
"profession",
"Conductor"
],
[
"Marvin_Hamlisch",
"profession",
"Conductor"
],
[
"Marvin_Hamlisch",
"profession",
"Pianist-GB"
],
[
"Michael_Nyman",
"profession",
"Pianist-GB"
],
[
"Michel_Colombier",
"profession",
"Conductor"
],
[
"Michel_Legrand",
"profession",
"Conductor"
],
[
"Michel_Legrand",
"profession",
"Pianist-GB"
],
[
"Mstislav_Rostropovich",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Mstislav_Rostropovich",
"award_nominee",
"Isaac_Stern"
],
[
"Mstislav_Rostropovich",
"award_winner",
"Isaac_Stern"
],
[
"Mstislav_Rostropovich",
"profession",
"Conductor"
],
[
"Music_Director",
"specialization_of",
"Conductor"
],
[
"Nikolai_Rimsky-Korsakov",
"place_of_death",
"Saint_Petersburg"
],
[
"Nikolai_Rimsky-Korsakov",
"profession",
"Conductor"
],
[
"Nino_Rota",
"profession",
"Conductor"
],
[
"Once_Upon_a_Time_in_America",
"award_winner",
"Ennio_Morricone"
],
[
"Opera",
"artists",
"Andrea_Bocelli"
],
[
"Opera",
"artists",
"Benjamin_Britten"
],
[
"Opera",
"artists",
"Dmitri_Shostakovich"
],
[
"Opera",
"artists",
"Erich_Wolfgang_Korngold"
],
[
"Opera",
"artists",
"Felix_Mendelssohn-Bartholdy"
],
[
"Opera",
"artists",
"Franz_Liszt"
],
[
"Opera",
"artists",
"Franz_Schubert"
],
[
"Opera",
"artists",
"George_Frideric_Handel"
],
[
"Opera",
"artists",
"George_Gershwin"
],
[
"Opera",
"artists",
"Gioacchino_Rossini"
],
[
"Opera",
"artists",
"Giuseppe_Verdi"
],
[
"Opera",
"artists",
"Igor_Stravinsky"
],
[
"Opera",
"artists",
"Jessye_Norman"
],
[
"Opera",
"artists",
"John_Cage"
],
[
"Opera",
"artists",
"Joseph_Haydn"
],
[
"Opera",
"artists",
"Leonard_Bernstein"
],
[
"Opera",
"artists",
"Lorenzo_Ferrero"
],
[
"Opera",
"artists",
"Ludwig_van_Beethoven"
],
[
"Opera",
"artists",
"Michael_Nyman"
],
[
"Opera",
"artists",
"Nikolai_Rimsky-Korsakov"
],
[
"Opera",
"artists",
"Nino_Rota"
],
[
"Opera",
"artists",
"Philip_Glass"
],
[
"Opera",
"artists",
"Pyotr_Ilyich_Tchaikovsky"
],
[
"Opera",
"artists",
"Ralph_Vaughan_Williams"
],
[
"Opera",
"artists",
"Richard_Strauss"
],
[
"Opera",
"artists",
"Richard_Wagner"
],
[
"Opera",
"artists",
"Robert_Alexander_Schumann"
],
[
"Opera",
"artists",
"Sergei_Prokofiev"
],
[
"Opera",
"artists",
"Sergei_Rachmaninoff"
],
[
"Opera",
"artists",
"Wolfgang_Amadeus_Mozart"
],
[
"Patricia_Clarkson",
"acted_in",
"All_the_King's_Men"
],
[
"Patricia_Clarkson",
"acted_in",
"The_Untouchables"
],
[
"Patrizia_von_Brandenstein",
"nominated_for",
"Amadeus"
],
[
"Patrizia_von_Brandenstein",
"nominated_for",
"The_Untouchables"
],
[
"Patton",
"film_music",
"Jerry_Goldsmith"
],
[
"Patton",
"language",
"Arabic_Language"
],
[
"Philip_Glass",
"profession",
"Pianist-GB"
],
[
"Pierre_Boulez",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Pierre_Boulez",
"award",
"Grammy_Award_for_Best_Classical_Contemporary_Composition"
],
[
"Pierre_Boulez",
"profession",
"Conductor"
],
[
"Pierre_Boulez",
"profession",
"Pianist-GB"
],
[
"Pyotr_Ilyich_Tchaikovsky",
"place_of_death",
"Saint_Petersburg"
],
[
"Razzie_Award_for_Worst_Original_Song",
"award_winner",
"Jerry_Goldsmith"
],
[
"Richard_Rodgers",
"profession",
"Conductor"
],
[
"Richard_Strauss",
"profession",
"Conductor"
],
[
"Richard_Wagner",
"profession",
"Conductor"
],
[
"Robert_Alexander_Schumann",
"profession",
"Pianist-GB"
],
[
"Russian",
"people",
"Dmitri_Shostakovich"
],
[
"Russian",
"people",
"Igor_Stravinsky"
],
[
"Russian",
"people",
"Pyotr_Ilyich_Tchaikovsky"
],
[
"Russian",
"people",
"Sergei_Prokofiev"
],
[
"Russian",
"people",
"Sergei_Rachmaninoff"
],
[
"Russian_American",
"people",
"Igor_Stravinsky"
],
[
"Russian_American",
"people",
"Sergei_Rachmaninoff"
],
[
"Ryuichi_Sakamoto",
"profession",
"Pianist-GB"
],
[
"Saint_Petersburg",
"contains",
"Saint_Petersburg_Conservatory"
],
[
"Saint_Petersburg_Conservatory",
"campuses",
"Saint_Petersburg_Conservatory"
],
[
"Saint_Petersburg_Conservatory",
"citytown",
"Saint_Petersburg"
],
[
"Saint_Petersburg_Conservatory",
"educational_institution",
"Saint_Petersburg_Conservatory"
],
[
"Saint_Petersburg_Conservatory",
"state_province_region",
"Saint_Petersburg"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Dimitri_Tiomkin"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Dmitri_Shostakovich"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Igor_Stravinsky"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Pyotr_Ilyich_Tchaikovsky"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Sergei_Prokofiev"
],
[
"Saint_Petersburg_Conservatory",
"student",
"Sergei_Rachmaninoff"
],
[
"Scott_Bradley",
"profession",
"Conductor"
],
[
"Scott_Bradley",
"profession",
"Pianist-GB"
],
[
"Sean_Connery",
"acted_in",
"The_Untouchables"
],
[
"Sean_Connery",
"nominated_for",
"The_Untouchables"
],
[
"Sergei_Prokofiev",
"profession",
"Conductor"
],
[
"Sergei_Prokofiev",
"profession",
"Pianist-GB"
],
[
"Sergei_Rachmaninoff",
"profession",
"Conductor"
],
[
"Sergei_Rachmaninoff",
"profession",
"Pianist-GB"
],
[
"Sicilian_Mafia",
"films",
"Bugsy"
],
[
"Sicilian_Mafia",
"films",
"Once_Upon_a_Time_in_America"
],
[
"Sicilian_Mafia",
"films",
"The_Untouchables"
],
[
"Six_Degrees_of_Separation",
"film_music",
"Jerry_Goldsmith"
],
[
"Six_Degrees_of_Separation",
"film_production_design_by",
"Patrizia_von_Brandenstein"
],
[
"The_Mummy",
"film_music",
"Jerry_Goldsmith"
],
[
"The_Mummy",
"language",
"Arabic_Language"
],
[
"The_Sum_of_All_Fears",
"film_music",
"Jerry_Goldsmith"
],
[
"The_Sum_of_All_Fears",
"language",
"Arabic_Language"
],
[
"The_Untouchables",
"award_honor_award",
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year"
],
[
"The_Untouchables",
"award_winner",
"Ennio_Morricone"
],
[
"The_Untouchables",
"film_music",
"Ennio_Morricone"
],
[
"Vladimir_Horowitz",
"award_nominee",
"Isaac_Stern"
],
[
"Vladimir_Horowitz",
"award_winner",
"Isaac_Stern"
],
[
"Vladimir_Horowitz",
"profession",
"Pianist-GB"
],
[
"Wolfgang_Amadeus_Mozart",
"profession",
"Pianist-GB"
],
[
"Yo-Yo_Ma",
"award",
"Grammy_Award_for_Best_Classical_Album"
],
[
"Yo-Yo_Ma",
"award_nominee",
"Isaac_Stern"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3380, Albert_Ludwigs_University_of_Freiburg
3644, Algeria
14053, Blood_Diamond
7647, Brazil
10757, Doctorate
6436, FC_Bayern_Munich
10052, FC_Vaslui
230, France
7173, Free_University_of_Berlin
4497, Friedrich_Schiller_University_of_Jena
3252, Germany
3063, Germany_national_football_team
4194, Goalkeeper
11841, Humboldt_University_of_Berlin
2980, Leo_Strauss
13909, Ludwig_Maximilian_University_of_Munich
11615, Martin_Heidegger
3605, Mexico
12212, Poland
12528, President
10977, South_Africa
10374, Technical_University_of_Berlin
12389, Technical_University_of_Munich
10672, Tsinghua_University
6107, University_of_Bonn
7448, University_of_Hamburg
7357, University_of_Kiel
6441, University_of_Leipzig
src, edge_attr, dst
14053, film_country, 3252
7647, combatants, 3252
10757, institution, 3380
10757, institution, 7173
10757, institution, 4497
10757, institution, 11841
10757, institution, 13909
10757, institution, 10374
10757, institution, 12389
10757, institution, 10672
10757, institution, 6107
10757, institution, 7448
10757, institution, 7357
10757, institution, 6441
10757, student, 2980
10757, student, 11615
6436, football_roster_position, 4194
6436, position, 4194
10052, football_roster_position, 4194
10052, position, 4194
230, adjoins, 3252
230, combatants, 3252
3252, adjoins, 230
3252, adjoins, 12212
3252, combatants, 7647
3252, combatants, 230
3252, combatants, 3605
3252, contains, 3380
3252, contains, 7173
3252, contains, 4497
3252, contains, 11841
3252, contains, 13909
3252, contains, 10374
3252, contains, 12389
3252, contains, 6107
3252, contains, 7448
3252, contains, 7357
3252, contains, 6441
3252, exported_to, 3644
3252, teams, 3063
3063, football_roster_position, 4194
3063, position, 4194
4194, team, 6436
4194, team, 3063
2980, nationality, 3252
11615, nationality, 3252
3605, combatants, 3252
12212, adjoins, 3252
12528, company, 6436
12528, company, 230
12528, jurisdiction_of_office, 3644
12528, jurisdiction_of_office, 7647
12528, jurisdiction_of_office, 230
12528, jurisdiction_of_office, 3252
12528, jurisdiction_of_office, 3605
12528, jurisdiction_of_office, 12212
12528, jurisdiction_of_office, 10977
12528, organization, 7173
12528, organization, 11841
12528, organization, 10374
12528, organization, 12389
12528, organization, 10672
12528, organization, 7448
12528, organization, 7357
10977, combatants, 3252
10672, campuses, 10672
Question: In what context are Blood_Diamond, FC_Vaslui, and Tsinghua_University connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Blood_Diamond",
"FC_Vaslui",
"Tsinghua_University"
],
"valid_edges": [
[
"Blood_Diamond",
"film_country",
"Germany"
],
[
"Brazil",
"combatants",
"Germany"
],
[
"Doctorate",
"institution",
"Albert_Ludwigs_University_of_Freiburg"
],
[
"Doctorate",
"institution",
"Free_University_of_Berlin"
],
[
"Doctorate",
"institution",
"Friedrich_Schiller_University_of_Jena"
],
[
"Doctorate",
"institution",
"Humboldt_University_of_Berlin"
],
[
"Doctorate",
"institution",
"Ludwig_Maximilian_University_of_Munich"
],
[
"Doctorate",
"institution",
"Technical_University_of_Berlin"
],
[
"Doctorate",
"institution",
"Technical_University_of_Munich"
],
[
"Doctorate",
"institution",
"Tsinghua_University"
],
[
"Doctorate",
"institution",
"University_of_Bonn"
],
[
"Doctorate",
"institution",
"University_of_Hamburg"
],
[
"Doctorate",
"institution",
"University_of_Kiel"
],
[
"Doctorate",
"institution",
"University_of_Leipzig"
],
[
"Doctorate",
"student",
"Leo_Strauss"
],
[
"Doctorate",
"student",
"Martin_Heidegger"
],
[
"FC_Bayern_Munich",
"football_roster_position",
"Goalkeeper"
],
[
"FC_Bayern_Munich",
"position",
"Goalkeeper"
],
[
"FC_Vaslui",
"football_roster_position",
"Goalkeeper"
],
[
"FC_Vaslui",
"position",
"Goalkeeper"
],
[
"France",
"adjoins",
"Germany"
],
[
"France",
"combatants",
"Germany"
],
[
"Germany",
"adjoins",
"France"
],
[
"Germany",
"adjoins",
"Poland"
],
[
"Germany",
"combatants",
"Brazil"
],
[
"Germany",
"combatants",
"France"
],
[
"Germany",
"combatants",
"Mexico"
],
[
"Germany",
"contains",
"Albert_Ludwigs_University_of_Freiburg"
],
[
"Germany",
"contains",
"Free_University_of_Berlin"
],
[
"Germany",
"contains",
"Friedrich_Schiller_University_of_Jena"
],
[
"Germany",
"contains",
"Humboldt_University_of_Berlin"
],
[
"Germany",
"contains",
"Ludwig_Maximilian_University_of_Munich"
],
[
"Germany",
"contains",
"Technical_University_of_Berlin"
],
[
"Germany",
"contains",
"Technical_University_of_Munich"
],
[
"Germany",
"contains",
"University_of_Bonn"
],
[
"Germany",
"contains",
"University_of_Hamburg"
],
[
"Germany",
"contains",
"University_of_Kiel"
],
[
"Germany",
"contains",
"University_of_Leipzig"
],
[
"Germany",
"exported_to",
"Algeria"
],
[
"Germany",
"teams",
"Germany_national_football_team"
],
[
"Germany_national_football_team",
"football_roster_position",
"Goalkeeper"
],
[
"Germany_national_football_team",
"position",
"Goalkeeper"
],
[
"Goalkeeper",
"team",
"FC_Bayern_Munich"
],
[
"Goalkeeper",
"team",
"Germany_national_football_team"
],
[
"Leo_Strauss",
"nationality",
"Germany"
],
[
"Martin_Heidegger",
"nationality",
"Germany"
],
[
"Mexico",
"combatants",
"Germany"
],
[
"Poland",
"adjoins",
"Germany"
],
[
"President",
"company",
"FC_Bayern_Munich"
],
[
"President",
"company",
"France"
],
[
"President",
"jurisdiction_of_office",
"Algeria"
],
[
"President",
"jurisdiction_of_office",
"Brazil"
],
[
"President",
"jurisdiction_of_office",
"France"
],
[
"President",
"jurisdiction_of_office",
"Germany"
],
[
"President",
"jurisdiction_of_office",
"Mexico"
],
[
"President",
"jurisdiction_of_office",
"Poland"
],
[
"President",
"jurisdiction_of_office",
"South_Africa"
],
[
"President",
"organization",
"Free_University_of_Berlin"
],
[
"President",
"organization",
"Humboldt_University_of_Berlin"
],
[
"President",
"organization",
"Technical_University_of_Berlin"
],
[
"President",
"organization",
"Technical_University_of_Munich"
],
[
"President",
"organization",
"Tsinghua_University"
],
[
"President",
"organization",
"University_of_Hamburg"
],
[
"President",
"organization",
"University_of_Kiel"
],
[
"South_Africa",
"combatants",
"Germany"
],
[
"Tsinghua_University",
"campuses",
"Tsinghua_University"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9441, 44th_Annual_Grammy_Awards
7209, 46th_Annual_Grammy_Awards
6500, 50_Cent
10064, Aerospace_Engineering-GB
7520, Anaheim
236, Artist-GB
111, Boston_Celtics
8956, Brandy_Norwood
12776, Buffalo_Sabres
10748, Business_Administration
8980, Busta_Rhymes
14090, California_Polytechnic_State_University
10051, California_State_University,_Los_Angeles
409, Carolina_Panthers
1764, Carson_City
13137, Celine_Dion
11937, Chicago_White_Sox
10334, Christina_Aguilera
3987, College_of_William_and_Mary
13915, Colorado_Buffaloes_football
3601, Compton
11116, Computer_Science
11854, Contemporary_R&B
2998, Dance-pop
4199, Dance_music
12028, Dr._Dre
2139, Eminem
3485, Fergie
9178, Finance
4172, Fred_Durst
10687, Fullerton
13060, G-funk
7884, Gangsta_rap
9006, Gold
3683, Golden_State_Warriors
5678, Grammy_Award_for_Best_Female_Pop_Vocal_Performance
1978, Grammy_Award_for_Best_Music_Video
5614, Grammy_Award_for_Best_New_Artist
13185, Grammy_Award_for_Best_Pop_Collaboration_with_Vocals
11111, Grammy_Award_for_Best_Pop_Vocal_Album
4023, Grammy_Award_for_Best_R&B_Performance_by_a_Duo_or_Group_with_Vocals
7183, Grammy_Award_for_Best_R&B_Song
3772, Grammy_Award_for_Best_Rap/Sung_Collaboration
1227, Grammy_Award_for_Best_Rap_Album
342, Grammy_Award_for_Best_Rap_Performance_by_a_Duo_or_Group
10750, Grammy_Award_for_Best_Rap_Solo_Performance
9607, Grammy_Award_for_Best_Rock_Album
9569, Grammy_Award_for_Song_of_the_Year
8583, Gwen_Stefani
13230, Hip_hop_music
1904, Indiana_Pacers
5707, Indianapolis
6420, Interscope_Records
9081, Jennifer_Lopez
238, Justin_Timberlake
10997, KYMX
4970, Kanye_West
8624, Kent_State_University
14166, Land-grant_university
10345, Las_Vegas
12954, Lenny_Kravitz
1481, Leonardo_DiCaprio
9698, Linda_Perry
834, Long_Island_University
13309, Los_Angeles_Angels_of_Anaheim
3215, MTV_Video_Music_Award_for_Artist_to_Watch
11269, MTV_Video_Music_Award_for_Best_Art_Direction
617, MTV_Video_Music_Award_for_Best_Choreography
1825, MTV_Video_Music_Award_for_Best_Direction
4178, MTV_Video_Music_Award_for_Best_Editing
2095, MTV_Video_Music_Award_for_Best_Female_Video
10227, MTV_Video_Music_Award_for_Best_Male_Video
7874, MTV_Video_Music_Award_for_Best_Pop_Video
3657, MTV_Video_Music_Award_for_Best_R&B_Video
10555, MTV_Video_Music_Award_for_Video_of_the_Year
2622, Madonna
11282, Mariah_Carey
1521, Marion_County
10825, Mark_Stent
2261, Marketing-GB
3626, Marquette_University
7957, Mathematics
8705, Mechanical_Engineering
6897, Missy_Elliott
10473, Navy_Blue
9215, Ne-Yo
7010, Nevada
5057, New_Mexico_State_University
532, Nick_Cannon
9051, No_Doubt
7486, Oakland_Raiders
10643, P!nk
13804, Pacific_Time_Zone
2752, Paris
10738, Phil_Tan
13024, Placer_County
5284, Psychology
8703, Punk_rock
7142, Queen_Latifah
3248, Razzie_Award_for_Worst_Actress
7431, Razzie_Award_for_Worst_Screen_Couple/Ensemble
6632, Reno
9695, Rihanna
6782, Robbie_Williams
8066, San_JosΓ©_State_University
11953, Sean_Combs
10650, Silver
426, Soul_music
6357, The_Neptunes
4823, Tupac_Shakur
2545, Tyrese_Gibson
7845, United_States_Naval_Academy
6515, University_of_Arizona
2363, University_of_California,_Davis
6644, University_of_California,_San_Diego
11425, University_of_Colorado_Boulder
2680, University_of_Idaho
3219, University_of_Memphis
13884, University_of_Northern_Colorado
6128, University_of_Southern_California
12455, University_of_Victoria
12276, Victoria_Beckham
5077, Washoe_County
9421, Wellington_College,_Berkshire
4528, West_Coast_hip_hop
5783, Will_Smith
src, edge_attr, dst
9441, award_winner, 8583
7209, award_winner, 10334
7209, award_winner, 2139
7209, award_winner, 238
7209, award_winner, 6897
7209, award_winner, 9051
7209, award_winner, 10643
7209, award_winner, 6357
6500, award_nominee, 12028
6500, award_winner, 12028
6500, company, 6420
7520, time_zones, 13804
111, colors, 9006
111, school, 11425
12776, colors, 9006
12776, colors, 10650
8980, award_nominee, 4970
8980, participant, 11282
14090, colors, 9006
14090, time_zones, 13804
10051, colors, 9006
10051, time_zones, 13804
409, colors, 10650
409, school, 3219
1764, adjoins, 5077
1764, time_zones, 13804
11937, colors, 10650
11937, school, 6515
3987, colors, 9006
3987, colors, 10650
13915, colors, 9006
13915, colors, 10650
3601, time_zones, 13804
11854, artists, 8956
11854, artists, 13137
11854, artists, 10334
11854, artists, 3485
11854, artists, 8583
11854, artists, 9081
11854, artists, 238
11854, artists, 4970
11854, artists, 9698
11854, artists, 11282
11854, artists, 6897
11854, artists, 9215
11854, artists, 10643
11854, artists, 7142
11854, artists, 9695
11854, artists, 6782
11854, artists, 11953
11854, artists, 6357
11854, artists, 2545
11854, artists, 12276
2998, artists, 8583
2998, artists, 2622
4199, artists, 13137
4199, artists, 10334
4199, artists, 8583
4199, artists, 9081
4199, artists, 238
4199, artists, 2622
4199, artists, 11282
4199, artists, 6897
4199, artists, 9215
4199, artists, 10643
4199, artists, 9695
4199, artists, 6782
4199, artists, 6357
12028, artist_origin, 3601
12028, award, 1978
12028, award, 3772
12028, award, 1227
12028, award, 342
12028, award, 10750
12028, award, 617
12028, award, 3657
12028, award_nominee, 6500
12028, award_nominee, 2139
12028, award_nominee, 8583
12028, award_nominee, 9698
12028, award_nominee, 10825
12028, award_nominee, 6897
12028, award_nominee, 10643
12028, award_nominee, 10738
12028, award_nominee, 9695
12028, award_nominee, 4823
12028, award_winner, 6500
12028, award_winner, 2139
12028, location, 3601
12028, participant, 2139
12028, place_of_birth, 3601
12028, profession, 236
2139, award, 3772
2139, award_nominee, 4970
2139, award_nominee, 10738
2139, award_winner, 12028
2139, participant, 12028
2139, participant, 11282
3485, award, 3772
3485, award_nominee, 4970
10687, time_zones, 13804
13060, artists, 12028
13060, parent_genre, 13230
7884, artists, 12028
7884, parent_genre, 13230
3683, colors, 9006
3683, school, 6515
3683, school, 11425
3683, school, 3219
5678, ceremony, 7209
1978, award_winner, 2622
1978, ceremony, 7209
5614, award_winner, 11282
5614, ceremony, 7209
13185, ceremony, 7209
11111, award_winner, 2622
11111, ceremony, 7209
4023, ceremony, 7209
7183, award_winner, 4970
7183, award_winner, 11282
7183, ceremony, 7209
3772, award_winner, 3485
3772, award_winner, 8583
3772, award_winner, 9695
3772, ceremony, 9441
3772, ceremony, 7209
1227, award_winner, 12028
1227, award_winner, 4970
1227, award_winner, 10738
1227, ceremony, 7209
342, award_winner, 12028
342, award_winner, 4970
342, ceremony, 7209
10750, award_winner, 12028
10750, award_winner, 4970
9607, award_winner, 10825
9607, ceremony, 7209
9569, ceremony, 7209
8583, artist_origin, 7520
8583, award, 5678
8583, award, 13185
8583, award, 11111
8583, award, 3772
8583, award, 9569
8583, award, 11269
8583, award, 4178
8583, award, 2095
8583, award, 10227
8583, award, 7874
8583, award, 10555
8583, award_nominee, 12028
8583, award_nominee, 1481
8583, award_nominee, 10825
8583, award_nominee, 10738
8583, award_nominee, 6357
8583, group, 9051
8583, location, 7520
8583, location, 10687
8583, participant, 12276
8583, place_of_birth, 10687
8583, profession, 236
13230, artists, 6500
13230, artists, 8956
13230, artists, 8980
13230, artists, 10334
13230, artists, 12028
13230, artists, 2139
13230, artists, 3485
13230, artists, 4172
13230, artists, 9081
13230, artists, 238
13230, artists, 4970
13230, artists, 11282
13230, artists, 6897
13230, artists, 9215
13230, artists, 532
13230, artists, 10643
13230, artists, 7142
13230, artists, 9695
13230, artists, 6782
13230, artists, 11953
13230, artists, 6357
13230, artists, 4823
13230, artists, 2545
13230, artists, 5783
1904, colors, 9006
1904, colors, 10473
1904, colors, 10650
1904, school, 5057
1904, school, 6515
1904, school, 11425
1904, school, 3219
5707, administrative_division, 1521
5707, county, 1521
5707, place, 5707
5707, teams, 1904
6420, artist, 6500
6420, artist, 8980
6420, artist, 12028
6420, artist, 2139
6420, artist, 3485
6420, artist, 4172
6420, artist, 8583
6420, artist, 9698
6420, artist, 2622
6420, artist, 9051
6420, artist, 7142
6420, artist, 11953
6420, artist, 6357
6420, artist, 4823
6420, artist, 5783
238, award, 3772
238, award_nominee, 2622
10997, artist, 2622
10997, artist, 11282
4970, award, 1978
4970, award, 5614
4970, award, 7183
4970, award, 3772
4970, award, 1227
4970, award, 9569
4970, award, 3215
4970, award, 11269
4970, award, 1825
4970, award, 4178
4970, award, 10227
4970, award, 10555
4970, award_nominee, 8980
4970, award_nominee, 2139
4970, award_nominee, 3485
4970, award_nominee, 11282
4970, award_nominee, 9215
4970, award_nominee, 10738
4970, award_nominee, 9695
4970, award_winner, 9695
4970, participant, 9695
4970, profession, 236
8624, colors, 9006
8624, colors, 10473
10345, time_zones, 13804
10345, vacationer, 8583
10345, vacationer, 11282
12954, participant, 2622
1481, award_nominee, 8583
1481, participant, 11282
9698, award, 9569
9698, award_nominee, 12028
9698, award_nominee, 8583
9698, award_nominee, 10825
9698, award_nominee, 10738
9698, award_nominee, 6357
834, colors, 9006
834, colors, 10650
13309, colors, 10473
13309, colors, 10650
11269, award_winner, 8583
11269, award_winner, 2622
617, award_winner, 8583
617, award_winner, 2622
1825, award_winner, 2622
4178, award_winner, 2622
2095, award_winner, 8583
2095, award_winner, 2622
10227, award_winner, 8583
10227, award_winner, 4970
10555, award_winner, 2622
2622, award, 5678
2622, award, 1978
2622, award, 13185
2622, award, 11111
2622, award, 3215
2622, award, 11269
2622, award, 617
2622, award, 1825
2622, award, 4178
2622, award, 2095
2622, award, 7874
2622, award, 10555
2622, award, 3248
2622, award, 7431
2622, award_nominee, 238
2622, award_nominee, 10825
2622, award_nominee, 6357
2622, award_winner, 10825
2622, participant, 12954
2622, participant, 4823
11282, award, 5678
11282, award, 5614
11282, award, 13185
11282, award, 11111
11282, award, 4023
11282, award, 7183
11282, award, 9569
11282, award, 2095
11282, award, 3657
11282, award, 3248
11282, award, 7431
11282, award_nominee, 4970
11282, award_nominee, 12954
11282, award_nominee, 10738
11282, award_nominee, 6357
11282, participant, 8980
11282, participant, 2139
11282, participant, 532
11282, participant, 11953
11282, participant, 2545
11282, participant, 5783
11282, profession, 236
11282, spouse, 532
1521, contains, 5707
1521, time_zones, 13804
10825, award, 9607
10825, award_nominee, 8583
10825, award_nominee, 9698
10825, award_nominee, 2622
10825, award_nominee, 6357
10825, award_winner, 2622
3626, colors, 9006
3626, colors, 10473
6897, award, 3772
6897, award_nominee, 12028
9215, award, 3772
9215, award_nominee, 4970
9215, award_nominee, 10738
7010, contains, 5077
7010, time_zones, 13804
5057, campuses, 5057
5057, educational_institution, 5057
5057, major_field_of_study, 10748
5057, major_field_of_study, 8705
5057, school_type, 14166
532, participant, 11282
532, spouse, 11282
7486, colors, 10650
7486, school, 11425
10643, award_nominee, 12028
2752, vacationer, 8583
2752, vacationer, 11282
10738, award, 1227
10738, award_nominee, 12028
10738, award_nominee, 2139
10738, award_nominee, 8583
10738, award_nominee, 4970
10738, award_nominee, 10825
10738, award_nominee, 6357
10738, award_winner, 9695
13024, adjoins, 5077
13024, time_zones, 13804
8703, artists, 8583
8703, artists, 10825
3248, award_winner, 2622
3248, award_winner, 11282
7431, award_winner, 2622
6632, administrative_division, 5077
6632, county, 5077
6632, time_zones, 13804
9695, award, 3772
9695, award_nominee, 12028
9695, award_nominee, 4970
9695, award_nominee, 10738
9695, award_winner, 4970
9695, award_winner, 10738
9695, participant, 4970
6782, award_nominee, 4970
8066, colors, 9006
8066, time_zones, 13804
11953, participant, 11282
426, artists, 4970
426, artists, 11282
6357, award, 3772
6357, award_nominee, 12028
6357, award_nominee, 8583
6357, award_nominee, 4970
6357, award_nominee, 9698
6357, award_nominee, 2622
6357, award_nominee, 11282
4823, award_nominee, 12028
4823, participant, 2622
2545, participant, 11282
7845, colors, 9006
7845, colors, 10473
6515, campuses, 6515
6515, colors, 10473
6515, educational_institution, 6515
6515, major_field_of_study, 10064
6515, major_field_of_study, 10748
6515, major_field_of_study, 11116
6515, major_field_of_study, 9178
6515, major_field_of_study, 2261
6515, major_field_of_study, 7957
6515, major_field_of_study, 5284
6515, school_type, 14166
2363, colors, 9006
2363, time_zones, 13804
6644, colors, 9006
6644, colors, 10473
6644, time_zones, 13804
11425, campuses, 11425
11425, colors, 9006
11425, colors, 10650
11425, educational_institution, 11425
11425, major_field_of_study, 10064
11425, major_field_of_study, 11116
11425, major_field_of_study, 2261
11425, major_field_of_study, 7957
11425, major_field_of_study, 8705
11425, major_field_of_study, 5284
11425, school_type, 14166
2680, colors, 10650
2680, time_zones, 13804
3219, campuses, 3219
3219, educational_institution, 3219
3219, major_field_of_study, 10748
3219, major_field_of_study, 11116
3219, major_field_of_study, 9178
3219, major_field_of_study, 5284
13884, colors, 9006
13884, colors, 10473
6128, colors, 9006
6128, time_zones, 13804
12455, colors, 9006
12455, time_zones, 13804
5077, county_seat, 6632
5077, time_zones, 13804
9421, colors, 9006
9421, colors, 10473
4528, artists, 12028
4528, parent_genre, 13230
Question: In what context are Indiana_Pacers, Placer_County, and The_Neptunes connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Indiana_Pacers",
"Placer_County",
"The_Neptunes"
],
"valid_edges": [
[
"44th_Annual_Grammy_Awards",
"award_winner",
"Gwen_Stefani"
],
[
"46th_Annual_Grammy_Awards",
"award_winner",
"Christina_Aguilera"
],
[
"46th_Annual_Grammy_Awards",
"award_winner",
"Eminem"
],
[
"46th_Annual_Grammy_Awards",
"award_winner",
"Justin_Timberlake"
],
[
"46th_Annual_Grammy_Awards",
"award_winner",
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"Linda_Perry",
"award",
"Grammy_Award_for_Song_of_the_Year"
],
[
"Linda_Perry",
"award_nominee",
"Dr._Dre"
],
[
"Linda_Perry",
"award_nominee",
"Gwen_Stefani"
],
[
"Linda_Perry",
"award_nominee",
"Mark_Stent"
],
[
"Linda_Perry",
"award_nominee",
"Phil_Tan"
],
[
"Linda_Perry",
"award_nominee",
"The_Neptunes"
],
[
"Long_Island_University",
"colors",
"Gold"
],
[
"Long_Island_University",
"colors",
"Silver"
],
[
"Los_Angeles_Angels_of_Anaheim",
"colors",
"Navy_Blue"
],
[
"Los_Angeles_Angels_of_Anaheim",
"colors",
"Silver"
],
[
"MTV_Video_Music_Award_for_Best_Art_Direction",
"award_winner",
"Gwen_Stefani"
],
[
"MTV_Video_Music_Award_for_Best_Art_Direction",
"award_winner",
"Madonna"
],
[
"MTV_Video_Music_Award_for_Best_Choreography",
"award_winner",
"Gwen_Stefani"
],
[
"MTV_Video_Music_Award_for_Best_Choreography",
"award_winner",
"Madonna"
],
[
"MTV_Video_Music_Award_for_Best_Direction",
"award_winner",
"Madonna"
],
[
"MTV_Video_Music_Award_for_Best_Editing",
"award_winner",
"Madonna"
],
[
"MTV_Video_Music_Award_for_Best_Female_Video",
"award_winner",
"Gwen_Stefani"
],
[
"MTV_Video_Music_Award_for_Best_Female_Video",
"award_winner",
"Madonna"
],
[
"MTV_Video_Music_Award_for_Best_Male_Video",
"award_winner",
"Gwen_Stefani"
],
[
"MTV_Video_Music_Award_for_Best_Male_Video",
"award_winner",
"Kanye_West"
],
[
"MTV_Video_Music_Award_for_Video_of_the_Year",
"award_winner",
"Madonna"
],
[
"Madonna",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Madonna",
"award",
"Grammy_Award_for_Best_Music_Video"
],
[
"Madonna",
"award",
"Grammy_Award_for_Best_Pop_Collaboration_with_Vocals"
],
[
"Madonna",
"award",
"Grammy_Award_for_Best_Pop_Vocal_Album"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Artist_to_Watch"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Art_Direction"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Choreography"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Direction"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Editing"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Female_Video"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Best_Pop_Video"
],
[
"Madonna",
"award",
"MTV_Video_Music_Award_for_Video_of_the_Year"
],
[
"Madonna",
"award",
"Razzie_Award_for_Worst_Actress"
],
[
"Madonna",
"award",
"Razzie_Award_for_Worst_Screen_Couple/Ensemble"
],
[
"Madonna",
"award_nominee",
"Justin_Timberlake"
],
[
"Madonna",
"award_nominee",
"Mark_Stent"
],
[
"Madonna",
"award_nominee",
"The_Neptunes"
],
[
"Madonna",
"award_winner",
"Mark_Stent"
],
[
"Madonna",
"participant",
"Lenny_Kravitz"
],
[
"Madonna",
"participant",
"Tupac_Shakur"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_Female_Pop_Vocal_Performance"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_New_Artist"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_Pop_Collaboration_with_Vocals"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_Pop_Vocal_Album"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_R&B_Performance_by_a_Duo_or_Group_with_Vocals"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Best_R&B_Song"
],
[
"Mariah_Carey",
"award",
"Grammy_Award_for_Song_of_the_Year"
],
[
"Mariah_Carey",
"award",
"MTV_Video_Music_Award_for_Best_Female_Video"
],
[
"Mariah_Carey",
"award",
"MTV_Video_Music_Award_for_Best_R&B_Video"
],
[
"Mariah_Carey",
"award",
"Razzie_Award_for_Worst_Actress"
],
[
"Mariah_Carey",
"award",
"Razzie_Award_for_Worst_Screen_Couple/Ensemble"
],
[
"Mariah_Carey",
"award_nominee",
"Kanye_West"
],
[
"Mariah_Carey",
"award_nominee",
"Lenny_Kravitz"
],
[
"Mariah_Carey",
"award_nominee",
"Phil_Tan"
],
[
"Mariah_Carey",
"award_nominee",
"The_Neptunes"
],
[
"Mariah_Carey",
"participant",
"Busta_Rhymes"
],
[
"Mariah_Carey",
"participant",
"Eminem"
],
[
"Mariah_Carey",
"participant",
"Nick_Cannon"
],
[
"Mariah_Carey",
"participant",
"Sean_Combs"
],
[
"Mariah_Carey",
"participant",
"Tyrese_Gibson"
],
[
"Mariah_Carey",
"participant",
"Will_Smith"
],
[
"Mariah_Carey",
"profession",
"Artist-GB"
],
[
"Mariah_Carey",
"spouse",
"Nick_Cannon"
],
[
"Marion_County",
"contains",
"Indianapolis"
],
[
"Marion_County",
"time_zones",
"Pacific_Time_Zone"
],
[
"Mark_Stent",
"award",
"Grammy_Award_for_Best_Rock_Album"
],
[
"Mark_Stent",
"award_nominee",
"Gwen_Stefani"
],
[
"Mark_Stent",
"award_nominee",
"Linda_Perry"
],
[
"Mark_Stent",
"award_nominee",
"Madonna"
],
[
"Mark_Stent",
"award_nominee",
"The_Neptunes"
],
[
"Mark_Stent",
"award_winner",
"Madonna"
],
[
"Marquette_University",
"colors",
"Gold"
],
[
"Marquette_University",
"colors",
"Navy_Blue"
],
[
"Missy_Elliott",
"award",
"Grammy_Award_for_Best_Rap/Sung_Collaboration"
],
[
"Missy_Elliott",
"award_nominee",
"Dr._Dre"
],
[
"Ne-Yo",
"award",
"Grammy_Award_for_Best_Rap/Sung_Collaboration"
],
[
"Ne-Yo",
"award_nominee",
"Kanye_West"
],
[
"Ne-Yo",
"award_nominee",
"Phil_Tan"
],
[
"Nevada",
"contains",
"Washoe_County"
],
[
"Nevada",
"time_zones",
"Pacific_Time_Zone"
],
[
"New_Mexico_State_University",
"campuses",
"New_Mexico_State_University"
],
[
"New_Mexico_State_University",
"educational_institution",
"New_Mexico_State_University"
],
[
"New_Mexico_State_University",
"major_field_of_study",
"Business_Administration"
],
[
"New_Mexico_State_University",
"major_field_of_study",
"Mechanical_Engineering"
],
[
"New_Mexico_State_University",
"school_type",
"Land-grant_university"
],
[
"Nick_Cannon",
"participant",
"Mariah_Carey"
],
[
"Nick_Cannon",
"spouse",
"Mariah_Carey"
],
[
"Oakland_Raiders",
"colors",
"Silver"
],
[
"Oakland_Raiders",
"school",
"University_of_Colorado_Boulder"
],
[
"P!nk",
"award_nominee",
"Dr._Dre"
],
[
"Paris",
"vacationer",
"Gwen_Stefani"
],
[
"Paris",
"vacationer",
"Mariah_Carey"
],
[
"Phil_Tan",
"award",
"Grammy_Award_for_Best_Rap_Album"
],
[
"Phil_Tan",
"award_nominee",
"Dr._Dre"
],
[
"Phil_Tan",
"award_nominee",
"Eminem"
],
[
"Phil_Tan",
"award_nominee",
"Gwen_Stefani"
],
[
"Phil_Tan",
"award_nominee",
"Kanye_West"
],
[
"Phil_Tan",
"award_nominee",
"Mark_Stent"
],
[
"Phil_Tan",
"award_nominee",
"The_Neptunes"
],
[
"Phil_Tan",
"award_winner",
"Rihanna"
],
[
"Placer_County",
"adjoins",
"Washoe_County"
],
[
"Placer_County",
"time_zones",
"Pacific_Time_Zone"
],
[
"Punk_rock",
"artists",
"Gwen_Stefani"
],
[
"Punk_rock",
"artists",
"Mark_Stent"
],
[
"Razzie_Award_for_Worst_Actress",
"award_winner",
"Madonna"
],
[
"Razzie_Award_for_Worst_Actress",
"award_winner",
"Mariah_Carey"
],
[
"Razzie_Award_for_Worst_Screen_Couple/Ensemble",
"award_winner",
"Madonna"
],
[
"Reno",
"administrative_division",
"Washoe_County"
],
[
"Reno",
"county",
"Washoe_County"
],
[
"Reno",
"time_zones",
"Pacific_Time_Zone"
],
[
"Rihanna",
"award",
"Grammy_Award_for_Best_Rap/Sung_Collaboration"
],
[
"Rihanna",
"award_nominee",
"Dr._Dre"
],
[
"Rihanna",
"award_nominee",
"Kanye_West"
],
[
"Rihanna",
"award_nominee",
"Phil_Tan"
],
[
"Rihanna",
"award_winner",
"Kanye_West"
],
[
"Rihanna",
"award_winner",
"Phil_Tan"
],
[
"Rihanna",
"participant",
"Kanye_West"
],
[
"Robbie_Williams",
"award_nominee",
"Kanye_West"
],
[
"San_JosΓ©_State_University",
"colors",
"Gold"
],
[
"San_JosΓ©_State_University",
"time_zones",
"Pacific_Time_Zone"
],
[
"Sean_Combs",
"participant",
"Mariah_Carey"
],
[
"Soul_music",
"artists",
"Kanye_West"
],
[
"Soul_music",
"artists",
"Mariah_Carey"
],
[
"The_Neptunes",
"award",
"Grammy_Award_for_Best_Rap/Sung_Collaboration"
],
[
"The_Neptunes",
"award_nominee",
"Dr._Dre"
],
[
"The_Neptunes",
"award_nominee",
"Gwen_Stefani"
],
[
"The_Neptunes",
"award_nominee",
"Kanye_West"
],
[
"The_Neptunes",
"award_nominee",
"Linda_Perry"
],
[
"The_Neptunes",
"award_nominee",
"Madonna"
],
[
"The_Neptunes",
"award_nominee",
"Mariah_Carey"
],
[
"Tupac_Shakur",
"award_nominee",
"Dr._Dre"
],
[
"Tupac_Shakur",
"participant",
"Madonna"
],
[
"Tyrese_Gibson",
"participant",
"Mariah_Carey"
],
[
"United_States_Naval_Academy",
"colors",
"Gold"
],
[
"United_States_Naval_Academy",
"colors",
"Navy_Blue"
],
[
"University_of_Arizona",
"campuses",
"University_of_Arizona"
],
[
"University_of_Arizona",
"colors",
"Navy_Blue"
],
[
"University_of_Arizona",
"educational_institution",
"University_of_Arizona"
],
[
"University_of_Arizona",
"major_field_of_study",
"Aerospace_Engineering-GB"
],
[
"University_of_Arizona",
"major_field_of_study",
"Business_Administration"
],
[
"University_of_Arizona",
"major_field_of_study",
"Computer_Science"
],
[
"University_of_Arizona",
"major_field_of_study",
"Finance"
],
[
"University_of_Arizona",
"major_field_of_study",
"Marketing-GB"
],
[
"University_of_Arizona",
"major_field_of_study",
"Mathematics"
],
[
"University_of_Arizona",
"major_field_of_study",
"Psychology"
],
[
"University_of_Arizona",
"school_type",
"Land-grant_university"
],
[
"University_of_California,_Davis",
"colors",
"Gold"
],
[
"University_of_California,_Davis",
"time_zones",
"Pacific_Time_Zone"
],
[
"University_of_California,_San_Diego",
"colors",
"Gold"
],
[
"University_of_California,_San_Diego",
"colors",
"Navy_Blue"
],
[
"University_of_California,_San_Diego",
"time_zones",
"Pacific_Time_Zone"
],
[
"University_of_Colorado_Boulder",
"campuses",
"University_of_Colorado_Boulder"
],
[
"University_of_Colorado_Boulder",
"colors",
"Gold"
],
[
"University_of_Colorado_Boulder",
"colors",
"Silver"
],
[
"University_of_Colorado_Boulder",
"educational_institution",
"University_of_Colorado_Boulder"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Aerospace_Engineering-GB"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Computer_Science"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Marketing-GB"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Mathematics"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Mechanical_Engineering"
],
[
"University_of_Colorado_Boulder",
"major_field_of_study",
"Psychology"
],
[
"University_of_Colorado_Boulder",
"school_type",
"Land-grant_university"
],
[
"University_of_Idaho",
"colors",
"Silver"
],
[
"University_of_Idaho",
"time_zones",
"Pacific_Time_Zone"
],
[
"University_of_Memphis",
"campuses",
"University_of_Memphis"
],
[
"University_of_Memphis",
"educational_institution",
"University_of_Memphis"
],
[
"University_of_Memphis",
"major_field_of_study",
"Business_Administration"
],
[
"University_of_Memphis",
"major_field_of_study",
"Computer_Science"
],
[
"University_of_Memphis",
"major_field_of_study",
"Finance"
],
[
"University_of_Memphis",
"major_field_of_study",
"Psychology"
],
[
"University_of_Northern_Colorado",
"colors",
"Gold"
],
[
"University_of_Northern_Colorado",
"colors",
"Navy_Blue"
],
[
"University_of_Southern_California",
"colors",
"Gold"
],
[
"University_of_Southern_California",
"time_zones",
"Pacific_Time_Zone"
],
[
"University_of_Victoria",
"colors",
"Gold"
],
[
"University_of_Victoria",
"time_zones",
"Pacific_Time_Zone"
],
[
"Washoe_County",
"county_seat",
"Reno"
],
[
"Washoe_County",
"time_zones",
"Pacific_Time_Zone"
],
[
"Wellington_College,_Berkshire",
"colors",
"Gold"
],
[
"Wellington_College,_Berkshire",
"colors",
"Navy_Blue"
],
[
"West_Coast_hip_hop",
"artists",
"Dr._Dre"
],
[
"West_Coast_hip_hop",
"parent_genre",
"Hip_hop_music"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
800, Alanine
8278, Alpha-Tocopherol
10611, American_Beauty
9303, Arginine
1490, Ash
7210, Aspartic_acid
2426, Avocado
8322, Basic_Instinct
4224, Bertrand_Russell
3573, Beta-carotene
838, Betaine
7465, Broccoli
9206, Cabbage
8833, Calcium
13561, California
2953, Capsicum
5891, Carbohydrate
3735, Carrot
384, Choline
432, Christopher_Young
346, Columbia_Pictures
2730, Copper
7411, Crouching_Tiger,_Hidden_Dragon
2803, Cryptoxanthin
6657, Cystine
3951, D-Glucose
11892, Dietary_fiber
7388, Film
11093, Fluoride
7613, Fructose
10213, Gary_Lucchesi
6175, Glutamic_acid
1069, Glycine
9986, Golden_Globe_Award_for_Best_Original_Score
7643, Histidine
1584, Iron
5396, Isoleucine
2116, King_Kong
9504, Lagaan:_Once_Upon_a_Time_in_India
12106, Legends_of_the_Fall
8809, Leucine
5472, Linoleic_acid
11767, Lipid
3719, Lysine
3864, Magnesium
6457, Management
1867, Manganese
2494, Methionine
7987, Monounsaturated_fat
12981, Niacin
10861, Oleic_acid
11936, Palmitic_acid
8578, Palmitoleic_acid
9120, Pantothenic_acid
10992, Phenylalanine
6197, Phosphorus
13486, Phytonadione
5951, Polyunsaturated_fat
11626, Potassium
1990, Proline
467, Protein
7335, Razzie_Award_for_Worst_Picture
12265, Riboflavin
8416, Rob_Reiner
7255, Romance_Film
6081, Saturated_fat
6492, Selenium
14207, Serine
10422, Shine
13094, Sideways
11898, Slumdog_Millionaire
5757, Sodium
2341, Stearic_acid
2641, Sugar
8056, Table_sugar
4942, The_Ugly_Truth
2650, Thiamine
12734, Threonine
2564, TriStar_Pictures
8836, Tryptophan
598, Tyrosine
1640, University_of_California,_Los_Angeles
10056, Valine
4258, Vitamin_A
11857, Vitamin_B-6
335, Vitamin_C
11776, Water
11772, Zinc
8673, alpha-Carotene
5165, gamma-Tocopherol
src, edge_attr, dst
10611, genre, 7255
2426, food_nutrient, 800
2426, food_nutrient, 8278
2426, food_nutrient, 9303
2426, food_nutrient, 1490
2426, food_nutrient, 7210
2426, food_nutrient, 3573
2426, food_nutrient, 838
2426, food_nutrient, 8833
2426, food_nutrient, 5891
2426, food_nutrient, 384
2426, food_nutrient, 2730
2426, food_nutrient, 2803
2426, food_nutrient, 6657
2426, food_nutrient, 3951
2426, food_nutrient, 11892
2426, food_nutrient, 11093
2426, food_nutrient, 7613
2426, food_nutrient, 6175
2426, food_nutrient, 1069
2426, food_nutrient, 7643
2426, food_nutrient, 1584
2426, food_nutrient, 5396
2426, food_nutrient, 8809
2426, food_nutrient, 5472
2426, food_nutrient, 11767
2426, food_nutrient, 3719
2426, food_nutrient, 3864
2426, food_nutrient, 1867
2426, food_nutrient, 2494
2426, food_nutrient, 7987
2426, food_nutrient, 12981
2426, food_nutrient, 10861
2426, food_nutrient, 11936
2426, food_nutrient, 8578
2426, food_nutrient, 9120
2426, food_nutrient, 10992
2426, food_nutrient, 6197
2426, food_nutrient, 13486
2426, food_nutrient, 5951
2426, food_nutrient, 11626
2426, food_nutrient, 1990
2426, food_nutrient, 467
2426, food_nutrient, 12265
2426, food_nutrient, 6081
2426, food_nutrient, 6492
2426, food_nutrient, 14207
2426, food_nutrient, 5757
2426, food_nutrient, 2341
2426, food_nutrient, 2641
2426, food_nutrient, 8056
2426, food_nutrient, 2650
2426, food_nutrient, 12734
2426, food_nutrient, 8836
2426, food_nutrient, 598
2426, food_nutrient, 10056
2426, food_nutrient, 4258
2426, food_nutrient, 11857
2426, food_nutrient, 335
2426, food_nutrient, 11776
2426, food_nutrient, 11772
2426, food_nutrient, 8673
2426, food_nutrient, 5165
8322, award_winner, 346
8322, production_companies, 2564
4224, company, 1640
7465, food_nutrient, 800
7465, food_nutrient, 8278
7465, food_nutrient, 9303
7465, food_nutrient, 1490
7465, food_nutrient, 7210
7465, food_nutrient, 3573
7465, food_nutrient, 838
7465, food_nutrient, 8833
7465, food_nutrient, 5891
7465, food_nutrient, 384
7465, food_nutrient, 2730
7465, food_nutrient, 2803
7465, food_nutrient, 6657
7465, food_nutrient, 3951
7465, food_nutrient, 11892
7465, food_nutrient, 7613
7465, food_nutrient, 6175
7465, food_nutrient, 1069
7465, food_nutrient, 7643
7465, food_nutrient, 1584
7465, food_nutrient, 5396
7465, food_nutrient, 8809
7465, food_nutrient, 5472
7465, food_nutrient, 11767
7465, food_nutrient, 3719
7465, food_nutrient, 3864
7465, food_nutrient, 1867
7465, food_nutrient, 2494
7465, food_nutrient, 7987
7465, food_nutrient, 12981
7465, food_nutrient, 10861
7465, food_nutrient, 11936
7465, food_nutrient, 9120
7465, food_nutrient, 10992
7465, food_nutrient, 6197
7465, food_nutrient, 13486
7465, food_nutrient, 5951
7465, food_nutrient, 11626
7465, food_nutrient, 1990
7465, food_nutrient, 467
7465, food_nutrient, 12265
7465, food_nutrient, 6081
7465, food_nutrient, 6492
7465, food_nutrient, 14207
7465, food_nutrient, 5757
7465, food_nutrient, 2341
7465, food_nutrient, 2641
7465, food_nutrient, 8056
7465, food_nutrient, 2650
7465, food_nutrient, 12734
7465, food_nutrient, 8836
7465, food_nutrient, 598
7465, food_nutrient, 10056
7465, food_nutrient, 4258
7465, food_nutrient, 11857
7465, food_nutrient, 335
7465, food_nutrient, 11776
7465, food_nutrient, 11772
7465, food_nutrient, 8673
7465, food_nutrient, 5165
9206, food_nutrient, 800
9206, food_nutrient, 8278
9206, food_nutrient, 9303
9206, food_nutrient, 1490
9206, food_nutrient, 7210
9206, food_nutrient, 3573
9206, food_nutrient, 838
9206, food_nutrient, 8833
9206, food_nutrient, 5891
9206, food_nutrient, 384
9206, food_nutrient, 2730
9206, food_nutrient, 6657
9206, food_nutrient, 3951
9206, food_nutrient, 11892
9206, food_nutrient, 11093
9206, food_nutrient, 7613
9206, food_nutrient, 6175
9206, food_nutrient, 1069
9206, food_nutrient, 7643
9206, food_nutrient, 1584
9206, food_nutrient, 5396
9206, food_nutrient, 8809
9206, food_nutrient, 5472
9206, food_nutrient, 11767
9206, food_nutrient, 3719
9206, food_nutrient, 3864
9206, food_nutrient, 1867
9206, food_nutrient, 2494
9206, food_nutrient, 7987
9206, food_nutrient, 12981
9206, food_nutrient, 10861
9206, food_nutrient, 11936
9206, food_nutrient, 9120
9206, food_nutrient, 10992
9206, food_nutrient, 6197
9206, food_nutrient, 13486
9206, food_nutrient, 5951
9206, food_nutrient, 11626
9206, food_nutrient, 1990
9206, food_nutrient, 467
9206, food_nutrient, 12265
9206, food_nutrient, 6081
9206, food_nutrient, 6492
9206, food_nutrient, 14207
9206, food_nutrient, 5757
9206, food_nutrient, 2641
9206, food_nutrient, 8056
9206, food_nutrient, 2650
9206, food_nutrient, 12734
9206, food_nutrient, 8836
9206, food_nutrient, 598
9206, food_nutrient, 10056
9206, food_nutrient, 4258
9206, food_nutrient, 11857
9206, food_nutrient, 335
9206, food_nutrient, 11776
9206, food_nutrient, 11772
9206, food_nutrient, 8673
2953, food_nutrient, 800
2953, food_nutrient, 8278
2953, food_nutrient, 9303
2953, food_nutrient, 1490
2953, food_nutrient, 7210
2953, food_nutrient, 3573
2953, food_nutrient, 838
2953, food_nutrient, 8833
2953, food_nutrient, 5891
2953, food_nutrient, 384
2953, food_nutrient, 2730
2953, food_nutrient, 2803
2953, food_nutrient, 6657
2953, food_nutrient, 3951
2953, food_nutrient, 11892
2953, food_nutrient, 7613
2953, food_nutrient, 6175
2953, food_nutrient, 1069
2953, food_nutrient, 7643
2953, food_nutrient, 1584
2953, food_nutrient, 5396
2953, food_nutrient, 8809
2953, food_nutrient, 5472
2953, food_nutrient, 11767
2953, food_nutrient, 3719
2953, food_nutrient, 3864
2953, food_nutrient, 1867
2953, food_nutrient, 2494
2953, food_nutrient, 7987
2953, food_nutrient, 12981
2953, food_nutrient, 10861
2953, food_nutrient, 11936
2953, food_nutrient, 8578
2953, food_nutrient, 9120
2953, food_nutrient, 10992
2953, food_nutrient, 6197
2953, food_nutrient, 13486
2953, food_nutrient, 5951
2953, food_nutrient, 11626
2953, food_nutrient, 1990
2953, food_nutrient, 467
2953, food_nutrient, 12265
2953, food_nutrient, 6081
2953, food_nutrient, 6492
2953, food_nutrient, 14207
2953, food_nutrient, 5757
2953, food_nutrient, 2341
2953, food_nutrient, 2641
2953, food_nutrient, 2650
2953, food_nutrient, 12734
2953, food_nutrient, 8836
2953, food_nutrient, 598
2953, food_nutrient, 10056
2953, food_nutrient, 4258
2953, food_nutrient, 11857
2953, food_nutrient, 335
2953, food_nutrient, 11776
2953, food_nutrient, 11772
2953, food_nutrient, 8673
2953, food_nutrient, 5165
3735, food_nutrient, 800
3735, food_nutrient, 8278
3735, food_nutrient, 9303
3735, food_nutrient, 1490
3735, food_nutrient, 7210
3735, food_nutrient, 3573
3735, food_nutrient, 838
3735, food_nutrient, 8833
3735, food_nutrient, 5891
3735, food_nutrient, 384
3735, food_nutrient, 2730
3735, food_nutrient, 6657
3735, food_nutrient, 3951
3735, food_nutrient, 11892
3735, food_nutrient, 11093
3735, food_nutrient, 7613
3735, food_nutrient, 6175
3735, food_nutrient, 1069
3735, food_nutrient, 7643
3735, food_nutrient, 1584
3735, food_nutrient, 5396
3735, food_nutrient, 8809
3735, food_nutrient, 5472
3735, food_nutrient, 11767
3735, food_nutrient, 3719
3735, food_nutrient, 3864
3735, food_nutrient, 1867
3735, food_nutrient, 2494
3735, food_nutrient, 7987
3735, food_nutrient, 12981
3735, food_nutrient, 10861
3735, food_nutrient, 11936
3735, food_nutrient, 8578
3735, food_nutrient, 9120
3735, food_nutrient, 10992
3735, food_nutrient, 6197
3735, food_nutrient, 13486
3735, food_nutrient, 5951
3735, food_nutrient, 11626
3735, food_nutrient, 1990
3735, food_nutrient, 467
3735, food_nutrient, 12265
3735, food_nutrient, 6081
3735, food_nutrient, 6492
3735, food_nutrient, 14207
3735, food_nutrient, 5757
3735, food_nutrient, 2341
3735, food_nutrient, 2641
3735, food_nutrient, 8056
3735, food_nutrient, 2650
3735, food_nutrient, 12734
3735, food_nutrient, 8836
3735, food_nutrient, 598
3735, food_nutrient, 10056
3735, food_nutrient, 4258
3735, food_nutrient, 11857
3735, food_nutrient, 335
3735, food_nutrient, 11776
3735, food_nutrient, 11772
3735, food_nutrient, 8673
432, award, 9986
346, award, 7335
346, award_nominee, 8416
346, child, 2564
346, film, 7411
346, film, 9504
346, film, 12106
346, film, 6457
346, film, 4942
346, industry, 7388
346, state_province_region, 13561
7411, genre, 7255
10213, company, 2564
9986, nominated_for, 10611
9986, nominated_for, 8322
9986, nominated_for, 7411
9986, nominated_for, 2116
9986, nominated_for, 12106
9986, nominated_for, 10422
9986, nominated_for, 13094
9986, nominated_for, 11898
2116, genre, 7255
9504, genre, 7255
12106, genre, 7255
12106, production_companies, 2564
6457, genre, 7255
7335, award_winner, 346
7335, award_winner, 2564
8416, award_nominee, 346
10422, genre, 7255
13094, genre, 7255
11898, award_honor_award, 9986
11898, genre, 7255
4942, genre, 7255
2564, film, 8322
2564, industry, 7388
1640, campuses, 1640
1640, educational_institution, 1640
1640, major_field_of_study, 7388
1640, split_to, 1640
1640, state_province_region, 13561
1640, student, 432
1640, student, 10213
1640, student, 8416
11776, genre, 7255
Question: For what reason are Bertrand_Russell, Legends_of_the_Fall, and alpha-Carotene associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bertrand_Russell",
"Legends_of_the_Fall",
"alpha-Carotene"
],
"valid_edges": [
[
"American_Beauty",
"genre",
"Romance_Film"
],
[
"Avocado",
"food_nutrient",
"Alanine"
],
[
"Avocado",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Avocado",
"food_nutrient",
"Arginine"
],
[
"Avocado",
"food_nutrient",
"Ash"
],
[
"Avocado",
"food_nutrient",
"Aspartic_acid"
],
[
"Avocado",
"food_nutrient",
"Beta-carotene"
],
[
"Avocado",
"food_nutrient",
"Betaine"
],
[
"Avocado",
"food_nutrient",
"Calcium"
],
[
"Avocado",
"food_nutrient",
"Carbohydrate"
],
[
"Avocado",
"food_nutrient",
"Choline"
],
[
"Avocado",
"food_nutrient",
"Copper"
],
[
"Avocado",
"food_nutrient",
"Cryptoxanthin"
],
[
"Avocado",
"food_nutrient",
"Cystine"
],
[
"Avocado",
"food_nutrient",
"D-Glucose"
],
[
"Avocado",
"food_nutrient",
"Dietary_fiber"
],
[
"Avocado",
"food_nutrient",
"Fluoride"
],
[
"Avocado",
"food_nutrient",
"Fructose"
],
[
"Avocado",
"food_nutrient",
"Glutamic_acid"
],
[
"Avocado",
"food_nutrient",
"Glycine"
],
[
"Avocado",
"food_nutrient",
"Histidine"
],
[
"Avocado",
"food_nutrient",
"Iron"
],
[
"Avocado",
"food_nutrient",
"Isoleucine"
],
[
"Avocado",
"food_nutrient",
"Leucine"
],
[
"Avocado",
"food_nutrient",
"Linoleic_acid"
],
[
"Avocado",
"food_nutrient",
"Lipid"
],
[
"Avocado",
"food_nutrient",
"Lysine"
],
[
"Avocado",
"food_nutrient",
"Magnesium"
],
[
"Avocado",
"food_nutrient",
"Manganese"
],
[
"Avocado",
"food_nutrient",
"Methionine"
],
[
"Avocado",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Avocado",
"food_nutrient",
"Niacin"
],
[
"Avocado",
"food_nutrient",
"Oleic_acid"
],
[
"Avocado",
"food_nutrient",
"Palmitic_acid"
],
[
"Avocado",
"food_nutrient",
"Palmitoleic_acid"
],
[
"Avocado",
"food_nutrient",
"Pantothenic_acid"
],
[
"Avocado",
"food_nutrient",
"Phenylalanine"
],
[
"Avocado",
"food_nutrient",
"Phosphorus"
],
[
"Avocado",
"food_nutrient",
"Phytonadione"
],
[
"Avocado",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Avocado",
"food_nutrient",
"Potassium"
],
[
"Avocado",
"food_nutrient",
"Proline"
],
[
"Avocado",
"food_nutrient",
"Protein"
],
[
"Avocado",
"food_nutrient",
"Riboflavin"
],
[
"Avocado",
"food_nutrient",
"Saturated_fat"
],
[
"Avocado",
"food_nutrient",
"Selenium"
],
[
"Avocado",
"food_nutrient",
"Serine"
],
[
"Avocado",
"food_nutrient",
"Sodium"
],
[
"Avocado",
"food_nutrient",
"Stearic_acid"
],
[
"Avocado",
"food_nutrient",
"Sugar"
],
[
"Avocado",
"food_nutrient",
"Table_sugar"
],
[
"Avocado",
"food_nutrient",
"Thiamine"
],
[
"Avocado",
"food_nutrient",
"Threonine"
],
[
"Avocado",
"food_nutrient",
"Tryptophan"
],
[
"Avocado",
"food_nutrient",
"Tyrosine"
],
[
"Avocado",
"food_nutrient",
"Valine"
],
[
"Avocado",
"food_nutrient",
"Vitamin_A"
],
[
"Avocado",
"food_nutrient",
"Vitamin_B-6"
],
[
"Avocado",
"food_nutrient",
"Vitamin_C"
],
[
"Avocado",
"food_nutrient",
"Water"
],
[
"Avocado",
"food_nutrient",
"Zinc"
],
[
"Avocado",
"food_nutrient",
"alpha-Carotene"
],
[
"Avocado",
"food_nutrient",
"gamma-Tocopherol"
],
[
"Basic_Instinct",
"award_winner",
"Columbia_Pictures"
],
[
"Basic_Instinct",
"production_companies",
"TriStar_Pictures"
],
[
"Bertrand_Russell",
"company",
"University_of_California,_Los_Angeles"
],
[
"Broccoli",
"food_nutrient",
"Alanine"
],
[
"Broccoli",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Broccoli",
"food_nutrient",
"Arginine"
],
[
"Broccoli",
"food_nutrient",
"Ash"
],
[
"Broccoli",
"food_nutrient",
"Aspartic_acid"
],
[
"Broccoli",
"food_nutrient",
"Beta-carotene"
],
[
"Broccoli",
"food_nutrient",
"Betaine"
],
[
"Broccoli",
"food_nutrient",
"Calcium"
],
[
"Broccoli",
"food_nutrient",
"Carbohydrate"
],
[
"Broccoli",
"food_nutrient",
"Choline"
],
[
"Broccoli",
"food_nutrient",
"Copper"
],
[
"Broccoli",
"food_nutrient",
"Cryptoxanthin"
],
[
"Broccoli",
"food_nutrient",
"Cystine"
],
[
"Broccoli",
"food_nutrient",
"D-Glucose"
],
[
"Broccoli",
"food_nutrient",
"Dietary_fiber"
],
[
"Broccoli",
"food_nutrient",
"Fructose"
],
[
"Broccoli",
"food_nutrient",
"Glutamic_acid"
],
[
"Broccoli",
"food_nutrient",
"Glycine"
],
[
"Broccoli",
"food_nutrient",
"Histidine"
],
[
"Broccoli",
"food_nutrient",
"Iron"
],
[
"Broccoli",
"food_nutrient",
"Isoleucine"
],
[
"Broccoli",
"food_nutrient",
"Leucine"
],
[
"Broccoli",
"food_nutrient",
"Linoleic_acid"
],
[
"Broccoli",
"food_nutrient",
"Lipid"
],
[
"Broccoli",
"food_nutrient",
"Lysine"
],
[
"Broccoli",
"food_nutrient",
"Magnesium"
],
[
"Broccoli",
"food_nutrient",
"Manganese"
],
[
"Broccoli",
"food_nutrient",
"Methionine"
],
[
"Broccoli",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Broccoli",
"food_nutrient",
"Niacin"
],
[
"Broccoli",
"food_nutrient",
"Oleic_acid"
],
[
"Broccoli",
"food_nutrient",
"Palmitic_acid"
],
[
"Broccoli",
"food_nutrient",
"Pantothenic_acid"
],
[
"Broccoli",
"food_nutrient",
"Phenylalanine"
],
[
"Broccoli",
"food_nutrient",
"Phosphorus"
],
[
"Broccoli",
"food_nutrient",
"Phytonadione"
],
[
"Broccoli",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Broccoli",
"food_nutrient",
"Potassium"
],
[
"Broccoli",
"food_nutrient",
"Proline"
],
[
"Broccoli",
"food_nutrient",
"Protein"
],
[
"Broccoli",
"food_nutrient",
"Riboflavin"
],
[
"Broccoli",
"food_nutrient",
"Saturated_fat"
],
[
"Broccoli",
"food_nutrient",
"Selenium"
],
[
"Broccoli",
"food_nutrient",
"Serine"
],
[
"Broccoli",
"food_nutrient",
"Sodium"
],
[
"Broccoli",
"food_nutrient",
"Stearic_acid"
],
[
"Broccoli",
"food_nutrient",
"Sugar"
],
[
"Broccoli",
"food_nutrient",
"Table_sugar"
],
[
"Broccoli",
"food_nutrient",
"Thiamine"
],
[
"Broccoli",
"food_nutrient",
"Threonine"
],
[
"Broccoli",
"food_nutrient",
"Tryptophan"
],
[
"Broccoli",
"food_nutrient",
"Tyrosine"
],
[
"Broccoli",
"food_nutrient",
"Valine"
],
[
"Broccoli",
"food_nutrient",
"Vitamin_A"
],
[
"Broccoli",
"food_nutrient",
"Vitamin_B-6"
],
[
"Broccoli",
"food_nutrient",
"Vitamin_C"
],
[
"Broccoli",
"food_nutrient",
"Water"
],
[
"Broccoli",
"food_nutrient",
"Zinc"
],
[
"Broccoli",
"food_nutrient",
"alpha-Carotene"
],
[
"Broccoli",
"food_nutrient",
"gamma-Tocopherol"
],
[
"Cabbage",
"food_nutrient",
"Alanine"
],
[
"Cabbage",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Cabbage",
"food_nutrient",
"Arginine"
],
[
"Cabbage",
"food_nutrient",
"Ash"
],
[
"Cabbage",
"food_nutrient",
"Aspartic_acid"
],
[
"Cabbage",
"food_nutrient",
"Beta-carotene"
],
[
"Cabbage",
"food_nutrient",
"Betaine"
],
[
"Cabbage",
"food_nutrient",
"Calcium"
],
[
"Cabbage",
"food_nutrient",
"Carbohydrate"
],
[
"Cabbage",
"food_nutrient",
"Choline"
],
[
"Cabbage",
"food_nutrient",
"Copper"
],
[
"Cabbage",
"food_nutrient",
"Cystine"
],
[
"Cabbage",
"food_nutrient",
"D-Glucose"
],
[
"Cabbage",
"food_nutrient",
"Dietary_fiber"
],
[
"Cabbage",
"food_nutrient",
"Fluoride"
],
[
"Cabbage",
"food_nutrient",
"Fructose"
],
[
"Cabbage",
"food_nutrient",
"Glutamic_acid"
],
[
"Cabbage",
"food_nutrient",
"Glycine"
],
[
"Cabbage",
"food_nutrient",
"Histidine"
],
[
"Cabbage",
"food_nutrient",
"Iron"
],
[
"Cabbage",
"food_nutrient",
"Isoleucine"
],
[
"Cabbage",
"food_nutrient",
"Leucine"
],
[
"Cabbage",
"food_nutrient",
"Linoleic_acid"
],
[
"Cabbage",
"food_nutrient",
"Lipid"
],
[
"Cabbage",
"food_nutrient",
"Lysine"
],
[
"Cabbage",
"food_nutrient",
"Magnesium"
],
[
"Cabbage",
"food_nutrient",
"Manganese"
],
[
"Cabbage",
"food_nutrient",
"Methionine"
],
[
"Cabbage",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Cabbage",
"food_nutrient",
"Niacin"
],
[
"Cabbage",
"food_nutrient",
"Oleic_acid"
],
[
"Cabbage",
"food_nutrient",
"Palmitic_acid"
],
[
"Cabbage",
"food_nutrient",
"Pantothenic_acid"
],
[
"Cabbage",
"food_nutrient",
"Phenylalanine"
],
[
"Cabbage",
"food_nutrient",
"Phosphorus"
],
[
"Cabbage",
"food_nutrient",
"Phytonadione"
],
[
"Cabbage",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Cabbage",
"food_nutrient",
"Potassium"
],
[
"Cabbage",
"food_nutrient",
"Proline"
],
[
"Cabbage",
"food_nutrient",
"Protein"
],
[
"Cabbage",
"food_nutrient",
"Riboflavin"
],
[
"Cabbage",
"food_nutrient",
"Saturated_fat"
],
[
"Cabbage",
"food_nutrient",
"Selenium"
],
[
"Cabbage",
"food_nutrient",
"Serine"
],
[
"Cabbage",
"food_nutrient",
"Sodium"
],
[
"Cabbage",
"food_nutrient",
"Sugar"
],
[
"Cabbage",
"food_nutrient",
"Table_sugar"
],
[
"Cabbage",
"food_nutrient",
"Thiamine"
],
[
"Cabbage",
"food_nutrient",
"Threonine"
],
[
"Cabbage",
"food_nutrient",
"Tryptophan"
],
[
"Cabbage",
"food_nutrient",
"Tyrosine"
],
[
"Cabbage",
"food_nutrient",
"Valine"
],
[
"Cabbage",
"food_nutrient",
"Vitamin_A"
],
[
"Cabbage",
"food_nutrient",
"Vitamin_B-6"
],
[
"Cabbage",
"food_nutrient",
"Vitamin_C"
],
[
"Cabbage",
"food_nutrient",
"Water"
],
[
"Cabbage",
"food_nutrient",
"Zinc"
],
[
"Cabbage",
"food_nutrient",
"alpha-Carotene"
],
[
"Capsicum",
"food_nutrient",
"Alanine"
],
[
"Capsicum",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Capsicum",
"food_nutrient",
"Arginine"
],
[
"Capsicum",
"food_nutrient",
"Ash"
],
[
"Capsicum",
"food_nutrient",
"Aspartic_acid"
],
[
"Capsicum",
"food_nutrient",
"Beta-carotene"
],
[
"Capsicum",
"food_nutrient",
"Betaine"
],
[
"Capsicum",
"food_nutrient",
"Calcium"
],
[
"Capsicum",
"food_nutrient",
"Carbohydrate"
],
[
"Capsicum",
"food_nutrient",
"Choline"
],
[
"Capsicum",
"food_nutrient",
"Copper"
],
[
"Capsicum",
"food_nutrient",
"Cryptoxanthin"
],
[
"Capsicum",
"food_nutrient",
"Cystine"
],
[
"Capsicum",
"food_nutrient",
"D-Glucose"
],
[
"Capsicum",
"food_nutrient",
"Dietary_fiber"
],
[
"Capsicum",
"food_nutrient",
"Fructose"
],
[
"Capsicum",
"food_nutrient",
"Glutamic_acid"
],
[
"Capsicum",
"food_nutrient",
"Glycine"
],
[
"Capsicum",
"food_nutrient",
"Histidine"
],
[
"Capsicum",
"food_nutrient",
"Iron"
],
[
"Capsicum",
"food_nutrient",
"Isoleucine"
],
[
"Capsicum",
"food_nutrient",
"Leucine"
],
[
"Capsicum",
"food_nutrient",
"Linoleic_acid"
],
[
"Capsicum",
"food_nutrient",
"Lipid"
],
[
"Capsicum",
"food_nutrient",
"Lysine"
],
[
"Capsicum",
"food_nutrient",
"Magnesium"
],
[
"Capsicum",
"food_nutrient",
"Manganese"
],
[
"Capsicum",
"food_nutrient",
"Methionine"
],
[
"Capsicum",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Capsicum",
"food_nutrient",
"Niacin"
],
[
"Capsicum",
"food_nutrient",
"Oleic_acid"
],
[
"Capsicum",
"food_nutrient",
"Palmitic_acid"
],
[
"Capsicum",
"food_nutrient",
"Palmitoleic_acid"
],
[
"Capsicum",
"food_nutrient",
"Pantothenic_acid"
],
[
"Capsicum",
"food_nutrient",
"Phenylalanine"
],
[
"Capsicum",
"food_nutrient",
"Phosphorus"
],
[
"Capsicum",
"food_nutrient",
"Phytonadione"
],
[
"Capsicum",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Capsicum",
"food_nutrient",
"Potassium"
],
[
"Capsicum",
"food_nutrient",
"Proline"
],
[
"Capsicum",
"food_nutrient",
"Protein"
],
[
"Capsicum",
"food_nutrient",
"Riboflavin"
],
[
"Capsicum",
"food_nutrient",
"Saturated_fat"
],
[
"Capsicum",
"food_nutrient",
"Selenium"
],
[
"Capsicum",
"food_nutrient",
"Serine"
],
[
"Capsicum",
"food_nutrient",
"Sodium"
],
[
"Capsicum",
"food_nutrient",
"Stearic_acid"
],
[
"Capsicum",
"food_nutrient",
"Sugar"
],
[
"Capsicum",
"food_nutrient",
"Thiamine"
],
[
"Capsicum",
"food_nutrient",
"Threonine"
],
[
"Capsicum",
"food_nutrient",
"Tryptophan"
],
[
"Capsicum",
"food_nutrient",
"Tyrosine"
],
[
"Capsicum",
"food_nutrient",
"Valine"
],
[
"Capsicum",
"food_nutrient",
"Vitamin_A"
],
[
"Capsicum",
"food_nutrient",
"Vitamin_B-6"
],
[
"Capsicum",
"food_nutrient",
"Vitamin_C"
],
[
"Capsicum",
"food_nutrient",
"Water"
],
[
"Capsicum",
"food_nutrient",
"Zinc"
],
[
"Capsicum",
"food_nutrient",
"alpha-Carotene"
],
[
"Capsicum",
"food_nutrient",
"gamma-Tocopherol"
],
[
"Carrot",
"food_nutrient",
"Alanine"
],
[
"Carrot",
"food_nutrient",
"Alpha-Tocopherol"
],
[
"Carrot",
"food_nutrient",
"Arginine"
],
[
"Carrot",
"food_nutrient",
"Ash"
],
[
"Carrot",
"food_nutrient",
"Aspartic_acid"
],
[
"Carrot",
"food_nutrient",
"Beta-carotene"
],
[
"Carrot",
"food_nutrient",
"Betaine"
],
[
"Carrot",
"food_nutrient",
"Calcium"
],
[
"Carrot",
"food_nutrient",
"Carbohydrate"
],
[
"Carrot",
"food_nutrient",
"Choline"
],
[
"Carrot",
"food_nutrient",
"Copper"
],
[
"Carrot",
"food_nutrient",
"Cystine"
],
[
"Carrot",
"food_nutrient",
"D-Glucose"
],
[
"Carrot",
"food_nutrient",
"Dietary_fiber"
],
[
"Carrot",
"food_nutrient",
"Fluoride"
],
[
"Carrot",
"food_nutrient",
"Fructose"
],
[
"Carrot",
"food_nutrient",
"Glutamic_acid"
],
[
"Carrot",
"food_nutrient",
"Glycine"
],
[
"Carrot",
"food_nutrient",
"Histidine"
],
[
"Carrot",
"food_nutrient",
"Iron"
],
[
"Carrot",
"food_nutrient",
"Isoleucine"
],
[
"Carrot",
"food_nutrient",
"Leucine"
],
[
"Carrot",
"food_nutrient",
"Linoleic_acid"
],
[
"Carrot",
"food_nutrient",
"Lipid"
],
[
"Carrot",
"food_nutrient",
"Lysine"
],
[
"Carrot",
"food_nutrient",
"Magnesium"
],
[
"Carrot",
"food_nutrient",
"Manganese"
],
[
"Carrot",
"food_nutrient",
"Methionine"
],
[
"Carrot",
"food_nutrient",
"Monounsaturated_fat"
],
[
"Carrot",
"food_nutrient",
"Niacin"
],
[
"Carrot",
"food_nutrient",
"Oleic_acid"
],
[
"Carrot",
"food_nutrient",
"Palmitic_acid"
],
[
"Carrot",
"food_nutrient",
"Palmitoleic_acid"
],
[
"Carrot",
"food_nutrient",
"Pantothenic_acid"
],
[
"Carrot",
"food_nutrient",
"Phenylalanine"
],
[
"Carrot",
"food_nutrient",
"Phosphorus"
],
[
"Carrot",
"food_nutrient",
"Phytonadione"
],
[
"Carrot",
"food_nutrient",
"Polyunsaturated_fat"
],
[
"Carrot",
"food_nutrient",
"Potassium"
],
[
"Carrot",
"food_nutrient",
"Proline"
],
[
"Carrot",
"food_nutrient",
"Protein"
],
[
"Carrot",
"food_nutrient",
"Riboflavin"
],
[
"Carrot",
"food_nutrient",
"Saturated_fat"
],
[
"Carrot",
"food_nutrient",
"Selenium"
],
[
"Carrot",
"food_nutrient",
"Serine"
],
[
"Carrot",
"food_nutrient",
"Sodium"
],
[
"Carrot",
"food_nutrient",
"Stearic_acid"
],
[
"Carrot",
"food_nutrient",
"Sugar"
],
[
"Carrot",
"food_nutrient",
"Table_sugar"
],
[
"Carrot",
"food_nutrient",
"Thiamine"
],
[
"Carrot",
"food_nutrient",
"Threonine"
],
[
"Carrot",
"food_nutrient",
"Tryptophan"
],
[
"Carrot",
"food_nutrient",
"Tyrosine"
],
[
"Carrot",
"food_nutrient",
"Valine"
],
[
"Carrot",
"food_nutrient",
"Vitamin_A"
],
[
"Carrot",
"food_nutrient",
"Vitamin_B-6"
],
[
"Carrot",
"food_nutrient",
"Vitamin_C"
],
[
"Carrot",
"food_nutrient",
"Water"
],
[
"Carrot",
"food_nutrient",
"Zinc"
],
[
"Carrot",
"food_nutrient",
"alpha-Carotene"
],
[
"Christopher_Young",
"award",
"Golden_Globe_Award_for_Best_Original_Score"
],
[
"Columbia_Pictures",
"award",
"Razzie_Award_for_Worst_Picture"
],
[
"Columbia_Pictures",
"award_nominee",
"Rob_Reiner"
],
[
"Columbia_Pictures",
"child",
"TriStar_Pictures"
],
[
"Columbia_Pictures",
"film",
"Crouching_Tiger,_Hidden_Dragon"
],
[
"Columbia_Pictures",
"film",
"Lagaan:_Once_Upon_a_Time_in_India"
],
[
"Columbia_Pictures",
"film",
"Legends_of_the_Fall"
],
[
"Columbia_Pictures",
"film",
"Management"
],
[
"Columbia_Pictures",
"film",
"The_Ugly_Truth"
],
[
"Columbia_Pictures",
"industry",
"Film"
],
[
"Columbia_Pictures",
"state_province_region",
"California"
],
[
"Crouching_Tiger,_Hidden_Dragon",
"genre",
"Romance_Film"
],
[
"Gary_Lucchesi",
"company",
"TriStar_Pictures"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"American_Beauty"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Basic_Instinct"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Crouching_Tiger,_Hidden_Dragon"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"King_Kong"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Legends_of_the_Fall"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Shine"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Sideways"
],
[
"Golden_Globe_Award_for_Best_Original_Score",
"nominated_for",
"Slumdog_Millionaire"
],
[
"King_Kong",
"genre",
"Romance_Film"
],
[
"Lagaan:_Once_Upon_a_Time_in_India",
"genre",
"Romance_Film"
],
[
"Legends_of_the_Fall",
"genre",
"Romance_Film"
],
[
"Legends_of_the_Fall",
"production_companies",
"TriStar_Pictures"
],
[
"Management",
"genre",
"Romance_Film"
],
[
"Razzie_Award_for_Worst_Picture",
"award_winner",
"Columbia_Pictures"
],
[
"Razzie_Award_for_Worst_Picture",
"award_winner",
"TriStar_Pictures"
],
[
"Rob_Reiner",
"award_nominee",
"Columbia_Pictures"
],
[
"Shine",
"genre",
"Romance_Film"
],
[
"Sideways",
"genre",
"Romance_Film"
],
[
"Slumdog_Millionaire",
"award_honor_award",
"Golden_Globe_Award_for_Best_Original_Score"
],
[
"Slumdog_Millionaire",
"genre",
"Romance_Film"
],
[
"The_Ugly_Truth",
"genre",
"Romance_Film"
],
[
"TriStar_Pictures",
"film",
"Basic_Instinct"
],
[
"TriStar_Pictures",
"industry",
"Film"
],
[
"University_of_California,_Los_Angeles",
"campuses",
"University_of_California,_Los_Angeles"
],
[
"University_of_California,_Los_Angeles",
"educational_institution",
"University_of_California,_Los_Angeles"
],
[
"University_of_California,_Los_Angeles",
"major_field_of_study",
"Film"
],
[
"University_of_California,_Los_Angeles",
"split_to",
"University_of_California,_Los_Angeles"
],
[
"University_of_California,_Los_Angeles",
"state_province_region",
"California"
],
[
"University_of_California,_Los_Angeles",
"student",
"Christopher_Young"
],
[
"University_of_California,_Los_Angeles",
"student",
"Gary_Lucchesi"
],
[
"University_of_California,_Los_Angeles",
"student",
"Rob_Reiner"
],
[
"Water",
"genre",
"Romance_Film"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9078, 2004_NBA_draft
5729, 2005_NBA_draft
1614, 2006_NBA_draft
6704, 2007_NBA_draft
10464, 2008_NBA_draft
5015, Alpha_Delta_Pi
4247, Atlanta_Hawks
10104, Basketball
9517, Baylor_University
111, Boston_Celtics
1174, Bradley_University
13111, Brooklyn_Nets
8471, Bryn_Mawr_College
5891, Carbohydrate
7081, Center
2928, Charlotte_Bobcats
10961, Chemistry
776, Chicago_Bulls
10400, Clemson_Tigers_men's_basketball
7292, Cleveland_Cavaliers
3414, Dallas_Mavericks
6966, Denver_Nuggets
7429, Detroit_Pistons
11881, Electrical_engineering
2735, FC_Kuban_Krasnodar
13983, Forward-center
13167, Georgia_Institute_of_Technology
692, Gonzaga_University
9243, Green
12054, Hobart_and_William_Smith_Colleges
10631, Houston_Rockets
1904, Indiana_Pacers
10240, Jimmy_Carter
11126, Los_Angeles_Clippers
287, Los_Angeles_Lakers
1088, Maccabi_Tel_Aviv_B.C.
10341, Memphis_Grizzlies
7689, Miami_Heat
4349, Michigan_State_University
6449, Milk
2462, Mills_College
9597, Milwaukee_Bucks
5243, Minnesota_Golden_Gophers_men's_basketball
6312, Minnesota_Timberwolves
8102, New_Orleans_Pelicans
8315, New_York_Knicks
4729, North_Dakota_State_University
93, Norwich_City_F.C.
6131, Oklahoma_City_Thunder
8205, Olympiacos_B.C.
11455, Oregon_Ducks_football
3409, Orlando_Magic
13554, Parsons_The_New_School_for_Design
8749, Philadelphia_76ers
10995, Phoenix_Suns
9293, Point_guard
2008, Polytechnic_Institute_of_New_York_University
3965, Portland_Trail_Blazers
8941, Private_school
845, Roosevelt_University
6596, Sacramento_Kings
10792, San_Antonio_Spurs
10821, Sarah_Lawrence_College
13123, Seattle_Storm
3376, Seattle_Supersonics
9480, Shooting_guard
10881, Skidmore_College
11001, Small_forward
6620, Stanford_University
9627, Stetson_University
4587, Texas_Longhorns_men's_basketball
11746, Times_Higher_Education_World_University_Rankings
5948, Toronto
3818, Toronto_Raptors
11342, UCLA_Bruins_men's_basketball
3871, University_of_Connecticut
221, University_of_Florida
694, University_of_Kansas
10254, University_of_Kentucky
12223, University_of_Miami
12256, University_of_Oregon
1613, University_of_Saskatchewan
5851, University_of_Texas_at_Austin
2823, University_of_Washington
6811, Upper_Canada_College
1913, Utah_Jazz
9275, Villanova_University
9813, Wake_Forest_Demon_Deacons_men's_basketball
4132, Washington_University_in_St._Louis
7408, Washington_Wizards
7080, Yellow
src, edge_attr, dst
9078, school, 6620
9078, school, 3871
9078, school, 12256
5729, school, 13167
5729, school, 692
5729, school, 3871
5729, school, 221
5729, school, 694
5729, school, 2823
1614, school, 1174
1614, school, 692
1614, school, 4349
1614, school, 3871
1614, school, 10254
1614, school, 5851
1614, school, 2823
1614, school, 9275
6704, school, 13167
6704, school, 2823
10464, school, 6620
10464, school, 221
10464, school, 694
10464, school, 10254
10464, school, 5851
4247, draft, 9078
4247, draft, 5729
4247, draft, 1614
4247, position, 7081
4247, position, 13983
4247, position, 9293
4247, position, 9480
4247, sport, 10104
9517, colors, 9243
9517, school_type, 8941
111, colors, 9243
111, draft, 9078
111, draft, 5729
111, draft, 1614
111, draft, 10464
111, position, 7081
111, position, 9293
111, position, 9480
111, position, 11001
111, sport, 10104
1174, school_type, 8941
13111, draft, 9078
13111, draft, 5729
13111, draft, 1614
13111, draft, 10464
13111, position, 7081
13111, position, 9293
13111, school, 3871
13111, sport, 10104
8471, colors, 7080
8471, school_type, 8941
7081, team, 4247
7081, team, 111
7081, team, 13111
7081, team, 10400
7081, team, 7292
7081, team, 3414
7081, team, 6966
7081, team, 10631
7081, team, 1904
7081, team, 11126
7081, team, 287
7081, team, 1088
7081, team, 10341
7081, team, 7689
7081, team, 9597
7081, team, 5243
7081, team, 6312
7081, team, 8102
7081, team, 8315
7081, team, 6131
7081, team, 8205
7081, team, 3409
7081, team, 8749
7081, team, 10995
7081, team, 6596
7081, team, 10792
7081, team, 13123
7081, team, 4587
7081, team, 3818
7081, team, 1913
7081, team, 9813
7081, team, 7408
2928, draft, 9078
2928, draft, 5729
2928, draft, 1614
2928, draft, 10464
2928, position, 7081
2928, position, 13983
2928, position, 9293
2928, position, 9480
2928, position, 11001
2928, school, 3871
2928, sport, 10104
776, draft, 9078
776, draft, 1614
776, draft, 10464
776, position, 7081
776, position, 9293
776, position, 9480
776, position, 11001
776, sport, 10104
10400, position, 7081
10400, position, 13983
10400, position, 11001
7292, draft, 9078
7292, draft, 1614
7292, draft, 10464
7292, position, 7081
7292, position, 13983
7292, position, 9293
7292, position, 9480
7292, position, 11001
7292, sport, 10104
3414, draft, 1614
3414, position, 7081
3414, position, 9293
3414, sport, 10104
6966, draft, 9078
6966, draft, 5729
6966, position, 9293
6966, position, 9480
6966, position, 11001
6966, school, 13167
6966, sport, 10104
7429, draft, 5729
7429, draft, 10464
7429, position, 7081
7429, position, 9293
7429, position, 9480
7429, position, 11001
7429, school, 3871
7429, sport, 10104
2735, colors, 9243
2735, colors, 7080
13983, team, 4247
13983, team, 111
13983, team, 2928
13983, team, 7292
13983, team, 287
13983, team, 7689
13983, team, 9597
13983, team, 5243
13983, team, 8102
13983, team, 8315
13983, team, 6131
13983, team, 3409
13983, team, 10792
13983, team, 13123
13983, team, 3818
13983, team, 11342
13983, team, 9813
13983, team, 7408
13167, educational_institution, 13167
13167, fraternities_and_sororities, 5015
13167, list, 11746
13167, major_field_of_study, 10961
13167, major_field_of_study, 11881
13167, student, 10240
692, school_type, 8941
12054, colors, 9243
12054, school_type, 8941
10631, draft, 5729
10631, draft, 1614
10631, draft, 10464
10631, position, 7081
10631, position, 9293
10631, position, 9480
10631, position, 11001
10631, school, 3871
10631, sport, 10104
1904, draft, 9078
1904, draft, 5729
1904, draft, 1614
1904, draft, 10464
1904, position, 7081
1904, position, 9293
1904, position, 9480
1904, position, 11001
1904, sport, 10104
11126, draft, 9078
11126, draft, 5729
11126, draft, 1614
11126, draft, 10464
11126, position, 7081
11126, position, 9480
11126, position, 11001
11126, sport, 10104
287, draft, 9078
287, draft, 5729
287, draft, 1614
287, draft, 10464
287, position, 7081
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93, colors, 7080
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9293, team, 8749
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9293, team, 6596
9293, team, 10792
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9293, team, 7408
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2008, school_type, 8941
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9480, team, 7292
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9480, team, 6312
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9480, team, 8205
9480, team, 3409
9480, team, 10995
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9480, team, 7408
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11001, team, 7408
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7408, sport, 10104
Question: In what context are Carbohydrate, Skidmore_College, and Toronto_Raptors connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
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"Toronto_Raptors"
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"2004_NBA_draft",
"school",
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"2004_NBA_draft",
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[
"2004_NBA_draft",
"school",
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"Utah_Jazz",
"draft",
"2005_NBA_draft"
],
[
"Utah_Jazz",
"draft",
"2006_NBA_draft"
],
[
"Utah_Jazz",
"draft",
"2008_NBA_draft"
],
[
"Utah_Jazz",
"position",
"Point_guard"
],
[
"Utah_Jazz",
"position",
"Shooting_guard"
],
[
"Utah_Jazz",
"position",
"Small_forward"
],
[
"Utah_Jazz",
"sport",
"Basketball"
],
[
"Villanova_University",
"school_type",
"Private_school"
],
[
"Wake_Forest_Demon_Deacons_men's_basketball",
"position",
"Center"
],
[
"Wake_Forest_Demon_Deacons_men's_basketball",
"position",
"Forward-center"
],
[
"Wake_Forest_Demon_Deacons_men's_basketball",
"position",
"Small_forward"
],
[
"Washington_University_in_St._Louis",
"colors",
"Green"
],
[
"Washington_University_in_St._Louis",
"school_type",
"Private_school"
],
[
"Washington_Wizards",
"draft",
"2004_NBA_draft"
],
[
"Washington_Wizards",
"draft",
"2006_NBA_draft"
],
[
"Washington_Wizards",
"draft",
"2008_NBA_draft"
],
[
"Washington_Wizards",
"position",
"Center"
],
[
"Washington_Wizards",
"position",
"Point_guard"
],
[
"Washington_Wizards",
"position",
"Small_forward"
],
[
"Washington_Wizards",
"sport",
"Basketball"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5836, Anglicanism
10351, Anthony_Newley
3022, Charles_Dickens
1200, Douglas_Adams
10901, Eric_Idle
12368, Gene_Wolfe
1221, Henry_James
13478, Hugo_Award_for_Best_Dramatic_Presentation
8908, Leslie_Bricusse
6454, MCA_Records
1773, Melvin_Van_Peebles
3802, Merle_Haggard
5543, Roald_Dahl
4514, Robert_Louis_Stevenson
3834, Rudyard_Kipling
9181, Rupert_Holmes
8475, T._S._Eliot
5036, Tony_Award_for_Best_Book_of_a_Musical
421, Willy_Wonka_&_the_Chocolate_Factory
src, edge_attr, dst
10351, award, 5036
10351, nominated_for, 421
3022, religion, 5836
1200, award, 13478
1200, influenced_by, 3022
10901, award, 13478
10901, award, 5036
12368, influenced_by, 3022
12368, influenced_by, 3834
1221, influenced_by, 3022
1221, influenced_by, 3834
8908, award, 5036
8908, nominated_for, 421
6454, artist, 3802
6454, artist, 9181
1773, award, 5036
5543, award, 13478
5543, influenced_by, 3022
5543, influenced_by, 3834
4514, influenced_by, 3022
3834, influenced_by, 4514
3834, religion, 5836
9181, award, 5036
8475, award, 5036
8475, influenced_by, 3022
5036, award_winner, 9181
421, film_music, 10351
421, story_by, 5543
Question: How are Melvin_Van_Peebles, Merle_Haggard, and Roald_Dahl related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Melvin_Van_Peebles",
"Merle_Haggard",
"Roald_Dahl"
],
"valid_edges": [
[
"Anthony_Newley",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Anthony_Newley",
"nominated_for",
"Willy_Wonka_&_the_Chocolate_Factory"
],
[
"Charles_Dickens",
"religion",
"Anglicanism"
],
[
"Douglas_Adams",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Douglas_Adams",
"influenced_by",
"Charles_Dickens"
],
[
"Eric_Idle",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Eric_Idle",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Gene_Wolfe",
"influenced_by",
"Charles_Dickens"
],
[
"Gene_Wolfe",
"influenced_by",
"Rudyard_Kipling"
],
[
"Henry_James",
"influenced_by",
"Charles_Dickens"
],
[
"Henry_James",
"influenced_by",
"Rudyard_Kipling"
],
[
"Leslie_Bricusse",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Leslie_Bricusse",
"nominated_for",
"Willy_Wonka_&_the_Chocolate_Factory"
],
[
"MCA_Records",
"artist",
"Merle_Haggard"
],
[
"MCA_Records",
"artist",
"Rupert_Holmes"
],
[
"Melvin_Van_Peebles",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"Roald_Dahl",
"award",
"Hugo_Award_for_Best_Dramatic_Presentation"
],
[
"Roald_Dahl",
"influenced_by",
"Charles_Dickens"
],
[
"Roald_Dahl",
"influenced_by",
"Rudyard_Kipling"
],
[
"Robert_Louis_Stevenson",
"influenced_by",
"Charles_Dickens"
],
[
"Rudyard_Kipling",
"influenced_by",
"Robert_Louis_Stevenson"
],
[
"Rudyard_Kipling",
"religion",
"Anglicanism"
],
[
"Rupert_Holmes",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"T._S._Eliot",
"award",
"Tony_Award_for_Best_Book_of_a_Musical"
],
[
"T._S._Eliot",
"influenced_by",
"Charles_Dickens"
],
[
"Tony_Award_for_Best_Book_of_a_Musical",
"award_winner",
"Rupert_Holmes"
],
[
"Willy_Wonka_&_the_Chocolate_Factory",
"film_music",
"Anthony_Newley"
],
[
"Willy_Wonka_&_the_Chocolate_Factory",
"story_by",
"Roald_Dahl"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9983, 65th_Golden_Globe_Awards
7279, Bruce_Berman
5257, Cats_&_Dogs
726, Charlton_Heston
14145, David_Duchovny
6796, Eddie_Vedder
12845, Elisha_Cuthbert
5399, Evanston
8095, House_of_Wax
6123, Jeremy_Piven
2129, Joan_Cusack
10318, Working_Girl
src, edge_attr, dst
9983, award_winner, 14145
9983, award_winner, 6796
9983, award_winner, 6123
5257, award_winner, 726
5257, executive_produced_by, 7279
726, acted_in, 5257
726, location, 5399
726, place_of_birth, 5399
14145, acted_in, 10318
6796, place_of_birth, 5399
12845, acted_in, 8095
5399, place, 5399
8095, executive_produced_by, 7279
6123, location, 5399
2129, acted_in, 10318
2129, location, 5399
Question: For what reason are Charlton_Heston, David_Duchovny, and Elisha_Cuthbert associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Charlton_Heston",
"David_Duchovny",
"Elisha_Cuthbert"
],
"valid_edges": [
[
"65th_Golden_Globe_Awards",
"award_winner",
"David_Duchovny"
],
[
"65th_Golden_Globe_Awards",
"award_winner",
"Eddie_Vedder"
],
[
"65th_Golden_Globe_Awards",
"award_winner",
"Jeremy_Piven"
],
[
"Cats_&_Dogs",
"award_winner",
"Charlton_Heston"
],
[
"Cats_&_Dogs",
"executive_produced_by",
"Bruce_Berman"
],
[
"Charlton_Heston",
"acted_in",
"Cats_&_Dogs"
],
[
"Charlton_Heston",
"location",
"Evanston"
],
[
"Charlton_Heston",
"place_of_birth",
"Evanston"
],
[
"David_Duchovny",
"acted_in",
"Working_Girl"
],
[
"Eddie_Vedder",
"place_of_birth",
"Evanston"
],
[
"Elisha_Cuthbert",
"acted_in",
"House_of_Wax"
],
[
"Evanston",
"place",
"Evanston"
],
[
"House_of_Wax",
"executive_produced_by",
"Bruce_Berman"
],
[
"Jeremy_Piven",
"location",
"Evanston"
],
[
"Joan_Cusack",
"acted_in",
"Working_Girl"
],
[
"Joan_Cusack",
"location",
"Evanston"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
87, 2009_Toronto_International_Film_Festival
7870, Adam_Sandler
9180, Albany_Law_School
7802, Alfre_Woodard
12169, Allahabad_University
8222, Anjelica_Huston
1897, Bachelor_of_Laws
8570, Boston_University_School_of_Law
11331, Bridget_Fonda
13751, Cairo_University
42, Canadian_dollar
360, Cape_Fear
5375, Catherine_O'Hara
12992, Christ_Church,_Oxford
3424, Columbia_Law_School
11566, Columbia_University
11491, Cornell_Law_School
2090, Dalhousie_University
12126, Dean-GB
12739, Dianne_Wiest
11110, Drew_Barrymore
12040, Ellen_Page
2145, Frances_McDormand
14189, Game_Change
10012, George_Washington_University
1077, Georgetown_University_Law_Center
5513, Harvard_Law_School
10392, Husbands_and_Wives
10072, Independent_Spirit_Award_for_Best_Supporting_Female
5927, Independent_record_label
8613, Indie
7414, Indie_film
12462, Jessica_Biel
7203, Jessica_Lange
8633, Jimmy_Fallon
14022, Judy_Davis
13509, Juliette_Lewis
7150, Kathy_Baker
7883, King's_College_London
12442, Law
11609, Law_degree
12322, Lily_Tomlin
513, London_School_of_Economics_and_Political_Science
12027, Marcia_Gay_Harden
10246, Mare_Winningham
11306, McGill_University
7783, McMaster_University
9791, New_York_University_School_of_Law
4866, Ontario
3969, Osgoode_Hall_Law_School
11025, Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie
4669, QuΓ©bec
6014, Ryerson_University
4025, Samantha_Morton
1685, Sarah_Polley
7808, Schulich_School_of_Law
13965, Shohreh_Aghdashloo
643, Stanford_Law_School
970, Stockard_Channing
1354, Susan_Sarandon
7306, The_George_Washington_University_Law_School
3164, The_Messenger
13637, Tisch_School_of_the_Arts
5948, Toronto
5618, Trinity_College,_Dublin
8748, University_of_Aberdeen
6831, University_of_Adelaide
11108, University_of_Auckland
4436, University_of_Bristol
2618, University_of_British_Columbia
1640, University_of_California,_Los_Angeles
6240, University_of_Cambridge
3457, University_of_Houston
13501, University_of_Manitoba
6936, University_of_Melbourne
1480, University_of_Michigan
8439, University_of_Michigan_Law_School
3463, University_of_Ottawa
5506, University_of_Toronto
7581, University_of_Virginia_School_of_Law
13118, University_of_Western_Australia
9570, University_of_Western_Ontario
12758, UniversitΓ©_Laval
4590, Vanessa_Redgrave
10000, Virginia_Madsen
13955, Whip_It!
5693, Woody_Harrelson
9510, Yale_Law_School
819, Yale_University
10689, York_University
src, edge_attr, dst
87, locations, 5948
7870, award_nominee, 12462
7870, award_winner, 11110
7870, participant, 12462
7802, award, 10072
7802, award, 11025
8222, award, 10072
8222, award, 11025
1897, institution, 9180
1897, institution, 12169
1897, institution, 13751
1897, institution, 12992
1897, institution, 3424
1897, institution, 11566
1897, institution, 11491
1897, institution, 2090
1897, institution, 10012
1897, institution, 5513
1897, institution, 7883
1897, institution, 513
1897, institution, 11306
1897, institution, 9791
1897, institution, 3969
1897, institution, 7808
1897, institution, 7306
1897, institution, 5618
1897, institution, 8748
1897, institution, 6831
1897, institution, 11108
1897, institution, 4436
1897, institution, 2618
1897, institution, 1640
1897, institution, 6240
1897, institution, 3457
1897, institution, 13501
1897, institution, 6936
1897, institution, 1480
1897, institution, 3463
1897, institution, 5506
1897, institution, 7581
1897, institution, 13118
1897, institution, 9570
1897, institution, 12758
1897, institution, 9510
1897, institution, 819
1897, major_field_of_study, 12442
11331, award, 10072
11331, award, 11025
5375, award, 11025
5375, location, 5948
5375, place_of_birth, 5948
2090, currency, 42
2090, international_tuition_currency, 42
12126, company, 3424
12126, company, 7883
12126, company, 643
12126, company, 819
12126, organization, 9180
12126, organization, 8570
12126, organization, 12992
12126, organization, 3424
12126, organization, 11491
12126, organization, 1077
12126, organization, 5513
12126, organization, 9791
12126, organization, 3969
12126, organization, 643
12126, organization, 7306
12126, organization, 13637
12126, organization, 8439
12126, organization, 7581
12126, organization, 9510
12739, award, 10072
12739, award, 11025
11110, acted_in, 13955
11110, award_nominee, 7870
11110, award_winner, 7870
11110, film, 13955
12040, acted_in, 13955
12040, location, 5948
2145, award, 10072
2145, award, 11025
10392, award_winner, 14022
10392, genre, 7414
10072, award_winner, 8222
10072, award_winner, 12739
10072, award_winner, 2145
10072, award_winner, 10246
10072, award_winner, 13965
10072, nominated_for, 3164
8613, split_to, 5927
8613, split_to, 7414
7414, split_to, 8613
12462, award_nominee, 7870
7203, acted_in, 360
7203, award, 11025
8633, acted_in, 13955
8633, celebrities_impersonated, 7870
8633, influenced_by, 7870
14022, award, 11025
14022, nominated_for, 10392
13509, acted_in, 360
13509, acted_in, 10392
13509, acted_in, 13955
13509, award, 10072
13509, award, 11025
13509, award_nominee, 5693
13509, nominated_for, 360
13509, participant, 7870
7150, award, 10072
7150, award, 11025
12442, films, 360
11609, institution, 12169
11609, institution, 8570
11609, institution, 13751
11609, institution, 3424
11609, institution, 11566
11609, institution, 10012
11609, institution, 1077
11609, institution, 5513
11609, institution, 513
11609, institution, 11306
11609, institution, 3969
11609, institution, 7808
11609, institution, 643
11609, institution, 5618
11609, institution, 8748
11609, institution, 6831
11609, institution, 11108
11609, institution, 4436
11609, institution, 1640
11609, institution, 6240
11609, institution, 3457
11609, institution, 6936
11609, institution, 1480
11609, institution, 8439
11609, institution, 3463
11609, institution, 7581
11609, institution, 13118
11609, institution, 12758
11609, institution, 9510
11609, major_field_of_study, 12442
12322, award, 10072
12322, award, 11025
12322, award_nominee, 5693
12027, acted_in, 13955
12027, award, 10072
12027, award, 11025
10246, award, 10072
10246, award, 11025
11306, currency, 42
11306, international_tuition_currency, 42
7783, currency, 42
7783, international_tuition_currency, 42
7783, state_province_region, 4866
4866, adjoins, 4669
4866, capital, 5948
4866, contains, 7783
4866, contains, 3969
4866, contains, 6014
4866, contains, 5948
4866, contains, 3463
4866, contains, 9570
4866, contains, 10689
4866, currency, 42
3969, campuses, 3969
3969, citytown, 5948
3969, educational_institution, 3969
3969, international_tuition_currency, 42
3969, state_province_region, 4866
11025, award_winner, 14022
11025, award_winner, 970
11025, award_winner, 4590
11025, nominated_for, 14189
4669, adjoins, 4866
4669, currency, 42
6014, citytown, 5948
6014, state_province_region, 4866
4025, award, 10072
4025, award, 11025
1685, award, 10072
1685, location, 5948
1685, place_of_birth, 5948
7808, currency, 42
7808, international_tuition_currency, 42
13965, award, 10072
13965, award, 11025
970, award, 10072
970, award, 11025
1354, award, 11025
1354, award_nominee, 7870
3164, award_winner, 5693
13637, student, 7870
5948, administrative_division, 4866
5948, contains, 3969
5948, contains, 6014
5948, contains, 5506
5948, contains, 10689
5948, vacationer, 12462
2618, currency, 42
13501, currency, 42
13501, international_tuition_currency, 42
3463, currency, 42
5506, citytown, 5948
5506, currency, 42
5506, state_province_region, 4866
9570, currency, 42
9570, international_tuition_currency, 42
9570, state_province_region, 4866
12758, currency, 42
4590, award, 10072
4590, award, 11025
10000, award, 10072
10000, award_nominee, 5693
13955, film_festivals, 87
13955, film_regional_debut_venue, 87
13955, produced_by, 11110
5693, acted_in, 14189
5693, acted_in, 3164
5693, award_nominee, 13509
5693, award_nominee, 12322
5693, nominated_for, 3164
10689, citytown, 5948
10689, currency, 42
10689, international_tuition_currency, 42
10689, state_province_region, 4866
Question: In what context are Independent_record_label, Juliette_Lewis, and Osgoode_Hall_Law_School connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Independent_record_label",
"Juliette_Lewis",
"Osgoode_Hall_Law_School"
],
"valid_edges": [
[
"2009_Toronto_International_Film_Festival",
"locations",
"Toronto"
],
[
"Adam_Sandler",
"award_nominee",
"Jessica_Biel"
],
[
"Adam_Sandler",
"award_winner",
"Drew_Barrymore"
],
[
"Adam_Sandler",
"participant",
"Jessica_Biel"
],
[
"Alfre_Woodard",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Alfre_Woodard",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Anjelica_Huston",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Anjelica_Huston",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Bachelor_of_Laws",
"institution",
"Albany_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Allahabad_University"
],
[
"Bachelor_of_Laws",
"institution",
"Cairo_University"
],
[
"Bachelor_of_Laws",
"institution",
"Christ_Church,_Oxford"
],
[
"Bachelor_of_Laws",
"institution",
"Columbia_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Columbia_University"
],
[
"Bachelor_of_Laws",
"institution",
"Cornell_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Dalhousie_University"
],
[
"Bachelor_of_Laws",
"institution",
"George_Washington_University"
],
[
"Bachelor_of_Laws",
"institution",
"Harvard_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"King's_College_London"
],
[
"Bachelor_of_Laws",
"institution",
"London_School_of_Economics_and_Political_Science"
],
[
"Bachelor_of_Laws",
"institution",
"McGill_University"
],
[
"Bachelor_of_Laws",
"institution",
"New_York_University_School_of_Law"
],
[
"Bachelor_of_Laws",
"institution",
"Osgoode_Hall_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Schulich_School_of_Law"
],
[
"Bachelor_of_Laws",
"institution",
"The_George_Washington_University_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Trinity_College,_Dublin"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Aberdeen"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Adelaide"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Auckland"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Bristol"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_British_Columbia"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_California,_Los_Angeles"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Cambridge"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Houston"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Manitoba"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Melbourne"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Michigan"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Ottawa"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Toronto"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Virginia_School_of_Law"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Western_Australia"
],
[
"Bachelor_of_Laws",
"institution",
"University_of_Western_Ontario"
],
[
"Bachelor_of_Laws",
"institution",
"UniversitΓ©_Laval"
],
[
"Bachelor_of_Laws",
"institution",
"Yale_Law_School"
],
[
"Bachelor_of_Laws",
"institution",
"Yale_University"
],
[
"Bachelor_of_Laws",
"major_field_of_study",
"Law"
],
[
"Bridget_Fonda",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Bridget_Fonda",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Catherine_O'Hara",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Catherine_O'Hara",
"location",
"Toronto"
],
[
"Catherine_O'Hara",
"place_of_birth",
"Toronto"
],
[
"Dalhousie_University",
"currency",
"Canadian_dollar"
],
[
"Dalhousie_University",
"international_tuition_currency",
"Canadian_dollar"
],
[
"Dean-GB",
"company",
"Columbia_Law_School"
],
[
"Dean-GB",
"company",
"King's_College_London"
],
[
"Dean-GB",
"company",
"Stanford_Law_School"
],
[
"Dean-GB",
"company",
"Yale_University"
],
[
"Dean-GB",
"organization",
"Albany_Law_School"
],
[
"Dean-GB",
"organization",
"Boston_University_School_of_Law"
],
[
"Dean-GB",
"organization",
"Christ_Church,_Oxford"
],
[
"Dean-GB",
"organization",
"Columbia_Law_School"
],
[
"Dean-GB",
"organization",
"Cornell_Law_School"
],
[
"Dean-GB",
"organization",
"Georgetown_University_Law_Center"
],
[
"Dean-GB",
"organization",
"Harvard_Law_School"
],
[
"Dean-GB",
"organization",
"New_York_University_School_of_Law"
],
[
"Dean-GB",
"organization",
"Osgoode_Hall_Law_School"
],
[
"Dean-GB",
"organization",
"Stanford_Law_School"
],
[
"Dean-GB",
"organization",
"The_George_Washington_University_Law_School"
],
[
"Dean-GB",
"organization",
"Tisch_School_of_the_Arts"
],
[
"Dean-GB",
"organization",
"University_of_Michigan_Law_School"
],
[
"Dean-GB",
"organization",
"University_of_Virginia_School_of_Law"
],
[
"Dean-GB",
"organization",
"Yale_Law_School"
],
[
"Dianne_Wiest",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Dianne_Wiest",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Drew_Barrymore",
"acted_in",
"Whip_It!"
],
[
"Drew_Barrymore",
"award_nominee",
"Adam_Sandler"
],
[
"Drew_Barrymore",
"award_winner",
"Adam_Sandler"
],
[
"Drew_Barrymore",
"film",
"Whip_It!"
],
[
"Ellen_Page",
"acted_in",
"Whip_It!"
],
[
"Ellen_Page",
"location",
"Toronto"
],
[
"Frances_McDormand",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Frances_McDormand",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Husbands_and_Wives",
"award_winner",
"Judy_Davis"
],
[
"Husbands_and_Wives",
"genre",
"Indie_film"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"award_winner",
"Anjelica_Huston"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"award_winner",
"Dianne_Wiest"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"award_winner",
"Frances_McDormand"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"award_winner",
"Mare_Winningham"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"award_winner",
"Shohreh_Aghdashloo"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"nominated_for",
"The_Messenger"
],
[
"Indie",
"split_to",
"Independent_record_label"
],
[
"Indie",
"split_to",
"Indie_film"
],
[
"Indie_film",
"split_to",
"Indie"
],
[
"Jessica_Biel",
"award_nominee",
"Adam_Sandler"
],
[
"Jessica_Lange",
"acted_in",
"Cape_Fear"
],
[
"Jessica_Lange",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Jimmy_Fallon",
"acted_in",
"Whip_It!"
],
[
"Jimmy_Fallon",
"celebrities_impersonated",
"Adam_Sandler"
],
[
"Jimmy_Fallon",
"influenced_by",
"Adam_Sandler"
],
[
"Judy_Davis",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Judy_Davis",
"nominated_for",
"Husbands_and_Wives"
],
[
"Juliette_Lewis",
"acted_in",
"Cape_Fear"
],
[
"Juliette_Lewis",
"acted_in",
"Husbands_and_Wives"
],
[
"Juliette_Lewis",
"acted_in",
"Whip_It!"
],
[
"Juliette_Lewis",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Juliette_Lewis",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Juliette_Lewis",
"award_nominee",
"Woody_Harrelson"
],
[
"Juliette_Lewis",
"nominated_for",
"Cape_Fear"
],
[
"Juliette_Lewis",
"participant",
"Adam_Sandler"
],
[
"Kathy_Baker",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Kathy_Baker",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Law",
"films",
"Cape_Fear"
],
[
"Law_degree",
"institution",
"Allahabad_University"
],
[
"Law_degree",
"institution",
"Boston_University_School_of_Law"
],
[
"Law_degree",
"institution",
"Cairo_University"
],
[
"Law_degree",
"institution",
"Columbia_Law_School"
],
[
"Law_degree",
"institution",
"Columbia_University"
],
[
"Law_degree",
"institution",
"George_Washington_University"
],
[
"Law_degree",
"institution",
"Georgetown_University_Law_Center"
],
[
"Law_degree",
"institution",
"Harvard_Law_School"
],
[
"Law_degree",
"institution",
"London_School_of_Economics_and_Political_Science"
],
[
"Law_degree",
"institution",
"McGill_University"
],
[
"Law_degree",
"institution",
"Osgoode_Hall_Law_School"
],
[
"Law_degree",
"institution",
"Schulich_School_of_Law"
],
[
"Law_degree",
"institution",
"Stanford_Law_School"
],
[
"Law_degree",
"institution",
"Trinity_College,_Dublin"
],
[
"Law_degree",
"institution",
"University_of_Aberdeen"
],
[
"Law_degree",
"institution",
"University_of_Adelaide"
],
[
"Law_degree",
"institution",
"University_of_Auckland"
],
[
"Law_degree",
"institution",
"University_of_Bristol"
],
[
"Law_degree",
"institution",
"University_of_California,_Los_Angeles"
],
[
"Law_degree",
"institution",
"University_of_Cambridge"
],
[
"Law_degree",
"institution",
"University_of_Houston"
],
[
"Law_degree",
"institution",
"University_of_Melbourne"
],
[
"Law_degree",
"institution",
"University_of_Michigan"
],
[
"Law_degree",
"institution",
"University_of_Michigan_Law_School"
],
[
"Law_degree",
"institution",
"University_of_Ottawa"
],
[
"Law_degree",
"institution",
"University_of_Virginia_School_of_Law"
],
[
"Law_degree",
"institution",
"University_of_Western_Australia"
],
[
"Law_degree",
"institution",
"UniversitΓ©_Laval"
],
[
"Law_degree",
"institution",
"Yale_Law_School"
],
[
"Law_degree",
"major_field_of_study",
"Law"
],
[
"Lily_Tomlin",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Lily_Tomlin",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Lily_Tomlin",
"award_nominee",
"Woody_Harrelson"
],
[
"Marcia_Gay_Harden",
"acted_in",
"Whip_It!"
],
[
"Marcia_Gay_Harden",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Marcia_Gay_Harden",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Mare_Winningham",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Mare_Winningham",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"McGill_University",
"currency",
"Canadian_dollar"
],
[
"McGill_University",
"international_tuition_currency",
"Canadian_dollar"
],
[
"McMaster_University",
"currency",
"Canadian_dollar"
],
[
"McMaster_University",
"international_tuition_currency",
"Canadian_dollar"
],
[
"McMaster_University",
"state_province_region",
"Ontario"
],
[
"Ontario",
"adjoins",
"QuΓ©bec"
],
[
"Ontario",
"capital",
"Toronto"
],
[
"Ontario",
"contains",
"McMaster_University"
],
[
"Ontario",
"contains",
"Osgoode_Hall_Law_School"
],
[
"Ontario",
"contains",
"Ryerson_University"
],
[
"Ontario",
"contains",
"Toronto"
],
[
"Ontario",
"contains",
"University_of_Ottawa"
],
[
"Ontario",
"contains",
"University_of_Western_Ontario"
],
[
"Ontario",
"contains",
"York_University"
],
[
"Ontario",
"currency",
"Canadian_dollar"
],
[
"Osgoode_Hall_Law_School",
"campuses",
"Osgoode_Hall_Law_School"
],
[
"Osgoode_Hall_Law_School",
"citytown",
"Toronto"
],
[
"Osgoode_Hall_Law_School",
"educational_institution",
"Osgoode_Hall_Law_School"
],
[
"Osgoode_Hall_Law_School",
"international_tuition_currency",
"Canadian_dollar"
],
[
"Osgoode_Hall_Law_School",
"state_province_region",
"Ontario"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"award_winner",
"Judy_Davis"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"award_winner",
"Stockard_Channing"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"award_winner",
"Vanessa_Redgrave"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie",
"nominated_for",
"Game_Change"
],
[
"QuΓ©bec",
"adjoins",
"Ontario"
],
[
"QuΓ©bec",
"currency",
"Canadian_dollar"
],
[
"Ryerson_University",
"citytown",
"Toronto"
],
[
"Ryerson_University",
"state_province_region",
"Ontario"
],
[
"Samantha_Morton",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Samantha_Morton",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Sarah_Polley",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Sarah_Polley",
"location",
"Toronto"
],
[
"Sarah_Polley",
"place_of_birth",
"Toronto"
],
[
"Schulich_School_of_Law",
"currency",
"Canadian_dollar"
],
[
"Schulich_School_of_Law",
"international_tuition_currency",
"Canadian_dollar"
],
[
"Shohreh_Aghdashloo",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Shohreh_Aghdashloo",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Stockard_Channing",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Stockard_Channing",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Susan_Sarandon",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Susan_Sarandon",
"award_nominee",
"Adam_Sandler"
],
[
"The_Messenger",
"award_winner",
"Woody_Harrelson"
],
[
"Tisch_School_of_the_Arts",
"student",
"Adam_Sandler"
],
[
"Toronto",
"administrative_division",
"Ontario"
],
[
"Toronto",
"contains",
"Osgoode_Hall_Law_School"
],
[
"Toronto",
"contains",
"Ryerson_University"
],
[
"Toronto",
"contains",
"University_of_Toronto"
],
[
"Toronto",
"contains",
"York_University"
],
[
"Toronto",
"vacationer",
"Jessica_Biel"
],
[
"University_of_British_Columbia",
"currency",
"Canadian_dollar"
],
[
"University_of_Manitoba",
"currency",
"Canadian_dollar"
],
[
"University_of_Manitoba",
"international_tuition_currency",
"Canadian_dollar"
],
[
"University_of_Ottawa",
"currency",
"Canadian_dollar"
],
[
"University_of_Toronto",
"citytown",
"Toronto"
],
[
"University_of_Toronto",
"currency",
"Canadian_dollar"
],
[
"University_of_Toronto",
"state_province_region",
"Ontario"
],
[
"University_of_Western_Ontario",
"currency",
"Canadian_dollar"
],
[
"University_of_Western_Ontario",
"international_tuition_currency",
"Canadian_dollar"
],
[
"University_of_Western_Ontario",
"state_province_region",
"Ontario"
],
[
"UniversitΓ©_Laval",
"currency",
"Canadian_dollar"
],
[
"Vanessa_Redgrave",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Vanessa_Redgrave",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actress_-_Miniseries_or_a_Movie"
],
[
"Virginia_Madsen",
"award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Virginia_Madsen",
"award_nominee",
"Woody_Harrelson"
],
[
"Whip_It!",
"film_festivals",
"2009_Toronto_International_Film_Festival"
],
[
"Whip_It!",
"film_regional_debut_venue",
"2009_Toronto_International_Film_Festival"
],
[
"Whip_It!",
"produced_by",
"Drew_Barrymore"
],
[
"Woody_Harrelson",
"acted_in",
"Game_Change"
],
[
"Woody_Harrelson",
"acted_in",
"The_Messenger"
],
[
"Woody_Harrelson",
"award_nominee",
"Juliette_Lewis"
],
[
"Woody_Harrelson",
"award_nominee",
"Lily_Tomlin"
],
[
"Woody_Harrelson",
"nominated_for",
"The_Messenger"
],
[
"York_University",
"citytown",
"Toronto"
],
[
"York_University",
"currency",
"Canadian_dollar"
],
[
"York_University",
"international_tuition_currency",
"Canadian_dollar"
],
[
"York_University",
"state_province_region",
"Ontario"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
857, Alain_Johannes
7785, Art_rock
10288, Artistic_gymnastics
4390, Asia
9877, Axl_Rose
7933, Brian_May
3211, Brian_Wilson
10817, Bronze_medal
12015, Bryan_Adams
1750, Buckethead
10813, Capitol_Records
10173, Carlos_Santana
6472, Carmen_Electra
966, Chicago_metropolitan_area
5379, Christianity
5747, Dave_Grohl
905, Dave_Navarro
13560, David_Bowie
82, David_Gilmour
3846, Debbie_Harry
4084, Deep_Purple
14204, Devin_Townsend
7793, Diving
4831, Duff_McKagan
5883, Eric_Burdon
1499, Eric_Clapton
9521, Europe
3097, Foo_Fighters
4172, Fred_Durst
6443, Fred_MacMurray
6963, Gary_Moore
4835, Glen_Campbell
5701, Gold_medal
3243, Grammy_Award_for_Best_Rock_Performance_by_a_Duo_or_Group_with_Vocal
6954, Guitarist-GB
6948, Hard_rock
9804, Hawkwind
10337, Heart
12610, Illinois
8264, Jack_Bruce
13408, Jane's_Addiction
3080, Jefferson_Airplane
4462, Jefferson_Starship
6122, Jethro_Tull
6235, Jimi_Hendrix
8347, Jimmy_Page
7574, Joe_Satriani
6176, John_Frusciante
4600, John_Lennon
10068, Joshua_Homme
3910, Katy_Perry
13201, Kharkiv
2480, King_Crimson
6351, Lou_Reed
5516, Mike_Watt
8989, Miles_Davis
1781, Nat_King_Cole
7092, Nick_Mason
9545, Ozzy_Osbourne
7353, PJ_Harvey
11160, Pete_Townshend
1071, Phish
9170, Pink_Floyd
2802, Porcupine_Tree
8126, Progressive_rock
1164, Psychedelic_rock
9297, Queen
10375, Queens_of_the_Stone_Age
1439, Red_Hot_Chili_Peppers
1081, Richard_Wright
5876, Ringo_Starr
3722, Ritchie_Blackmore
5214, Robert_Fripp
4077, Rod_Stewart
11948, Roger_Waters
5453, Russian_Language
1391, Santa_Monica
3035, Serj_Tankian
4413, Shooting_sport
6332, Silver_medal
486, Soviet_Union
5508, Steve_Hackett
459, Steve_Howe
5168, Steve_Miller_Band
4920, Steve_Vai
7969, Steve_Winwood
13332, Steven_Wilson
11656, The_Black_Keys
1829, The_Guess_Who
1982, The_Mars_Volta
4824, The_Mothers_of_Invention
4851, The_Rolling_Stones
8187, The_Smashing_Pumpkins
2591, The_Who
9942, Todd_Rundgren
12071, Track_cycling
1357, Trevor_Rabin
36, Ukraine
7850, United_Nations
8001, Yes
src, edge_attr, dst
857, profession, 6954
7785, artists, 13408
7785, parent_genre, 1164
10288, country, 486
10288, country, 36
4390, partially_contains, 486
9877, profession, 6954
7933, profession, 6954
12015, profession, 6954
1750, profession, 6954
10813, artist, 3211
10813, artist, 5747
10813, artist, 905
10813, artist, 82
10813, artist, 3846
10813, artist, 3097
10813, artist, 4835
10813, artist, 10337
10813, artist, 13408
10813, artist, 6122
10813, artist, 6235
10813, artist, 4600
10813, artist, 3910
10813, artist, 8989
10813, artist, 1781
10813, artist, 7092
10813, artist, 9170
10813, artist, 9297
10813, artist, 1081
10813, artist, 5876
10813, artist, 11948
10813, artist, 5168
10173, profession, 6954
6472, participant, 4172
6472, religion, 5379
6472, spouse, 905
5747, profession, 6954
905, group, 13408
905, group, 1439
905, location, 1391
905, participant, 6472
905, place_of_birth, 1391
905, profession, 6954
905, spouse, 6472
13560, profession, 6954
82, profession, 6954
14204, profession, 6954
7793, country, 486
7793, country, 36
4831, group, 13408
4831, profession, 6954
5883, profession, 6954
1499, profession, 6954
9521, contains, 36
9521, countries_within, 36
9521, partially_contains, 486
4172, participant, 6472
4172, profession, 6954
6443, location, 12610
6443, place_of_death, 1391
6963, profession, 6954
4835, profession, 6954
3243, award_winner, 1439
6948, artists, 857
6948, artists, 4390
6948, artists, 9877
6948, artists, 7933
6948, artists, 12015
6948, artists, 1750
6948, artists, 10173
6948, artists, 5747
6948, artists, 905
6948, artists, 13560
6948, artists, 82
6948, artists, 3846
6948, artists, 4084
6948, artists, 14204
6948, artists, 4831
6948, artists, 5883
6948, artists, 1499
6948, artists, 3097
6948, artists, 6963
6948, artists, 9804
6948, artists, 10337
6948, artists, 8264
6948, artists, 13408
6948, artists, 3080
6948, artists, 4462
6948, artists, 6122
6948, artists, 6235
6948, artists, 8347
6948, artists, 7574
6948, artists, 10068
6948, artists, 2480
6948, artists, 6351
6948, artists, 5516
6948, artists, 7092
6948, artists, 9545
6948, artists, 7353
6948, artists, 11160
6948, artists, 1071
6948, artists, 9170
6948, artists, 2802
6948, artists, 9297
6948, artists, 10375
6948, artists, 1439
6948, artists, 1081
6948, artists, 3722
6948, artists, 5214
6948, artists, 4077
6948, artists, 11948
6948, artists, 3035
6948, artists, 5508
6948, artists, 459
6948, artists, 4920
6948, artists, 11656
6948, artists, 1829
6948, artists, 1982
6948, artists, 4824
6948, artists, 4851
6948, artists, 8187
6948, artists, 2591
6948, artists, 9942
6948, artists, 1357
6948, artists, 8001
12610, contains, 966
12610, religion, 5379
13408, award, 3243
6235, profession, 6954
8347, profession, 6954
7574, profession, 6954
6176, group, 1439
6176, profession, 6954
4600, profession, 6954
10068, profession, 6954
3910, profession, 6954
6351, profession, 6954
8989, place_of_death, 1391
1781, place_of_death, 1391
9545, profession, 6954
7353, profession, 6954
11160, profession, 6954
8126, parent_genre, 6948
8126, parent_genre, 1164
1164, artists, 857
1164, artists, 3211
1164, artists, 10173
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1164, artists, 13560
1164, artists, 82
1164, artists, 4084
1164, artists, 5883
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1164, artists, 6963
1164, artists, 9804
1164, artists, 8264
1164, artists, 3080
1164, artists, 4462
1164, artists, 6122
1164, artists, 6235
1164, artists, 6176
1164, artists, 4600
1164, artists, 10068
1164, artists, 2480
1164, artists, 6351
1164, artists, 5516
1164, artists, 7092
1164, artists, 1071
1164, artists, 9170
1164, artists, 2802
1164, artists, 10375
1164, artists, 1439
1164, artists, 1081
1164, artists, 5876
1164, artists, 3722
1164, artists, 5214
1164, artists, 11948
1164, artists, 3035
1164, artists, 459
1164, artists, 5168
1164, artists, 7969
1164, artists, 13332
1164, artists, 11656
1164, artists, 1829
1164, artists, 1982
1164, artists, 4824
1164, artists, 4851
1164, artists, 8187
1164, artists, 2591
1164, artists, 9942
1164, artists, 8001
1439, award, 3243
3722, profession, 6954
5214, profession, 6954
4077, profession, 6954
11948, profession, 6954
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1391, place, 1391
3035, profession, 6954
4413, country, 486
4413, country, 36
486, contains, 13201
486, medal, 10817
486, medal, 5701
486, medal, 6332
486, official_language, 5453
486, organization, 7850
5508, profession, 6954
459, profession, 6954
4920, profession, 6954
7969, profession, 6954
13332, profession, 6954
12071, country, 486
12071, country, 36
1357, profession, 6954
36, contains, 13201
36, medal, 10817
36, medal, 5701
36, medal, 6332
36, organization, 7850
Question: How are Chicago_metropolitan_area, Dave_Navarro, and Kharkiv related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Chicago_metropolitan_area",
"Dave_Navarro",
"Kharkiv"
],
"valid_edges": [
[
"Alain_Johannes",
"profession",
"Guitarist-GB"
],
[
"Art_rock",
"artists",
"Jane's_Addiction"
],
[
"Art_rock",
"parent_genre",
"Psychedelic_rock"
],
[
"Artistic_gymnastics",
"country",
"Soviet_Union"
],
[
"Artistic_gymnastics",
"country",
"Ukraine"
],
[
"Asia",
"partially_contains",
"Soviet_Union"
],
[
"Axl_Rose",
"profession",
"Guitarist-GB"
],
[
"Brian_May",
"profession",
"Guitarist-GB"
],
[
"Bryan_Adams",
"profession",
"Guitarist-GB"
],
[
"Buckethead",
"profession",
"Guitarist-GB"
],
[
"Capitol_Records",
"artist",
"Brian_Wilson"
],
[
"Capitol_Records",
"artist",
"Dave_Grohl"
],
[
"Capitol_Records",
"artist",
"Dave_Navarro"
],
[
"Capitol_Records",
"artist",
"David_Gilmour"
],
[
"Capitol_Records",
"artist",
"Debbie_Harry"
],
[
"Capitol_Records",
"artist",
"Foo_Fighters"
],
[
"Capitol_Records",
"artist",
"Glen_Campbell"
],
[
"Capitol_Records",
"artist",
"Heart"
],
[
"Capitol_Records",
"artist",
"Jane's_Addiction"
],
[
"Capitol_Records",
"artist",
"Jethro_Tull"
],
[
"Capitol_Records",
"artist",
"Jimi_Hendrix"
],
[
"Capitol_Records",
"artist",
"John_Lennon"
],
[
"Capitol_Records",
"artist",
"Katy_Perry"
],
[
"Capitol_Records",
"artist",
"Miles_Davis"
],
[
"Capitol_Records",
"artist",
"Nat_King_Cole"
],
[
"Capitol_Records",
"artist",
"Nick_Mason"
],
[
"Capitol_Records",
"artist",
"Pink_Floyd"
],
[
"Capitol_Records",
"artist",
"Queen"
],
[
"Capitol_Records",
"artist",
"Richard_Wright"
],
[
"Capitol_Records",
"artist",
"Ringo_Starr"
],
[
"Capitol_Records",
"artist",
"Roger_Waters"
],
[
"Capitol_Records",
"artist",
"Steve_Miller_Band"
],
[
"Carlos_Santana",
"profession",
"Guitarist-GB"
],
[
"Carmen_Electra",
"participant",
"Fred_Durst"
],
[
"Carmen_Electra",
"religion",
"Christianity"
],
[
"Carmen_Electra",
"spouse",
"Dave_Navarro"
],
[
"Dave_Grohl",
"profession",
"Guitarist-GB"
],
[
"Dave_Navarro",
"group",
"Jane's_Addiction"
],
[
"Dave_Navarro",
"group",
"Red_Hot_Chili_Peppers"
],
[
"Dave_Navarro",
"location",
"Santa_Monica"
],
[
"Dave_Navarro",
"participant",
"Carmen_Electra"
],
[
"Dave_Navarro",
"place_of_birth",
"Santa_Monica"
],
[
"Dave_Navarro",
"profession",
"Guitarist-GB"
],
[
"Dave_Navarro",
"spouse",
"Carmen_Electra"
],
[
"David_Bowie",
"profession",
"Guitarist-GB"
],
[
"David_Gilmour",
"profession",
"Guitarist-GB"
],
[
"Devin_Townsend",
"profession",
"Guitarist-GB"
],
[
"Diving",
"country",
"Soviet_Union"
],
[
"Diving",
"country",
"Ukraine"
],
[
"Duff_McKagan",
"group",
"Jane's_Addiction"
],
[
"Duff_McKagan",
"profession",
"Guitarist-GB"
],
[
"Eric_Burdon",
"profession",
"Guitarist-GB"
],
[
"Eric_Clapton",
"profession",
"Guitarist-GB"
],
[
"Europe",
"contains",
"Ukraine"
],
[
"Europe",
"countries_within",
"Ukraine"
],
[
"Europe",
"partially_contains",
"Soviet_Union"
],
[
"Fred_Durst",
"participant",
"Carmen_Electra"
],
[
"Fred_Durst",
"profession",
"Guitarist-GB"
],
[
"Fred_MacMurray",
"location",
"Illinois"
],
[
"Fred_MacMurray",
"place_of_death",
"Santa_Monica"
],
[
"Gary_Moore",
"profession",
"Guitarist-GB"
],
[
"Glen_Campbell",
"profession",
"Guitarist-GB"
],
[
"Grammy_Award_for_Best_Rock_Performance_by_a_Duo_or_Group_with_Vocal",
"award_winner",
"Red_Hot_Chili_Peppers"
],
[
"Hard_rock",
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"Alain_Johannes"
],
[
"Hard_rock",
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],
[
"Hard_rock",
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"Axl_Rose"
],
[
"Hard_rock",
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"Brian_May"
],
[
"Hard_rock",
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"Bryan_Adams"
],
[
"Hard_rock",
"artists",
"Buckethead"
],
[
"Hard_rock",
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"Carlos_Santana"
],
[
"Hard_rock",
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"Dave_Grohl"
],
[
"Hard_rock",
"artists",
"Dave_Navarro"
],
[
"Hard_rock",
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"David_Bowie"
],
[
"Hard_rock",
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"David_Gilmour"
],
[
"Hard_rock",
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"Debbie_Harry"
],
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"Hard_rock",
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"Deep_Purple"
],
[
"Hard_rock",
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],
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"Hard_rock",
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"Duff_McKagan"
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[
"Hard_rock",
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"Eric_Burdon"
],
[
"Hard_rock",
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"Eric_Clapton"
],
[
"Hard_rock",
"artists",
"Foo_Fighters"
],
[
"Hard_rock",
"artists",
"Gary_Moore"
],
[
"Hard_rock",
"artists",
"Hawkwind"
],
[
"Hard_rock",
"artists",
"Heart"
],
[
"Hard_rock",
"artists",
"Jack_Bruce"
],
[
"Hard_rock",
"artists",
"Jane's_Addiction"
],
[
"Hard_rock",
"artists",
"Jefferson_Airplane"
],
[
"Hard_rock",
"artists",
"Jefferson_Starship"
],
[
"Hard_rock",
"artists",
"Jethro_Tull"
],
[
"Hard_rock",
"artists",
"Jimi_Hendrix"
],
[
"Hard_rock",
"artists",
"Jimmy_Page"
],
[
"Hard_rock",
"artists",
"Joe_Satriani"
],
[
"Hard_rock",
"artists",
"Joshua_Homme"
],
[
"Hard_rock",
"artists",
"King_Crimson"
],
[
"Hard_rock",
"artists",
"Lou_Reed"
],
[
"Hard_rock",
"artists",
"Mike_Watt"
],
[
"Hard_rock",
"artists",
"Nick_Mason"
],
[
"Hard_rock",
"artists",
"Ozzy_Osbourne"
],
[
"Hard_rock",
"artists",
"PJ_Harvey"
],
[
"Hard_rock",
"artists",
"Pete_Townshend"
],
[
"Hard_rock",
"artists",
"Phish"
],
[
"Hard_rock",
"artists",
"Pink_Floyd"
],
[
"Hard_rock",
"artists",
"Porcupine_Tree"
],
[
"Hard_rock",
"artists",
"Queen"
],
[
"Hard_rock",
"artists",
"Queens_of_the_Stone_Age"
],
[
"Hard_rock",
"artists",
"Red_Hot_Chili_Peppers"
],
[
"Hard_rock",
"artists",
"Richard_Wright"
],
[
"Hard_rock",
"artists",
"Ritchie_Blackmore"
],
[
"Hard_rock",
"artists",
"Robert_Fripp"
],
[
"Hard_rock",
"artists",
"Rod_Stewart"
],
[
"Hard_rock",
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"Roger_Waters"
],
[
"Hard_rock",
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"Serj_Tankian"
],
[
"Hard_rock",
"artists",
"Steve_Hackett"
],
[
"Hard_rock",
"artists",
"Steve_Howe"
],
[
"Hard_rock",
"artists",
"Steve_Vai"
],
[
"Hard_rock",
"artists",
"The_Black_Keys"
],
[
"Hard_rock",
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"The_Guess_Who"
],
[
"Hard_rock",
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"The_Mars_Volta"
],
[
"Hard_rock",
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"The_Mothers_of_Invention"
],
[
"Hard_rock",
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"The_Rolling_Stones"
],
[
"Hard_rock",
"artists",
"The_Smashing_Pumpkins"
],
[
"Hard_rock",
"artists",
"The_Who"
],
[
"Hard_rock",
"artists",
"Todd_Rundgren"
],
[
"Hard_rock",
"artists",
"Trevor_Rabin"
],
[
"Hard_rock",
"artists",
"Yes"
],
[
"Illinois",
"contains",
"Chicago_metropolitan_area"
],
[
"Illinois",
"religion",
"Christianity"
],
[
"Jane's_Addiction",
"award",
"Grammy_Award_for_Best_Rock_Performance_by_a_Duo_or_Group_with_Vocal"
],
[
"Jimi_Hendrix",
"profession",
"Guitarist-GB"
],
[
"Jimmy_Page",
"profession",
"Guitarist-GB"
],
[
"Joe_Satriani",
"profession",
"Guitarist-GB"
],
[
"John_Frusciante",
"group",
"Red_Hot_Chili_Peppers"
],
[
"John_Frusciante",
"profession",
"Guitarist-GB"
],
[
"John_Lennon",
"profession",
"Guitarist-GB"
],
[
"Joshua_Homme",
"profession",
"Guitarist-GB"
],
[
"Katy_Perry",
"profession",
"Guitarist-GB"
],
[
"Lou_Reed",
"profession",
"Guitarist-GB"
],
[
"Miles_Davis",
"place_of_death",
"Santa_Monica"
],
[
"Nat_King_Cole",
"place_of_death",
"Santa_Monica"
],
[
"Ozzy_Osbourne",
"profession",
"Guitarist-GB"
],
[
"PJ_Harvey",
"profession",
"Guitarist-GB"
],
[
"Pete_Townshend",
"profession",
"Guitarist-GB"
],
[
"Progressive_rock",
"parent_genre",
"Hard_rock"
],
[
"Progressive_rock",
"parent_genre",
"Psychedelic_rock"
],
[
"Psychedelic_rock",
"artists",
"Alain_Johannes"
],
[
"Psychedelic_rock",
"artists",
"Brian_Wilson"
],
[
"Psychedelic_rock",
"artists",
"Carlos_Santana"
],
[
"Psychedelic_rock",
"artists",
"Dave_Navarro"
],
[
"Psychedelic_rock",
"artists",
"David_Bowie"
],
[
"Psychedelic_rock",
"artists",
"David_Gilmour"
],
[
"Psychedelic_rock",
"artists",
"Deep_Purple"
],
[
"Psychedelic_rock",
"artists",
"Eric_Burdon"
],
[
"Psychedelic_rock",
"artists",
"Eric_Clapton"
],
[
"Psychedelic_rock",
"artists",
"Gary_Moore"
],
[
"Psychedelic_rock",
"artists",
"Hawkwind"
],
[
"Psychedelic_rock",
"artists",
"Jack_Bruce"
],
[
"Psychedelic_rock",
"artists",
"Jefferson_Airplane"
],
[
"Psychedelic_rock",
"artists",
"Jefferson_Starship"
],
[
"Psychedelic_rock",
"artists",
"Jethro_Tull"
],
[
"Psychedelic_rock",
"artists",
"Jimi_Hendrix"
],
[
"Psychedelic_rock",
"artists",
"John_Frusciante"
],
[
"Psychedelic_rock",
"artists",
"John_Lennon"
],
[
"Psychedelic_rock",
"artists",
"Joshua_Homme"
],
[
"Psychedelic_rock",
"artists",
"King_Crimson"
],
[
"Psychedelic_rock",
"artists",
"Lou_Reed"
],
[
"Psychedelic_rock",
"artists",
"Mike_Watt"
],
[
"Psychedelic_rock",
"artists",
"Nick_Mason"
],
[
"Psychedelic_rock",
"artists",
"Phish"
],
[
"Psychedelic_rock",
"artists",
"Pink_Floyd"
],
[
"Psychedelic_rock",
"artists",
"Porcupine_Tree"
],
[
"Psychedelic_rock",
"artists",
"Queens_of_the_Stone_Age"
],
[
"Psychedelic_rock",
"artists",
"Red_Hot_Chili_Peppers"
],
[
"Psychedelic_rock",
"artists",
"Richard_Wright"
],
[
"Psychedelic_rock",
"artists",
"Ringo_Starr"
],
[
"Psychedelic_rock",
"artists",
"Ritchie_Blackmore"
],
[
"Psychedelic_rock",
"artists",
"Robert_Fripp"
],
[
"Psychedelic_rock",
"artists",
"Roger_Waters"
],
[
"Psychedelic_rock",
"artists",
"Serj_Tankian"
],
[
"Psychedelic_rock",
"artists",
"Steve_Howe"
],
[
"Psychedelic_rock",
"artists",
"Steve_Miller_Band"
],
[
"Psychedelic_rock",
"artists",
"Steve_Winwood"
],
[
"Psychedelic_rock",
"artists",
"Steven_Wilson"
],
[
"Psychedelic_rock",
"artists",
"The_Black_Keys"
],
[
"Psychedelic_rock",
"artists",
"The_Guess_Who"
],
[
"Psychedelic_rock",
"artists",
"The_Mars_Volta"
],
[
"Psychedelic_rock",
"artists",
"The_Mothers_of_Invention"
],
[
"Psychedelic_rock",
"artists",
"The_Rolling_Stones"
],
[
"Psychedelic_rock",
"artists",
"The_Smashing_Pumpkins"
],
[
"Psychedelic_rock",
"artists",
"The_Who"
],
[
"Psychedelic_rock",
"artists",
"Todd_Rundgren"
],
[
"Psychedelic_rock",
"artists",
"Yes"
],
[
"Red_Hot_Chili_Peppers",
"award",
"Grammy_Award_for_Best_Rock_Performance_by_a_Duo_or_Group_with_Vocal"
],
[
"Ritchie_Blackmore",
"profession",
"Guitarist-GB"
],
[
"Robert_Fripp",
"profession",
"Guitarist-GB"
],
[
"Rod_Stewart",
"profession",
"Guitarist-GB"
],
[
"Roger_Waters",
"profession",
"Guitarist-GB"
],
[
"Russian_Language",
"countries_spoken_in",
"Ukraine"
],
[
"Santa_Monica",
"place",
"Santa_Monica"
],
[
"Serj_Tankian",
"profession",
"Guitarist-GB"
],
[
"Shooting_sport",
"country",
"Soviet_Union"
],
[
"Shooting_sport",
"country",
"Ukraine"
],
[
"Soviet_Union",
"contains",
"Kharkiv"
],
[
"Soviet_Union",
"medal",
"Bronze_medal"
],
[
"Soviet_Union",
"medal",
"Gold_medal"
],
[
"Soviet_Union",
"medal",
"Silver_medal"
],
[
"Soviet_Union",
"official_language",
"Russian_Language"
],
[
"Soviet_Union",
"organization",
"United_Nations"
],
[
"Steve_Hackett",
"profession",
"Guitarist-GB"
],
[
"Steve_Howe",
"profession",
"Guitarist-GB"
],
[
"Steve_Vai",
"profession",
"Guitarist-GB"
],
[
"Steve_Winwood",
"profession",
"Guitarist-GB"
],
[
"Steven_Wilson",
"profession",
"Guitarist-GB"
],
[
"Track_cycling",
"country",
"Soviet_Union"
],
[
"Track_cycling",
"country",
"Ukraine"
],
[
"Trevor_Rabin",
"profession",
"Guitarist-GB"
],
[
"Ukraine",
"contains",
"Kharkiv"
],
[
"Ukraine",
"medal",
"Bronze_medal"
],
[
"Ukraine",
"medal",
"Gold_medal"
],
[
"Ukraine",
"medal",
"Silver_medal"
],
[
"Ukraine",
"organization",
"United_Nations"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4936, A._R._Rahman
7852, Alan_Menken
11991, Aldo_Nova
8558, Alyson_Stoner
9737, Amy_Winehouse
10351, Anthony_Newley
5367, Ashley_Tisdale
8950, Ayumi_Hamasaki
3107, Babyface
10577, Barbra_Streisand
6997, Barry_Manilow
6724, Ben_Folds
6365, Benny_Andersson
7991, Bill_Hader
2291, Billy_Bob_Thornton
9603, Billy_Joel
13845, Bobby_McFerrin
4225, Brian_Jones
3211, Brian_Wilson
702, Burt_Bacharach
13137, Celine_Dion
3616, Charlie_Daniels
4210, Chris_Seefried
10334, Christina_Aguilera
2577, Christopher_Cerf
10452, Cole_Porter
10409, Composer
13599, Courtney_Love
3346, Cy_Coleman
695, Damon_Albarn
9221, Danny_McBride
13560, David_Bowie
8480, David_Foster
3824, Diane_Warren
1635, Dolly_Parton
9812, Donna_Summer
7312, Donovan
4662, Drake
13687, Duke_Ellington
13394, Ed_Begley,_Jr.
4027, Elliot_Goldenthal
9344, Elton_John
160, Elvis_Presley
10901, Eric_Idle
9765, Frank_Loesser
8871, George_Martin
3850, Graeme_Revell
12503, Greece
10283, Gustavo_Cerati
8583, Gwen_Stefani
6302, Hal_David
3369, Harry_Connick,_Jr.
11328, Harry_Warren
4415, Hayden_Panettiere
10023, Herb_Alpert
8137, Hikaru_Utada
12572, Himesh_Reshammiya
9343, Irving_Berlin
3137, James_Remar
12325, James_Taylor
11606, Jared_Leto
10202, Jean-Jacques_Goldman
8497, Jeff_Lynne
1243, Jeff_Moss
8840, Jennifer_Love_Hewitt
5458, Jerry_Herman
6546, Jesse_McCartney
8135, Jim_Dale
8516, Jim_Steinman
10909, Joe_Jonas
1153, Joey_Fatone
9950, John_Coltrane
1948, John_Denver
4550, Johnny_Mercer
12860, Johnny_Yong_Bosch
8142, Jon_Bon_Jovi
1152, Jules_Bass
1736, Justin_Long
6736, Kamal_Haasan
3910, Katy_Perry
11668, Keith_Moon
12836, Keith_Richards
12770, Kenny_Loggins
4765, Kenny_Rogers
8790, Kylie_Minogue
10345, Las_Vegas
12954, Lenny_Kravitz
8908, Leslie_Bricusse
3775, Lorenz_Hart
6764, Ludwig_van_Beethoven
13030, Lukasz_Gottwald
10897, Lyricist
3725, Maaya_Sakamoto
2419, Macedonia_national_football_team
10110, Mamoru_Miyano
10073, Mandy_Moore
3955, Marc_Anthony
1608, Marc_Shaiman
11282, Mariah_Carey
14234, Mark_Ronson
12157, Marvin_Gaye
8080, Max_Martin
1633, Megumi_Hayashibara
8496, Mel_Brooks
2315, Michael_Jackson
7418, Michael_McKean
2638, Michael_Stipe
4464, Michael_W._Smith
11133, Mike_Judge
5916, Mike_Nawrocki
11801, Mike_Oldfield
2450, Mike_Patton
9037, Minami_Takayama
3917, Natalie_Cole
9215, Ne-Yo
10633, New_Wave
12023, Nick_Cave
6528, Nico
9545, Ozzy_Osbourne
7555, Paul_McCartney
6339, Paul_Shaffer
13910, Paul_Weller
649, Paul_Williams
10638, Pete_Seeger
11160, Pete_Townshend
6838, Pineapple_Express
12795, Pop_music
5241, Pop_rock
8902, Pritam_Chakraborty
7107, Quincy_Jones
882, R._Kelly
1606, Rabindranath_Tagore
11646, Randy_Newman
8708, Ray_Charles
11920, Republic_of_Macedonia
10167, Richard_M._Sherman
11107, Richard_Rodgers
4648, Rick_Wakeman
7205, Ringo_Sheena
5876, Ringo_Starr
2166, Rivers_Cuomo
11577, Robert_Wachtel
95, Robin_Gibb
3021, Robin_Thicke
2669, Roy_Wood
9181, Rupert_Holmes
3509, Seth_MacFarlane
11416, Seth_Rogen
12987, Sheena_Easton
5960, Sheryl_Crow
5277, Singer-songwriter-GB
4007, Stanley_Clarke
2258, Stephen_Schwartz
5771, Stephen_Sondheim
11585, Stevie_Wonder
7172, Stewart_Copeland
2447, Sting
11922, Tim_Curry
10264, Toby_Keith
321, Trey_Parker
12766, Tricky_Stewart
6410, Usher
3661, Van_Morrison
8156, Vishal_Bharadwaj
2013, Voice_Actor
13379, Wendy_Melvoin
7295, Will.i.am
2405, Wynton_Marsalis
1260, Yui_Horie
826, Yusuf_Islam
src, edge_attr, dst
4936, profession, 10409
7852, profession, 10409
11991, award_nominee, 8480
11991, award_nominee, 10202
11991, award_winner, 13137
11991, award_winner, 10202
11991, award_winner, 8516
11991, profession, 5277
8558, profession, 2013
9737, profession, 10409
10351, profession, 10409
10351, profession, 10897
5367, profession, 2013
8950, location_of_ceremony, 10345
8950, profession, 10409
8950, profession, 10897
3107, award_nominee, 8480
3107, award_winner, 8480
10577, award_nominee, 13137
10577, award_nominee, 12770
6997, profession, 10409
6724, location_of_ceremony, 10345
6724, profession, 10409
6365, profession, 10409
7991, acted_in, 6838
7991, profession, 2013
2291, location_of_ceremony, 10345
2291, profession, 2013
9603, profession, 10409
9603, profession, 10897
13845, profession, 10409
4225, profession, 10409
3211, profession, 10409
702, profession, 10409
13137, award_nominee, 11991
13137, award_nominee, 10577
13137, award_nominee, 8480
13137, award_nominee, 8516
13137, award_nominee, 882
13137, award_winner, 11991
13137, award_winner, 10577
13137, award_winner, 8480
13137, award_winner, 10202
13137, award_winner, 8516
13137, location, 10345
3616, profession, 10409
3616, profession, 10897
4210, profession, 10409
2577, profession, 10409
2577, profession, 10897
2577, profession, 2013
10452, profession, 10409
10452, profession, 10897
13599, location_of_ceremony, 10345
13599, profession, 10897
3346, profession, 10409
3346, profession, 10897
695, profession, 10409
9221, acted_in, 6838
9221, nominated_for, 6838
9221, profession, 2013
13560, profession, 10409
13560, profession, 10897
8480, award_nominee, 3107
8480, award_nominee, 13137
8480, award_nominee, 3917
8480, award_winner, 11991
8480, award_winner, 13137
8480, award_winner, 10202
8480, award_winner, 8516
8480, profession, 10409
3824, profession, 10409
3824, profession, 10897
1635, profession, 10409
9812, profession, 10409
9812, profession, 10897
7312, profession, 10409
7312, profession, 10897
4662, profession, 10409
13687, profession, 10409
13687, profession, 10897
13394, acted_in, 6838
13394, location_of_ceremony, 10345
13394, profession, 2013
4027, profession, 10409
4027, profession, 10897
9344, profession, 10409
160, location_of_ceremony, 10345
10901, profession, 10409
10901, profession, 10897
9765, profession, 10409
9765, profession, 10897
8871, profession, 10409
3850, profession, 10409
12503, adjoins, 11920
10283, profession, 10409
6302, profession, 10897
3369, profession, 10409
3369, profession, 10897
11328, profession, 10409
11328, profession, 10897
4415, profession, 2013
10023, profession, 10409
8137, profession, 10409
12572, profession, 10409
12572, profession, 10897
9343, profession, 10409
9343, profession, 10897
3137, acted_in, 6838
3137, profession, 2013
12325, profession, 10409
12325, profession, 10897
11606, profession, 10409
11606, profession, 10897
10202, award_nominee, 11991
10202, award_nominee, 13137
10202, award_nominee, 8480
10202, award_nominee, 8516
10202, award_winner, 11991
10202, award_winner, 8480
10202, award_winner, 8516
10202, profession, 5277
8497, profession, 10409
1243, profession, 10897
1243, profession, 2013
8840, profession, 2013
5458, profession, 10409
5458, profession, 10897
6546, profession, 2013
8135, profession, 10897
8135, profession, 2013
8516, award_nominee, 12770
8516, award_winner, 11991
8516, award_winner, 13137
8516, award_winner, 8480
8516, award_winner, 10202
8516, profession, 10409
8516, profession, 10897
10909, profession, 2013
1153, profession, 2013
9950, profession, 10409
9950, profession, 10897
1948, profession, 10409
1948, profession, 10897
4550, profession, 10409
4550, profession, 10897
12860, profession, 2013
8142, location_of_ceremony, 10345
8142, profession, 10409
1152, profession, 10409
1152, profession, 10897
1736, acted_in, 6838
1736, profession, 2013
6736, profession, 10897
6736, profession, 2013
3910, profession, 2013
11668, profession, 10409
12836, profession, 10409
12836, profession, 10897
12770, award_nominee, 8516
12770, award_nominee, 649
12770, award_nominee, 9181
12770, profession, 10409
12770, profession, 10897
12770, profession, 5277
4765, profession, 10409
8790, profession, 10409
10345, place, 10345
10345, vacationer, 10334
10345, vacationer, 8583
10345, vacationer, 1153
10345, vacationer, 10073
10345, vacationer, 11282
12954, profession, 10409
12954, profession, 10897
8908, profession, 10409
8908, profession, 10897
3775, profession, 10409
3775, profession, 10897
6764, profession, 10409
6764, profession, 10897
13030, profession, 10409
3725, profession, 10897
3725, profession, 2013
10110, profession, 2013
3955, location_of_ceremony, 10345
1608, profession, 10409
1608, profession, 10897
11282, profession, 10409
14234, profession, 10409
12157, profession, 10409
8080, profession, 10409
1633, profession, 10897
1633, profession, 2013
8496, profession, 10409
8496, profession, 10897
8496, profession, 2013
2315, profession, 10409
7418, profession, 10409
7418, profession, 2013
2638, profession, 10897
4464, profession, 10409
11133, profession, 10409
11133, profession, 2013
5916, profession, 10409
5916, profession, 2013
11801, profession, 10409
2450, profession, 10409
2450, profession, 2013
9037, profession, 2013
3917, award_nominee, 8480
3917, award_winner, 8480
9215, artist_origin, 10345
9215, location, 10345
10633, artists, 10202
10633, parent_genre, 12795
12023, profession, 10409
12023, profession, 10897
6528, profession, 10409
6528, profession, 10897
9545, profession, 10409
9545, profession, 10897
7555, profession, 10409
6339, profession, 10409
6339, profession, 2013
13910, profession, 10409
13910, profession, 10897
649, award_nominee, 12770
649, profession, 2013
10638, profession, 10409
10638, profession, 10897
11160, profession, 10409
11160, profession, 10897
6838, film_music, 3850
6838, film_release_region, 12503
6838, written_by, 11416
12795, artists, 4936
12795, artists, 7852
12795, artists, 8558
12795, artists, 9737
12795, artists, 5367
12795, artists, 8950
12795, artists, 3107
12795, artists, 6997
12795, artists, 6365
12795, artists, 9603
12795, artists, 13845
12795, artists, 4225
12795, artists, 3211
12795, artists, 702
12795, artists, 13137
12795, artists, 4210
12795, artists, 10334
12795, artists, 3346
12795, artists, 695
12795, artists, 13560
12795, artists, 8480
12795, artists, 1635
12795, artists, 9812
12795, artists, 4662
12795, artists, 9344
12795, artists, 160
12795, artists, 8871
12795, artists, 10283
12795, artists, 8583
12795, artists, 6302
12795, artists, 4415
12795, artists, 10023
12795, artists, 8137
12795, artists, 12572
12795, artists, 12325
12795, artists, 10202
12795, artists, 8497
12795, artists, 8840
12795, artists, 6546
12795, artists, 8516
12795, artists, 10909
12795, artists, 1153
12795, artists, 1948
12795, artists, 12860
12795, artists, 3910
12795, artists, 11668
12795, artists, 12770
12795, artists, 4765
12795, artists, 8790
12795, artists, 13030
12795, artists, 3725
12795, artists, 10110
12795, artists, 10073
12795, artists, 3955
12795, artists, 11282
12795, artists, 14234
12795, artists, 12157
12795, artists, 8080
12795, artists, 2315
12795, artists, 2638
12795, artists, 4464
12795, artists, 11801
12795, artists, 9037
12795, artists, 3917
12795, artists, 9215
12795, artists, 6528
12795, artists, 7555
12795, artists, 649
12795, artists, 8902
12795, artists, 7107
12795, artists, 882
12795, artists, 11646
12795, artists, 8708
12795, artists, 4648
12795, artists, 7205
12795, artists, 5876
12795, artists, 11577
12795, artists, 95
12795, artists, 3021
12795, artists, 2669
12795, artists, 9181
12795, artists, 12987
12795, artists, 5960
12795, artists, 4007
12795, artists, 11585
12795, artists, 7172
12795, artists, 2447
12795, artists, 12766
12795, artists, 6410
12795, artists, 13379
12795, artists, 7295
12795, artists, 1260
12795, artists, 826
5241, artists, 11991
5241, artists, 13137
5241, artists, 8480
5241, artists, 10202
5241, artists, 12770
8902, profession, 10409
7107, profession, 10409
882, award_nominee, 13137
1606, profession, 10409
1606, profession, 10897
11646, profession, 10409
8708, profession, 10409
11920, teams, 2419
10167, profession, 10409
10167, profession, 10897
11107, profession, 10409
11107, profession, 10897
4648, profession, 10409
7205, profession, 10409
5876, profession, 10409
5876, profession, 10897
2166, profession, 10409
2166, profession, 10897
11577, profession, 10409
95, profession, 10409
3021, profession, 10409
2669, profession, 10409
9181, award_nominee, 12770
9181, profession, 10409
9181, profession, 10897
3509, profession, 10409
3509, profession, 2013
11416, acted_in, 6838
11416, nominated_for, 6838
11416, profession, 2013
12987, location_of_ceremony, 10345
5960, profession, 10409
4007, profession, 10409
2258, profession, 10409
2258, profession, 10897
5771, profession, 10409
5771, profession, 10897
11585, profession, 10409
11585, profession, 10897
7172, profession, 10409
2447, profession, 10409
11922, profession, 10409
11922, profession, 2013
10264, profession, 10409
10264, profession, 10897
321, profession, 10409
321, profession, 10897
321, profession, 2013
12766, profession, 10409
6410, profession, 10409
3661, profession, 10409
3661, profession, 10897
8156, profession, 10409
8156, profession, 10897
13379, profession, 10409
7295, profession, 10897
7295, profession, 2013
2405, profession, 10409
2405, profession, 10897
1260, profession, 2013
826, profession, 10409
Question: For what reason are Ed_Begley,_Jr., Jim_Steinman, and Macedonia_national_football_team associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Ed_Begley,_Jr.",
"Jim_Steinman",
"Macedonia_national_football_team"
],
"valid_edges": [
[
"A._R._Rahman",
"profession",
"Composer"
],
[
"Alan_Menken",
"profession",
"Composer"
],
[
"Aldo_Nova",
"award_nominee",
"David_Foster"
],
[
"Aldo_Nova",
"award_nominee",
"Jean-Jacques_Goldman"
],
[
"Aldo_Nova",
"award_winner",
"Celine_Dion"
],
[
"Aldo_Nova",
"award_winner",
"Jean-Jacques_Goldman"
],
[
"Aldo_Nova",
"award_winner",
"Jim_Steinman"
],
[
"Aldo_Nova",
"profession",
"Singer-songwriter-GB"
],
[
"Alyson_Stoner",
"profession",
"Voice_Actor"
],
[
"Amy_Winehouse",
"profession",
"Composer"
],
[
"Anthony_Newley",
"profession",
"Composer"
],
[
"Anthony_Newley",
"profession",
"Lyricist"
],
[
"Ashley_Tisdale",
"profession",
"Voice_Actor"
],
[
"Ayumi_Hamasaki",
"location_of_ceremony",
"Las_Vegas"
],
[
"Ayumi_Hamasaki",
"profession",
"Composer"
],
[
"Ayumi_Hamasaki",
"profession",
"Lyricist"
],
[
"Babyface",
"award_nominee",
"David_Foster"
],
[
"Babyface",
"award_winner",
"David_Foster"
],
[
"Barbra_Streisand",
"award_nominee",
"Celine_Dion"
],
[
"Barbra_Streisand",
"award_nominee",
"Kenny_Loggins"
],
[
"Barry_Manilow",
"profession",
"Composer"
],
[
"Ben_Folds",
"location_of_ceremony",
"Las_Vegas"
],
[
"Ben_Folds",
"profession",
"Composer"
],
[
"Benny_Andersson",
"profession",
"Composer"
],
[
"Bill_Hader",
"acted_in",
"Pineapple_Express"
],
[
"Bill_Hader",
"profession",
"Voice_Actor"
],
[
"Billy_Bob_Thornton",
"location_of_ceremony",
"Las_Vegas"
],
[
"Billy_Bob_Thornton",
"profession",
"Voice_Actor"
],
[
"Billy_Joel",
"profession",
"Composer"
],
[
"Billy_Joel",
"profession",
"Lyricist"
],
[
"Bobby_McFerrin",
"profession",
"Composer"
],
[
"Brian_Jones",
"profession",
"Composer"
],
[
"Brian_Wilson",
"profession",
"Composer"
],
[
"Burt_Bacharach",
"profession",
"Composer"
],
[
"Celine_Dion",
"award_nominee",
"Aldo_Nova"
],
[
"Celine_Dion",
"award_nominee",
"Barbra_Streisand"
],
[
"Celine_Dion",
"award_nominee",
"David_Foster"
],
[
"Celine_Dion",
"award_nominee",
"Jim_Steinman"
],
[
"Celine_Dion",
"award_nominee",
"R._Kelly"
],
[
"Celine_Dion",
"award_winner",
"Aldo_Nova"
],
[
"Celine_Dion",
"award_winner",
"Barbra_Streisand"
],
[
"Celine_Dion",
"award_winner",
"David_Foster"
],
[
"Celine_Dion",
"award_winner",
"Jean-Jacques_Goldman"
],
[
"Celine_Dion",
"award_winner",
"Jim_Steinman"
],
[
"Celine_Dion",
"location",
"Las_Vegas"
],
[
"Charlie_Daniels",
"profession",
"Composer"
],
[
"Charlie_Daniels",
"profession",
"Lyricist"
],
[
"Chris_Seefried",
"profession",
"Composer"
],
[
"Christopher_Cerf",
"profession",
"Composer"
],
[
"Christopher_Cerf",
"profession",
"Lyricist"
],
[
"Christopher_Cerf",
"profession",
"Voice_Actor"
],
[
"Cole_Porter",
"profession",
"Composer"
],
[
"Cole_Porter",
"profession",
"Lyricist"
],
[
"Courtney_Love",
"location_of_ceremony",
"Las_Vegas"
],
[
"Courtney_Love",
"profession",
"Lyricist"
],
[
"Cy_Coleman",
"profession",
"Composer"
],
[
"Cy_Coleman",
"profession",
"Lyricist"
],
[
"Damon_Albarn",
"profession",
"Composer"
],
[
"Danny_McBride",
"acted_in",
"Pineapple_Express"
],
[
"Danny_McBride",
"nominated_for",
"Pineapple_Express"
],
[
"Danny_McBride",
"profession",
"Voice_Actor"
],
[
"David_Bowie",
"profession",
"Composer"
],
[
"David_Bowie",
"profession",
"Lyricist"
],
[
"David_Foster",
"award_nominee",
"Babyface"
],
[
"David_Foster",
"award_nominee",
"Celine_Dion"
],
[
"David_Foster",
"award_nominee",
"Natalie_Cole"
],
[
"David_Foster",
"award_winner",
"Aldo_Nova"
],
[
"David_Foster",
"award_winner",
"Celine_Dion"
],
[
"David_Foster",
"award_winner",
"Jean-Jacques_Goldman"
],
[
"David_Foster",
"award_winner",
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"Kenny_Loggins"
],
[
"Rupert_Holmes",
"profession",
"Composer"
],
[
"Rupert_Holmes",
"profession",
"Lyricist"
],
[
"Seth_MacFarlane",
"profession",
"Composer"
],
[
"Seth_MacFarlane",
"profession",
"Voice_Actor"
],
[
"Seth_Rogen",
"acted_in",
"Pineapple_Express"
],
[
"Seth_Rogen",
"nominated_for",
"Pineapple_Express"
],
[
"Seth_Rogen",
"profession",
"Voice_Actor"
],
[
"Sheena_Easton",
"location_of_ceremony",
"Las_Vegas"
],
[
"Sheryl_Crow",
"profession",
"Composer"
],
[
"Stanley_Clarke",
"profession",
"Composer"
],
[
"Stephen_Schwartz",
"profession",
"Composer"
],
[
"Stephen_Schwartz",
"profession",
"Lyricist"
],
[
"Stephen_Sondheim",
"profession",
"Composer"
],
[
"Stephen_Sondheim",
"profession",
"Lyricist"
],
[
"Stevie_Wonder",
"profession",
"Composer"
],
[
"Stevie_Wonder",
"profession",
"Lyricist"
],
[
"Stewart_Copeland",
"profession",
"Composer"
],
[
"Sting",
"profession",
"Composer"
],
[
"Tim_Curry",
"profession",
"Composer"
],
[
"Tim_Curry",
"profession",
"Voice_Actor"
],
[
"Toby_Keith",
"profession",
"Composer"
],
[
"Toby_Keith",
"profession",
"Lyricist"
],
[
"Trey_Parker",
"profession",
"Composer"
],
[
"Trey_Parker",
"profession",
"Lyricist"
],
[
"Trey_Parker",
"profession",
"Voice_Actor"
],
[
"Tricky_Stewart",
"profession",
"Composer"
],
[
"Usher",
"profession",
"Composer"
],
[
"Van_Morrison",
"profession",
"Composer"
],
[
"Van_Morrison",
"profession",
"Lyricist"
],
[
"Vishal_Bharadwaj",
"profession",
"Composer"
],
[
"Vishal_Bharadwaj",
"profession",
"Lyricist"
],
[
"Wendy_Melvoin",
"profession",
"Composer"
],
[
"Will.i.am",
"profession",
"Lyricist"
],
[
"Will.i.am",
"profession",
"Voice_Actor"
],
[
"Wynton_Marsalis",
"profession",
"Composer"
],
[
"Wynton_Marsalis",
"profession",
"Lyricist"
],
[
"Yui_Horie",
"profession",
"Voice_Actor"
],
[
"Yusuf_Islam",
"profession",
"Composer"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
6780, Charlie_Parker
10702, Chuck_Berry
9022, David_Foster_Wallace
13177, Erwin_Rommel
8512, F._Scott_Fitzgerald
11101, Gilles_Deleuze
461, Hunter_S._Thompson
9308, Jack_Kerouac
9741, Libya
8450, Marcel_Proust
9196, North_African_Campaign
1008, Suicide
3718, Taekwondo
5812, Walter_Benjamin
13681, Western_Desert_Campaign
src, edge_attr, dst
10702, award_winner, 6780
9022, influenced_by, 461
11101, influenced_by, 8512
11101, influenced_by, 8450
461, influenced_by, 8512
461, influenced_by, 9308
9308, influenced_by, 6780
9196, entity_involved, 13177
9196, locations, 9741
1008, people, 9022
1008, people, 13177
1008, people, 11101
1008, people, 461
1008, people, 5812
3718, country, 9741
5812, influenced_by, 8450
13681, entity_involved, 13177
13681, locations, 9741
Question: How are Chuck_Berry, Suicide, and Taekwondo related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Chuck_Berry",
"Suicide",
"Taekwondo"
],
"valid_edges": [
[
"Chuck_Berry",
"award_winner",
"Charlie_Parker"
],
[
"David_Foster_Wallace",
"influenced_by",
"Hunter_S._Thompson"
],
[
"Gilles_Deleuze",
"influenced_by",
"F._Scott_Fitzgerald"
],
[
"Gilles_Deleuze",
"influenced_by",
"Marcel_Proust"
],
[
"Hunter_S._Thompson",
"influenced_by",
"F._Scott_Fitzgerald"
],
[
"Hunter_S._Thompson",
"influenced_by",
"Jack_Kerouac"
],
[
"Jack_Kerouac",
"influenced_by",
"Charlie_Parker"
],
[
"North_African_Campaign",
"entity_involved",
"Erwin_Rommel"
],
[
"North_African_Campaign",
"locations",
"Libya"
],
[
"Suicide",
"people",
"David_Foster_Wallace"
],
[
"Suicide",
"people",
"Erwin_Rommel"
],
[
"Suicide",
"people",
"Gilles_Deleuze"
],
[
"Suicide",
"people",
"Hunter_S._Thompson"
],
[
"Suicide",
"people",
"Walter_Benjamin"
],
[
"Taekwondo",
"country",
"Libya"
],
[
"Walter_Benjamin",
"influenced_by",
"Marcel_Proust"
],
[
"Western_Desert_Campaign",
"entity_involved",
"Erwin_Rommel"
],
[
"Western_Desert_Campaign",
"locations",
"Libya"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5863, 1965_Major_League_Baseball_Season
8602, 1985_Major_League_Baseball_season
7050, 1995_Major_League_Baseball_Draft
2864, 1997_Major_League_Baseball_Draft
7286, 2000_Major_League_Baseball_season
7022, 2002_Major_League_Baseball_Draft
9417, 2003_Major_League_Baseball_Draft
4772, 2003_Major_League_Baseball_season
10504, 2004_Major_League_Baseball_Draft
9239, 2004_Major_League_Baseball_season
4861, 2005_Major_League_Baseball_Draft
433, 2005_Major_League_Baseball_season
10242, 2006_Major_League_Baseball_Draft
12160, 2006_Major_League_Baseball_season
12586, 2007_Major_League_Baseball_Draft
12383, 2007_Major_League_Baseball_season
6578, 2008_Major_League_Baseball_season
8656, Al_Gore
1241, Arizona_State_University
7494, Baseball
9517, Baylor_University
11630, California_State_University,_Fresno
26, California_State_University,_Long_Beach
14112, Catcher
11937, Chicago_White_Sox
1229, First_baseman
13167, Georgia_Institute_of_Technology
7095, Holly_Marie_Combs
9193, Infielder
6989, John_Barrowman
12152, Louisiana_State_University
11494, Midway_Games
12702, Minnesota_Twins
13248, Mississippi_State_University
10473, Navy_Blue
532, Nick_Cannon
6832, Oakland_Athletics
4456, Outfielder
12747, Pitcher
4983, PopCap_Games
1882, Preity_Zinta
813, Presenter-GB
12302, Relief_pitcher
2507, Rice_University
12488, Rickey_Henderson
11436, San_Diego
3621, San_Diego_State_University
4542, San_Francisco_Giants
12583, Seattle
8849, Seattle_Mariners
1132, Second_baseman
10650, Silver
841, Starting_pitcher
11036, Third_baseman
8082, University_of_Minnesota
13108, University_of_South_Florida
2838, Vice_President-GB
600, Video_game
13621, Video_game_industry
7636, Warner_Bros._Interactive_Entertainment
src, edge_attr, dst
8656, basic_title, 2838
8656, profession, 813
14112, team, 11937
14112, team, 12702
14112, team, 6832
14112, team, 4542
14112, team, 8849
11937, colors, 10650
11937, draft, 7050
11937, draft, 2864
11937, draft, 7022
11937, draft, 9417
11937, draft, 10504
11937, draft, 4861
11937, draft, 10242
11937, draft, 12586
11937, position, 14112
11937, position, 9193
11937, position, 4456
11937, position, 12747
11937, position, 12302
11937, position, 841
11937, school, 9517
11937, school, 26
11937, school, 13248
11937, school, 3621
11937, school, 13108
11937, season, 5863
11937, season, 8602
11937, season, 7286
11937, season, 4772
11937, season, 9239
11937, season, 433
11937, season, 12160
11937, season, 12383
11937, season, 6578
11937, sport, 7494
1229, team, 11937
7095, place_of_birth, 11436
7095, profession, 813
9193, team, 11937
9193, team, 12702
9193, team, 6832
9193, team, 4542
6989, location, 11436
6989, profession, 813
11494, citytown, 11436
11494, industry, 600
11494, industry, 13621
12702, colors, 10473
12702, draft, 7050
12702, draft, 2864
12702, draft, 7022
12702, draft, 9417
12702, draft, 10504
12702, draft, 4861
12702, draft, 10242
12702, draft, 12586
12702, position, 14112
12702, position, 9193
12702, position, 4456
12702, position, 12747
12702, position, 12302
12702, school, 1241
12702, school, 11630
12702, school, 13167
12702, school, 12152
12702, school, 3621
12702, school, 8082
12702, season, 5863
12702, season, 8602
12702, season, 7286
12702, season, 4772
12702, season, 9239
12702, season, 433
12702, season, 12160
12702, season, 12383
12702, season, 6578
12702, sport, 7494
532, artist_origin, 11436
532, place_of_birth, 11436
532, profession, 813
6832, draft, 7050
6832, draft, 2864
6832, draft, 7022
6832, draft, 9417
6832, draft, 10504
6832, draft, 4861
6832, draft, 12586
6832, position, 14112
6832, position, 1229
6832, position, 4456
6832, position, 12747
6832, position, 12302
6832, position, 1132
6832, position, 841
6832, school, 1241
6832, school, 9517
6832, school, 11630
6832, school, 26
6832, school, 13248
6832, school, 3621
6832, school, 8082
6832, school, 13108
6832, season, 8602
6832, season, 7286
6832, season, 4772
6832, season, 9239
6832, season, 433
6832, season, 12160
6832, season, 12383
6832, season, 6578
6832, sport, 7494
4456, team, 11937
4456, team, 12702
4456, team, 6832
4456, team, 4542
4456, team, 8849
12747, team, 11937
12747, team, 12702
12747, team, 6832
12747, team, 4542
12747, team, 8849
4983, industry, 600
4983, industry, 13621
1882, profession, 813
12302, team, 11937
12302, team, 12702
12302, team, 6832
12302, team, 4542
12302, team, 8849
12488, team, 6832
12488, team, 8849
11436, contains, 3621
11436, place, 11436
3621, citytown, 11436
4542, draft, 7050
4542, draft, 2864
4542, draft, 7022
4542, draft, 9417
4542, draft, 10242
4542, draft, 12586
4542, position, 14112
4542, position, 1229
4542, position, 9193
4542, position, 4456
4542, position, 12747
4542, position, 12302
4542, position, 1132
4542, position, 841
4542, school, 11630
4542, school, 12152
4542, school, 13248
4542, school, 2507
4542, school, 3621
4542, season, 5863
4542, season, 8602
4542, season, 7286
4542, season, 4772
4542, season, 9239
4542, season, 433
4542, season, 12160
4542, season, 12383
4542, season, 6578
4542, sport, 7494
12583, teams, 8849
8849, colors, 10473
8849, colors, 10650
8849, draft, 7050
8849, draft, 2864
8849, draft, 7022
8849, draft, 4861
8849, draft, 10242
8849, draft, 12586
8849, position, 14112
8849, position, 9193
8849, position, 4456
8849, position, 841
8849, school, 13167
8849, school, 2507
8849, season, 8602
8849, season, 7286
8849, season, 4772
8849, season, 9239
8849, season, 433
8849, season, 12160
8849, season, 12383
8849, season, 6578
8849, sport, 7494
1132, team, 12702
1132, team, 6832
1132, team, 4542
841, team, 12702
841, team, 4542
841, team, 8849
11036, team, 11937
11036, team, 4542
2838, company, 11494
7636, child, 11494
7636, citytown, 12583
7636, industry, 600
Question: How are Midway_Games, Preity_Zinta, and Relief_pitcher related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Midway_Games",
"Preity_Zinta",
"Relief_pitcher"
],
"valid_edges": [
[
"Al_Gore",
"basic_title",
"Vice_President-GB"
],
[
"Al_Gore",
"profession",
"Presenter-GB"
],
[
"Catcher",
"team",
"Chicago_White_Sox"
],
[
"Catcher",
"team",
"Minnesota_Twins"
],
[
"Catcher",
"team",
"Oakland_Athletics"
],
[
"Catcher",
"team",
"San_Francisco_Giants"
],
[
"Catcher",
"team",
"Seattle_Mariners"
],
[
"Chicago_White_Sox",
"colors",
"Silver"
],
[
"Chicago_White_Sox",
"draft",
"1995_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"1997_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2002_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2003_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2004_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2005_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2006_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"draft",
"2007_Major_League_Baseball_Draft"
],
[
"Chicago_White_Sox",
"position",
"Catcher"
],
[
"Chicago_White_Sox",
"position",
"Infielder"
],
[
"Chicago_White_Sox",
"position",
"Outfielder"
],
[
"Chicago_White_Sox",
"position",
"Pitcher"
],
[
"Chicago_White_Sox",
"position",
"Relief_pitcher"
],
[
"Chicago_White_Sox",
"position",
"Starting_pitcher"
],
[
"Chicago_White_Sox",
"school",
"Baylor_University"
],
[
"Chicago_White_Sox",
"school",
"California_State_University,_Long_Beach"
],
[
"Chicago_White_Sox",
"school",
"Mississippi_State_University"
],
[
"Chicago_White_Sox",
"school",
"San_Diego_State_University"
],
[
"Chicago_White_Sox",
"school",
"University_of_South_Florida"
],
[
"Chicago_White_Sox",
"season",
"1965_Major_League_Baseball_Season"
],
[
"Chicago_White_Sox",
"season",
"1985_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2000_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2003_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2004_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2005_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2006_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2007_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"season",
"2008_Major_League_Baseball_season"
],
[
"Chicago_White_Sox",
"sport",
"Baseball"
],
[
"First_baseman",
"team",
"Chicago_White_Sox"
],
[
"Holly_Marie_Combs",
"place_of_birth",
"San_Diego"
],
[
"Holly_Marie_Combs",
"profession",
"Presenter-GB"
],
[
"Infielder",
"team",
"Chicago_White_Sox"
],
[
"Infielder",
"team",
"Minnesota_Twins"
],
[
"Infielder",
"team",
"Oakland_Athletics"
],
[
"Infielder",
"team",
"San_Francisco_Giants"
],
[
"John_Barrowman",
"location",
"San_Diego"
],
[
"John_Barrowman",
"profession",
"Presenter-GB"
],
[
"Midway_Games",
"citytown",
"San_Diego"
],
[
"Midway_Games",
"industry",
"Video_game"
],
[
"Midway_Games",
"industry",
"Video_game_industry"
],
[
"Minnesota_Twins",
"colors",
"Navy_Blue"
],
[
"Minnesota_Twins",
"draft",
"1995_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"1997_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2002_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2003_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2004_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2005_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2006_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"draft",
"2007_Major_League_Baseball_Draft"
],
[
"Minnesota_Twins",
"position",
"Catcher"
],
[
"Minnesota_Twins",
"position",
"Infielder"
],
[
"Minnesota_Twins",
"position",
"Outfielder"
],
[
"Minnesota_Twins",
"position",
"Pitcher"
],
[
"Minnesota_Twins",
"position",
"Relief_pitcher"
],
[
"Minnesota_Twins",
"school",
"Arizona_State_University"
],
[
"Minnesota_Twins",
"school",
"California_State_University,_Fresno"
],
[
"Minnesota_Twins",
"school",
"Georgia_Institute_of_Technology"
],
[
"Minnesota_Twins",
"school",
"Louisiana_State_University"
],
[
"Minnesota_Twins",
"school",
"San_Diego_State_University"
],
[
"Minnesota_Twins",
"school",
"University_of_Minnesota"
],
[
"Minnesota_Twins",
"season",
"1965_Major_League_Baseball_Season"
],
[
"Minnesota_Twins",
"season",
"1985_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2000_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2003_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2004_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2005_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2006_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2007_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"season",
"2008_Major_League_Baseball_season"
],
[
"Minnesota_Twins",
"sport",
"Baseball"
],
[
"Nick_Cannon",
"artist_origin",
"San_Diego"
],
[
"Nick_Cannon",
"place_of_birth",
"San_Diego"
],
[
"Nick_Cannon",
"profession",
"Presenter-GB"
],
[
"Oakland_Athletics",
"draft",
"1995_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"1997_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"2002_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"2003_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"2004_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"2005_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"draft",
"2007_Major_League_Baseball_Draft"
],
[
"Oakland_Athletics",
"position",
"Catcher"
],
[
"Oakland_Athletics",
"position",
"First_baseman"
],
[
"Oakland_Athletics",
"position",
"Outfielder"
],
[
"Oakland_Athletics",
"position",
"Pitcher"
],
[
"Oakland_Athletics",
"position",
"Relief_pitcher"
],
[
"Oakland_Athletics",
"position",
"Second_baseman"
],
[
"Oakland_Athletics",
"position",
"Starting_pitcher"
],
[
"Oakland_Athletics",
"school",
"Arizona_State_University"
],
[
"Oakland_Athletics",
"school",
"Baylor_University"
],
[
"Oakland_Athletics",
"school",
"California_State_University,_Fresno"
],
[
"Oakland_Athletics",
"school",
"California_State_University,_Long_Beach"
],
[
"Oakland_Athletics",
"school",
"Mississippi_State_University"
],
[
"Oakland_Athletics",
"school",
"San_Diego_State_University"
],
[
"Oakland_Athletics",
"school",
"University_of_Minnesota"
],
[
"Oakland_Athletics",
"school",
"University_of_South_Florida"
],
[
"Oakland_Athletics",
"season",
"1985_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2000_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2003_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2004_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2005_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2006_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2007_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"season",
"2008_Major_League_Baseball_season"
],
[
"Oakland_Athletics",
"sport",
"Baseball"
],
[
"Outfielder",
"team",
"Chicago_White_Sox"
],
[
"Outfielder",
"team",
"Minnesota_Twins"
],
[
"Outfielder",
"team",
"Oakland_Athletics"
],
[
"Outfielder",
"team",
"San_Francisco_Giants"
],
[
"Outfielder",
"team",
"Seattle_Mariners"
],
[
"Pitcher",
"team",
"Chicago_White_Sox"
],
[
"Pitcher",
"team",
"Minnesota_Twins"
],
[
"Pitcher",
"team",
"Oakland_Athletics"
],
[
"Pitcher",
"team",
"San_Francisco_Giants"
],
[
"Pitcher",
"team",
"Seattle_Mariners"
],
[
"PopCap_Games",
"industry",
"Video_game"
],
[
"PopCap_Games",
"industry",
"Video_game_industry"
],
[
"Preity_Zinta",
"profession",
"Presenter-GB"
],
[
"Relief_pitcher",
"team",
"Chicago_White_Sox"
],
[
"Relief_pitcher",
"team",
"Minnesota_Twins"
],
[
"Relief_pitcher",
"team",
"Oakland_Athletics"
],
[
"Relief_pitcher",
"team",
"San_Francisco_Giants"
],
[
"Relief_pitcher",
"team",
"Seattle_Mariners"
],
[
"Rickey_Henderson",
"team",
"Oakland_Athletics"
],
[
"Rickey_Henderson",
"team",
"Seattle_Mariners"
],
[
"San_Diego",
"contains",
"San_Diego_State_University"
],
[
"San_Diego",
"place",
"San_Diego"
],
[
"San_Diego_State_University",
"citytown",
"San_Diego"
],
[
"San_Francisco_Giants",
"draft",
"1995_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"draft",
"1997_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"draft",
"2002_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"draft",
"2003_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"draft",
"2006_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"draft",
"2007_Major_League_Baseball_Draft"
],
[
"San_Francisco_Giants",
"position",
"Catcher"
],
[
"San_Francisco_Giants",
"position",
"First_baseman"
],
[
"San_Francisco_Giants",
"position",
"Infielder"
],
[
"San_Francisco_Giants",
"position",
"Outfielder"
],
[
"San_Francisco_Giants",
"position",
"Pitcher"
],
[
"San_Francisco_Giants",
"position",
"Relief_pitcher"
],
[
"San_Francisco_Giants",
"position",
"Second_baseman"
],
[
"San_Francisco_Giants",
"position",
"Starting_pitcher"
],
[
"San_Francisco_Giants",
"school",
"California_State_University,_Fresno"
],
[
"San_Francisco_Giants",
"school",
"Louisiana_State_University"
],
[
"San_Francisco_Giants",
"school",
"Mississippi_State_University"
],
[
"San_Francisco_Giants",
"school",
"Rice_University"
],
[
"San_Francisco_Giants",
"school",
"San_Diego_State_University"
],
[
"San_Francisco_Giants",
"season",
"1965_Major_League_Baseball_Season"
],
[
"San_Francisco_Giants",
"season",
"1985_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2000_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2003_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2004_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2005_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2006_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2007_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"season",
"2008_Major_League_Baseball_season"
],
[
"San_Francisco_Giants",
"sport",
"Baseball"
],
[
"Seattle",
"teams",
"Seattle_Mariners"
],
[
"Seattle_Mariners",
"colors",
"Navy_Blue"
],
[
"Seattle_Mariners",
"colors",
"Silver"
],
[
"Seattle_Mariners",
"draft",
"1995_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"draft",
"1997_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"draft",
"2002_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"draft",
"2005_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"draft",
"2006_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"draft",
"2007_Major_League_Baseball_Draft"
],
[
"Seattle_Mariners",
"position",
"Catcher"
],
[
"Seattle_Mariners",
"position",
"Infielder"
],
[
"Seattle_Mariners",
"position",
"Outfielder"
],
[
"Seattle_Mariners",
"position",
"Starting_pitcher"
],
[
"Seattle_Mariners",
"school",
"Georgia_Institute_of_Technology"
],
[
"Seattle_Mariners",
"school",
"Rice_University"
],
[
"Seattle_Mariners",
"season",
"1985_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2000_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2003_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2004_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2005_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2006_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2007_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"season",
"2008_Major_League_Baseball_season"
],
[
"Seattle_Mariners",
"sport",
"Baseball"
],
[
"Second_baseman",
"team",
"Minnesota_Twins"
],
[
"Second_baseman",
"team",
"Oakland_Athletics"
],
[
"Second_baseman",
"team",
"San_Francisco_Giants"
],
[
"Starting_pitcher",
"team",
"Minnesota_Twins"
],
[
"Starting_pitcher",
"team",
"San_Francisco_Giants"
],
[
"Starting_pitcher",
"team",
"Seattle_Mariners"
],
[
"Third_baseman",
"team",
"Chicago_White_Sox"
],
[
"Third_baseman",
"team",
"San_Francisco_Giants"
],
[
"Vice_President-GB",
"company",
"Midway_Games"
],
[
"Warner_Bros._Interactive_Entertainment",
"child",
"Midway_Games"
],
[
"Warner_Bros._Interactive_Entertainment",
"citytown",
"Seattle"
],
[
"Warner_Bros._Interactive_Entertainment",
"industry",
"Video_game"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
11546, Action
10329, Adult_Swim
7401, American_Dad!
7726, Andrea_Romano
3756, Animated_cartoon
8905, Animated_series
8591, Anime
320, Avatar:_The_Last_Airbender
11279, Batman:_Gotham_Knight
11432, Ben_10
5731, Bill_Fagerbakke
11336, Bleach:_Memories_of_Nobody
4183, Breckin_Meyer
3301, Cartoon
14223, Cartoon_Network
10811, Case_Closed:_Captured_in_Her_Eyes
1338, Children's_television_series
11911, Clancy_Brown
12318, Corey_Burton
6607, David_Ogden_Stiers
13739, Daytime_Emmy_Award_for_Outstanding_Children's_Animated_Program
10106, Dee_Bradley_Baker
10181, Family_Guy
754, Fist_of_the_North_Star
11859, Frank_Welker
8758, Gate_Keepers_21
2780, Grey_DeLisle
10092, Jason_Marsden
4785, Jeff_Bennett
634, John_DiMaggio
2293, Kaneto_Shiozawa
11919, Kath_Soucie
13518, Kevin_Michael_Richardson
6790, Kid_vs._Kat
477, Kirk_Thornton
12431, Lilo_&_Stitch
3062, Mike_Barker
10733, Mobile_Suit_Gundam
12804, Nickelodeon
13442, Pamela_Adlon
8162, Porco_Rosso
8626, Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)
45, Primetime_Emmy_Award_for_Outstanding_Short-format_Animation
12727, Recess:_School's_Out
12639, Rob_Paulsen
11725, Robot_Chicken
7516, SeiyΕ«-GB
6872, Seth_Green
10042, Sitcom
5449, SpongeBob_SquarePants
6743, Star_Wars:_The_Clone_Wars
4330, Street_Fighter_II:_The_Animated_Movie
13198, Street_Fighter_II_V
14213, Tara_Strong
5579, The_Animatrix
6802, The_Fairly_OddParents
13982, The_Penguins_of_Madagascar
11513, Tom_Kenny
2290, Tress_MacNeille
9819, Vernon_Chatman
9619, Warner_Home_Video
13348, YTV
src, edge_attr, dst
10329, program, 11725
7401, actor, 10106
7401, genre, 3756
7401, genre, 10042
7401, program_creator, 3062
7726, acted_in, 11279
7726, nominated_for, 5449
320, actor, 10106
320, actor, 2780
320, award_winner, 12804
320, genre, 11546
320, genre, 8905
320, genre, 1338
11279, genre, 8591
11432, actor, 10106
11432, actor, 4785
11432, actor, 634
11432, actor, 13518
11432, actor, 12639
11432, actor, 14213
11432, genre, 11546
11432, genre, 8905
11432, genre, 1338
11336, actor, 477
11336, genre, 8591
4183, award, 8626
4183, award_nominee, 6872
4183, nominated_for, 11725
4183, tv_program, 11725
3301, titles, 11432
3301, titles, 5449
3301, titles, 6802
14223, program, 6790
14223, program, 11725
14223, titles, 11432
14223, titles, 11725
10811, genre, 8591
11911, acted_in, 12727
12318, acted_in, 11279
12318, acted_in, 6743
6607, acted_in, 12431
13739, nominated_for, 5449
13739, nominated_for, 13982
10106, acted_in, 6743
10181, actor, 6872
754, actor, 2293
754, actor, 477
754, genre, 8591
8758, actor, 477
8758, genre, 8591
10092, acted_in, 11279
4785, nominated_for, 13982
2293, acted_in, 10811
2293, acted_in, 754
2293, acted_in, 4330
2293, special_performance_type, 7516
11919, acted_in, 12727
13518, acted_in, 11279
13518, acted_in, 12431
13518, acted_in, 12727
13518, acted_in, 6743
13518, acted_in, 5579
6790, actor, 11859
6790, actor, 2780
6790, actor, 4785
6790, actor, 11919
6790, actor, 13518
6790, actor, 13442
6790, actor, 12639
6790, actor, 14213
6790, actor, 11513
6790, actor, 2290
6790, genre, 11546
6790, genre, 8905
6790, genre, 3301
6790, genre, 1338
6790, genre, 10042
3062, award, 8626
3062, program, 7401
3062, program, 10181
3062, tv_program, 7401
3062, tv_program, 10181
10733, actor, 2293
10733, genre, 8591
12804, program, 6790
12804, program, 5449
12804, program, 6802
12804, program, 13982
12804, titles, 320
12804, titles, 5449
12804, titles, 6802
13442, acted_in, 12727
13442, acted_in, 5579
8162, actor, 5731
8162, actor, 12318
8162, actor, 6607
8162, actor, 10106
8162, actor, 11859
8162, actor, 4785
8162, actor, 13518
8162, actor, 12639
8162, actor, 11513
8162, actor, 2290
8162, genre, 8591
8626, nominated_for, 7401
8626, nominated_for, 320
8626, nominated_for, 11725
8626, nominated_for, 5449
45, award_winner, 6872
45, nominated_for, 11725
45, nominated_for, 5449
12639, acted_in, 11279
11725, actor, 6872
11725, award_honor_award, 45
11725, award_winner, 6872
11725, genre, 10042
7516, film, 8162
7516, film, 5579
6872, award, 8626
6872, award, 45
6872, award_nominee, 4183
6872, nominated_for, 11725
6872, organizations_founded, 10329
6872, program, 11725
6872, tv_program, 11725
5449, actor, 5731
5449, actor, 11911
5449, actor, 10106
5449, actor, 11513
5449, genre, 8905
5449, genre, 10042
4330, actor, 477
4330, genre, 8591
13198, actor, 2293
13198, actor, 477
13198, genre, 8591
5579, genre, 8591
6802, actor, 10106
6802, actor, 2780
6802, actor, 10092
6802, actor, 13518
6802, actor, 14213
6802, actor, 11513
6802, genre, 3756
6802, genre, 8905
13982, actor, 4785
13982, actor, 634
13982, actor, 13518
13982, actor, 14213
13982, genre, 11546
13982, genre, 1338
2290, acted_in, 12727
9819, award, 8626
9819, award_nominee, 13442
9819, award_winner, 13442
9619, film, 11279
9619, film, 6743
9619, film, 5579
13348, program, 6790
13348, program, 5449
13348, program, 6802
Question: How are Kevin_Michael_Richardson, Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour), and Street_Fighter_II_V related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Kevin_Michael_Richardson",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"Street_Fighter_II_V"
],
"valid_edges": [
[
"Adult_Swim",
"program",
"Robot_Chicken"
],
[
"American_Dad!",
"actor",
"Dee_Bradley_Baker"
],
[
"American_Dad!",
"genre",
"Animated_cartoon"
],
[
"American_Dad!",
"genre",
"Sitcom"
],
[
"American_Dad!",
"program_creator",
"Mike_Barker"
],
[
"Andrea_Romano",
"acted_in",
"Batman:_Gotham_Knight"
],
[
"Andrea_Romano",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Avatar:_The_Last_Airbender",
"actor",
"Dee_Bradley_Baker"
],
[
"Avatar:_The_Last_Airbender",
"actor",
"Grey_DeLisle"
],
[
"Avatar:_The_Last_Airbender",
"award_winner",
"Nickelodeon"
],
[
"Avatar:_The_Last_Airbender",
"genre",
"Action"
],
[
"Avatar:_The_Last_Airbender",
"genre",
"Animated_series"
],
[
"Avatar:_The_Last_Airbender",
"genre",
"Children's_television_series"
],
[
"Batman:_Gotham_Knight",
"genre",
"Anime"
],
[
"Ben_10",
"actor",
"Dee_Bradley_Baker"
],
[
"Ben_10",
"actor",
"Jeff_Bennett"
],
[
"Ben_10",
"actor",
"John_DiMaggio"
],
[
"Ben_10",
"actor",
"Kevin_Michael_Richardson"
],
[
"Ben_10",
"actor",
"Rob_Paulsen"
],
[
"Ben_10",
"actor",
"Tara_Strong"
],
[
"Ben_10",
"genre",
"Action"
],
[
"Ben_10",
"genre",
"Animated_series"
],
[
"Ben_10",
"genre",
"Children's_television_series"
],
[
"Bleach:_Memories_of_Nobody",
"actor",
"Kirk_Thornton"
],
[
"Bleach:_Memories_of_Nobody",
"genre",
"Anime"
],
[
"Breckin_Meyer",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Breckin_Meyer",
"award_nominee",
"Seth_Green"
],
[
"Breckin_Meyer",
"nominated_for",
"Robot_Chicken"
],
[
"Breckin_Meyer",
"tv_program",
"Robot_Chicken"
],
[
"Cartoon",
"titles",
"Ben_10"
],
[
"Cartoon",
"titles",
"SpongeBob_SquarePants"
],
[
"Cartoon",
"titles",
"The_Fairly_OddParents"
],
[
"Cartoon_Network",
"program",
"Kid_vs._Kat"
],
[
"Cartoon_Network",
"program",
"Robot_Chicken"
],
[
"Cartoon_Network",
"titles",
"Ben_10"
],
[
"Cartoon_Network",
"titles",
"Robot_Chicken"
],
[
"Case_Closed:_Captured_in_Her_Eyes",
"genre",
"Anime"
],
[
"Clancy_Brown",
"acted_in",
"Recess:_School's_Out"
],
[
"Corey_Burton",
"acted_in",
"Batman:_Gotham_Knight"
],
[
"Corey_Burton",
"acted_in",
"Star_Wars:_The_Clone_Wars"
],
[
"David_Ogden_Stiers",
"acted_in",
"Lilo_&_Stitch"
],
[
"Daytime_Emmy_Award_for_Outstanding_Children's_Animated_Program",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Daytime_Emmy_Award_for_Outstanding_Children's_Animated_Program",
"nominated_for",
"The_Penguins_of_Madagascar"
],
[
"Dee_Bradley_Baker",
"acted_in",
"Star_Wars:_The_Clone_Wars"
],
[
"Family_Guy",
"actor",
"Seth_Green"
],
[
"Fist_of_the_North_Star",
"actor",
"Kaneto_Shiozawa"
],
[
"Fist_of_the_North_Star",
"actor",
"Kirk_Thornton"
],
[
"Fist_of_the_North_Star",
"genre",
"Anime"
],
[
"Gate_Keepers_21",
"actor",
"Kirk_Thornton"
],
[
"Gate_Keepers_21",
"genre",
"Anime"
],
[
"Jason_Marsden",
"acted_in",
"Batman:_Gotham_Knight"
],
[
"Jeff_Bennett",
"nominated_for",
"The_Penguins_of_Madagascar"
],
[
"Kaneto_Shiozawa",
"acted_in",
"Case_Closed:_Captured_in_Her_Eyes"
],
[
"Kaneto_Shiozawa",
"acted_in",
"Fist_of_the_North_Star"
],
[
"Kaneto_Shiozawa",
"acted_in",
"Street_Fighter_II:_The_Animated_Movie"
],
[
"Kaneto_Shiozawa",
"special_performance_type",
"SeiyΕ«-GB"
],
[
"Kath_Soucie",
"acted_in",
"Recess:_School's_Out"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"Batman:_Gotham_Knight"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"Lilo_&_Stitch"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"Recess:_School's_Out"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"Star_Wars:_The_Clone_Wars"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"The_Animatrix"
],
[
"Kid_vs._Kat",
"actor",
"Frank_Welker"
],
[
"Kid_vs._Kat",
"actor",
"Grey_DeLisle"
],
[
"Kid_vs._Kat",
"actor",
"Jeff_Bennett"
],
[
"Kid_vs._Kat",
"actor",
"Kath_Soucie"
],
[
"Kid_vs._Kat",
"actor",
"Kevin_Michael_Richardson"
],
[
"Kid_vs._Kat",
"actor",
"Pamela_Adlon"
],
[
"Kid_vs._Kat",
"actor",
"Rob_Paulsen"
],
[
"Kid_vs._Kat",
"actor",
"Tara_Strong"
],
[
"Kid_vs._Kat",
"actor",
"Tom_Kenny"
],
[
"Kid_vs._Kat",
"actor",
"Tress_MacNeille"
],
[
"Kid_vs._Kat",
"genre",
"Action"
],
[
"Kid_vs._Kat",
"genre",
"Animated_series"
],
[
"Kid_vs._Kat",
"genre",
"Cartoon"
],
[
"Kid_vs._Kat",
"genre",
"Children's_television_series"
],
[
"Kid_vs._Kat",
"genre",
"Sitcom"
],
[
"Mike_Barker",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Mike_Barker",
"program",
"American_Dad!"
],
[
"Mike_Barker",
"program",
"Family_Guy"
],
[
"Mike_Barker",
"tv_program",
"American_Dad!"
],
[
"Mike_Barker",
"tv_program",
"Family_Guy"
],
[
"Mobile_Suit_Gundam",
"actor",
"Kaneto_Shiozawa"
],
[
"Mobile_Suit_Gundam",
"genre",
"Anime"
],
[
"Nickelodeon",
"program",
"Kid_vs._Kat"
],
[
"Nickelodeon",
"program",
"SpongeBob_SquarePants"
],
[
"Nickelodeon",
"program",
"The_Fairly_OddParents"
],
[
"Nickelodeon",
"program",
"The_Penguins_of_Madagascar"
],
[
"Nickelodeon",
"titles",
"Avatar:_The_Last_Airbender"
],
[
"Nickelodeon",
"titles",
"SpongeBob_SquarePants"
],
[
"Nickelodeon",
"titles",
"The_Fairly_OddParents"
],
[
"Pamela_Adlon",
"acted_in",
"Recess:_School's_Out"
],
[
"Pamela_Adlon",
"acted_in",
"The_Animatrix"
],
[
"Porco_Rosso",
"actor",
"Bill_Fagerbakke"
],
[
"Porco_Rosso",
"actor",
"Corey_Burton"
],
[
"Porco_Rosso",
"actor",
"David_Ogden_Stiers"
],
[
"Porco_Rosso",
"actor",
"Dee_Bradley_Baker"
],
[
"Porco_Rosso",
"actor",
"Frank_Welker"
],
[
"Porco_Rosso",
"actor",
"Jeff_Bennett"
],
[
"Porco_Rosso",
"actor",
"Kevin_Michael_Richardson"
],
[
"Porco_Rosso",
"actor",
"Rob_Paulsen"
],
[
"Porco_Rosso",
"actor",
"Tom_Kenny"
],
[
"Porco_Rosso",
"actor",
"Tress_MacNeille"
],
[
"Porco_Rosso",
"genre",
"Anime"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"American_Dad!"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"Avatar:_The_Last_Airbender"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"Robot_Chicken"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"award_winner",
"Seth_Green"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"nominated_for",
"Robot_Chicken"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Rob_Paulsen",
"acted_in",
"Batman:_Gotham_Knight"
],
[
"Robot_Chicken",
"actor",
"Seth_Green"
],
[
"Robot_Chicken",
"award_honor_award",
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation"
],
[
"Robot_Chicken",
"award_winner",
"Seth_Green"
],
[
"Robot_Chicken",
"genre",
"Sitcom"
],
[
"SeiyΕ«-GB",
"film",
"Porco_Rosso"
],
[
"SeiyΕ«-GB",
"film",
"The_Animatrix"
],
[
"Seth_Green",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Seth_Green",
"award",
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation"
],
[
"Seth_Green",
"award_nominee",
"Breckin_Meyer"
],
[
"Seth_Green",
"nominated_for",
"Robot_Chicken"
],
[
"Seth_Green",
"organizations_founded",
"Adult_Swim"
],
[
"Seth_Green",
"program",
"Robot_Chicken"
],
[
"Seth_Green",
"tv_program",
"Robot_Chicken"
],
[
"SpongeBob_SquarePants",
"actor",
"Bill_Fagerbakke"
],
[
"SpongeBob_SquarePants",
"actor",
"Clancy_Brown"
],
[
"SpongeBob_SquarePants",
"actor",
"Dee_Bradley_Baker"
],
[
"SpongeBob_SquarePants",
"actor",
"Tom_Kenny"
],
[
"SpongeBob_SquarePants",
"genre",
"Animated_series"
],
[
"SpongeBob_SquarePants",
"genre",
"Sitcom"
],
[
"Street_Fighter_II:_The_Animated_Movie",
"actor",
"Kirk_Thornton"
],
[
"Street_Fighter_II:_The_Animated_Movie",
"genre",
"Anime"
],
[
"Street_Fighter_II_V",
"actor",
"Kaneto_Shiozawa"
],
[
"Street_Fighter_II_V",
"actor",
"Kirk_Thornton"
],
[
"Street_Fighter_II_V",
"genre",
"Anime"
],
[
"The_Animatrix",
"genre",
"Anime"
],
[
"The_Fairly_OddParents",
"actor",
"Dee_Bradley_Baker"
],
[
"The_Fairly_OddParents",
"actor",
"Grey_DeLisle"
],
[
"The_Fairly_OddParents",
"actor",
"Jason_Marsden"
],
[
"The_Fairly_OddParents",
"actor",
"Kevin_Michael_Richardson"
],
[
"The_Fairly_OddParents",
"actor",
"Tara_Strong"
],
[
"The_Fairly_OddParents",
"actor",
"Tom_Kenny"
],
[
"The_Fairly_OddParents",
"genre",
"Animated_cartoon"
],
[
"The_Fairly_OddParents",
"genre",
"Animated_series"
],
[
"The_Penguins_of_Madagascar",
"actor",
"Jeff_Bennett"
],
[
"The_Penguins_of_Madagascar",
"actor",
"John_DiMaggio"
],
[
"The_Penguins_of_Madagascar",
"actor",
"Kevin_Michael_Richardson"
],
[
"The_Penguins_of_Madagascar",
"actor",
"Tara_Strong"
],
[
"The_Penguins_of_Madagascar",
"genre",
"Action"
],
[
"The_Penguins_of_Madagascar",
"genre",
"Children's_television_series"
],
[
"Tress_MacNeille",
"acted_in",
"Recess:_School's_Out"
],
[
"Vernon_Chatman",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Vernon_Chatman",
"award_nominee",
"Pamela_Adlon"
],
[
"Vernon_Chatman",
"award_winner",
"Pamela_Adlon"
],
[
"Warner_Home_Video",
"film",
"Batman:_Gotham_Knight"
],
[
"Warner_Home_Video",
"film",
"Star_Wars:_The_Clone_Wars"
],
[
"Warner_Home_Video",
"film",
"The_Animatrix"
],
[
"YTV",
"program",
"Kid_vs._Kat"
],
[
"YTV",
"program",
"SpongeBob_SquarePants"
],
[
"YTV",
"program",
"The_Fairly_OddParents"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
2633, Ennio_Morricone
4014, Italian_people
13770, John_Debney
3067, Latin_Language
9384, Lounge_music
5526, Meet_Dave
25, Mike_O'Malley
2270, The_Passion_of_the_Christ
6688, University_of_New_Hampshire
src, edge_attr, dst
4014, languages_spoken, 3067
4014, people, 2633
13770, nominated_for, 2270
9384, artists, 2633
5526, film_music, 13770
25, acted_in, 5526
2270, film_music, 13770
2270, language, 3067
6688, campuses, 6688
6688, educational_institution, 6688
6688, student, 25
Question: In what context are Lounge_music, The_Passion_of_the_Christ, and University_of_New_Hampshire connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Lounge_music",
"The_Passion_of_the_Christ",
"University_of_New_Hampshire"
],
"valid_edges": [
[
"Italian_people",
"languages_spoken",
"Latin_Language"
],
[
"Italian_people",
"people",
"Ennio_Morricone"
],
[
"John_Debney",
"nominated_for",
"The_Passion_of_the_Christ"
],
[
"Lounge_music",
"artists",
"Ennio_Morricone"
],
[
"Meet_Dave",
"film_music",
"John_Debney"
],
[
"Mike_O'Malley",
"acted_in",
"Meet_Dave"
],
[
"The_Passion_of_the_Christ",
"film_music",
"John_Debney"
],
[
"The_Passion_of_the_Christ",
"language",
"Latin_Language"
],
[
"University_of_New_Hampshire",
"campuses",
"University_of_New_Hampshire"
],
[
"University_of_New_Hampshire",
"educational_institution",
"University_of_New_Hampshire"
],
[
"University_of_New_Hampshire",
"student",
"Mike_O'Malley"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
3613, Burgess_Meredith
6822, Charlie_Sheen
1410, David_Carradine
14145, David_Duchovny
14016, Forest_Lawn_Memorial_Park
6915, Hollywood_Walk_of_Fame
7320, How_the_West_Was_Won
8289, In_Harm's_Way
5414, James_Stewart
13339, June_Allyson
12064, Malibu
8813, Nick_Nolte
3160, Olivia_de_Havilland
10587, Pulmonary_embolism
8113, Rich_Man,_Poor_Man
8053, Sound
5315, Stephen_Harper
11653, The_Glenn_Miller_Story
5506, University_of_Toronto
3604, William_B._Davis
10016, William_H._Daniels
src, edge_attr, dst
3613, acted_in, 8289
3613, place_of_death, 12064
6822, location, 12064
1410, location_of_ceremony, 12064
1410, place_of_burial, 14016
14145, location, 12064
6915, inductee, 6822
6915, inductee, 13339
8289, film_crew_role, 8053
5414, acted_in, 7320
5414, acted_in, 11653
5414, nominated_for, 11653
5414, participant, 3160
5414, place_of_burial, 14016
13339, acted_in, 11653
12064, place, 12064
8813, acted_in, 8113
8813, location, 12064
8813, nominated_for, 8113
3160, participant, 3613
3160, participant, 5414
10587, people, 5414
10587, people, 13339
8113, actor, 8813
8113, film_crew_role, 8053
11653, cinematography, 10016
11653, film_crew_role, 8053
5506, campuses, 5506
5506, student, 5315
5506, student, 3604
3604, award_nominee, 14145
10016, nominated_for, 7320
10016, place_of_burial, 14016
Question: In what context are Malibu, Stephen_Harper, and The_Glenn_Miller_Story connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Malibu",
"Stephen_Harper",
"The_Glenn_Miller_Story"
],
"valid_edges": [
[
"Burgess_Meredith",
"acted_in",
"In_Harm's_Way"
],
[
"Burgess_Meredith",
"place_of_death",
"Malibu"
],
[
"Charlie_Sheen",
"location",
"Malibu"
],
[
"David_Carradine",
"location_of_ceremony",
"Malibu"
],
[
"David_Carradine",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"David_Duchovny",
"location",
"Malibu"
],
[
"Hollywood_Walk_of_Fame",
"inductee",
"Charlie_Sheen"
],
[
"Hollywood_Walk_of_Fame",
"inductee",
"June_Allyson"
],
[
"In_Harm's_Way",
"film_crew_role",
"Sound"
],
[
"James_Stewart",
"acted_in",
"How_the_West_Was_Won"
],
[
"James_Stewart",
"acted_in",
"The_Glenn_Miller_Story"
],
[
"James_Stewart",
"nominated_for",
"The_Glenn_Miller_Story"
],
[
"James_Stewart",
"participant",
"Olivia_de_Havilland"
],
[
"James_Stewart",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
],
[
"June_Allyson",
"acted_in",
"The_Glenn_Miller_Story"
],
[
"Malibu",
"place",
"Malibu"
],
[
"Nick_Nolte",
"acted_in",
"Rich_Man,_Poor_Man"
],
[
"Nick_Nolte",
"location",
"Malibu"
],
[
"Nick_Nolte",
"nominated_for",
"Rich_Man,_Poor_Man"
],
[
"Olivia_de_Havilland",
"participant",
"Burgess_Meredith"
],
[
"Olivia_de_Havilland",
"participant",
"James_Stewart"
],
[
"Pulmonary_embolism",
"people",
"James_Stewart"
],
[
"Pulmonary_embolism",
"people",
"June_Allyson"
],
[
"Rich_Man,_Poor_Man",
"actor",
"Nick_Nolte"
],
[
"Rich_Man,_Poor_Man",
"film_crew_role",
"Sound"
],
[
"The_Glenn_Miller_Story",
"cinematography",
"William_H._Daniels"
],
[
"The_Glenn_Miller_Story",
"film_crew_role",
"Sound"
],
[
"University_of_Toronto",
"campuses",
"University_of_Toronto"
],
[
"University_of_Toronto",
"student",
"Stephen_Harper"
],
[
"University_of_Toronto",
"student",
"William_B._Davis"
],
[
"William_B._Davis",
"award_nominee",
"David_Duchovny"
],
[
"William_H._Daniels",
"nominated_for",
"How_the_West_Was_Won"
],
[
"William_H._Daniels",
"place_of_burial",
"Forest_Lawn_Memorial_Park"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7506, Academy_Award_for_Best_Director
656, Academy_Award_for_Best_Writing_Adapted_Screenplay
7330, Albania
14126, Argo
4389, Austria
8091, BAFTA_Award_for_Best_Direction
1486, BAFTA_Award_for_Best_Film
14123, Back_to_the_Future
6077, Batman_Begins
13765, Bavaria
11332, Belgium
6692, Bernardo_Bertolucci
13653, Black_Swan
8083, Central_European_Time_Zone-US
6199, China
12683, Copenhagen
4288, Cowboys_&_Aliens
12945, Czech_Republic
10002, Dancer_in_the_Dark
12757, Denmark-GB
11485, E.T._the_Extra-Terrestrial
638, French_Language
9846, Georgia
10562, Golden_Globe_Award_for_Best_Director_-_Motion_Picture
2124, Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture
7355, Hong_Kong
6222, Hungary
11599, India
9263, Italian_Language
4643, Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film
12532, Jurassic_Park
4029, Lars_von_Trier
12486, Leipzig
7334, London
8757, Malta
13504, Men_in_Black_3
6652, Moneyball
1777, Munich
2703, Naples
3320, National_Society_of_Film_Critics_Award_for_Best_Director
6164, New_York_Film_Critics_Circle_Award_for_Best_Film
9966, Norway
2621, Once_Upon_a_Time_in_America
12782, Pakistan
11182, Palme_d'Or
4064, Parma
12212, Poland
14107, Rome
3446, S._Manivannan
5592, Saxony
11423, Seven_Years'_War
6173, Shanghai
12667, Singapore
7484, Skyfall
80, Slovakia
4264, Spain
10546, Steven_Spielberg
11026, Super_8
1, Sweden
5075, Switzerland
9256, The_Dark_Knight
5833, The_Dark_Knight_Rises
7952, The_Last_Emperor
1715, The_Social_Network
1790, The_Tree_of_Life
1693, Transformers
8937, Transformers:_Dark_of_the_Moon
6441, University_of_Leipzig
6869, University_of_Rome_La_Sapienza
src, edge_attr, dst
7506, award_winner, 6692
7506, award_winner, 10546
7506, nominated_for, 13653
7506, nominated_for, 11485
7506, nominated_for, 7952
7506, nominated_for, 1715
656, nominated_for, 6652
656, nominated_for, 7952
7330, time_zones, 8083
14126, award_honor_award, 656
14126, award_honor_award, 1486
14126, award_honor_award, 10562
14126, film_release_region, 11332
14126, film_release_region, 12757
14126, film_release_region, 7355
14126, film_release_region, 6222
14126, film_release_region, 11599
14126, film_release_region, 9966
14126, film_release_region, 12212
14126, film_release_region, 12667
14126, film_release_region, 4264
14126, film_release_region, 1
14126, film_release_region, 5075
4389, time_zones, 8083
8091, award_winner, 10546
8091, nominated_for, 14126
8091, nominated_for, 13653
8091, nominated_for, 11485
8091, nominated_for, 2621
8091, nominated_for, 7952
8091, nominated_for, 1715
1486, award_winner, 10546
1486, nominated_for, 14126
1486, nominated_for, 14123
1486, nominated_for, 13653
1486, nominated_for, 11485
1486, nominated_for, 7952
1486, nominated_for, 1715
14123, award_honor_award, 4643
14123, award_winner, 10546
14123, executive_produced_by, 10546
14123, film_release_region, 12757
14123, film_release_region, 4264
6077, film_release_region, 11599
13765, adjoins, 5592
13765, time_zones, 8083
11332, time_zones, 8083
6692, award, 7506
6692, award, 656
6692, award, 8091
6692, award, 1486
6692, award, 10562
6692, award, 2124
6692, award, 3320
6692, film, 7952
6692, nominated_for, 7952
6692, place_of_birth, 4064
13653, film_release_region, 11332
13653, film_release_region, 12945
13653, film_release_region, 12757
13653, film_release_region, 9846
13653, film_release_region, 7355
13653, film_release_region, 6222
13653, film_release_region, 11599
13653, film_release_region, 9966
13653, film_release_region, 12782
13653, film_release_region, 12212
13653, film_release_region, 12667
13653, film_release_region, 4264
13653, film_release_region, 1
13653, language, 638
13653, language, 9263
6199, adjoins, 11599
6199, titles, 7952
12683, time_zones, 8083
4288, executive_produced_by, 10546
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Question: For what reason are Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film, Leipzig, and S._Manivannan associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
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|
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"Palme_d'Or"
],
[
"Lars_von_Trier",
"location",
"Copenhagen"
],
[
"Lars_von_Trier",
"nationality",
"Denmark-GB"
],
[
"Leipzig",
"contains",
"University_of_Leipzig"
],
[
"Leipzig",
"state",
"Saxony"
],
[
"Leipzig",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Malta",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Men_in_Black_3",
"executive_produced_by",
"Steven_Spielberg"
],
[
"Men_in_Black_3",
"film_release_region",
"India"
],
[
"Moneyball",
"film_release_region",
"Belgium"
],
[
"Moneyball",
"film_release_region",
"Denmark-GB"
],
[
"Moneyball",
"film_release_region",
"Hong_Kong"
],
[
"Moneyball",
"film_release_region",
"Hungary"
],
[
"Moneyball",
"film_release_region",
"India"
],
[
"Moneyball",
"film_release_region",
"Malta"
],
[
"Moneyball",
"film_release_region",
"Norway"
],
[
"Moneyball",
"film_release_region",
"Poland"
],
[
"Moneyball",
"film_release_region",
"Singapore"
],
[
"Moneyball",
"film_release_region",
"Spain"
],
[
"Moneyball",
"film_release_region",
"Sweden"
],
[
"Moneyball",
"film_release_region",
"Switzerland"
],
[
"Moneyball",
"honored_for",
"The_Tree_of_Life"
],
[
"Munich",
"produced_by",
"Steven_Spielberg"
],
[
"Munich",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Naples",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"award_winner",
"Bernardo_Bertolucci"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"award_winner",
"Lars_von_Trier"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"award_winner",
"Steven_Spielberg"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"E.T._the_Extra-Terrestrial"
],
[
"National_Society_of_Film_Critics_Award_for_Best_Director",
"nominated_for",
"The_Social_Network"
],
[
"New_York_Film_Critics_Circle_Award_for_Best_Film",
"award_winner",
"Steven_Spielberg"
],
[
"Norway",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Once_Upon_a_Time_in_America",
"award_honor_award",
"Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Czech_Republic"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Denmark-GB"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Hong_Kong"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Hungary"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"India"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Norway"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Rome"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Spain"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Sweden"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Switzerland"
],
[
"Once_Upon_a_Time_in_America",
"language",
"French_Language"
],
[
"Once_Upon_a_Time_in_America",
"language",
"Italian_Language"
],
[
"Pakistan",
"adjoins",
"India"
],
[
"Parma",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Poland",
"adjoins",
"Saxony"
],
[
"Poland",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Rome",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"S._Manivannan",
"nationality",
"India"
],
[
"Saxony",
"adjoins",
"Bavaria"
],
[
"Saxony",
"adjoins",
"Czech_Republic"
],
[
"Saxony",
"adjoins",
"Poland"
],
[
"Saxony",
"contains",
"Leipzig"
],
[
"Saxony",
"contains",
"University_of_Leipzig"
],
[
"Saxony",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Seven_Years'_War",
"combatants",
"Saxony"
],
[
"Seven_Years'_War",
"locations",
"India"
],
[
"Shanghai",
"film_release_region",
"India"
],
[
"Skyfall",
"featured_film_locations",
"London"
],
[
"Skyfall",
"featured_film_locations",
"Shanghai"
],
[
"Skyfall",
"film_release_region",
"Albania"
],
[
"Skyfall",
"film_release_region",
"Austria"
],
[
"Skyfall",
"film_release_region",
"Belgium"
],
[
"Skyfall",
"film_release_region",
"China"
],
[
"Skyfall",
"film_release_region",
"Czech_Republic"
],
[
"Skyfall",
"film_release_region",
"Denmark-GB"
],
[
"Skyfall",
"film_release_region",
"Hong_Kong"
],
[
"Skyfall",
"film_release_region",
"Hungary"
],
[
"Skyfall",
"film_release_region",
"India"
],
[
"Skyfall",
"film_release_region",
"Malta"
],
[
"Skyfall",
"film_release_region",
"Norway"
],
[
"Skyfall",
"film_release_region",
"Pakistan"
],
[
"Skyfall",
"film_release_region",
"Poland"
],
[
"Skyfall",
"film_release_region",
"Singapore"
],
[
"Skyfall",
"film_release_region",
"Slovakia"
],
[
"Skyfall",
"film_release_region",
"Spain"
],
[
"Skyfall",
"film_release_region",
"Sweden"
],
[
"Skyfall",
"film_release_region",
"Switzerland"
],
[
"Slovakia",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Spain",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Steven_Spielberg",
"award",
"Academy_Award_for_Best_Director"
],
[
"Steven_Spielberg",
"award",
"BAFTA_Award_for_Best_Direction"
],
[
"Steven_Spielberg",
"award",
"BAFTA_Award_for_Best_Film"
],
[
"Steven_Spielberg",
"award",
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture"
],
[
"Steven_Spielberg",
"award",
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture"
],
[
"Steven_Spielberg",
"film",
"E.T._the_Extra-Terrestrial"
],
[
"Steven_Spielberg",
"film",
"Jurassic_Park"
],
[
"Steven_Spielberg",
"film",
"Munich"
],
[
"Steven_Spielberg",
"location",
"Naples"
],
[
"Steven_Spielberg",
"nominated_for",
"E.T._the_Extra-Terrestrial"
],
[
"Steven_Spielberg",
"nominated_for",
"Munich"
],
[
"Super_8",
"film_release_region",
"India"
],
[
"Super_8",
"produced_by",
"Steven_Spielberg"
],
[
"Sweden",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"Switzerland",
"time_zones",
"Central_European_Time_Zone-US"
],
[
"The_Dark_Knight",
"award_honor_award",
"Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film"
],
[
"The_Dark_Knight",
"featured_film_locations",
"Hong_Kong"
],
[
"The_Dark_Knight",
"film_regional_debut_venue",
"London"
],
[
"The_Dark_Knight",
"film_release_region",
"Austria"
],
[
"The_Dark_Knight",
"film_release_region",
"Belgium"
],
[
"The_Dark_Knight",
"film_release_region",
"Czech_Republic"
],
[
"The_Dark_Knight",
"film_release_region",
"Denmark-GB"
],
[
"The_Dark_Knight",
"film_release_region",
"Hong_Kong"
],
[
"The_Dark_Knight",
"film_release_region",
"Hungary"
],
[
"The_Dark_Knight",
"film_release_region",
"India"
],
[
"The_Dark_Knight",
"film_release_region",
"Norway"
],
[
"The_Dark_Knight",
"film_release_region",
"Pakistan"
],
[
"The_Dark_Knight",
"film_release_region",
"Poland"
],
[
"The_Dark_Knight",
"film_release_region",
"Singapore"
],
[
"The_Dark_Knight",
"film_release_region",
"Slovakia"
],
[
"The_Dark_Knight",
"film_release_region",
"Spain"
],
[
"The_Dark_Knight",
"film_release_region",
"Sweden"
],
[
"The_Dark_Knight",
"film_release_region",
"Switzerland"
],
[
"The_Dark_Knight",
"prequel",
"Batman_Begins"
],
[
"The_Dark_Knight_Rises",
"film_regional_debut_venue",
"London"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Belgium"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"China"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Denmark-GB"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Georgia"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Hong_Kong"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Hungary"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"India"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Norway"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Pakistan"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Poland"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Singapore"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Spain"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Sweden"
],
[
"The_Dark_Knight_Rises",
"film_release_region",
"Switzerland"
],
[
"The_Dark_Knight_Rises",
"prequel",
"The_Dark_Knight"
],
[
"The_Last_Emperor",
"award_honor_award",
"Academy_Award_for_Best_Director"
],
[
"The_Last_Emperor",
"award_honor_award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"The_Last_Emperor",
"award_honor_award",
"BAFTA_Award_for_Best_Film"
],
[
"The_Last_Emperor",
"award_honor_award",
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture"
],
[
"The_Last_Emperor",
"award_honor_award",
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture"
],
[
"The_Last_Emperor",
"award_honor_award",
"Japan_Academy_Prize_for_Outstanding_Foreign_Language_Film"
],
[
"The_Last_Emperor",
"award_winner",
"Bernardo_Bertolucci"
],
[
"The_Last_Emperor",
"featured_film_locations",
"Rome"
],
[
"The_Last_Emperor",
"film_country",
"China"
],
[
"The_Last_Emperor",
"film_release_region",
"Denmark-GB"
],
[
"The_Last_Emperor",
"film_release_region",
"Sweden"
],
[
"The_Last_Emperor",
"film_release_region",
"Switzerland"
],
[
"The_Last_Emperor",
"written_by",
"Bernardo_Bertolucci"
],
[
"The_Social_Network",
"award_honor_award",
"Academy_Award_for_Best_Writing_Adapted_Screenplay"
],
[
"The_Social_Network",
"award_honor_award",
"BAFTA_Award_for_Best_Direction"
],
[
"The_Social_Network",
"award_honor_award",
"Golden_Globe_Award_for_Best_Director_-_Motion_Picture"
],
[
"The_Social_Network",
"award_honor_award",
"Golden_Globe_Award_for_Best_Screenplay_-_Motion_Picture"
],
[
"The_Social_Network",
"award_honor_award",
"National_Society_of_Film_Critics_Award_for_Best_Director"
],
[
"The_Social_Network",
"award_honor_award",
"New_York_Film_Critics_Circle_Award_for_Best_Film"
],
[
"The_Social_Network",
"film_release_region",
"Austria"
],
[
"The_Social_Network",
"film_release_region",
"Belgium"
],
[
"The_Social_Network",
"film_release_region",
"Czech_Republic"
],
[
"The_Social_Network",
"film_release_region",
"Denmark-GB"
],
[
"The_Social_Network",
"film_release_region",
"Georgia"
],
[
"The_Social_Network",
"film_release_region",
"Hong_Kong"
],
[
"The_Social_Network",
"film_release_region",
"Hungary"
],
[
"The_Social_Network",
"film_release_region",
"India"
],
[
"The_Social_Network",
"film_release_region",
"Norway"
],
[
"The_Social_Network",
"film_release_region",
"Poland"
],
[
"The_Social_Network",
"film_release_region",
"Singapore"
],
[
"The_Social_Network",
"film_release_region",
"Slovakia"
],
[
"The_Social_Network",
"film_release_region",
"Spain"
],
[
"The_Social_Network",
"film_release_region",
"Sweden"
],
[
"The_Social_Network",
"film_release_region",
"Switzerland"
],
[
"The_Social_Network",
"language",
"French_Language"
],
[
"The_Tree_of_Life",
"film_release_region",
"India"
],
[
"The_Tree_of_Life",
"honored_for",
"Moneyball"
],
[
"The_Tree_of_Life",
"nominated_for",
"Moneyball"
],
[
"Transformers",
"executive_produced_by",
"Steven_Spielberg"
],
[
"Transformers",
"film_release_region",
"India"
],
[
"Transformers:_Dark_of_the_Moon",
"executive_produced_by",
"Steven_Spielberg"
],
[
"Transformers:_Dark_of_the_Moon",
"film_release_region",
"India"
],
[
"University_of_Leipzig",
"citytown",
"Leipzig"
],
[
"University_of_Leipzig",
"educational_institution",
"University_of_Leipzig"
],
[
"University_of_Leipzig",
"state_province_region",
"Saxony"
],
[
"University_of_Rome_La_Sapienza",
"student",
"Bernardo_Bertolucci"
],
[
"University_of_Rome_La_Sapienza",
"time_zones",
"Central_European_Time_Zone-US"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5561, 1960_Summer_Olympics
1044, Clemson_University
594, Dial_M_for_Murder
10548, Dolph_Lundgren
5780, German_Democratic_Republic
4276, Madrid
9296, Stockholm
7197, Tampa_Bay_Buccaneers
4045, Train
src, edge_attr, dst
1044, campuses, 1044
1044, student, 10548
594, film_release_region, 5780
594, film_release_region, 4276
10548, location, 9296
10548, location_of_ceremony, 9296
10548, place_of_birth, 9296
5780, olympics, 5561
4276, mode_of_transportation, 4045
9296, mode_of_transportation, 4045
7197, school, 1044
Question: In what context are 1960_Summer_Olympics, Tampa_Bay_Buccaneers, and Train connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"1960_Summer_Olympics",
"Tampa_Bay_Buccaneers",
"Train"
],
"valid_edges": [
[
"Clemson_University",
"campuses",
"Clemson_University"
],
[
"Clemson_University",
"student",
"Dolph_Lundgren"
],
[
"Dial_M_for_Murder",
"film_release_region",
"German_Democratic_Republic"
],
[
"Dial_M_for_Murder",
"film_release_region",
"Madrid"
],
[
"Dolph_Lundgren",
"location",
"Stockholm"
],
[
"Dolph_Lundgren",
"location_of_ceremony",
"Stockholm"
],
[
"Dolph_Lundgren",
"place_of_birth",
"Stockholm"
],
[
"German_Democratic_Republic",
"olympics",
"1960_Summer_Olympics"
],
[
"Madrid",
"mode_of_transportation",
"Train"
],
[
"Stockholm",
"mode_of_transportation",
"Train"
],
[
"Tampa_Bay_Buccaneers",
"school",
"Clemson_University"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5424, Ames
10331, B.B._King
13028, Batman_&_Robin
148, Batman_Forever
8574, Country_blues
7757, Don_Rickles
4027, Elliot_Goldenthal
11496, George_Carlin
12472, H._Jon_Benjamin
2813, Iowa
9471, Jerry_Seinfeld
6434, Johnny_Carson
10361, Michael_Gough
5532, Pat_Hingle
3932, Razzie_Award_for_Worst_Original_Song
13370, U2
src, edge_attr, dst
5424, place, 5424
5424, state, 2813
10331, award_nominee, 13370
10331, award_winner, 13370
13028, film_music, 4027
13028, prequel, 148
148, film_music, 4027
8574, artists, 10331
12472, influenced_by, 7757
12472, influenced_by, 11496
12472, influenced_by, 6434
12472, influenced_by, 10361
12472, influenced_by, 5532
2813, contains, 5424
9471, influenced_by, 7757
9471, influenced_by, 11496
9471, influenced_by, 6434
9471, influenced_by, 10361
9471, influenced_by, 5532
6434, location, 2813
10361, acted_in, 13028
10361, acted_in, 148
5532, acted_in, 13028
5532, acted_in, 148
3932, nominated_for, 13028
3932, nominated_for, 148
13370, nominated_for, 148
Question: How are Ames, Country_blues, and Pat_Hingle related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Ames",
"Country_blues",
"Pat_Hingle"
],
"valid_edges": [
[
"Ames",
"place",
"Ames"
],
[
"Ames",
"state",
"Iowa"
],
[
"B.B._King",
"award_nominee",
"U2"
],
[
"B.B._King",
"award_winner",
"U2"
],
[
"Batman_&_Robin",
"film_music",
"Elliot_Goldenthal"
],
[
"Batman_&_Robin",
"prequel",
"Batman_Forever"
],
[
"Batman_Forever",
"film_music",
"Elliot_Goldenthal"
],
[
"Country_blues",
"artists",
"B.B._King"
],
[
"H._Jon_Benjamin",
"influenced_by",
"Don_Rickles"
],
[
"H._Jon_Benjamin",
"influenced_by",
"George_Carlin"
],
[
"H._Jon_Benjamin",
"influenced_by",
"Johnny_Carson"
],
[
"H._Jon_Benjamin",
"influenced_by",
"Michael_Gough"
],
[
"H._Jon_Benjamin",
"influenced_by",
"Pat_Hingle"
],
[
"Iowa",
"contains",
"Ames"
],
[
"Jerry_Seinfeld",
"influenced_by",
"Don_Rickles"
],
[
"Jerry_Seinfeld",
"influenced_by",
"George_Carlin"
],
[
"Jerry_Seinfeld",
"influenced_by",
"Johnny_Carson"
],
[
"Jerry_Seinfeld",
"influenced_by",
"Michael_Gough"
],
[
"Jerry_Seinfeld",
"influenced_by",
"Pat_Hingle"
],
[
"Johnny_Carson",
"location",
"Iowa"
],
[
"Michael_Gough",
"acted_in",
"Batman_&_Robin"
],
[
"Michael_Gough",
"acted_in",
"Batman_Forever"
],
[
"Pat_Hingle",
"acted_in",
"Batman_&_Robin"
],
[
"Pat_Hingle",
"acted_in",
"Batman_Forever"
],
[
"Razzie_Award_for_Worst_Original_Song",
"nominated_for",
"Batman_&_Robin"
],
[
"Razzie_Award_for_Worst_Original_Song",
"nominated_for",
"Batman_Forever"
],
[
"U2",
"nominated_for",
"Batman_Forever"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
5344, Amherst_College
3613, Burgess_Meredith
4901, Case_Western_Reserve_University
386, Christine_Langan
3418, Cleveland
8895, Cleveland_Institute_of_Music
7218, Cleveland_State_University
8201, Columbus
10177, Cuyahoga_County
5542, E._W._Scripps_Company
6960, Fish_Tank
12072, Frank_Marshall
1018, Franklin_County
5685, Joel_Grey
1125, Kathleen_Kennedy
1147, Lakewood
3045, Licking_County
12064, Malibu
590, Ohio
10379, Rock_and_Roll_Hall_of_Fame
2949, Tony_Award_for_Best_Direction_of_a_Play
10931, Twilight_Zone:_The_Movie
src, edge_attr, dst
5344, campuses, 5344
5344, educational_institution, 5344
5344, student, 3613
3613, acted_in, 10931
3613, award, 2949
3613, location, 3418
3613, place_of_birth, 3418
3613, place_of_death, 12064
4901, citytown, 3418
4901, state_province_region, 590
386, award_nominee, 12072
386, award_nominee, 1125
3418, adjoins, 1147
3418, contains, 4901
3418, contains, 8895
3418, contains, 7218
3418, county, 10177
3418, place, 3418
8895, state_province_region, 590
7218, citytown, 3418
7218, state_province_region, 590
8201, administrative_division, 1018
10177, contains, 3418
10177, county_seat, 3418
5542, place_founded, 3418
5542, state_province_region, 590
6960, executive_produced_by, 386
12072, award_nominee, 386
1018, adjoins, 3045
1018, partially_contains, 8201
5685, award, 2949
5685, place_of_birth, 3418
1147, adjoins, 3418
3045, adjoins, 1018
12064, place, 12064
590, capital, 8201
590, contains, 4901
590, contains, 3418
590, contains, 7218
590, contains, 8201
590, contains, 10177
590, contains, 1018
590, contains, 1147
590, contains, 3045
10379, citytown, 3418
10379, state_province_region, 590
10931, executive_produced_by, 12072
10931, produced_by, 1125
Question: How are Burgess_Meredith, Fish_Tank, and Licking_County related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Burgess_Meredith",
"Fish_Tank",
"Licking_County"
],
"valid_edges": [
[
"Amherst_College",
"campuses",
"Amherst_College"
],
[
"Amherst_College",
"educational_institution",
"Amherst_College"
],
[
"Amherst_College",
"student",
"Burgess_Meredith"
],
[
"Burgess_Meredith",
"acted_in",
"Twilight_Zone:_The_Movie"
],
[
"Burgess_Meredith",
"award",
"Tony_Award_for_Best_Direction_of_a_Play"
],
[
"Burgess_Meredith",
"location",
"Cleveland"
],
[
"Burgess_Meredith",
"place_of_birth",
"Cleveland"
],
[
"Burgess_Meredith",
"place_of_death",
"Malibu"
],
[
"Case_Western_Reserve_University",
"citytown",
"Cleveland"
],
[
"Case_Western_Reserve_University",
"state_province_region",
"Ohio"
],
[
"Christine_Langan",
"award_nominee",
"Frank_Marshall"
],
[
"Christine_Langan",
"award_nominee",
"Kathleen_Kennedy"
],
[
"Cleveland",
"adjoins",
"Lakewood"
],
[
"Cleveland",
"contains",
"Case_Western_Reserve_University"
],
[
"Cleveland",
"contains",
"Cleveland_Institute_of_Music"
],
[
"Cleveland",
"contains",
"Cleveland_State_University"
],
[
"Cleveland",
"county",
"Cuyahoga_County"
],
[
"Cleveland",
"place",
"Cleveland"
],
[
"Cleveland_Institute_of_Music",
"state_province_region",
"Ohio"
],
[
"Cleveland_State_University",
"citytown",
"Cleveland"
],
[
"Cleveland_State_University",
"state_province_region",
"Ohio"
],
[
"Columbus",
"administrative_division",
"Franklin_County"
],
[
"Cuyahoga_County",
"contains",
"Cleveland"
],
[
"Cuyahoga_County",
"county_seat",
"Cleveland"
],
[
"E._W._Scripps_Company",
"place_founded",
"Cleveland"
],
[
"E._W._Scripps_Company",
"state_province_region",
"Ohio"
],
[
"Fish_Tank",
"executive_produced_by",
"Christine_Langan"
],
[
"Frank_Marshall",
"award_nominee",
"Christine_Langan"
],
[
"Franklin_County",
"adjoins",
"Licking_County"
],
[
"Franklin_County",
"partially_contains",
"Columbus"
],
[
"Joel_Grey",
"award",
"Tony_Award_for_Best_Direction_of_a_Play"
],
[
"Joel_Grey",
"place_of_birth",
"Cleveland"
],
[
"Lakewood",
"adjoins",
"Cleveland"
],
[
"Licking_County",
"adjoins",
"Franklin_County"
],
[
"Malibu",
"place",
"Malibu"
],
[
"Ohio",
"capital",
"Columbus"
],
[
"Ohio",
"contains",
"Case_Western_Reserve_University"
],
[
"Ohio",
"contains",
"Cleveland"
],
[
"Ohio",
"contains",
"Cleveland_State_University"
],
[
"Ohio",
"contains",
"Columbus"
],
[
"Ohio",
"contains",
"Cuyahoga_County"
],
[
"Ohio",
"contains",
"Franklin_County"
],
[
"Ohio",
"contains",
"Lakewood"
],
[
"Ohio",
"contains",
"Licking_County"
],
[
"Rock_and_Roll_Hall_of_Fame",
"citytown",
"Cleveland"
],
[
"Rock_and_Roll_Hall_of_Fame",
"state_province_region",
"Ohio"
],
[
"Twilight_Zone:_The_Movie",
"executive_produced_by",
"Frank_Marshall"
],
[
"Twilight_Zone:_The_Movie",
"produced_by",
"Kathleen_Kennedy"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
13465, Aladdin
4358, Art_Center_College_of_Design
2790, Chicken_Little
6614, Cinderella
8446, DeWitt_Clinton_High_School
11471, Disney's_House_of_Mouse
7538, Ellen_Barkin
8852, Fairy_tale
3733, Fantastic_Four
9012, Fiorello_H._LaGuardia_High_School
348, Garry_Marshall
6372, Hercules
6933, Irene_Cara
222, Jerry_Orbach
4968, Jim_Cummings
9095, Keith_David
4955, Kerry_Washington
13518, Kevin_Michael_Richardson
1219, Kim_Carnes
12431, Lilo_&_Stitch
2745, Martin_Balsam
935, Mr._&_Mrs._Smith
5652, Pasadena
4775, Pocahontas
7008, Regis_Philbin
3945, She_Hate_Me
2877, Shrek_Forever_After
6608, Shrek_the_Third
6895, Snow_White_and_the_Seven_Dwarfs
3909, State_school
9382, Steve_Jordan
2007, Technical_Director
9531, Television_Hall_of_Fame
10983, Terror_in_the_Aisles
6092, The_Bronx
10996, The_Bronx_High_School_of_Science
11435, The_Hunchback_of_Notre_Dame
13822, The_Little_Mermaid
14259, The_Princess_and_the_Frog
3296, Tony_Award_for_Best_Featured_Actor_in_a_Musical
469, Walt_Disney_Animation_Studios
1753, Wesley_Snipes
src, edge_attr, dst
13465, production_companies, 469
4358, campuses, 4358
4358, educational_institution, 4358
2790, production_companies, 469
6614, production_companies, 469
8446, citytown, 6092
8446, school_type, 3909
8446, student, 348
8446, student, 2745
11471, actor, 222
11471, actor, 4968
11471, actor, 9095
7538, acted_in, 3945
7538, location, 6092
7538, place_of_birth, 6092
8852, films, 13465
8852, films, 6614
8852, films, 6895
8852, films, 13822
3733, film_crew_role, 2007
9012, student, 7538
9012, student, 9095
9012, student, 9382
9012, student, 1753
348, acted_in, 2790
348, location, 6092
348, place_of_birth, 6092
6372, production_companies, 469
6933, award_winner, 1219
6933, location, 6092
222, award, 3296
222, location, 6092
222, place_of_birth, 6092
4968, acted_in, 13465
4968, acted_in, 6372
4968, acted_in, 4775
4968, acted_in, 11435
4968, acted_in, 13822
4968, acted_in, 14259
9095, acted_in, 6372
9095, acted_in, 935
9095, acted_in, 10983
9095, acted_in, 14259
9095, award, 3296
4955, acted_in, 3733
4955, acted_in, 935
4955, acted_in, 3945
4955, place_of_birth, 6092
13518, acted_in, 12431
13518, location, 6092
13518, place_of_birth, 6092
1219, artist_origin, 5652
1219, award_nominee, 6933
1219, award_winner, 6933
12431, production_companies, 469
2745, acted_in, 10983
2745, location, 6092
2745, place_of_birth, 6092
5652, contains, 4358
5652, place, 5652
4775, production_companies, 469
7008, acted_in, 2877
7008, acted_in, 6608
7008, location, 6092
7008, place_of_birth, 6092
2877, film_crew_role, 2007
2877, genre, 8852
6608, film_crew_role, 2007
6608, genre, 8852
6895, production_companies, 469
9382, artist_origin, 6092
9531, inductee, 348
9531, inductee, 7008
6092, county_seat, 6092
10996, citytown, 6092
10996, school_type, 3909
11435, production_companies, 469
13822, production_companies, 469
14259, film_crew_role, 2007
14259, genre, 8852
14259, production_companies, 469
1753, location, 6092
Question: How are Art_Center_College_of_Design, The_Bronx, and The_Princess_and_the_Frog related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Art_Center_College_of_Design",
"The_Bronx",
"The_Princess_and_the_Frog"
],
"valid_edges": [
[
"Aladdin",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Art_Center_College_of_Design",
"campuses",
"Art_Center_College_of_Design"
],
[
"Art_Center_College_of_Design",
"educational_institution",
"Art_Center_College_of_Design"
],
[
"Chicken_Little",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Cinderella",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"DeWitt_Clinton_High_School",
"citytown",
"The_Bronx"
],
[
"DeWitt_Clinton_High_School",
"school_type",
"State_school"
],
[
"DeWitt_Clinton_High_School",
"student",
"Garry_Marshall"
],
[
"DeWitt_Clinton_High_School",
"student",
"Martin_Balsam"
],
[
"Disney's_House_of_Mouse",
"actor",
"Jerry_Orbach"
],
[
"Disney's_House_of_Mouse",
"actor",
"Jim_Cummings"
],
[
"Disney's_House_of_Mouse",
"actor",
"Keith_David"
],
[
"Ellen_Barkin",
"acted_in",
"She_Hate_Me"
],
[
"Ellen_Barkin",
"location",
"The_Bronx"
],
[
"Ellen_Barkin",
"place_of_birth",
"The_Bronx"
],
[
"Fairy_tale",
"films",
"Aladdin"
],
[
"Fairy_tale",
"films",
"Cinderella"
],
[
"Fairy_tale",
"films",
"Snow_White_and_the_Seven_Dwarfs"
],
[
"Fairy_tale",
"films",
"The_Little_Mermaid"
],
[
"Fantastic_Four",
"film_crew_role",
"Technical_Director"
],
[
"Fiorello_H._LaGuardia_High_School",
"student",
"Ellen_Barkin"
],
[
"Fiorello_H._LaGuardia_High_School",
"student",
"Keith_David"
],
[
"Fiorello_H._LaGuardia_High_School",
"student",
"Steve_Jordan"
],
[
"Fiorello_H._LaGuardia_High_School",
"student",
"Wesley_Snipes"
],
[
"Garry_Marshall",
"acted_in",
"Chicken_Little"
],
[
"Garry_Marshall",
"location",
"The_Bronx"
],
[
"Garry_Marshall",
"place_of_birth",
"The_Bronx"
],
[
"Hercules",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Irene_Cara",
"award_winner",
"Kim_Carnes"
],
[
"Irene_Cara",
"location",
"The_Bronx"
],
[
"Jerry_Orbach",
"award",
"Tony_Award_for_Best_Featured_Actor_in_a_Musical"
],
[
"Jerry_Orbach",
"location",
"The_Bronx"
],
[
"Jerry_Orbach",
"place_of_birth",
"The_Bronx"
],
[
"Jim_Cummings",
"acted_in",
"Aladdin"
],
[
"Jim_Cummings",
"acted_in",
"Hercules"
],
[
"Jim_Cummings",
"acted_in",
"Pocahontas"
],
[
"Jim_Cummings",
"acted_in",
"The_Hunchback_of_Notre_Dame"
],
[
"Jim_Cummings",
"acted_in",
"The_Little_Mermaid"
],
[
"Jim_Cummings",
"acted_in",
"The_Princess_and_the_Frog"
],
[
"Keith_David",
"acted_in",
"Hercules"
],
[
"Keith_David",
"acted_in",
"Mr._&_Mrs._Smith"
],
[
"Keith_David",
"acted_in",
"Terror_in_the_Aisles"
],
[
"Keith_David",
"acted_in",
"The_Princess_and_the_Frog"
],
[
"Keith_David",
"award",
"Tony_Award_for_Best_Featured_Actor_in_a_Musical"
],
[
"Kerry_Washington",
"acted_in",
"Fantastic_Four"
],
[
"Kerry_Washington",
"acted_in",
"Mr._&_Mrs._Smith"
],
[
"Kerry_Washington",
"acted_in",
"She_Hate_Me"
],
[
"Kerry_Washington",
"place_of_birth",
"The_Bronx"
],
[
"Kevin_Michael_Richardson",
"acted_in",
"Lilo_&_Stitch"
],
[
"Kevin_Michael_Richardson",
"location",
"The_Bronx"
],
[
"Kevin_Michael_Richardson",
"place_of_birth",
"The_Bronx"
],
[
"Kim_Carnes",
"artist_origin",
"Pasadena"
],
[
"Kim_Carnes",
"award_nominee",
"Irene_Cara"
],
[
"Kim_Carnes",
"award_winner",
"Irene_Cara"
],
[
"Lilo_&_Stitch",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Martin_Balsam",
"acted_in",
"Terror_in_the_Aisles"
],
[
"Martin_Balsam",
"location",
"The_Bronx"
],
[
"Martin_Balsam",
"place_of_birth",
"The_Bronx"
],
[
"Pasadena",
"contains",
"Art_Center_College_of_Design"
],
[
"Pasadena",
"place",
"Pasadena"
],
[
"Pocahontas",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Regis_Philbin",
"acted_in",
"Shrek_Forever_After"
],
[
"Regis_Philbin",
"acted_in",
"Shrek_the_Third"
],
[
"Regis_Philbin",
"location",
"The_Bronx"
],
[
"Regis_Philbin",
"place_of_birth",
"The_Bronx"
],
[
"Shrek_Forever_After",
"film_crew_role",
"Technical_Director"
],
[
"Shrek_Forever_After",
"genre",
"Fairy_tale"
],
[
"Shrek_the_Third",
"film_crew_role",
"Technical_Director"
],
[
"Shrek_the_Third",
"genre",
"Fairy_tale"
],
[
"Snow_White_and_the_Seven_Dwarfs",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Steve_Jordan",
"artist_origin",
"The_Bronx"
],
[
"Television_Hall_of_Fame",
"inductee",
"Garry_Marshall"
],
[
"Television_Hall_of_Fame",
"inductee",
"Regis_Philbin"
],
[
"The_Bronx",
"county_seat",
"The_Bronx"
],
[
"The_Bronx_High_School_of_Science",
"citytown",
"The_Bronx"
],
[
"The_Bronx_High_School_of_Science",
"school_type",
"State_school"
],
[
"The_Hunchback_of_Notre_Dame",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"The_Little_Mermaid",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"The_Princess_and_the_Frog",
"film_crew_role",
"Technical_Director"
],
[
"The_Princess_and_the_Frog",
"genre",
"Fairy_tale"
],
[
"The_Princess_and_the_Frog",
"production_companies",
"Walt_Disney_Animation_Studios"
],
[
"Wesley_Snipes",
"location",
"The_Bronx"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
1453, 2004_NFL_Draft
13900, 2005_NFL_Draft
10242, 2006_Major_League_Baseball_Draft
1614, 2006_NBA_draft
5584, 2006_NFL_Draft
6704, 2007_NBA_draft
11442, 2007_NFL_Draft
10464, 2008_NBA_draft
9826, 2008_NFL_Draft
10363, 2008_Toronto_International_Film_Festival
5015, Alpha_Delta_Pi
12398, Alpha_Sigma_Phi
1775, Association_of_American_Universities
11639, Bachelor_of_Business_Administration
2532, Bachelor_of_Fine_Arts
13923, Bad_Education
2215, Billy_Zane
1549, Boston_College
3541, Cannes_Film_Festival
1191, Cave_of_Forgotten_Dreams
1413, Chemical_Engineering
4211, Civil_Engineering
1044, Clemson_University
5301, Colorado_Rockies
3292, Coriolanus
3649, Deadwood
7776, Dimeback
4739, Doctor_of_Medicine
10699, Election_2
6960, Fish_Tank
8816, Florida_State_University
5187, Garret_Dillahunt
7526, Good
7712, Heartbeats
7391, Heaven's_Gate
2810, Hebrew_Language
8502, IFC_Films
2727, Icon_Productions
11303, Insidious
1525, Jacksonville_Jaguars
8755, Kaboom
10928, Lawless
8093, Let_Me_In
12917, Looper
287, Los_Angeles_Lakers
12152, Louisiana_State_University
2261, Marketing-GB
8736, Marshall_University
13994, Mary_and_Max
8615, Medicine
12228, Minnesota_Vikings
7103, National_Football_League
8102, New_Orleans_Pelicans
2160, North_Carolina_State_University
1212, Ohio_State_University
8835, On_the_Road
3965, Portland_Trail_Blazers
5765, Purple
2067, Quadrophenia
12470, Rango
7319, Red_Road
11364, Requiem_for_a_Dream
6061, Restless
4227, Robert_Gates
4542, San_Francisco_Giants
3622, Saw
2993, Seraphim_Falls
3163, Synecdoche,_New_York
7197, Tampa_Bay_Buccaneers
2007, Technical_Director
14119, The_Assassination_of_Jesse_James_by_the_Coward_Robert_Ford
13072, The_Beaver
562, The_Believer
2575, The_Good,_the_Bad,_the_Weird
5147, The_Host
2270, The_Passion_of_the_Christ
3007, The_Road
13846, This_Must_Be_the_Place
8625, Tombstone
5464, Toronto_International_Film_Festival
2889, Ulysses'_Gaze
595, University_of_Iowa
5314, University_of_Maryland,_College_Park
3219, University_of_Memphis
12223, University_of_Miami
8082, University_of_Minnesota
5265, University_of_Oklahoma
7468, University_of_South_Carolina
2688, University_of_Tennessee
9596, University_of_Virginia
2823, University_of_Washington
7116, Vanderbilt_University
13008, Waltz_with_Bashir
3458, Western
8666, Zack_and_Miri_Make_a_Porno
src, edge_attr, dst
1453, school, 12152
1453, school, 2160
1453, school, 1212
1453, school, 595
1453, school, 12223
1453, school, 5265
1453, school, 7468
13900, school, 8816
13900, school, 12152
13900, school, 5314
13900, school, 12223
13900, school, 5265
13900, school, 7468
13900, school, 9596
10242, school, 1044
10242, school, 2688
1614, school, 12152
1614, school, 2160
1614, school, 3219
1614, school, 7468
5584, school, 1549
5584, school, 1044
5584, school, 8816
5584, school, 12152
5584, school, 2160
5584, school, 1212
5584, school, 595
5584, school, 5314
5584, school, 3219
5584, school, 12223
5584, school, 8082
5584, school, 5265
5584, school, 7468
5584, school, 2688
5584, school, 9596
5584, school, 7116
6704, school, 1549
6704, school, 8816
6704, school, 12152
6704, school, 1212
6704, school, 595
6704, school, 5314
6704, school, 7116
11442, school, 1044
11442, school, 8816
11442, school, 12152
11442, school, 1212
11442, school, 12223
11442, school, 5265
10464, school, 12152
10464, school, 2160
10464, school, 3219
9826, school, 1549
9826, school, 12152
9826, school, 1212
9826, school, 12223
9826, school, 2688
9826, school, 9596
9826, school, 7116
10363, instance_of_recurring_event, 5464
11639, institution, 1549
11639, institution, 1212
11639, institution, 595
11639, institution, 12223
11639, institution, 8082
11639, institution, 5265
2532, institution, 1549
2532, institution, 8816
2532, institution, 1212
2532, institution, 12223
13923, film_regional_debut_venue, 3541
13923, film_regional_debut_venue, 5464
2215, acted_in, 562
2215, acted_in, 8625
1549, campuses, 1549
1549, educational_institution, 1549
1549, major_field_of_study, 2261
1191, film_regional_debut_venue, 5464
1044, campuses, 1044
1044, colors, 5765
1044, fraternities_and_sororities, 5015
1044, fraternities_and_sororities, 12398
1044, major_field_of_study, 2261
5301, school, 2688
5301, school, 7116
3292, film_regional_debut_venue, 5464
3649, actor, 5187
3649, genre, 3458
7776, team, 1525
7776, team, 12228
4739, institution, 5314
4739, institution, 8082
4739, institution, 5265
4739, institution, 9596
4739, institution, 7116
10699, film_regional_debut_venue, 3541
10699, film_regional_debut_venue, 5464
6960, film_regional_debut_venue, 3541
6960, film_regional_debut_venue, 5464
8816, campuses, 8816
8816, educational_institution, 8816
8816, fraternities_and_sororities, 5015
8816, major_field_of_study, 2261
5187, acted_in, 12917
5187, acted_in, 14119
5187, acted_in, 562
5187, acted_in, 3007
7526, film_festivals, 10363
7526, film_regional_debut_venue, 5464
7712, film_regional_debut_venue, 3541
7712, film_regional_debut_venue, 5464
7391, film_regional_debut_venue, 3541
7391, genre, 3458
8502, film, 1191
8502, film, 6960
8502, film, 7712
8502, film, 8755
8502, film, 13994
8502, film, 8835
8502, film, 2575
8502, nominated_for, 1191
2727, film, 3292
2727, film, 11303
2727, film, 8093
2727, film, 13994
2727, film, 8835
2727, film, 2993
2727, film, 13072
2727, film, 2575
2727, film, 2270
2727, film, 3007
11303, film_regional_debut_venue, 5464
1525, draft, 1453
1525, draft, 13900
1525, draft, 5584
1525, draft, 11442
1525, draft, 9826
1525, school, 8736
1525, school, 2823
8755, film_regional_debut_venue, 3541
8755, film_regional_debut_venue, 5464
10928, film_regional_debut_venue, 3541
10928, genre, 3458
8093, film_regional_debut_venue, 5464
12917, film_regional_debut_venue, 5464
287, school, 1044
287, school, 8082
12152, campuses, 12152
12152, colors, 5765
12152, educational_institution, 12152
12152, major_field_of_study, 1413
12228, colors, 5765
12228, draft, 1453
12228, draft, 13900
12228, draft, 5584
12228, draft, 11442
12228, position_s, 7776
12228, school, 8736
12228, school, 595
12228, school, 5265
12228, school, 7468
7103, team, 1525
7103, team, 12228
7103, team, 7197
8102, school, 2160
8102, school, 595
2160, campuses, 2160
2160, educational_institution, 2160
2160, fraternities_and_sororities, 5015
2160, fraternities_and_sororities, 12398
2160, major_field_of_study, 1413
1212, campuses, 1212
1212, educational_institution, 1212
1212, fraternities_and_sororities, 5015
1212, fraternities_and_sororities, 12398
1212, major_field_of_study, 1413
1212, major_field_of_study, 8615
1212, organization, 1775
8835, film_regional_debut_venue, 3541
8835, film_regional_debut_venue, 5464
3965, school, 12152
3965, school, 1212
3965, school, 7116
2067, film_regional_debut_venue, 3541
2067, film_regional_debut_venue, 5464
12470, film_crew_role, 2007
12470, genre, 3458
7319, film_regional_debut_venue, 3541
7319, film_regional_debut_venue, 5464
11364, film_regional_debut_venue, 3541
11364, film_regional_debut_venue, 5464
6061, film_regional_debut_venue, 3541
6061, film_regional_debut_venue, 5464
4227, company, 12152
4227, company, 5265
4227, company, 7116
4542, school, 12152
4542, school, 2688
3622, film_regional_debut_venue, 3541
3622, film_regional_debut_venue, 5464
2993, genre, 3458
2993, production_companies, 2727
3163, film_festivals, 10363
3163, film_regional_debut_venue, 3541
7197, draft, 1453
7197, draft, 13900
7197, draft, 5584
7197, draft, 11442
7197, draft, 9826
7197, position_s, 7776
7197, school, 1044
7197, school, 12152
7197, school, 5265
7197, school, 2823
14119, genre, 3458
13072, film_regional_debut_venue, 3541
562, film_regional_debut_venue, 5464
562, language, 2810
2575, film_crew_role, 2007
2575, film_festivals, 10363
2575, film_regional_debut_venue, 3541
2575, film_regional_debut_venue, 5464
2575, genre, 3458
5147, film_regional_debut_venue, 3541
5147, film_regional_debut_venue, 5464
2270, language, 2810
13846, film_regional_debut_venue, 3541
13846, language, 2810
8625, genre, 3458
2889, film_regional_debut_venue, 3541
2889, film_regional_debut_venue, 5464
595, fraternities_and_sororities, 5015
595, fraternities_and_sororities, 12398
595, major_field_of_study, 4211
595, organization, 1775
5314, educational_institution, 5314
5314, fraternities_and_sororities, 5015
5314, fraternities_and_sororities, 12398
5314, major_field_of_study, 2261
5314, organization, 1775
3219, campuses, 3219
3219, educational_institution, 3219
3219, fraternities_and_sororities, 5015
12223, campuses, 12223
12223, educational_institution, 12223
12223, fraternities_and_sororities, 5015
8082, campuses, 8082
8082, educational_institution, 8082
8082, fraternities_and_sororities, 12398
8082, major_field_of_study, 1413
8082, major_field_of_study, 8615
8082, organization, 1775
5265, campuses, 5265
5265, educational_institution, 5265
5265, fraternities_and_sororities, 12398
7468, campuses, 7468
7468, educational_institution, 7468
7468, fraternities_and_sororities, 5015
2688, campuses, 2688
2688, fraternities_and_sororities, 5015
2688, major_field_of_study, 1413
2688, major_field_of_study, 8615
9596, educational_institution, 9596
9596, fraternities_and_sororities, 5015
9596, major_field_of_study, 8615
9596, organization, 1775
2823, student, 5187
7116, campuses, 7116
7116, educational_institution, 7116
7116, fraternities_and_sororities, 5015
7116, major_field_of_study, 1413
7116, major_field_of_study, 4211
7116, major_field_of_study, 8615
7116, organization, 1775
13008, film_festivals, 10363
13008, language, 2810
3458, titles, 3649
3458, titles, 7391
3458, titles, 14119
3458, titles, 8625
8666, film_festivals, 10363
8666, film_regional_debut_venue, 5464
Question: How are 2006_NFL_Draft, The_Believer, and The_Good,_the_Bad,_the_Weird related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"2006_NFL_Draft",
"The_Believer",
"The_Good,_the_Bad,_the_Weird"
],
"valid_edges": [
[
"2004_NFL_Draft",
"school",
"Louisiana_State_University"
],
[
"2004_NFL_Draft",
"school",
"North_Carolina_State_University"
],
[
"2004_NFL_Draft",
"school",
"Ohio_State_University"
],
[
"2004_NFL_Draft",
"school",
"University_of_Iowa"
],
[
"2004_NFL_Draft",
"school",
"University_of_Miami"
],
[
"2004_NFL_Draft",
"school",
"University_of_Oklahoma"
],
[
"2004_NFL_Draft",
"school",
"University_of_South_Carolina"
],
[
"2005_NFL_Draft",
"school",
"Florida_State_University"
],
[
"2005_NFL_Draft",
"school",
"Louisiana_State_University"
],
[
"2005_NFL_Draft",
"school",
"University_of_Maryland,_College_Park"
],
[
"2005_NFL_Draft",
"school",
"University_of_Miami"
],
[
"2005_NFL_Draft",
"school",
"University_of_Oklahoma"
],
[
"2005_NFL_Draft",
"school",
"University_of_South_Carolina"
],
[
"2005_NFL_Draft",
"school",
"University_of_Virginia"
],
[
"2006_Major_League_Baseball_Draft",
"school",
"Clemson_University"
],
[
"2006_Major_League_Baseball_Draft",
"school",
"University_of_Tennessee"
],
[
"2006_NBA_draft",
"school",
"Louisiana_State_University"
],
[
"2006_NBA_draft",
"school",
"North_Carolina_State_University"
],
[
"2006_NBA_draft",
"school",
"University_of_Memphis"
],
[
"2006_NBA_draft",
"school",
"University_of_South_Carolina"
],
[
"2006_NFL_Draft",
"school",
"Boston_College"
],
[
"2006_NFL_Draft",
"school",
"Clemson_University"
],
[
"2006_NFL_Draft",
"school",
"Florida_State_University"
],
[
"2006_NFL_Draft",
"school",
"Louisiana_State_University"
],
[
"2006_NFL_Draft",
"school",
"North_Carolina_State_University"
],
[
"2006_NFL_Draft",
"school",
"Ohio_State_University"
],
[
"2006_NFL_Draft",
"school",
"University_of_Iowa"
],
[
"2006_NFL_Draft",
"school",
"University_of_Maryland,_College_Park"
],
[
"2006_NFL_Draft",
"school",
"University_of_Memphis"
],
[
"2006_NFL_Draft",
"school",
"University_of_Miami"
],
[
"2006_NFL_Draft",
"school",
"University_of_Minnesota"
],
[
"2006_NFL_Draft",
"school",
"University_of_Oklahoma"
],
[
"2006_NFL_Draft",
"school",
"University_of_South_Carolina"
],
[
"2006_NFL_Draft",
"school",
"University_of_Tennessee"
],
[
"2006_NFL_Draft",
"school",
"University_of_Virginia"
],
[
"2006_NFL_Draft",
"school",
"Vanderbilt_University"
],
[
"2007_NBA_draft",
"school",
"Boston_College"
],
[
"2007_NBA_draft",
"school",
"Florida_State_University"
],
[
"2007_NBA_draft",
"school",
"Louisiana_State_University"
],
[
"2007_NBA_draft",
"school",
"Ohio_State_University"
],
[
"2007_NBA_draft",
"school",
"University_of_Iowa"
],
[
"2007_NBA_draft",
"school",
"University_of_Maryland,_College_Park"
],
[
"2007_NBA_draft",
"school",
"Vanderbilt_University"
],
[
"2007_NFL_Draft",
"school",
"Clemson_University"
],
[
"2007_NFL_Draft",
"school",
"Florida_State_University"
],
[
"2007_NFL_Draft",
"school",
"Louisiana_State_University"
],
[
"2007_NFL_Draft",
"school",
"Ohio_State_University"
],
[
"2007_NFL_Draft",
"school",
"University_of_Miami"
],
[
"2007_NFL_Draft",
"school",
"University_of_Oklahoma"
],
[
"2008_NBA_draft",
"school",
"Louisiana_State_University"
],
[
"2008_NBA_draft",
"school",
"North_Carolina_State_University"
],
[
"2008_NBA_draft",
"school",
"University_of_Memphis"
],
[
"2008_NFL_Draft",
"school",
"Boston_College"
],
[
"2008_NFL_Draft",
"school",
"Louisiana_State_University"
],
[
"2008_NFL_Draft",
"school",
"Ohio_State_University"
],
[
"2008_NFL_Draft",
"school",
"University_of_Miami"
],
[
"2008_NFL_Draft",
"school",
"University_of_Tennessee"
],
[
"2008_NFL_Draft",
"school",
"University_of_Virginia"
],
[
"2008_NFL_Draft",
"school",
"Vanderbilt_University"
],
[
"2008_Toronto_International_Film_Festival",
"instance_of_recurring_event",
"Toronto_International_Film_Festival"
],
[
"Bachelor_of_Business_Administration",
"institution",
"Boston_College"
],
[
"Bachelor_of_Business_Administration",
"institution",
"Ohio_State_University"
],
[
"Bachelor_of_Business_Administration",
"institution",
"University_of_Iowa"
],
[
"Bachelor_of_Business_Administration",
"institution",
"University_of_Miami"
],
[
"Bachelor_of_Business_Administration",
"institution",
"University_of_Minnesota"
],
[
"Bachelor_of_Business_Administration",
"institution",
"University_of_Oklahoma"
],
[
"Bachelor_of_Fine_Arts",
"institution",
"Boston_College"
],
[
"Bachelor_of_Fine_Arts",
"institution",
"Florida_State_University"
],
[
"Bachelor_of_Fine_Arts",
"institution",
"Ohio_State_University"
],
[
"Bachelor_of_Fine_Arts",
"institution",
"University_of_Miami"
],
[
"Bad_Education",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Bad_Education",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Billy_Zane",
"acted_in",
"The_Believer"
],
[
"Billy_Zane",
"acted_in",
"Tombstone"
],
[
"Boston_College",
"campuses",
"Boston_College"
],
[
"Boston_College",
"educational_institution",
"Boston_College"
],
[
"Boston_College",
"major_field_of_study",
"Marketing-GB"
],
[
"Cave_of_Forgotten_Dreams",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Clemson_University",
"campuses",
"Clemson_University"
],
[
"Clemson_University",
"colors",
"Purple"
],
[
"Clemson_University",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"Clemson_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Clemson_University",
"major_field_of_study",
"Marketing-GB"
],
[
"Colorado_Rockies",
"school",
"University_of_Tennessee"
],
[
"Colorado_Rockies",
"school",
"Vanderbilt_University"
],
[
"Coriolanus",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Deadwood",
"actor",
"Garret_Dillahunt"
],
[
"Deadwood",
"genre",
"Western"
],
[
"Dimeback",
"team",
"Jacksonville_Jaguars"
],
[
"Dimeback",
"team",
"Minnesota_Vikings"
],
[
"Doctor_of_Medicine",
"institution",
"University_of_Maryland,_College_Park"
],
[
"Doctor_of_Medicine",
"institution",
"University_of_Minnesota"
],
[
"Doctor_of_Medicine",
"institution",
"University_of_Oklahoma"
],
[
"Doctor_of_Medicine",
"institution",
"University_of_Virginia"
],
[
"Doctor_of_Medicine",
"institution",
"Vanderbilt_University"
],
[
"Election_2",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Election_2",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Fish_Tank",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Fish_Tank",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Florida_State_University",
"campuses",
"Florida_State_University"
],
[
"Florida_State_University",
"educational_institution",
"Florida_State_University"
],
[
"Florida_State_University",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"Florida_State_University",
"major_field_of_study",
"Marketing-GB"
],
[
"Garret_Dillahunt",
"acted_in",
"Looper"
],
[
"Garret_Dillahunt",
"acted_in",
"The_Assassination_of_Jesse_James_by_the_Coward_Robert_Ford"
],
[
"Garret_Dillahunt",
"acted_in",
"The_Believer"
],
[
"Garret_Dillahunt",
"acted_in",
"The_Road"
],
[
"Good",
"film_festivals",
"2008_Toronto_International_Film_Festival"
],
[
"Good",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Heartbeats",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Heartbeats",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Heaven's_Gate",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Heaven's_Gate",
"genre",
"Western"
],
[
"IFC_Films",
"film",
"Cave_of_Forgotten_Dreams"
],
[
"IFC_Films",
"film",
"Fish_Tank"
],
[
"IFC_Films",
"film",
"Heartbeats"
],
[
"IFC_Films",
"film",
"Kaboom"
],
[
"IFC_Films",
"film",
"Mary_and_Max"
],
[
"IFC_Films",
"film",
"On_the_Road"
],
[
"IFC_Films",
"film",
"The_Good,_the_Bad,_the_Weird"
],
[
"IFC_Films",
"nominated_for",
"Cave_of_Forgotten_Dreams"
],
[
"Icon_Productions",
"film",
"Coriolanus"
],
[
"Icon_Productions",
"film",
"Insidious"
],
[
"Icon_Productions",
"film",
"Let_Me_In"
],
[
"Icon_Productions",
"film",
"Mary_and_Max"
],
[
"Icon_Productions",
"film",
"On_the_Road"
],
[
"Icon_Productions",
"film",
"Seraphim_Falls"
],
[
"Icon_Productions",
"film",
"The_Beaver"
],
[
"Icon_Productions",
"film",
"The_Good,_the_Bad,_the_Weird"
],
[
"Icon_Productions",
"film",
"The_Passion_of_the_Christ"
],
[
"Icon_Productions",
"film",
"The_Road"
],
[
"Insidious",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Jacksonville_Jaguars",
"draft",
"2004_NFL_Draft"
],
[
"Jacksonville_Jaguars",
"draft",
"2005_NFL_Draft"
],
[
"Jacksonville_Jaguars",
"draft",
"2006_NFL_Draft"
],
[
"Jacksonville_Jaguars",
"draft",
"2007_NFL_Draft"
],
[
"Jacksonville_Jaguars",
"draft",
"2008_NFL_Draft"
],
[
"Jacksonville_Jaguars",
"school",
"Marshall_University"
],
[
"Jacksonville_Jaguars",
"school",
"University_of_Washington"
],
[
"Kaboom",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Kaboom",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Lawless",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Lawless",
"genre",
"Western"
],
[
"Let_Me_In",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Looper",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Los_Angeles_Lakers",
"school",
"Clemson_University"
],
[
"Los_Angeles_Lakers",
"school",
"University_of_Minnesota"
],
[
"Louisiana_State_University",
"campuses",
"Louisiana_State_University"
],
[
"Louisiana_State_University",
"colors",
"Purple"
],
[
"Louisiana_State_University",
"educational_institution",
"Louisiana_State_University"
],
[
"Louisiana_State_University",
"major_field_of_study",
"Chemical_Engineering"
],
[
"Minnesota_Vikings",
"colors",
"Purple"
],
[
"Minnesota_Vikings",
"draft",
"2004_NFL_Draft"
],
[
"Minnesota_Vikings",
"draft",
"2005_NFL_Draft"
],
[
"Minnesota_Vikings",
"draft",
"2006_NFL_Draft"
],
[
"Minnesota_Vikings",
"draft",
"2007_NFL_Draft"
],
[
"Minnesota_Vikings",
"position_s",
"Dimeback"
],
[
"Minnesota_Vikings",
"school",
"Marshall_University"
],
[
"Minnesota_Vikings",
"school",
"University_of_Iowa"
],
[
"Minnesota_Vikings",
"school",
"University_of_Oklahoma"
],
[
"Minnesota_Vikings",
"school",
"University_of_South_Carolina"
],
[
"National_Football_League",
"team",
"Jacksonville_Jaguars"
],
[
"National_Football_League",
"team",
"Minnesota_Vikings"
],
[
"National_Football_League",
"team",
"Tampa_Bay_Buccaneers"
],
[
"New_Orleans_Pelicans",
"school",
"North_Carolina_State_University"
],
[
"New_Orleans_Pelicans",
"school",
"University_of_Iowa"
],
[
"North_Carolina_State_University",
"campuses",
"North_Carolina_State_University"
],
[
"North_Carolina_State_University",
"educational_institution",
"North_Carolina_State_University"
],
[
"North_Carolina_State_University",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"North_Carolina_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"North_Carolina_State_University",
"major_field_of_study",
"Chemical_Engineering"
],
[
"Ohio_State_University",
"campuses",
"Ohio_State_University"
],
[
"Ohio_State_University",
"educational_institution",
"Ohio_State_University"
],
[
"Ohio_State_University",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"Ohio_State_University",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"Ohio_State_University",
"major_field_of_study",
"Chemical_Engineering"
],
[
"Ohio_State_University",
"major_field_of_study",
"Medicine"
],
[
"Ohio_State_University",
"organization",
"Association_of_American_Universities"
],
[
"On_the_Road",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"On_the_Road",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Portland_Trail_Blazers",
"school",
"Louisiana_State_University"
],
[
"Portland_Trail_Blazers",
"school",
"Ohio_State_University"
],
[
"Portland_Trail_Blazers",
"school",
"Vanderbilt_University"
],
[
"Quadrophenia",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Quadrophenia",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Rango",
"film_crew_role",
"Technical_Director"
],
[
"Rango",
"genre",
"Western"
],
[
"Red_Road",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Red_Road",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Requiem_for_a_Dream",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Requiem_for_a_Dream",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Restless",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Restless",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Robert_Gates",
"company",
"Louisiana_State_University"
],
[
"Robert_Gates",
"company",
"University_of_Oklahoma"
],
[
"Robert_Gates",
"company",
"Vanderbilt_University"
],
[
"San_Francisco_Giants",
"school",
"Louisiana_State_University"
],
[
"San_Francisco_Giants",
"school",
"University_of_Tennessee"
],
[
"Saw",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Saw",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Seraphim_Falls",
"genre",
"Western"
],
[
"Seraphim_Falls",
"production_companies",
"Icon_Productions"
],
[
"Synecdoche,_New_York",
"film_festivals",
"2008_Toronto_International_Film_Festival"
],
[
"Synecdoche,_New_York",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Tampa_Bay_Buccaneers",
"draft",
"2004_NFL_Draft"
],
[
"Tampa_Bay_Buccaneers",
"draft",
"2005_NFL_Draft"
],
[
"Tampa_Bay_Buccaneers",
"draft",
"2006_NFL_Draft"
],
[
"Tampa_Bay_Buccaneers",
"draft",
"2007_NFL_Draft"
],
[
"Tampa_Bay_Buccaneers",
"draft",
"2008_NFL_Draft"
],
[
"Tampa_Bay_Buccaneers",
"position_s",
"Dimeback"
],
[
"Tampa_Bay_Buccaneers",
"school",
"Clemson_University"
],
[
"Tampa_Bay_Buccaneers",
"school",
"Louisiana_State_University"
],
[
"Tampa_Bay_Buccaneers",
"school",
"University_of_Oklahoma"
],
[
"Tampa_Bay_Buccaneers",
"school",
"University_of_Washington"
],
[
"The_Assassination_of_Jesse_James_by_the_Coward_Robert_Ford",
"genre",
"Western"
],
[
"The_Beaver",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"The_Believer",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"The_Believer",
"language",
"Hebrew_Language"
],
[
"The_Good,_the_Bad,_the_Weird",
"film_crew_role",
"Technical_Director"
],
[
"The_Good,_the_Bad,_the_Weird",
"film_festivals",
"2008_Toronto_International_Film_Festival"
],
[
"The_Good,_the_Bad,_the_Weird",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"The_Good,_the_Bad,_the_Weird",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"The_Good,_the_Bad,_the_Weird",
"genre",
"Western"
],
[
"The_Host",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"The_Host",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"The_Passion_of_the_Christ",
"language",
"Hebrew_Language"
],
[
"This_Must_Be_the_Place",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"This_Must_Be_the_Place",
"language",
"Hebrew_Language"
],
[
"Tombstone",
"genre",
"Western"
],
[
"Ulysses'_Gaze",
"film_regional_debut_venue",
"Cannes_Film_Festival"
],
[
"Ulysses'_Gaze",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"University_of_Iowa",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Iowa",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Iowa",
"major_field_of_study",
"Civil_Engineering"
],
[
"University_of_Iowa",
"organization",
"Association_of_American_Universities"
],
[
"University_of_Maryland,_College_Park",
"educational_institution",
"University_of_Maryland,_College_Park"
],
[
"University_of_Maryland,_College_Park",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Maryland,_College_Park",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Maryland,_College_Park",
"major_field_of_study",
"Marketing-GB"
],
[
"University_of_Maryland,_College_Park",
"organization",
"Association_of_American_Universities"
],
[
"University_of_Memphis",
"campuses",
"University_of_Memphis"
],
[
"University_of_Memphis",
"educational_institution",
"University_of_Memphis"
],
[
"University_of_Memphis",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Miami",
"campuses",
"University_of_Miami"
],
[
"University_of_Miami",
"educational_institution",
"University_of_Miami"
],
[
"University_of_Miami",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Minnesota",
"campuses",
"University_of_Minnesota"
],
[
"University_of_Minnesota",
"educational_institution",
"University_of_Minnesota"
],
[
"University_of_Minnesota",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_Minnesota",
"major_field_of_study",
"Chemical_Engineering"
],
[
"University_of_Minnesota",
"major_field_of_study",
"Medicine"
],
[
"University_of_Minnesota",
"organization",
"Association_of_American_Universities"
],
[
"University_of_Oklahoma",
"campuses",
"University_of_Oklahoma"
],
[
"University_of_Oklahoma",
"educational_institution",
"University_of_Oklahoma"
],
[
"University_of_Oklahoma",
"fraternities_and_sororities",
"Alpha_Sigma_Phi"
],
[
"University_of_South_Carolina",
"campuses",
"University_of_South_Carolina"
],
[
"University_of_South_Carolina",
"educational_institution",
"University_of_South_Carolina"
],
[
"University_of_South_Carolina",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Tennessee",
"campuses",
"University_of_Tennessee"
],
[
"University_of_Tennessee",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Tennessee",
"major_field_of_study",
"Chemical_Engineering"
],
[
"University_of_Tennessee",
"major_field_of_study",
"Medicine"
],
[
"University_of_Virginia",
"educational_institution",
"University_of_Virginia"
],
[
"University_of_Virginia",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"University_of_Virginia",
"major_field_of_study",
"Medicine"
],
[
"University_of_Virginia",
"organization",
"Association_of_American_Universities"
],
[
"University_of_Washington",
"student",
"Garret_Dillahunt"
],
[
"Vanderbilt_University",
"campuses",
"Vanderbilt_University"
],
[
"Vanderbilt_University",
"educational_institution",
"Vanderbilt_University"
],
[
"Vanderbilt_University",
"fraternities_and_sororities",
"Alpha_Delta_Pi"
],
[
"Vanderbilt_University",
"major_field_of_study",
"Chemical_Engineering"
],
[
"Vanderbilt_University",
"major_field_of_study",
"Civil_Engineering"
],
[
"Vanderbilt_University",
"major_field_of_study",
"Medicine"
],
[
"Vanderbilt_University",
"organization",
"Association_of_American_Universities"
],
[
"Waltz_with_Bashir",
"film_festivals",
"2008_Toronto_International_Film_Festival"
],
[
"Waltz_with_Bashir",
"language",
"Hebrew_Language"
],
[
"Western",
"titles",
"Deadwood"
],
[
"Western",
"titles",
"Heaven's_Gate"
],
[
"Western",
"titles",
"The_Assassination_of_Jesse_James_by_the_Coward_Robert_Ford"
],
[
"Western",
"titles",
"Tombstone"
],
[
"Zack_and_Miri_Make_a_Porno",
"film_festivals",
"2008_Toronto_International_Film_Festival"
],
[
"Zack_and_Miri_Make_a_Porno",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4103, Billy_Ray_Cyrus
12746, George_Strait
12456, Grammy_Award_for_Best_Male_Country_Vocal_Performance
14108, Jane_Campion
4340, Los_Angeles_Film_Critics_Association_Award_for_Best_Director
1875, Mulholland_Drive
2709, Painting
8066, San_JosΓ©_State_University
1285, Software_Engineering
src, edge_attr, dst
4103, acted_in, 1875
4103, award, 12456
12746, award, 12456
4340, award_winner, 14108
1875, award_honor_award, 4340
2709, student, 14108
8066, campuses, 8066
8066, educational_institution, 8066
8066, major_field_of_study, 2709
8066, major_field_of_study, 1285
Question: In what context are George_Strait, Los_Angeles_Film_Critics_Association_Award_for_Best_Director, and Software_Engineering connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"George_Strait",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Director",
"Software_Engineering"
],
"valid_edges": [
[
"Billy_Ray_Cyrus",
"acted_in",
"Mulholland_Drive"
],
[
"Billy_Ray_Cyrus",
"award",
"Grammy_Award_for_Best_Male_Country_Vocal_Performance"
],
[
"George_Strait",
"award",
"Grammy_Award_for_Best_Male_Country_Vocal_Performance"
],
[
"Los_Angeles_Film_Critics_Association_Award_for_Best_Director",
"award_winner",
"Jane_Campion"
],
[
"Mulholland_Drive",
"award_honor_award",
"Los_Angeles_Film_Critics_Association_Award_for_Best_Director"
],
[
"Painting",
"student",
"Jane_Campion"
],
[
"San_JosΓ©_State_University",
"campuses",
"San_JosΓ©_State_University"
],
[
"San_JosΓ©_State_University",
"educational_institution",
"San_JosΓ©_State_University"
],
[
"San_JosΓ©_State_University",
"major_field_of_study",
"Painting"
],
[
"San_JosΓ©_State_University",
"major_field_of_study",
"Software_Engineering"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
8873, 14th_United_States_Congress
6166, Andy_Ackerman
13260, Bruce_Willis
13620, Carol_Leifer
11684, Cheers
8432, Dan_O'Shannon
7154, David_Angell
10109, David_Lee
10915, Frasier
6706, Friends
256, Glen_Charles
1129, James_Burrows
9471, Jerry_Seinfeld
109, Kelsey_Grammer
13221, Peter_Casey
9716, Rhode_Island
13262, Rod_Serling
604, Sam_Simon
5593, Seinfeld
10042, Sitcom
6049, Taxi
9531, Television_Hall_of_Fame
10727, The_Twilight_Zone
src, edge_attr, dst
8873, district_represented, 9716
6166, award_nominee, 8432
6166, award_nominee, 1129
6166, award_winner, 8432
6166, award_winner, 256
6166, award_winner, 1129
6166, nominated_for, 5593
6166, program, 5593
13620, award_nominee, 9471
13620, celebrity, 9471
13620, influenced_by, 9471
13620, nominated_for, 5593
13620, program, 5593
11684, award_winner, 6166
11684, award_winner, 8432
11684, award_winner, 7154
11684, award_winner, 10109
11684, award_winner, 256
11684, award_winner, 1129
11684, award_winner, 13221
11684, genre, 10042
11684, program_creator, 256
11684, program_creator, 1129
8432, award_nominee, 6166
8432, award_nominee, 10109
8432, award_nominee, 256
8432, award_nominee, 1129
8432, award_nominee, 13221
8432, award_winner, 6166
8432, award_winner, 13620
8432, award_winner, 256
8432, award_winner, 1129
8432, nominated_for, 11684
8432, nominated_for, 10915
7154, award_nominee, 8432
7154, award_nominee, 256
7154, award_nominee, 1129
7154, award_winner, 256
7154, award_winner, 1129
7154, location, 9716
7154, nominated_for, 11684
10109, award_nominee, 8432
10109, award_nominee, 256
10109, award_nominee, 1129
10109, award_winner, 256
10109, award_winner, 1129
10109, nominated_for, 11684
10109, program, 11684
10915, award_winner, 1129
6706, award_winner, 13260
256, award_nominee, 6166
256, award_nominee, 8432
256, award_nominee, 1129
256, award_nominee, 13221
256, award_winner, 6166
256, award_winner, 8432
256, award_winner, 10109
256, award_winner, 1129
256, award_winner, 13221
256, nominated_for, 11684
256, program, 6049
1129, award_nominee, 8432
1129, award_nominee, 7154
1129, award_nominee, 10109
1129, award_nominee, 256
1129, award_nominee, 13221
1129, award_nominee, 604
1129, award_winner, 6166
1129, award_winner, 8432
1129, award_winner, 7154
1129, award_winner, 10109
1129, award_winner, 256
1129, award_winner, 13221
1129, nominated_for, 11684
1129, nominated_for, 10915
1129, nominated_for, 6706
1129, program, 11684
9471, award_nominee, 6166
9471, award_nominee, 13620
9471, celebrity, 13620
9471, nominated_for, 5593
9471, program, 5593
109, award_nominee, 8432
109, nominated_for, 11684
13221, award_nominee, 8432
13221, award_nominee, 256
13221, award_nominee, 1129
13221, award_winner, 256
13221, award_winner, 1129
13221, program, 11684
13262, tv_program, 10727
604, award_nominee, 256
604, award_nominee, 1129
604, tv_program, 11684
5593, actor, 9471
5593, award_winner, 6166
5593, award_winner, 9471
5593, genre, 10042
5593, program_creator, 9471
6049, award_winner, 1129
9531, inductee, 1129
9531, inductee, 13262
10727, actor, 13260
10727, program_creator, 10727
Question: In what context are 14th_United_States_Congress, Andy_Ackerman, and The_Twilight_Zone connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"14th_United_States_Congress",
"Andy_Ackerman",
"The_Twilight_Zone"
],
"valid_edges": [
[
"14th_United_States_Congress",
"district_represented",
"Rhode_Island"
],
[
"Andy_Ackerman",
"award_nominee",
"Dan_O'Shannon"
],
[
"Andy_Ackerman",
"award_nominee",
"James_Burrows"
],
[
"Andy_Ackerman",
"award_winner",
"Dan_O'Shannon"
],
[
"Andy_Ackerman",
"award_winner",
"Glen_Charles"
],
[
"Andy_Ackerman",
"award_winner",
"James_Burrows"
],
[
"Andy_Ackerman",
"nominated_for",
"Seinfeld"
],
[
"Andy_Ackerman",
"program",
"Seinfeld"
],
[
"Carol_Leifer",
"award_nominee",
"Jerry_Seinfeld"
],
[
"Carol_Leifer",
"celebrity",
"Jerry_Seinfeld"
],
[
"Carol_Leifer",
"influenced_by",
"Jerry_Seinfeld"
],
[
"Carol_Leifer",
"nominated_for",
"Seinfeld"
],
[
"Carol_Leifer",
"program",
"Seinfeld"
],
[
"Cheers",
"award_winner",
"Andy_Ackerman"
],
[
"Cheers",
"award_winner",
"Dan_O'Shannon"
],
[
"Cheers",
"award_winner",
"David_Angell"
],
[
"Cheers",
"award_winner",
"David_Lee"
],
[
"Cheers",
"award_winner",
"Glen_Charles"
],
[
"Cheers",
"award_winner",
"James_Burrows"
],
[
"Cheers",
"award_winner",
"Peter_Casey"
],
[
"Cheers",
"genre",
"Sitcom"
],
[
"Cheers",
"program_creator",
"Glen_Charles"
],
[
"Cheers",
"program_creator",
"James_Burrows"
],
[
"Dan_O'Shannon",
"award_nominee",
"Andy_Ackerman"
],
[
"Dan_O'Shannon",
"award_nominee",
"David_Lee"
],
[
"Dan_O'Shannon",
"award_nominee",
"Glen_Charles"
],
[
"Dan_O'Shannon",
"award_nominee",
"James_Burrows"
],
[
"Dan_O'Shannon",
"award_nominee",
"Peter_Casey"
],
[
"Dan_O'Shannon",
"award_winner",
"Andy_Ackerman"
],
[
"Dan_O'Shannon",
"award_winner",
"Carol_Leifer"
],
[
"Dan_O'Shannon",
"award_winner",
"Glen_Charles"
],
[
"Dan_O'Shannon",
"award_winner",
"James_Burrows"
],
[
"Dan_O'Shannon",
"nominated_for",
"Cheers"
],
[
"Dan_O'Shannon",
"nominated_for",
"Frasier"
],
[
"David_Angell",
"award_nominee",
"Dan_O'Shannon"
],
[
"David_Angell",
"award_nominee",
"Glen_Charles"
],
[
"David_Angell",
"award_nominee",
"James_Burrows"
],
[
"David_Angell",
"award_winner",
"Glen_Charles"
],
[
"David_Angell",
"award_winner",
"James_Burrows"
],
[
"David_Angell",
"location",
"Rhode_Island"
],
[
"David_Angell",
"nominated_for",
"Cheers"
],
[
"David_Lee",
"award_nominee",
"Dan_O'Shannon"
],
[
"David_Lee",
"award_nominee",
"Glen_Charles"
],
[
"David_Lee",
"award_nominee",
"James_Burrows"
],
[
"David_Lee",
"award_winner",
"Glen_Charles"
],
[
"David_Lee",
"award_winner",
"James_Burrows"
],
[
"David_Lee",
"nominated_for",
"Cheers"
],
[
"David_Lee",
"program",
"Cheers"
],
[
"Frasier",
"award_winner",
"James_Burrows"
],
[
"Friends",
"award_winner",
"Bruce_Willis"
],
[
"Glen_Charles",
"award_nominee",
"Andy_Ackerman"
],
[
"Glen_Charles",
"award_nominee",
"Dan_O'Shannon"
],
[
"Glen_Charles",
"award_nominee",
"James_Burrows"
],
[
"Glen_Charles",
"award_nominee",
"Peter_Casey"
],
[
"Glen_Charles",
"award_winner",
"Andy_Ackerman"
],
[
"Glen_Charles",
"award_winner",
"Dan_O'Shannon"
],
[
"Glen_Charles",
"award_winner",
"David_Lee"
],
[
"Glen_Charles",
"award_winner",
"James_Burrows"
],
[
"Glen_Charles",
"award_winner",
"Peter_Casey"
],
[
"Glen_Charles",
"nominated_for",
"Cheers"
],
[
"Glen_Charles",
"program",
"Taxi"
],
[
"James_Burrows",
"award_nominee",
"Dan_O'Shannon"
],
[
"James_Burrows",
"award_nominee",
"David_Angell"
],
[
"James_Burrows",
"award_nominee",
"David_Lee"
],
[
"James_Burrows",
"award_nominee",
"Glen_Charles"
],
[
"James_Burrows",
"award_nominee",
"Peter_Casey"
],
[
"James_Burrows",
"award_nominee",
"Sam_Simon"
],
[
"James_Burrows",
"award_winner",
"Andy_Ackerman"
],
[
"James_Burrows",
"award_winner",
"Dan_O'Shannon"
],
[
"James_Burrows",
"award_winner",
"David_Angell"
],
[
"James_Burrows",
"award_winner",
"David_Lee"
],
[
"James_Burrows",
"award_winner",
"Glen_Charles"
],
[
"James_Burrows",
"award_winner",
"Peter_Casey"
],
[
"James_Burrows",
"nominated_for",
"Cheers"
],
[
"James_Burrows",
"nominated_for",
"Frasier"
],
[
"James_Burrows",
"nominated_for",
"Friends"
],
[
"James_Burrows",
"program",
"Cheers"
],
[
"Jerry_Seinfeld",
"award_nominee",
"Andy_Ackerman"
],
[
"Jerry_Seinfeld",
"award_nominee",
"Carol_Leifer"
],
[
"Jerry_Seinfeld",
"celebrity",
"Carol_Leifer"
],
[
"Jerry_Seinfeld",
"nominated_for",
"Seinfeld"
],
[
"Jerry_Seinfeld",
"program",
"Seinfeld"
],
[
"Kelsey_Grammer",
"award_nominee",
"Dan_O'Shannon"
],
[
"Kelsey_Grammer",
"nominated_for",
"Cheers"
],
[
"Peter_Casey",
"award_nominee",
"Dan_O'Shannon"
],
[
"Peter_Casey",
"award_nominee",
"Glen_Charles"
],
[
"Peter_Casey",
"award_nominee",
"James_Burrows"
],
[
"Peter_Casey",
"award_winner",
"Glen_Charles"
],
[
"Peter_Casey",
"award_winner",
"James_Burrows"
],
[
"Peter_Casey",
"program",
"Cheers"
],
[
"Rod_Serling",
"tv_program",
"The_Twilight_Zone"
],
[
"Sam_Simon",
"award_nominee",
"Glen_Charles"
],
[
"Sam_Simon",
"award_nominee",
"James_Burrows"
],
[
"Sam_Simon",
"tv_program",
"Cheers"
],
[
"Seinfeld",
"actor",
"Jerry_Seinfeld"
],
[
"Seinfeld",
"award_winner",
"Andy_Ackerman"
],
[
"Seinfeld",
"award_winner",
"Jerry_Seinfeld"
],
[
"Seinfeld",
"genre",
"Sitcom"
],
[
"Seinfeld",
"program_creator",
"Jerry_Seinfeld"
],
[
"Taxi",
"award_winner",
"James_Burrows"
],
[
"Television_Hall_of_Fame",
"inductee",
"James_Burrows"
],
[
"Television_Hall_of_Fame",
"inductee",
"Rod_Serling"
],
[
"The_Twilight_Zone",
"actor",
"Bruce_Willis"
],
[
"The_Twilight_Zone",
"program_creator",
"The_Twilight_Zone"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9438, Ashley_Judd
288, Heat
9970, Heist_film
13197, Henry_Rollins
10268, Longview
3400, Matthew_McConaughey
5430, The_Newton_Boys
8438, The_Taking_of_Pelham_123
src, edge_attr, dst
9438, acted_in, 288
9438, participant, 3400
288, genre, 9970
9970, titles, 288
9970, titles, 5430
13197, acted_in, 288
10268, place, 10268
3400, acted_in, 5430
3400, location, 10268
5430, genre, 9970
8438, genre, 9970
Question: In what context are Henry_Rollins, Longview, and The_Taking_of_Pelham_123 connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Henry_Rollins",
"Longview",
"The_Taking_of_Pelham_123"
],
"valid_edges": [
[
"Ashley_Judd",
"acted_in",
"Heat"
],
[
"Ashley_Judd",
"participant",
"Matthew_McConaughey"
],
[
"Heat",
"genre",
"Heist_film"
],
[
"Heist_film",
"titles",
"Heat"
],
[
"Heist_film",
"titles",
"The_Newton_Boys"
],
[
"Henry_Rollins",
"acted_in",
"Heat"
],
[
"Longview",
"place",
"Longview"
],
[
"Matthew_McConaughey",
"acted_in",
"The_Newton_Boys"
],
[
"Matthew_McConaughey",
"location",
"Longview"
],
[
"The_Newton_Boys",
"genre",
"Heist_film"
],
[
"The_Taking_of_Pelham_123",
"genre",
"Heist_film"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9906, Analyze_This
909, BAFTA_Award_for_Best_Animated_Film
5798, Brad_Bird
7279, Bruce_Berman
10553, Channing_Tatum
1791, Chazz_Palminteri
10229, Coach_Carter
7477, Constantine
3285, Emile_Hirsch
163, Happy_Feet
7567, I_Am_Legend
7283, Mary-Kate_Olsen
10453, Nicole_Richie
277, Percy_Jackson_&_the_Olympians:_The_Lightning_Thief
10803, Rick_Kline
11529, Rosario_Dawson
12843, Shia_LaBeouf
12738, Skip_Lievsay
7964, Speed_Racer
src, edge_attr, dst
9906, executive_produced_by, 7279
909, award_winner, 5798
909, nominated_for, 163
5798, award, 909
10553, acted_in, 10229
10553, award_winner, 1791
10553, award_winner, 11529
10553, award_winner, 12843
1791, acted_in, 9906
1791, award_winner, 11529
1791, award_winner, 12843
10229, crewmember, 10803
7477, crewmember, 12738
3285, acted_in, 7964
3285, participant, 10453
163, award_honor_award, 909
163, executive_produced_by, 7279
7567, executive_produced_by, 7279
7283, participant, 10453
7283, participant, 12843
10453, participant, 3285
10453, participant, 7283
277, crewmember, 10803
10803, award_nominee, 12738
10803, nominated_for, 7567
11529, acted_in, 277
11529, award_winner, 10553
11529, award_winner, 1791
11529, award_winner, 12843
12843, acted_in, 7477
12843, award_winner, 1791
12843, award_winner, 11529
12843, participant, 7283
12738, award_nominee, 10803
7964, crewmember, 10803
7964, executive_produced_by, 7279
Question: For what reason are Brad_Bird, Shia_LaBeouf, and Speed_Racer associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Brad_Bird",
"Shia_LaBeouf",
"Speed_Racer"
],
"valid_edges": [
[
"Analyze_This",
"executive_produced_by",
"Bruce_Berman"
],
[
"BAFTA_Award_for_Best_Animated_Film",
"award_winner",
"Brad_Bird"
],
[
"BAFTA_Award_for_Best_Animated_Film",
"nominated_for",
"Happy_Feet"
],
[
"Brad_Bird",
"award",
"BAFTA_Award_for_Best_Animated_Film"
],
[
"Channing_Tatum",
"acted_in",
"Coach_Carter"
],
[
"Channing_Tatum",
"award_winner",
"Chazz_Palminteri"
],
[
"Channing_Tatum",
"award_winner",
"Rosario_Dawson"
],
[
"Channing_Tatum",
"award_winner",
"Shia_LaBeouf"
],
[
"Chazz_Palminteri",
"acted_in",
"Analyze_This"
],
[
"Chazz_Palminteri",
"award_winner",
"Rosario_Dawson"
],
[
"Chazz_Palminteri",
"award_winner",
"Shia_LaBeouf"
],
[
"Coach_Carter",
"crewmember",
"Rick_Kline"
],
[
"Constantine",
"crewmember",
"Skip_Lievsay"
],
[
"Emile_Hirsch",
"acted_in",
"Speed_Racer"
],
[
"Emile_Hirsch",
"participant",
"Nicole_Richie"
],
[
"Happy_Feet",
"award_honor_award",
"BAFTA_Award_for_Best_Animated_Film"
],
[
"Happy_Feet",
"executive_produced_by",
"Bruce_Berman"
],
[
"I_Am_Legend",
"executive_produced_by",
"Bruce_Berman"
],
[
"Mary-Kate_Olsen",
"participant",
"Nicole_Richie"
],
[
"Mary-Kate_Olsen",
"participant",
"Shia_LaBeouf"
],
[
"Nicole_Richie",
"participant",
"Emile_Hirsch"
],
[
"Nicole_Richie",
"participant",
"Mary-Kate_Olsen"
],
[
"Percy_Jackson_&_the_Olympians:_The_Lightning_Thief",
"crewmember",
"Rick_Kline"
],
[
"Rick_Kline",
"award_nominee",
"Skip_Lievsay"
],
[
"Rick_Kline",
"nominated_for",
"I_Am_Legend"
],
[
"Rosario_Dawson",
"acted_in",
"Percy_Jackson_&_the_Olympians:_The_Lightning_Thief"
],
[
"Rosario_Dawson",
"award_winner",
"Channing_Tatum"
],
[
"Rosario_Dawson",
"award_winner",
"Chazz_Palminteri"
],
[
"Rosario_Dawson",
"award_winner",
"Shia_LaBeouf"
],
[
"Shia_LaBeouf",
"acted_in",
"Constantine"
],
[
"Shia_LaBeouf",
"award_winner",
"Chazz_Palminteri"
],
[
"Shia_LaBeouf",
"award_winner",
"Rosario_Dawson"
],
[
"Shia_LaBeouf",
"participant",
"Mary-Kate_Olsen"
],
[
"Skip_Lievsay",
"award_nominee",
"Rick_Kline"
],
[
"Speed_Racer",
"crewmember",
"Rick_Kline"
],
[
"Speed_Racer",
"executive_produced_by",
"Bruce_Berman"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
8375, Birkenhead
4629, European_Union_Member_States
3366, Glenda_Jackson
3265, Jamie_Lee_Curtis
13456, Kevin_Pollak
8757, Malta
6728, Member_of_Parliament-GB
2068, Red_State
10824, True_Lies
src, edge_attr, dst
4629, member_states, 8757
3366, basic_title, 6728
3366, place_of_birth, 8375
3265, acted_in, 10824
3265, nominated_for, 10824
3265, participant, 13456
13456, acted_in, 2068
8757, organization, 4629
6728, jurisdiction_of_office, 4629
2068, film_release_region, 8757
10824, award_winner, 3265
Question: In what context are Birkenhead, Malta, and True_Lies connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Birkenhead",
"Malta",
"True_Lies"
],
"valid_edges": [
[
"European_Union_Member_States",
"member_states",
"Malta"
],
[
"Glenda_Jackson",
"basic_title",
"Member_of_Parliament-GB"
],
[
"Glenda_Jackson",
"place_of_birth",
"Birkenhead"
],
[
"Jamie_Lee_Curtis",
"acted_in",
"True_Lies"
],
[
"Jamie_Lee_Curtis",
"nominated_for",
"True_Lies"
],
[
"Jamie_Lee_Curtis",
"participant",
"Kevin_Pollak"
],
[
"Kevin_Pollak",
"acted_in",
"Red_State"
],
[
"Malta",
"organization",
"European_Union_Member_States"
],
[
"Member_of_Parliament-GB",
"jurisdiction_of_office",
"European_Union_Member_States"
],
[
"Red_State",
"film_release_region",
"Malta"
],
[
"True_Lies",
"award_winner",
"Jamie_Lee_Curtis"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
6109, A.S._Roma
11131, Air_travel
7020, Angels_and_Demons
1131, April
13428, August
2763, Chivas_USA
5063, Dante_Spinotti
4721, David_Beckham
1421, December
5715, Defender
2596, Eva_Longoria
6648, Eva_Mendes
5426, FC_Midtjylland
7184, February
6809, Gladiator
8081, January
7804, July
4422, June
238, Justin_Timberlake
2393, Lindsay_Lohan
13022, Los_Angeles
1158, Lyngby_Boldklub
6522, March
1112, May
6542, November
8619, October
2621, Once_Upon_a_Time_in_America
14107, Rome
1833, September
2698, Sophia_Loren
7952, The_Last_Emperor
1644, Tom_Brady
4045, Train
6852, United_States_Department_of_Housing_and_Urban_Development
src, edge_attr, dst
6109, football_roster_position, 5715
6109, position, 5715
7020, featured_film_locations, 13022
7020, featured_film_locations, 14107
2763, football_roster_position, 5715
5063, location, 13022
5063, location, 14107
4721, location, 13022
5715, team, 6109
5715, team, 2763
5715, team, 1158
2596, location, 13022
6648, location, 13022
6648, participant, 2393
5426, position, 5715
6809, film_release_region, 13022
238, location, 13022
2393, location, 13022
2393, participant, 6648
13022, mode_of_transportation, 11131
13022, mode_of_transportation, 4045
13022, month, 1131
13022, month, 13428
13022, month, 1421
13022, month, 7184
13022, month, 8081
13022, month, 7804
13022, month, 4422
13022, month, 6522
13022, month, 1112
13022, month, 6542
13022, month, 8619
13022, month, 1833
13022, place, 13022
13022, source, 6852
13022, teams, 2763
13022, vacationer, 1644
1158, football_roster_position, 5715
1158, position, 5715
2621, film_release_region, 13022
2621, film_release_region, 14107
14107, films, 6809
14107, mode_of_transportation, 11131
14107, mode_of_transportation, 4045
14107, month, 1131
14107, month, 13428
14107, month, 1421
14107, month, 7184
14107, month, 8081
14107, month, 7804
14107, month, 4422
14107, month, 6522
14107, month, 1112
14107, month, 6542
14107, month, 8619
14107, month, 1833
14107, place, 14107
14107, source, 6852
14107, teams, 6109
14107, vacationer, 4721
14107, vacationer, 2596
14107, vacationer, 6648
14107, vacationer, 238
14107, vacationer, 2393
14107, vacationer, 1644
2698, location, 13022
2698, location, 14107
7952, featured_film_locations, 14107
7952, film_release_region, 13022
Question: In what context are FC_Midtjylland, Lindsay_Lohan, and Lyngby_Boldklub connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"FC_Midtjylland",
"Lindsay_Lohan",
"Lyngby_Boldklub"
],
"valid_edges": [
[
"A.S._Roma",
"football_roster_position",
"Defender"
],
[
"A.S._Roma",
"position",
"Defender"
],
[
"Angels_and_Demons",
"featured_film_locations",
"Los_Angeles"
],
[
"Angels_and_Demons",
"featured_film_locations",
"Rome"
],
[
"Chivas_USA",
"football_roster_position",
"Defender"
],
[
"Dante_Spinotti",
"location",
"Los_Angeles"
],
[
"Dante_Spinotti",
"location",
"Rome"
],
[
"David_Beckham",
"location",
"Los_Angeles"
],
[
"Defender",
"team",
"A.S._Roma"
],
[
"Defender",
"team",
"Chivas_USA"
],
[
"Defender",
"team",
"Lyngby_Boldklub"
],
[
"Eva_Longoria",
"location",
"Los_Angeles"
],
[
"Eva_Mendes",
"location",
"Los_Angeles"
],
[
"Eva_Mendes",
"participant",
"Lindsay_Lohan"
],
[
"FC_Midtjylland",
"position",
"Defender"
],
[
"Gladiator",
"film_release_region",
"Los_Angeles"
],
[
"Justin_Timberlake",
"location",
"Los_Angeles"
],
[
"Lindsay_Lohan",
"location",
"Los_Angeles"
],
[
"Lindsay_Lohan",
"participant",
"Eva_Mendes"
],
[
"Los_Angeles",
"mode_of_transportation",
"Air_travel"
],
[
"Los_Angeles",
"mode_of_transportation",
"Train"
],
[
"Los_Angeles",
"month",
"April"
],
[
"Los_Angeles",
"month",
"August"
],
[
"Los_Angeles",
"month",
"December"
],
[
"Los_Angeles",
"month",
"February"
],
[
"Los_Angeles",
"month",
"January"
],
[
"Los_Angeles",
"month",
"July"
],
[
"Los_Angeles",
"month",
"June"
],
[
"Los_Angeles",
"month",
"March"
],
[
"Los_Angeles",
"month",
"May"
],
[
"Los_Angeles",
"month",
"November"
],
[
"Los_Angeles",
"month",
"October"
],
[
"Los_Angeles",
"month",
"September"
],
[
"Los_Angeles",
"place",
"Los_Angeles"
],
[
"Los_Angeles",
"source",
"United_States_Department_of_Housing_and_Urban_Development"
],
[
"Los_Angeles",
"teams",
"Chivas_USA"
],
[
"Los_Angeles",
"vacationer",
"Tom_Brady"
],
[
"Lyngby_Boldklub",
"football_roster_position",
"Defender"
],
[
"Lyngby_Boldklub",
"position",
"Defender"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Los_Angeles"
],
[
"Once_Upon_a_Time_in_America",
"film_release_region",
"Rome"
],
[
"Rome",
"films",
"Gladiator"
],
[
"Rome",
"mode_of_transportation",
"Air_travel"
],
[
"Rome",
"mode_of_transportation",
"Train"
],
[
"Rome",
"month",
"April"
],
[
"Rome",
"month",
"August"
],
[
"Rome",
"month",
"December"
],
[
"Rome",
"month",
"February"
],
[
"Rome",
"month",
"January"
],
[
"Rome",
"month",
"July"
],
[
"Rome",
"month",
"June"
],
[
"Rome",
"month",
"March"
],
[
"Rome",
"month",
"May"
],
[
"Rome",
"month",
"November"
],
[
"Rome",
"month",
"October"
],
[
"Rome",
"month",
"September"
],
[
"Rome",
"place",
"Rome"
],
[
"Rome",
"source",
"United_States_Department_of_Housing_and_Urban_Development"
],
[
"Rome",
"teams",
"A.S._Roma"
],
[
"Rome",
"vacationer",
"David_Beckham"
],
[
"Rome",
"vacationer",
"Eva_Longoria"
],
[
"Rome",
"vacationer",
"Eva_Mendes"
],
[
"Rome",
"vacationer",
"Justin_Timberlake"
],
[
"Rome",
"vacationer",
"Lindsay_Lohan"
],
[
"Rome",
"vacationer",
"Tom_Brady"
],
[
"Sophia_Loren",
"location",
"Los_Angeles"
],
[
"Sophia_Loren",
"location",
"Rome"
],
[
"The_Last_Emperor",
"featured_film_locations",
"Rome"
],
[
"The_Last_Emperor",
"film_release_region",
"Los_Angeles"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
670, 15th_Screen_Actors_Guild_Awards
12652, Amy_Brenneman
1055, Ben_Stein
3194, Casper
6978, Columbia_College_of_Columbia_University_in_the_City_of_New_York
1626, Irrfan_Khan
9394, National_School_of_Drama
8455, Raj_Babbar
2230, Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Drama_Series
src, edge_attr, dst
670, award_winner, 1626
12652, acted_in, 3194
12652, award, 2230
1055, acted_in, 3194
6978, campuses, 6978
6978, educational_institution, 6978
6978, student, 1055
9394, campuses, 9394
9394, educational_institution, 9394
9394, student, 1626
9394, student, 8455
2230, ceremony, 670
Question: For what reason are Columbia_College_of_Columbia_University_in_the_City_of_New_York, Raj_Babbar, and Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Drama_Series associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Columbia_College_of_Columbia_University_in_the_City_of_New_York",
"Raj_Babbar",
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Drama_Series"
],
"valid_edges": [
[
"15th_Screen_Actors_Guild_Awards",
"award_winner",
"Irrfan_Khan"
],
[
"Amy_Brenneman",
"acted_in",
"Casper"
],
[
"Amy_Brenneman",
"award",
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Drama_Series"
],
[
"Ben_Stein",
"acted_in",
"Casper"
],
[
"Columbia_College_of_Columbia_University_in_the_City_of_New_York",
"campuses",
"Columbia_College_of_Columbia_University_in_the_City_of_New_York"
],
[
"Columbia_College_of_Columbia_University_in_the_City_of_New_York",
"educational_institution",
"Columbia_College_of_Columbia_University_in_the_City_of_New_York"
],
[
"Columbia_College_of_Columbia_University_in_the_City_of_New_York",
"student",
"Ben_Stein"
],
[
"National_School_of_Drama",
"campuses",
"National_School_of_Drama"
],
[
"National_School_of_Drama",
"educational_institution",
"National_School_of_Drama"
],
[
"National_School_of_Drama",
"student",
"Irrfan_Khan"
],
[
"National_School_of_Drama",
"student",
"Raj_Babbar"
],
[
"Screen_Actors_Guild_Award_for_Outstanding_Performance_by_a_Female_Actor_in_a_Drama_Series",
"ceremony",
"15th_Screen_Actors_Guild_Awards"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9305, Broadcast_Film_Critics_Association_Award_for_Best_Actress
9506, French_food
10993, He's_Just_Not_That_Into_You
4473, Indie_rock
2557, Jennifer_Connelly
4282, John_Mayer
4171, Julie_&_Julia
1736, Justin_Long
9486, Riot_grrrl
src, edge_attr, dst
9305, nominated_for, 4171
9506, films, 4171
4473, artists, 4282
2557, acted_in, 10993
2557, award, 9305
4282, participant, 1736
4171, award_honor_award, 9305
1736, acted_in, 10993
1736, participant, 4282
9486, parent_genre, 4473
Question: How are French_food, He's_Just_Not_That_Into_You, and Riot_grrrl related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"French_food",
"He's_Just_Not_That_Into_You",
"Riot_grrrl"
],
"valid_edges": [
[
"Broadcast_Film_Critics_Association_Award_for_Best_Actress",
"nominated_for",
"Julie_&_Julia"
],
[
"French_food",
"films",
"Julie_&_Julia"
],
[
"Indie_rock",
"artists",
"John_Mayer"
],
[
"Jennifer_Connelly",
"acted_in",
"He's_Just_Not_That_Into_You"
],
[
"Jennifer_Connelly",
"award",
"Broadcast_Film_Critics_Association_Award_for_Best_Actress"
],
[
"John_Mayer",
"participant",
"Justin_Long"
],
[
"Julie_&_Julia",
"award_honor_award",
"Broadcast_Film_Critics_Association_Award_for_Best_Actress"
],
[
"Justin_Long",
"acted_in",
"He's_Just_Not_That_Into_You"
],
[
"Justin_Long",
"participant",
"John_Mayer"
],
[
"Riot_grrrl",
"parent_genre",
"Indie_rock"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7800, Agnosticism
11535, American_football
9906, Analyze_This
1529, Carl_Sagan
1791, Chazz_Palminteri
863, Cornell_University
13587, Howard_Shore
2701, Jim_Thorpe
9252, Literature
6042, Locus_Award_for_Best_Science_Fiction_Novel
927, Michel_Foucault
13926, Professor-GB
587, Pulitzer_Prize_for_General_Non-Fiction
2569, Richard_Roundtree
5190, Roman_Catholic_Church
13863, Seven
1937, Stephen_Jay_Gould
12281, The_Usual_Suspects
3848, University_of_California,_Berkeley
src, edge_attr, dst
11535, athlete, 2701
11535, athlete, 2569
9906, film_music, 13587
1529, award, 6042
1529, company, 863
1529, profession, 13926
1529, religion, 7800
1791, acted_in, 9906
1791, acted_in, 12281
1791, religion, 5190
863, major_field_of_study, 9252
13587, nominated_for, 9906
2701, religion, 5190
6042, disciplines_or_subjects, 9252
927, company, 3848
927, religion, 5190
587, award_winner, 1529
587, disciplines_or_subjects, 9252
2569, acted_in, 13863
13863, film_music, 13587
13863, nominated_for, 12281
1937, award, 587
1937, profession, 13926
1937, religion, 7800
12281, nominated_for, 13863
3848, major_field_of_study, 9252
Question: How are Pulitzer_Prize_for_General_Non-Fiction, Roman_Catholic_Church, and Seven related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Pulitzer_Prize_for_General_Non-Fiction",
"Roman_Catholic_Church",
"Seven"
],
"valid_edges": [
[
"American_football",
"athlete",
"Jim_Thorpe"
],
[
"American_football",
"athlete",
"Richard_Roundtree"
],
[
"Analyze_This",
"film_music",
"Howard_Shore"
],
[
"Carl_Sagan",
"award",
"Locus_Award_for_Best_Science_Fiction_Novel"
],
[
"Carl_Sagan",
"company",
"Cornell_University"
],
[
"Carl_Sagan",
"profession",
"Professor-GB"
],
[
"Carl_Sagan",
"religion",
"Agnosticism"
],
[
"Chazz_Palminteri",
"acted_in",
"Analyze_This"
],
[
"Chazz_Palminteri",
"acted_in",
"The_Usual_Suspects"
],
[
"Chazz_Palminteri",
"religion",
"Roman_Catholic_Church"
],
[
"Cornell_University",
"major_field_of_study",
"Literature"
],
[
"Howard_Shore",
"nominated_for",
"Analyze_This"
],
[
"Jim_Thorpe",
"religion",
"Roman_Catholic_Church"
],
[
"Locus_Award_for_Best_Science_Fiction_Novel",
"disciplines_or_subjects",
"Literature"
],
[
"Michel_Foucault",
"company",
"University_of_California,_Berkeley"
],
[
"Michel_Foucault",
"religion",
"Roman_Catholic_Church"
],
[
"Pulitzer_Prize_for_General_Non-Fiction",
"award_winner",
"Carl_Sagan"
],
[
"Pulitzer_Prize_for_General_Non-Fiction",
"disciplines_or_subjects",
"Literature"
],
[
"Richard_Roundtree",
"acted_in",
"Seven"
],
[
"Seven",
"film_music",
"Howard_Shore"
],
[
"Seven",
"nominated_for",
"The_Usual_Suspects"
],
[
"Stephen_Jay_Gould",
"award",
"Pulitzer_Prize_for_General_Non-Fiction"
],
[
"Stephen_Jay_Gould",
"profession",
"Professor-GB"
],
[
"Stephen_Jay_Gould",
"religion",
"Agnosticism"
],
[
"The_Usual_Suspects",
"nominated_for",
"Seven"
],
[
"University_of_California,_Berkeley",
"major_field_of_study",
"Literature"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4117, Christopher_Doyle
6942, Gary
4314, George_S._Clinton
11195, London_Film_Critics_Circle_Award_for_Actor_of_the_Year
10413, Mark_Mothersbaugh
805, Morgan_Freeman
4174, The_Love_Guru
13824, The_Quiet_American
src, edge_attr, dst
6942, place, 6942
4314, award_nominee, 10413
11195, award_winner, 805
11195, nominated_for, 13824
10413, award_nominee, 4314
805, acted_in, 4174
805, location, 6942
4174, film_music, 4314
13824, award_honor_award, 11195
13824, cinematography, 4117
Question: How are Christopher_Doyle, Gary, and Mark_Mothersbaugh related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Christopher_Doyle",
"Gary",
"Mark_Mothersbaugh"
],
"valid_edges": [
[
"Gary",
"place",
"Gary"
],
[
"George_S._Clinton",
"award_nominee",
"Mark_Mothersbaugh"
],
[
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year",
"award_winner",
"Morgan_Freeman"
],
[
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year",
"nominated_for",
"The_Quiet_American"
],
[
"Mark_Mothersbaugh",
"award_nominee",
"George_S._Clinton"
],
[
"Morgan_Freeman",
"acted_in",
"The_Love_Guru"
],
[
"Morgan_Freeman",
"location",
"Gary"
],
[
"The_Love_Guru",
"film_music",
"George_S._Clinton"
],
[
"The_Quiet_American",
"award_honor_award",
"London_Film_Critics_Circle_Award_for_Actor_of_the_Year"
],
[
"The_Quiet_American",
"cinematography",
"Christopher_Doyle"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9565, Adult_contemporary_music
9517, Baylor_University
702, Burt_Bacharach
8938, Carole_Bayer_Sager
3268, Carole_King
12697, Drew_Goddard
2573, Edward_Kitsis
389, Grammy_Award_for_Best_Country_Performance_by_a_Duo_or_Group_with_Vocal
12456, Grammy_Award_for_Best_Male_Country_Vocal_Performance
7909, Grammy_Award_for_Best_Traditional_Pop_Vocal_Album
2275, James_Ingram
4765, Kenny_Rogers
7390, Philadelphia_Phillies
9725, Pianist-GB
9886, U.S.A._for_Africa
11425, University_of_Colorado_Boulder
7034, Willie_Nelson
src, edge_attr, dst
9565, artists, 3268
9565, artists, 2275
9517, campuses, 9517
9517, educational_institution, 9517
9517, student, 7034
702, award_nominee, 8938
702, award_nominee, 4765
702, award_winner, 8938
702, participant, 8938
702, profession, 9725
702, spouse, 8938
8938, award_nominee, 702
8938, award_nominee, 3268
8938, award_nominee, 2275
8938, award_nominee, 4765
8938, award_winner, 702
8938, spouse, 702
3268, award, 7909
3268, profession, 9725
12697, award_nominee, 2573
12697, award_winner, 2573
2573, award_nominee, 12697
389, award_winner, 7034
12456, award_winner, 4765
12456, award_winner, 7034
2275, award_nominee, 8938
2275, group, 9886
4765, award, 389
4765, award, 12456
4765, award_nominee, 702
4765, award_nominee, 8938
4765, group, 9886
7390, school, 9517
7390, school, 11425
11425, student, 12697
7034, award, 12456
7034, award, 7909
7034, group, 9886
Question: In what context are Baylor_University, Carole_Bayer_Sager, and Edward_Kitsis connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Baylor_University",
"Carole_Bayer_Sager",
"Edward_Kitsis"
],
"valid_edges": [
[
"Adult_contemporary_music",
"artists",
"Carole_King"
],
[
"Adult_contemporary_music",
"artists",
"James_Ingram"
],
[
"Baylor_University",
"campuses",
"Baylor_University"
],
[
"Baylor_University",
"educational_institution",
"Baylor_University"
],
[
"Baylor_University",
"student",
"Willie_Nelson"
],
[
"Burt_Bacharach",
"award_nominee",
"Carole_Bayer_Sager"
],
[
"Burt_Bacharach",
"award_nominee",
"Kenny_Rogers"
],
[
"Burt_Bacharach",
"award_winner",
"Carole_Bayer_Sager"
],
[
"Burt_Bacharach",
"participant",
"Carole_Bayer_Sager"
],
[
"Burt_Bacharach",
"profession",
"Pianist-GB"
],
[
"Burt_Bacharach",
"spouse",
"Carole_Bayer_Sager"
],
[
"Carole_Bayer_Sager",
"award_nominee",
"Burt_Bacharach"
],
[
"Carole_Bayer_Sager",
"award_nominee",
"Carole_King"
],
[
"Carole_Bayer_Sager",
"award_nominee",
"James_Ingram"
],
[
"Carole_Bayer_Sager",
"award_nominee",
"Kenny_Rogers"
],
[
"Carole_Bayer_Sager",
"award_winner",
"Burt_Bacharach"
],
[
"Carole_Bayer_Sager",
"spouse",
"Burt_Bacharach"
],
[
"Carole_King",
"award",
"Grammy_Award_for_Best_Traditional_Pop_Vocal_Album"
],
[
"Carole_King",
"profession",
"Pianist-GB"
],
[
"Drew_Goddard",
"award_nominee",
"Edward_Kitsis"
],
[
"Drew_Goddard",
"award_winner",
"Edward_Kitsis"
],
[
"Edward_Kitsis",
"award_nominee",
"Drew_Goddard"
],
[
"Grammy_Award_for_Best_Country_Performance_by_a_Duo_or_Group_with_Vocal",
"award_winner",
"Willie_Nelson"
],
[
"Grammy_Award_for_Best_Male_Country_Vocal_Performance",
"award_winner",
"Kenny_Rogers"
],
[
"Grammy_Award_for_Best_Male_Country_Vocal_Performance",
"award_winner",
"Willie_Nelson"
],
[
"James_Ingram",
"award_nominee",
"Carole_Bayer_Sager"
],
[
"James_Ingram",
"group",
"U.S.A._for_Africa"
],
[
"Kenny_Rogers",
"award",
"Grammy_Award_for_Best_Country_Performance_by_a_Duo_or_Group_with_Vocal"
],
[
"Kenny_Rogers",
"award",
"Grammy_Award_for_Best_Male_Country_Vocal_Performance"
],
[
"Kenny_Rogers",
"award_nominee",
"Burt_Bacharach"
],
[
"Kenny_Rogers",
"award_nominee",
"Carole_Bayer_Sager"
],
[
"Kenny_Rogers",
"group",
"U.S.A._for_Africa"
],
[
"Philadelphia_Phillies",
"school",
"Baylor_University"
],
[
"Philadelphia_Phillies",
"school",
"University_of_Colorado_Boulder"
],
[
"University_of_Colorado_Boulder",
"student",
"Drew_Goddard"
],
[
"Willie_Nelson",
"award",
"Grammy_Award_for_Best_Male_Country_Vocal_Performance"
],
[
"Willie_Nelson",
"award",
"Grammy_Award_for_Best_Traditional_Pop_Vocal_Album"
],
[
"Willie_Nelson",
"group",
"U.S.A._for_Africa"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
8885, Argentina_national_football_team
10990, Bath
14179, Boca_Juniors
8320, Brasenose_College,_Oxford
7879, FC_Barcelona_B
7857, Jane_Austen
13799, Lady_Margaret_Hall,_Oxford
101, Lionel_Messi
1299, Oxford
13922, Oxfordshire
9011, Wadham_College,_Oxford
7080, Yellow
src, edge_attr, dst
8885, current_club, 14179
14179, colors, 7080
8320, citytown, 1299
8320, colors, 7080
8320, state_province_region, 13922
7857, location, 10990
7857, location, 1299
13799, citytown, 1299
13799, colors, 7080
13799, educational_institution, 13799
13799, state_province_region, 13922
101, team, 8885
101, team, 7879
1299, contains, 13799
13922, contains, 13799
9011, campuses, 9011
9011, citytown, 1299
9011, colors, 7080
9011, educational_institution, 9011
Question: In what context are Bath, FC_Barcelona_B, and Yellow connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bath",
"FC_Barcelona_B",
"Yellow"
],
"valid_edges": [
[
"Argentina_national_football_team",
"current_club",
"Boca_Juniors"
],
[
"Boca_Juniors",
"colors",
"Yellow"
],
[
"Brasenose_College,_Oxford",
"citytown",
"Oxford"
],
[
"Brasenose_College,_Oxford",
"colors",
"Yellow"
],
[
"Brasenose_College,_Oxford",
"state_province_region",
"Oxfordshire"
],
[
"Jane_Austen",
"location",
"Bath"
],
[
"Jane_Austen",
"location",
"Oxford"
],
[
"Lady_Margaret_Hall,_Oxford",
"citytown",
"Oxford"
],
[
"Lady_Margaret_Hall,_Oxford",
"colors",
"Yellow"
],
[
"Lady_Margaret_Hall,_Oxford",
"educational_institution",
"Lady_Margaret_Hall,_Oxford"
],
[
"Lady_Margaret_Hall,_Oxford",
"state_province_region",
"Oxfordshire"
],
[
"Lionel_Messi",
"team",
"Argentina_national_football_team"
],
[
"Lionel_Messi",
"team",
"FC_Barcelona_B"
],
[
"Oxford",
"contains",
"Lady_Margaret_Hall,_Oxford"
],
[
"Oxfordshire",
"contains",
"Lady_Margaret_Hall,_Oxford"
],
[
"Wadham_College,_Oxford",
"campuses",
"Wadham_College,_Oxford"
],
[
"Wadham_College,_Oxford",
"citytown",
"Oxford"
],
[
"Wadham_College,_Oxford",
"colors",
"Yellow"
],
[
"Wadham_College,_Oxford",
"educational_institution",
"Wadham_College,_Oxford"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12844, Bob_Clampett
4745, Chaplin
10359, Charles_Darwin
5436, Charlie_Chaplin
3139, Chuck_Jones
7305, Copley_Medal
13169, Heart_failure
5704, Niels_Henrik_David_Bohr
402, Notting_Hill
9323, Scientist-GB
10878, Stuart_Craig
src, edge_attr, dst
12844, influenced_by, 5436
12844, peers, 3139
4745, film_production_design_by, 10878
4745, story_by, 5436
10359, profession, 9323
7305, award_winner, 10359
7305, award_winner, 5704
13169, people, 10359
13169, people, 3139
13169, people, 5704
5704, profession, 9323
402, film_production_design_by, 10878
10878, nominated_for, 4745
Question: How are Bob_Clampett, Copley_Medal, and Notting_Hill related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bob_Clampett",
"Copley_Medal",
"Notting_Hill"
],
"valid_edges": [
[
"Bob_Clampett",
"influenced_by",
"Charlie_Chaplin"
],
[
"Bob_Clampett",
"peers",
"Chuck_Jones"
],
[
"Chaplin",
"film_production_design_by",
"Stuart_Craig"
],
[
"Chaplin",
"story_by",
"Charlie_Chaplin"
],
[
"Charles_Darwin",
"profession",
"Scientist-GB"
],
[
"Copley_Medal",
"award_winner",
"Charles_Darwin"
],
[
"Copley_Medal",
"award_winner",
"Niels_Henrik_David_Bohr"
],
[
"Heart_failure",
"people",
"Charles_Darwin"
],
[
"Heart_failure",
"people",
"Chuck_Jones"
],
[
"Heart_failure",
"people",
"Niels_Henrik_David_Bohr"
],
[
"Niels_Henrik_David_Bohr",
"profession",
"Scientist-GB"
],
[
"Notting_Hill",
"film_production_design_by",
"Stuart_Craig"
],
[
"Stuart_Craig",
"nominated_for",
"Chaplin"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12862, Alvin_and_the_Chipmunks:_The_Squeakquel
2724, Anthony_B._Richmond
1459, Arnold_Schoenberg
10938, Basil_Poledouris
9571, Bonnie_and_Clyde
2089, Brian_Grazer
11563, Burnett_Guffey
8160, Caleb_Deschanel
6920, Cinematographer-GB
797, Conductor
3237, Conrad_L._Hall
12459, Daryl_Hannah
13644, David_Newman
8684, Dean_Cundey
8777, Dean_Semler
204, Ernest_Haller
8343, Gene_Hackman
11493, George_Lucas
9006, Gold
10888, Gone_with_the_Wind
1547, Image_Entertainment
3602, Imagine_Entertainment
8065, Jack_Warner
5428, James_Horner
5823, Jerry_Goldsmith
11983, John_Bailey
7060, Lee_Garmes
9860, Lyle_R._Wheeler
8399, MTV_Movie_Award_for_Best_Comedic_Performance
4296, Max_Steiner
7400, Mildred_Pierce
7621, National_Film_Registry
12471, Nutty_Professor_II:_The_Klumps
6355, Richard_A._Baker
4088, Richard_Edlund
2601, Robert_Elswit
11165, Romantic_comedy
251, Slapstick
12998, Steve_Oedekerk
4409, Swansea_City_A.F.C.
7174, The_Flintstones
10795, The_Nutty_Professor
9659, Thomas_Newman
6128, University_of_Southern_California
2117, Warren_Feeney
5079, William_A._Fraker
src, edge_attr, dst
12862, cinematography, 2724
12862, film_music, 13644
2724, profession, 6920
1459, company, 6128
1459, profession, 797
10938, profession, 797
9571, award_winner, 11563
9571, award_winner, 8343
9571, cinematography, 11563
9571, list, 7621
11563, profession, 6920
8160, profession, 6920
3237, profession, 6920
12459, profession, 6920
13644, nominated_for, 9571
13644, profession, 797
13644, sibling, 9659
8684, profession, 6920
8777, profession, 6920
204, nominated_for, 10888
204, nominated_for, 7400
204, profession, 6920
8343, acted_in, 9571
8343, nominated_for, 9571
11493, profession, 6920
10888, award_winner, 204
10888, award_winner, 9860
10888, cinematography, 204
10888, cinematography, 7060
10888, film_art_direction_by, 9860
10888, film_music, 4296
10888, list, 7621
5428, profession, 797
5823, profession, 797
11983, profession, 6920
7060, profession, 6920
9860, nominated_for, 10888
8399, nominated_for, 12471
8399, nominated_for, 10795
4296, profession, 797
7400, cinematography, 204
7400, executive_produced_by, 8065
7400, film_music, 4296
7400, list, 7621
12471, cinematography, 8777
12471, crewmember, 6355
12471, film_music, 13644
12471, genre, 11165
12471, genre, 251
12471, prequel, 10795
12471, produced_by, 2089
12471, production_companies, 1547
12471, production_companies, 3602
12471, story_by, 12998
6355, nominated_for, 10795
4088, profession, 6920
2601, profession, 6920
251, titles, 10795
12998, film, 12471
4409, colors, 9006
7174, cinematography, 8684
7174, film_music, 13644
10795, award_winner, 6355
10795, film_music, 13644
10795, genre, 11165
10795, produced_by, 2089
10795, production_companies, 1547
10795, production_companies, 3602
10795, written_by, 12998
9659, profession, 797
9659, sibling, 13644
6128, campuses, 6128
6128, colors, 9006
6128, educational_institution, 6128
6128, split_to, 6128
6128, student, 10938
6128, student, 2089
6128, student, 8160
6128, student, 3237
6128, student, 12459
6128, student, 13644
6128, student, 8343
6128, student, 11493
6128, student, 8065
6128, student, 5428
6128, student, 5823
6128, student, 11983
6128, student, 9860
6128, student, 4088
6128, student, 2601
6128, student, 9659
6128, student, 5079
2117, team, 4409
5079, profession, 6920
Question: In what context are David_Newman, Ernest_Haller, and Warren_Feeney connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"David_Newman",
"Ernest_Haller",
"Warren_Feeney"
],
"valid_edges": [
[
"Alvin_and_the_Chipmunks:_The_Squeakquel",
"cinematography",
"Anthony_B._Richmond"
],
[
"Alvin_and_the_Chipmunks:_The_Squeakquel",
"film_music",
"David_Newman"
],
[
"Anthony_B._Richmond",
"profession",
"Cinematographer-GB"
],
[
"Arnold_Schoenberg",
"company",
"University_of_Southern_California"
],
[
"Arnold_Schoenberg",
"profession",
"Conductor"
],
[
"Basil_Poledouris",
"profession",
"Conductor"
],
[
"Bonnie_and_Clyde",
"award_winner",
"Burnett_Guffey"
],
[
"Bonnie_and_Clyde",
"award_winner",
"Gene_Hackman"
],
[
"Bonnie_and_Clyde",
"cinematography",
"Burnett_Guffey"
],
[
"Bonnie_and_Clyde",
"list",
"National_Film_Registry"
],
[
"Burnett_Guffey",
"profession",
"Cinematographer-GB"
],
[
"Caleb_Deschanel",
"profession",
"Cinematographer-GB"
],
[
"Conrad_L._Hall",
"profession",
"Cinematographer-GB"
],
[
"Daryl_Hannah",
"profession",
"Cinematographer-GB"
],
[
"David_Newman",
"nominated_for",
"Bonnie_and_Clyde"
],
[
"David_Newman",
"profession",
"Conductor"
],
[
"David_Newman",
"sibling",
"Thomas_Newman"
],
[
"Dean_Cundey",
"profession",
"Cinematographer-GB"
],
[
"Dean_Semler",
"profession",
"Cinematographer-GB"
],
[
"Ernest_Haller",
"nominated_for",
"Gone_with_the_Wind"
],
[
"Ernest_Haller",
"nominated_for",
"Mildred_Pierce"
],
[
"Ernest_Haller",
"profession",
"Cinematographer-GB"
],
[
"Gene_Hackman",
"acted_in",
"Bonnie_and_Clyde"
],
[
"Gene_Hackman",
"nominated_for",
"Bonnie_and_Clyde"
],
[
"George_Lucas",
"profession",
"Cinematographer-GB"
],
[
"Gone_with_the_Wind",
"award_winner",
"Ernest_Haller"
],
[
"Gone_with_the_Wind",
"award_winner",
"Lyle_R._Wheeler"
],
[
"Gone_with_the_Wind",
"cinematography",
"Ernest_Haller"
],
[
"Gone_with_the_Wind",
"cinematography",
"Lee_Garmes"
],
[
"Gone_with_the_Wind",
"film_art_direction_by",
"Lyle_R._Wheeler"
],
[
"Gone_with_the_Wind",
"film_music",
"Max_Steiner"
],
[
"Gone_with_the_Wind",
"list",
"National_Film_Registry"
],
[
"James_Horner",
"profession",
"Conductor"
],
[
"Jerry_Goldsmith",
"profession",
"Conductor"
],
[
"John_Bailey",
"profession",
"Cinematographer-GB"
],
[
"Lee_Garmes",
"profession",
"Cinematographer-GB"
],
[
"Lyle_R._Wheeler",
"nominated_for",
"Gone_with_the_Wind"
],
[
"MTV_Movie_Award_for_Best_Comedic_Performance",
"nominated_for",
"Nutty_Professor_II:_The_Klumps"
],
[
"MTV_Movie_Award_for_Best_Comedic_Performance",
"nominated_for",
"The_Nutty_Professor"
],
[
"Max_Steiner",
"profession",
"Conductor"
],
[
"Mildred_Pierce",
"cinematography",
"Ernest_Haller"
],
[
"Mildred_Pierce",
"executive_produced_by",
"Jack_Warner"
],
[
"Mildred_Pierce",
"film_music",
"Max_Steiner"
],
[
"Mildred_Pierce",
"list",
"National_Film_Registry"
],
[
"Nutty_Professor_II:_The_Klumps",
"cinematography",
"Dean_Semler"
],
[
"Nutty_Professor_II:_The_Klumps",
"crewmember",
"Richard_A._Baker"
],
[
"Nutty_Professor_II:_The_Klumps",
"film_music",
"David_Newman"
],
[
"Nutty_Professor_II:_The_Klumps",
"genre",
"Romantic_comedy"
],
[
"Nutty_Professor_II:_The_Klumps",
"genre",
"Slapstick"
],
[
"Nutty_Professor_II:_The_Klumps",
"prequel",
"The_Nutty_Professor"
],
[
"Nutty_Professor_II:_The_Klumps",
"produced_by",
"Brian_Grazer"
],
[
"Nutty_Professor_II:_The_Klumps",
"production_companies",
"Image_Entertainment"
],
[
"Nutty_Professor_II:_The_Klumps",
"production_companies",
"Imagine_Entertainment"
],
[
"Nutty_Professor_II:_The_Klumps",
"story_by",
"Steve_Oedekerk"
],
[
"Richard_A._Baker",
"nominated_for",
"The_Nutty_Professor"
],
[
"Richard_Edlund",
"profession",
"Cinematographer-GB"
],
[
"Robert_Elswit",
"profession",
"Cinematographer-GB"
],
[
"Slapstick",
"titles",
"The_Nutty_Professor"
],
[
"Steve_Oedekerk",
"film",
"Nutty_Professor_II:_The_Klumps"
],
[
"Swansea_City_A.F.C.",
"colors",
"Gold"
],
[
"The_Flintstones",
"cinematography",
"Dean_Cundey"
],
[
"The_Flintstones",
"film_music",
"David_Newman"
],
[
"The_Nutty_Professor",
"award_winner",
"Richard_A._Baker"
],
[
"The_Nutty_Professor",
"film_music",
"David_Newman"
],
[
"The_Nutty_Professor",
"genre",
"Romantic_comedy"
],
[
"The_Nutty_Professor",
"produced_by",
"Brian_Grazer"
],
[
"The_Nutty_Professor",
"production_companies",
"Image_Entertainment"
],
[
"The_Nutty_Professor",
"production_companies",
"Imagine_Entertainment"
],
[
"The_Nutty_Professor",
"written_by",
"Steve_Oedekerk"
],
[
"Thomas_Newman",
"profession",
"Conductor"
],
[
"Thomas_Newman",
"sibling",
"David_Newman"
],
[
"University_of_Southern_California",
"campuses",
"University_of_Southern_California"
],
[
"University_of_Southern_California",
"colors",
"Gold"
],
[
"University_of_Southern_California",
"educational_institution",
"University_of_Southern_California"
],
[
"University_of_Southern_California",
"split_to",
"University_of_Southern_California"
],
[
"University_of_Southern_California",
"student",
"Basil_Poledouris"
],
[
"University_of_Southern_California",
"student",
"Brian_Grazer"
],
[
"University_of_Southern_California",
"student",
"Caleb_Deschanel"
],
[
"University_of_Southern_California",
"student",
"Conrad_L._Hall"
],
[
"University_of_Southern_California",
"student",
"Daryl_Hannah"
],
[
"University_of_Southern_California",
"student",
"David_Newman"
],
[
"University_of_Southern_California",
"student",
"Gene_Hackman"
],
[
"University_of_Southern_California",
"student",
"George_Lucas"
],
[
"University_of_Southern_California",
"student",
"Jack_Warner"
],
[
"University_of_Southern_California",
"student",
"James_Horner"
],
[
"University_of_Southern_California",
"student",
"Jerry_Goldsmith"
],
[
"University_of_Southern_California",
"student",
"John_Bailey"
],
[
"University_of_Southern_California",
"student",
"Lyle_R._Wheeler"
],
[
"University_of_Southern_California",
"student",
"Richard_Edlund"
],
[
"University_of_Southern_California",
"student",
"Robert_Elswit"
],
[
"University_of_Southern_California",
"student",
"Thomas_Newman"
],
[
"University_of_Southern_California",
"student",
"William_A._Fraker"
],
[
"Warren_Feeney",
"team",
"Swansea_City_A.F.C."
],
[
"William_A._Fraker",
"profession",
"Cinematographer-GB"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
10556, 2000_NCAA_Men's_Division_I_Basketball_Tournament
3688, Adam_Ant
2945, Alternative_rock
6214, Austin
8998, Bono
12944, Central_Time_Zone
5379, Christianity
11918, Demi_Lovato
4801, Depeche_Mode
3803, Dixie_Chicks
9888, Duran_Duran
7445, Emily_Osment
8063, Everything_but_the_Girl
10283, Gustavo_Cerati
4369, INXS
12197, Indie_pop
4473, Indie_rock
13834, Luci_Christian
5516, Mike_Watt
209, Morrissey
9979, New_Order
4599, Nick_Cave_and_the_Bad_Seeds
10091, Oingo_Boingo
8511, Pixies
9951, Post-punk
6984, Robert_Smith
12581, Simple_Minds
12349, Sonic_Youth
3961, Texas
10159, The_B-52's
12339, The_Cars
3707, The_Fall
12390, The_Flaming_Lips
7600, The_Prodigy
13370, U2
src, edge_attr, dst
10556, locations, 6214
2945, artists, 3688
2945, artists, 8998
2945, artists, 4801
2945, artists, 3803
2945, artists, 9888
2945, artists, 7445
2945, artists, 8063
2945, artists, 10283
2945, artists, 4369
2945, artists, 5516
2945, artists, 209
2945, artists, 9979
2945, artists, 4599
2945, artists, 10091
2945, artists, 8511
2945, artists, 6984
2945, artists, 12581
2945, artists, 12349
2945, artists, 10159
2945, artists, 12339
2945, artists, 3707
2945, artists, 12390
2945, artists, 7600
2945, artists, 13370
2945, parent_genre, 9951
6214, administrative_division, 3961
6214, place, 6214
6214, state, 3961
6214, time_zones, 12944
11918, location, 3961
11918, religion, 5379
3803, artist_origin, 6214
7445, religion, 5379
12197, parent_genre, 2945
12197, parent_genre, 9951
4473, parent_genre, 2945
4473, parent_genre, 9951
13834, location, 3961
13834, religion, 5379
9951, artists, 3688
9951, artists, 8998
9951, artists, 4801
9951, artists, 9888
9951, artists, 8063
9951, artists, 10283
9951, artists, 4369
9951, artists, 5516
9951, artists, 209
9951, artists, 9979
9951, artists, 4599
9951, artists, 10091
9951, artists, 8511
9951, artists, 6984
9951, artists, 12581
9951, artists, 12349
9951, artists, 10159
9951, artists, 12339
9951, artists, 3707
9951, artists, 12390
9951, artists, 7600
9951, artists, 13370
3961, capital, 6214
3961, religion, 5379
3961, time_zones, 12944
Question: For what reason are 2000_NCAA_Men's_Division_I_Basketball_Tournament, Luci_Christian, and The_Fall associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"2000_NCAA_Men's_Division_I_Basketball_Tournament",
"Luci_Christian",
"The_Fall"
],
"valid_edges": [
[
"2000_NCAA_Men's_Division_I_Basketball_Tournament",
"locations",
"Austin"
],
[
"Alternative_rock",
"artists",
"Adam_Ant"
],
[
"Alternative_rock",
"artists",
"Bono"
],
[
"Alternative_rock",
"artists",
"Depeche_Mode"
],
[
"Alternative_rock",
"artists",
"Dixie_Chicks"
],
[
"Alternative_rock",
"artists",
"Duran_Duran"
],
[
"Alternative_rock",
"artists",
"Emily_Osment"
],
[
"Alternative_rock",
"artists",
"Everything_but_the_Girl"
],
[
"Alternative_rock",
"artists",
"Gustavo_Cerati"
],
[
"Alternative_rock",
"artists",
"INXS"
],
[
"Alternative_rock",
"artists",
"Mike_Watt"
],
[
"Alternative_rock",
"artists",
"Morrissey"
],
[
"Alternative_rock",
"artists",
"New_Order"
],
[
"Alternative_rock",
"artists",
"Nick_Cave_and_the_Bad_Seeds"
],
[
"Alternative_rock",
"artists",
"Oingo_Boingo"
],
[
"Alternative_rock",
"artists",
"Pixies"
],
[
"Alternative_rock",
"artists",
"Robert_Smith"
],
[
"Alternative_rock",
"artists",
"Simple_Minds"
],
[
"Alternative_rock",
"artists",
"Sonic_Youth"
],
[
"Alternative_rock",
"artists",
"The_B-52's"
],
[
"Alternative_rock",
"artists",
"The_Cars"
],
[
"Alternative_rock",
"artists",
"The_Fall"
],
[
"Alternative_rock",
"artists",
"The_Flaming_Lips"
],
[
"Alternative_rock",
"artists",
"The_Prodigy"
],
[
"Alternative_rock",
"artists",
"U2"
],
[
"Alternative_rock",
"parent_genre",
"Post-punk"
],
[
"Austin",
"administrative_division",
"Texas"
],
[
"Austin",
"place",
"Austin"
],
[
"Austin",
"state",
"Texas"
],
[
"Austin",
"time_zones",
"Central_Time_Zone"
],
[
"Demi_Lovato",
"location",
"Texas"
],
[
"Demi_Lovato",
"religion",
"Christianity"
],
[
"Dixie_Chicks",
"artist_origin",
"Austin"
],
[
"Emily_Osment",
"religion",
"Christianity"
],
[
"Indie_pop",
"parent_genre",
"Alternative_rock"
],
[
"Indie_pop",
"parent_genre",
"Post-punk"
],
[
"Indie_rock",
"parent_genre",
"Alternative_rock"
],
[
"Indie_rock",
"parent_genre",
"Post-punk"
],
[
"Luci_Christian",
"location",
"Texas"
],
[
"Luci_Christian",
"religion",
"Christianity"
],
[
"Post-punk",
"artists",
"Adam_Ant"
],
[
"Post-punk",
"artists",
"Bono"
],
[
"Post-punk",
"artists",
"Depeche_Mode"
],
[
"Post-punk",
"artists",
"Duran_Duran"
],
[
"Post-punk",
"artists",
"Everything_but_the_Girl"
],
[
"Post-punk",
"artists",
"Gustavo_Cerati"
],
[
"Post-punk",
"artists",
"INXS"
],
[
"Post-punk",
"artists",
"Mike_Watt"
],
[
"Post-punk",
"artists",
"Morrissey"
],
[
"Post-punk",
"artists",
"New_Order"
],
[
"Post-punk",
"artists",
"Nick_Cave_and_the_Bad_Seeds"
],
[
"Post-punk",
"artists",
"Oingo_Boingo"
],
[
"Post-punk",
"artists",
"Pixies"
],
[
"Post-punk",
"artists",
"Robert_Smith"
],
[
"Post-punk",
"artists",
"Simple_Minds"
],
[
"Post-punk",
"artists",
"Sonic_Youth"
],
[
"Post-punk",
"artists",
"The_B-52's"
],
[
"Post-punk",
"artists",
"The_Cars"
],
[
"Post-punk",
"artists",
"The_Fall"
],
[
"Post-punk",
"artists",
"The_Flaming_Lips"
],
[
"Post-punk",
"artists",
"The_Prodigy"
],
[
"Post-punk",
"artists",
"U2"
],
[
"Texas",
"capital",
"Austin"
],
[
"Texas",
"religion",
"Christianity"
],
[
"Texas",
"time_zones",
"Central_Time_Zone"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
42, Canadian_dollar
1535, Chairman
2462, Mills_College
13085, National_Theatre_School_of_Canada
4100, New_York_Stories
93, Norwich_City_F.C.
12298, Sofia_Coppola
8288, University_of_Rochester
1613, University_of_Saskatchewan
7080, Yellow
src, edge_attr, dst
1535, company, 8288
1535, organization, 13085
2462, colors, 7080
2462, student, 12298
13085, campuses, 13085
13085, currency, 42
13085, educational_institution, 13085
13085, international_tuition_currency, 42
4100, written_by, 12298
93, colors, 7080
8288, colors, 7080
1613, colors, 7080
1613, currency, 42
Question: For what reason are National_Theatre_School_of_Canada, New_York_Stories, and Norwich_City_F.C. associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"National_Theatre_School_of_Canada",
"New_York_Stories",
"Norwich_City_F.C."
],
"valid_edges": [
[
"Chairman",
"company",
"University_of_Rochester"
],
[
"Chairman",
"organization",
"National_Theatre_School_of_Canada"
],
[
"Mills_College",
"colors",
"Yellow"
],
[
"Mills_College",
"student",
"Sofia_Coppola"
],
[
"National_Theatre_School_of_Canada",
"campuses",
"National_Theatre_School_of_Canada"
],
[
"National_Theatre_School_of_Canada",
"currency",
"Canadian_dollar"
],
[
"National_Theatre_School_of_Canada",
"educational_institution",
"National_Theatre_School_of_Canada"
],
[
"National_Theatre_School_of_Canada",
"international_tuition_currency",
"Canadian_dollar"
],
[
"New_York_Stories",
"written_by",
"Sofia_Coppola"
],
[
"Norwich_City_F.C.",
"colors",
"Yellow"
],
[
"University_of_Rochester",
"colors",
"Yellow"
],
[
"University_of_Saskatchewan",
"colors",
"Yellow"
],
[
"University_of_Saskatchewan",
"currency",
"Canadian_dollar"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
9703, (500)_Days_of_Summer
11774, 35_mm_film
7697, A_History_of_Violence
9261, A_Separation
11203, Acting
8721, Albert_Nobbs
2027, Alec_Baldwin
2112, An_Education
1461, Antichrist
13923, Bad_Education
6077, Batman_Begins
9562, Battlestar_Galactica-GB
10495, Beasts_of_the_Southern_Wild
4666, Beginners
13653, Black_Swan
7767, Blue
4978, Broadcast_Film_Critics_Association_Award_for_Best_Film
4649, Brothers
10297, Callum_Keith_Rennie
6273, Cars_2
8535, Cold_Mountain
1796, Colombia
8756, Cosmopolis
4288, Cowboys_&_Aliens
7753, Crash
12407, David_Cronenberg
6360, Dead_Ringers
594, Dial_M_for_Murder
1106, Django_Unchained
12826, Don't_Be_Afraid_of_the_Dark
13516, Don't_Say_a_Word
10458, Donald_Sutherland
5645, E1_Entertainment
2964, Fair_Game
7388, Film
1036, Final_Destination_5
2289, Frankenstein
241, Green_Lantern
9550, Guy_Pearce
13849, Hairspray
4359, Home_Alone
10755, Ice_Age
5106, Incheon_United_FC
6506, Independent_Spirit_Award_for_Best_Director
10072, Independent_Spirit_Award_for_Best_Supporting_Female
883, Inglourious_Basterds
5239, Inland_Empire
11303, Insidious
13696, Iron_Man
12099, Iron_Man_2
11670, Jorja_Fox
2685, Juno
8755, Kaboom
5661, Kung_Fu_Panda_2
2712, Kuwait
14021, Lantana
10345, Las_Vegas
1934, Lee_Strasberg_Theatre_and_Film_Institute
1602, Lorne_Michaels
9863, Lost_Highway
8745, Marley
7487, Marley_&_Me
1706, Mean_Girls
11146, Melancholia
6583, Memento
76, Mr._Nobody
5768, Murder_by_Decree
13680, PS,_I_Love_You
10744, Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl
246, Precious:_Based_on_the_Novel_Push_by_Sapphire
10280, Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie
2673, Psycho
3978, Psychological_thriller
269, Reading_F.C.
2068, Red_State
11364, Requiem_for_a_Dream
6014, Ryerson_University
3622, Saw
4179, Saw_III
9572, Saw_IV
293, Scottish_Canadian
12136, Seol_Ki-Hyeon
7577, Shrek
8754, Shutter_Island
3506, Signs
80, Slovakia
6610, Summit_Entertainment
9738, Sunset_Boulevard
11026, Super_8
1596, Taken
12627, The_Avengers
13072, The_Beaver
12394, The_Butterfly_Effect
11795, The_Cabin_in_the_Woods
12629, The_Clearing
9256, The_Dark_Knight
11514, The_Devil's_Double
7644, The_Expendables
2003, The_Ghost_Writer
723, The_Hunger_Games
7675, The_Hurt_Locker
13624, The_Sixth_Sense
6076, The_Talented_Mr._Ripley
7513, The_Three_Musketeers
12168, The_Whistleblower
5859, There_Will_Be_Blood
5948, Toronto
5464, Toronto_International_Film_Festival
1693, Transformers
8937, Transformers:_Dark_of_the_Moon
10397, Twilight
5506, University_of_Toronto
11139, Uruguay
13975, X-Men_Origins:_Wolverine
src, edge_attr, dst
9703, film_format, 11774
9703, film_release_region, 5948
9703, film_release_region, 11139
7697, genre, 3978
9261, film_format, 11774
9261, film_release_region, 2712
11203, student, 2027
8721, film_regional_debut_venue, 5464
8721, film_release_region, 1796
8721, film_release_region, 2712
2027, award_winner, 1602
2112, film_format, 11774
1461, film_format, 11774
13923, film_format, 11774
13923, film_regional_debut_venue, 5464
6077, film_release_region, 1796
6077, film_release_region, 2712
6077, film_release_region, 80
6077, film_release_region, 11139
9562, actor, 10297
9562, genre, 3978
10495, film_release_region, 2712
4666, film_regional_debut_venue, 5464
13653, award_honor_award, 6506
13653, film_release_region, 5948
13653, film_release_region, 11139
13653, genre, 3978
4978, nominated_for, 2112
4978, nominated_for, 10495
4978, nominated_for, 13653
4978, nominated_for, 8535
4978, nominated_for, 7753
4978, nominated_for, 1106
4978, nominated_for, 883
4978, nominated_for, 2685
4978, nominated_for, 6583
4978, nominated_for, 246
4978, nominated_for, 7577
4978, nominated_for, 9256
4978, nominated_for, 13624
4978, nominated_for, 6076
4978, nominated_for, 5859
4649, film_format, 11774
4649, genre, 3978
10297, acted_in, 6583
10297, acted_in, 12394
6273, film_release_region, 1796
6273, film_release_region, 2712
8756, film_release_region, 80
4288, film_release_region, 1796
4288, film_release_region, 2712
4288, film_release_region, 11139
7753, award_winner, 12407
7753, featured_film_locations, 5948
7753, genre, 3978
7753, produced_by, 12407
7753, written_by, 12407
12407, film, 7697
12407, film, 8756
12407, film, 7753
12407, film, 6360
12407, location, 5948
12407, nominated_for, 7697
12407, nominated_for, 7753
12407, nominated_for, 6360
12407, place_of_birth, 5948
6360, award_winner, 12407
6360, featured_film_locations, 5948
6360, genre, 3978
6360, produced_by, 12407
6360, written_by, 12407
594, film_regional_debut_venue, 5464
1106, film_release_region, 2712
12826, film_format, 11774
13516, featured_film_locations, 5948
10458, acted_in, 8535
10458, acted_in, 5768
10458, acted_in, 723
10458, award, 10280
5645, citytown, 5948
5645, film, 8721
5645, film, 10495
5645, film, 8756
5645, film, 2964
5645, film, 6583
5645, film, 2068
5645, film, 13072
5645, film, 2003
5645, film, 7513
5645, industry, 7388
1036, film_release_region, 1796
1036, film_release_region, 2712
2289, film_format, 11774
2289, film_release_region, 11139
241, film_release_region, 1796
241, film_release_region, 2712
241, film_release_region, 11139
9550, acted_in, 12826
9550, acted_in, 6583
9550, acted_in, 7675
9550, award, 10280
9550, nominated_for, 7675
13849, featured_film_locations, 5948
13849, film_release_region, 1796
13849, film_release_region, 2712
13849, film_release_region, 80
4359, film_release_region, 1796
4359, film_release_region, 11139
10755, film_release_region, 1796
10755, film_release_region, 2712
6506, nominated_for, 10495
6506, nominated_for, 4666
6506, nominated_for, 2685
6506, nominated_for, 6583
6506, nominated_for, 246
6506, nominated_for, 11364
10072, disciplines_or_subjects, 11203
10072, nominated_for, 8721
10072, nominated_for, 6583
10072, nominated_for, 246
10072, nominated_for, 11364
883, film_release_region, 1796
883, film_release_region, 2712
883, film_release_region, 80
883, film_release_region, 11139
5239, film_format, 11774
5239, genre, 3978
11303, film_regional_debut_venue, 5464
13696, film_release_region, 1796
13696, film_release_region, 2712
13696, film_release_region, 80
13696, film_release_region, 11139
12099, film_format, 11774
12099, film_release_region, 1796
12099, film_release_region, 2712
12099, film_release_region, 80
12099, film_release_region, 11139
11670, acted_in, 6583
8755, film_regional_debut_venue, 5948
8755, film_regional_debut_venue, 5464
8755, genre, 3978
5661, film_release_region, 1796
5661, film_release_region, 2712
5661, film_release_region, 11139
14021, film_format, 11774
14021, genre, 3978
10345, place, 10345
1934, major_field_of_study, 11203
1934, student, 11670
1602, award_nominee, 2027
1602, location, 5948
9863, film_release_region, 11139
9863, genre, 3978
8745, film_format, 11774
8745, film_release_region, 2712
7487, film_release_region, 2712
7487, film_release_region, 80
1706, featured_film_locations, 5948
1706, produced_by, 1602
11146, film_format, 11774
11146, film_release_region, 1796
6583, award_honor_award, 6506
6583, award_honor_award, 10072
6583, featured_film_locations, 10345
6583, film_format, 11774
6583, film_regional_debut_venue, 5464
6583, film_release_region, 1796
6583, film_release_region, 2712
6583, film_release_region, 80
6583, film_release_region, 11139
6583, genre, 3978
76, film_format, 11774
76, film_regional_debut_venue, 5464
5768, film_format, 11774
13680, film_format, 11774
13680, film_release_region, 1796
13680, film_release_region, 80
10744, film_release_region, 1796
10744, film_release_region, 2712
10744, film_release_region, 80
10744, film_release_region, 11139
246, award_honor_award, 6506
246, award_honor_award, 10072
246, film_format, 11774
10280, award_winner, 10458
10280, award_winner, 9550
2673, film_release_region, 11139
2673, genre, 3978
3978, titles, 7697
3978, titles, 1461
3978, titles, 13923
3978, titles, 13653
3978, titles, 7753
3978, titles, 6360
3978, titles, 594
3978, titles, 13516
3978, titles, 5239
3978, titles, 11303
3978, titles, 14021
3978, titles, 9863
3978, titles, 6583
3978, titles, 2068
3978, titles, 3622
3978, titles, 4179
3978, titles, 9572
3978, titles, 8754
3978, titles, 9738
3978, titles, 12394
3978, titles, 12629
3978, titles, 13624
3978, titles, 6076
3978, titles, 5859
269, colors, 7767
2068, film_format, 11774
11364, film_regional_debut_venue, 5464
11364, film_release_region, 1796
6014, citytown, 5948
6014, colors, 7767
3622, film_regional_debut_venue, 5464
3622, film_release_region, 80
3622, film_release_region, 11139
3622, genre, 3978
4179, featured_film_locations, 5948
4179, genre, 3978
9572, featured_film_locations, 5948
293, people, 10297
293, people, 10458
12136, team, 5106
12136, team, 269
7577, film_release_region, 1796
7577, film_release_region, 2712
8754, film_format, 11774
8754, genre, 3978
3506, film_release_region, 1796
3506, film_release_region, 2712
6610, film, 2964
6610, film, 6583
6610, film, 13680
6610, film, 13072
6610, film, 2003
6610, film, 7513
6610, film, 10397
6610, industry, 7388
6610, nominated_for, 2003
6610, nominated_for, 7675
9738, film_release_region, 11139
11026, film_release_region, 1796
11026, film_release_region, 2712
11026, film_release_region, 11139
1596, film_release_region, 1796
1596, film_release_region, 11139
1596, genre, 3978
12627, film_release_region, 1796
12627, film_release_region, 2712
12627, film_release_region, 11139
13072, film_release_region, 2712
13072, film_release_region, 11139
12394, genre, 3978
11795, film_format, 11774
11795, film_release_region, 1796
12629, film_release_region, 2712
9256, film_format, 11774
9256, film_release_region, 1796
9256, film_release_region, 2712
9256, film_release_region, 80
9256, film_release_region, 11139
11514, film_format, 11774
11514, film_regional_debut_venue, 5948
7644, film_release_region, 2712
7644, film_release_region, 80
7644, film_release_region, 11139
2003, genre, 3978
723, film_release_region, 1796
723, film_release_region, 2712
723, film_release_region, 80
723, film_release_region, 11139
7675, award_honor_award, 4978
7675, award_winner, 9550
7675, award_winner, 6610
7675, production_companies, 6610
13624, genre, 3978
6076, film_format, 11774
6076, genre, 3978
7513, film_release_region, 2712
12168, film_format, 11774
12168, film_regional_debut_venue, 5464
12168, film_release_region, 11139
5948, contains, 6014
5948, contains, 5506
1693, film_release_region, 1796
1693, film_release_region, 2712
1693, film_release_region, 80
8937, film_release_region, 1796
8937, film_release_region, 2712
10397, film_release_region, 1796
10397, film_release_region, 2712
10397, film_release_region, 80
10397, film_release_region, 11139
10397, production_companies, 6610
5506, campuses, 5506
5506, citytown, 5948
5506, colors, 7767
5506, major_field_of_study, 11203
5506, student, 12407
5506, student, 10458
5506, student, 1602
13975, film_release_region, 1796
13975, film_release_region, 2712
13975, film_release_region, 80
13975, film_release_region, 11139
Question: How are Incheon_United_FC, Memento, and University_of_Toronto related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Incheon_United_FC",
"Memento",
"University_of_Toronto"
],
"valid_edges": [
[
"(500)_Days_of_Summer",
"film_format",
"35_mm_film"
],
[
"(500)_Days_of_Summer",
"film_release_region",
"Toronto"
],
[
"(500)_Days_of_Summer",
"film_release_region",
"Uruguay"
],
[
"A_History_of_Violence",
"genre",
"Psychological_thriller"
],
[
"A_Separation",
"film_format",
"35_mm_film"
],
[
"A_Separation",
"film_release_region",
"Kuwait"
],
[
"Acting",
"student",
"Alec_Baldwin"
],
[
"Albert_Nobbs",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Albert_Nobbs",
"film_release_region",
"Colombia"
],
[
"Albert_Nobbs",
"film_release_region",
"Kuwait"
],
[
"Alec_Baldwin",
"award_winner",
"Lorne_Michaels"
],
[
"An_Education",
"film_format",
"35_mm_film"
],
[
"Antichrist",
"film_format",
"35_mm_film"
],
[
"Bad_Education",
"film_format",
"35_mm_film"
],
[
"Bad_Education",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Batman_Begins",
"film_release_region",
"Colombia"
],
[
"Batman_Begins",
"film_release_region",
"Kuwait"
],
[
"Batman_Begins",
"film_release_region",
"Slovakia"
],
[
"Batman_Begins",
"film_release_region",
"Uruguay"
],
[
"Battlestar_Galactica-GB",
"actor",
"Callum_Keith_Rennie"
],
[
"Battlestar_Galactica-GB",
"genre",
"Psychological_thriller"
],
[
"Beasts_of_the_Southern_Wild",
"film_release_region",
"Kuwait"
],
[
"Beginners",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Black_Swan",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Director"
],
[
"Black_Swan",
"film_release_region",
"Toronto"
],
[
"Black_Swan",
"film_release_region",
"Uruguay"
],
[
"Black_Swan",
"genre",
"Psychological_thriller"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"An_Education"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Beasts_of_the_Southern_Wild"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Black_Swan"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Cold_Mountain"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Crash"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Django_Unchained"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Inglourious_Basterds"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Juno"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Memento"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Precious:_Based_on_the_Novel_Push_by_Sapphire"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"Shrek"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"The_Dark_Knight"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"The_Sixth_Sense"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"The_Talented_Mr._Ripley"
],
[
"Broadcast_Film_Critics_Association_Award_for_Best_Film",
"nominated_for",
"There_Will_Be_Blood"
],
[
"Brothers",
"film_format",
"35_mm_film"
],
[
"Brothers",
"genre",
"Psychological_thriller"
],
[
"Callum_Keith_Rennie",
"acted_in",
"Memento"
],
[
"Callum_Keith_Rennie",
"acted_in",
"The_Butterfly_Effect"
],
[
"Cars_2",
"film_release_region",
"Colombia"
],
[
"Cars_2",
"film_release_region",
"Kuwait"
],
[
"Cosmopolis",
"film_release_region",
"Slovakia"
],
[
"Cowboys_&_Aliens",
"film_release_region",
"Colombia"
],
[
"Cowboys_&_Aliens",
"film_release_region",
"Kuwait"
],
[
"Cowboys_&_Aliens",
"film_release_region",
"Uruguay"
],
[
"Crash",
"award_winner",
"David_Cronenberg"
],
[
"Crash",
"featured_film_locations",
"Toronto"
],
[
"Crash",
"genre",
"Psychological_thriller"
],
[
"Crash",
"produced_by",
"David_Cronenberg"
],
[
"Crash",
"written_by",
"David_Cronenberg"
],
[
"David_Cronenberg",
"film",
"A_History_of_Violence"
],
[
"David_Cronenberg",
"film",
"Cosmopolis"
],
[
"David_Cronenberg",
"film",
"Crash"
],
[
"David_Cronenberg",
"film",
"Dead_Ringers"
],
[
"David_Cronenberg",
"location",
"Toronto"
],
[
"David_Cronenberg",
"nominated_for",
"A_History_of_Violence"
],
[
"David_Cronenberg",
"nominated_for",
"Crash"
],
[
"David_Cronenberg",
"nominated_for",
"Dead_Ringers"
],
[
"David_Cronenberg",
"place_of_birth",
"Toronto"
],
[
"Dead_Ringers",
"award_winner",
"David_Cronenberg"
],
[
"Dead_Ringers",
"featured_film_locations",
"Toronto"
],
[
"Dead_Ringers",
"genre",
"Psychological_thriller"
],
[
"Dead_Ringers",
"produced_by",
"David_Cronenberg"
],
[
"Dead_Ringers",
"written_by",
"David_Cronenberg"
],
[
"Dial_M_for_Murder",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Django_Unchained",
"film_release_region",
"Kuwait"
],
[
"Don't_Be_Afraid_of_the_Dark",
"film_format",
"35_mm_film"
],
[
"Don't_Say_a_Word",
"featured_film_locations",
"Toronto"
],
[
"Donald_Sutherland",
"acted_in",
"Cold_Mountain"
],
[
"Donald_Sutherland",
"acted_in",
"Murder_by_Decree"
],
[
"Donald_Sutherland",
"acted_in",
"The_Hunger_Games"
],
[
"Donald_Sutherland",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie"
],
[
"E1_Entertainment",
"citytown",
"Toronto"
],
[
"E1_Entertainment",
"film",
"Albert_Nobbs"
],
[
"E1_Entertainment",
"film",
"Beasts_of_the_Southern_Wild"
],
[
"E1_Entertainment",
"film",
"Cosmopolis"
],
[
"E1_Entertainment",
"film",
"Fair_Game"
],
[
"E1_Entertainment",
"film",
"Memento"
],
[
"E1_Entertainment",
"film",
"Red_State"
],
[
"E1_Entertainment",
"film",
"The_Beaver"
],
[
"E1_Entertainment",
"film",
"The_Ghost_Writer"
],
[
"E1_Entertainment",
"film",
"The_Three_Musketeers"
],
[
"E1_Entertainment",
"industry",
"Film"
],
[
"Final_Destination_5",
"film_release_region",
"Colombia"
],
[
"Final_Destination_5",
"film_release_region",
"Kuwait"
],
[
"Frankenstein",
"film_format",
"35_mm_film"
],
[
"Frankenstein",
"film_release_region",
"Uruguay"
],
[
"Green_Lantern",
"film_release_region",
"Colombia"
],
[
"Green_Lantern",
"film_release_region",
"Kuwait"
],
[
"Green_Lantern",
"film_release_region",
"Uruguay"
],
[
"Guy_Pearce",
"acted_in",
"Don't_Be_Afraid_of_the_Dark"
],
[
"Guy_Pearce",
"acted_in",
"Memento"
],
[
"Guy_Pearce",
"acted_in",
"The_Hurt_Locker"
],
[
"Guy_Pearce",
"award",
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie"
],
[
"Guy_Pearce",
"nominated_for",
"The_Hurt_Locker"
],
[
"Hairspray",
"featured_film_locations",
"Toronto"
],
[
"Hairspray",
"film_release_region",
"Colombia"
],
[
"Hairspray",
"film_release_region",
"Kuwait"
],
[
"Hairspray",
"film_release_region",
"Slovakia"
],
[
"Home_Alone",
"film_release_region",
"Colombia"
],
[
"Home_Alone",
"film_release_region",
"Uruguay"
],
[
"Ice_Age",
"film_release_region",
"Colombia"
],
[
"Ice_Age",
"film_release_region",
"Kuwait"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Beasts_of_the_Southern_Wild"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Beginners"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Juno"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Memento"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Precious:_Based_on_the_Novel_Push_by_Sapphire"
],
[
"Independent_Spirit_Award_for_Best_Director",
"nominated_for",
"Requiem_for_a_Dream"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"disciplines_or_subjects",
"Acting"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"nominated_for",
"Albert_Nobbs"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"nominated_for",
"Memento"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"nominated_for",
"Precious:_Based_on_the_Novel_Push_by_Sapphire"
],
[
"Independent_Spirit_Award_for_Best_Supporting_Female",
"nominated_for",
"Requiem_for_a_Dream"
],
[
"Inglourious_Basterds",
"film_release_region",
"Colombia"
],
[
"Inglourious_Basterds",
"film_release_region",
"Kuwait"
],
[
"Inglourious_Basterds",
"film_release_region",
"Slovakia"
],
[
"Inglourious_Basterds",
"film_release_region",
"Uruguay"
],
[
"Inland_Empire",
"film_format",
"35_mm_film"
],
[
"Inland_Empire",
"genre",
"Psychological_thriller"
],
[
"Insidious",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Iron_Man",
"film_release_region",
"Colombia"
],
[
"Iron_Man",
"film_release_region",
"Kuwait"
],
[
"Iron_Man",
"film_release_region",
"Slovakia"
],
[
"Iron_Man",
"film_release_region",
"Uruguay"
],
[
"Iron_Man_2",
"film_format",
"35_mm_film"
],
[
"Iron_Man_2",
"film_release_region",
"Colombia"
],
[
"Iron_Man_2",
"film_release_region",
"Kuwait"
],
[
"Iron_Man_2",
"film_release_region",
"Slovakia"
],
[
"Iron_Man_2",
"film_release_region",
"Uruguay"
],
[
"Jorja_Fox",
"acted_in",
"Memento"
],
[
"Kaboom",
"film_regional_debut_venue",
"Toronto"
],
[
"Kaboom",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Kaboom",
"genre",
"Psychological_thriller"
],
[
"Kung_Fu_Panda_2",
"film_release_region",
"Colombia"
],
[
"Kung_Fu_Panda_2",
"film_release_region",
"Kuwait"
],
[
"Kung_Fu_Panda_2",
"film_release_region",
"Uruguay"
],
[
"Lantana",
"film_format",
"35_mm_film"
],
[
"Lantana",
"genre",
"Psychological_thriller"
],
[
"Las_Vegas",
"place",
"Las_Vegas"
],
[
"Lee_Strasberg_Theatre_and_Film_Institute",
"major_field_of_study",
"Acting"
],
[
"Lee_Strasberg_Theatre_and_Film_Institute",
"student",
"Jorja_Fox"
],
[
"Lorne_Michaels",
"award_nominee",
"Alec_Baldwin"
],
[
"Lorne_Michaels",
"location",
"Toronto"
],
[
"Lost_Highway",
"film_release_region",
"Uruguay"
],
[
"Lost_Highway",
"genre",
"Psychological_thriller"
],
[
"Marley",
"film_format",
"35_mm_film"
],
[
"Marley",
"film_release_region",
"Kuwait"
],
[
"Marley_&_Me",
"film_release_region",
"Kuwait"
],
[
"Marley_&_Me",
"film_release_region",
"Slovakia"
],
[
"Mean_Girls",
"featured_film_locations",
"Toronto"
],
[
"Mean_Girls",
"produced_by",
"Lorne_Michaels"
],
[
"Melancholia",
"film_format",
"35_mm_film"
],
[
"Melancholia",
"film_release_region",
"Colombia"
],
[
"Memento",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Director"
],
[
"Memento",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Memento",
"featured_film_locations",
"Las_Vegas"
],
[
"Memento",
"film_format",
"35_mm_film"
],
[
"Memento",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Memento",
"film_release_region",
"Colombia"
],
[
"Memento",
"film_release_region",
"Kuwait"
],
[
"Memento",
"film_release_region",
"Slovakia"
],
[
"Memento",
"film_release_region",
"Uruguay"
],
[
"Memento",
"genre",
"Psychological_thriller"
],
[
"Mr._Nobody",
"film_format",
"35_mm_film"
],
[
"Mr._Nobody",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Murder_by_Decree",
"film_format",
"35_mm_film"
],
[
"PS,_I_Love_You",
"film_format",
"35_mm_film"
],
[
"PS,_I_Love_You",
"film_release_region",
"Colombia"
],
[
"PS,_I_Love_You",
"film_release_region",
"Slovakia"
],
[
"Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl",
"film_release_region",
"Colombia"
],
[
"Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl",
"film_release_region",
"Kuwait"
],
[
"Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl",
"film_release_region",
"Slovakia"
],
[
"Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl",
"film_release_region",
"Uruguay"
],
[
"Precious:_Based_on_the_Novel_Push_by_Sapphire",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Director"
],
[
"Precious:_Based_on_the_Novel_Push_by_Sapphire",
"award_honor_award",
"Independent_Spirit_Award_for_Best_Supporting_Female"
],
[
"Precious:_Based_on_the_Novel_Push_by_Sapphire",
"film_format",
"35_mm_film"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"Donald_Sutherland"
],
[
"Primetime_Emmy_Award_for_Outstanding_Supporting_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"Guy_Pearce"
],
[
"Psycho",
"film_release_region",
"Uruguay"
],
[
"Psycho",
"genre",
"Psychological_thriller"
],
[
"Psychological_thriller",
"titles",
"A_History_of_Violence"
],
[
"Psychological_thriller",
"titles",
"Antichrist"
],
[
"Psychological_thriller",
"titles",
"Bad_Education"
],
[
"Psychological_thriller",
"titles",
"Black_Swan"
],
[
"Psychological_thriller",
"titles",
"Crash"
],
[
"Psychological_thriller",
"titles",
"Dead_Ringers"
],
[
"Psychological_thriller",
"titles",
"Dial_M_for_Murder"
],
[
"Psychological_thriller",
"titles",
"Don't_Say_a_Word"
],
[
"Psychological_thriller",
"titles",
"Inland_Empire"
],
[
"Psychological_thriller",
"titles",
"Insidious"
],
[
"Psychological_thriller",
"titles",
"Lantana"
],
[
"Psychological_thriller",
"titles",
"Lost_Highway"
],
[
"Psychological_thriller",
"titles",
"Memento"
],
[
"Psychological_thriller",
"titles",
"Red_State"
],
[
"Psychological_thriller",
"titles",
"Saw"
],
[
"Psychological_thriller",
"titles",
"Saw_III"
],
[
"Psychological_thriller",
"titles",
"Saw_IV"
],
[
"Psychological_thriller",
"titles",
"Shutter_Island"
],
[
"Psychological_thriller",
"titles",
"Sunset_Boulevard"
],
[
"Psychological_thriller",
"titles",
"The_Butterfly_Effect"
],
[
"Psychological_thriller",
"titles",
"The_Clearing"
],
[
"Psychological_thriller",
"titles",
"The_Sixth_Sense"
],
[
"Psychological_thriller",
"titles",
"The_Talented_Mr._Ripley"
],
[
"Psychological_thriller",
"titles",
"There_Will_Be_Blood"
],
[
"Reading_F.C.",
"colors",
"Blue"
],
[
"Red_State",
"film_format",
"35_mm_film"
],
[
"Requiem_for_a_Dream",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Requiem_for_a_Dream",
"film_release_region",
"Colombia"
],
[
"Ryerson_University",
"citytown",
"Toronto"
],
[
"Ryerson_University",
"colors",
"Blue"
],
[
"Saw",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"Saw",
"film_release_region",
"Slovakia"
],
[
"Saw",
"film_release_region",
"Uruguay"
],
[
"Saw",
"genre",
"Psychological_thriller"
],
[
"Saw_III",
"featured_film_locations",
"Toronto"
],
[
"Saw_III",
"genre",
"Psychological_thriller"
],
[
"Saw_IV",
"featured_film_locations",
"Toronto"
],
[
"Scottish_Canadian",
"people",
"Callum_Keith_Rennie"
],
[
"Scottish_Canadian",
"people",
"Donald_Sutherland"
],
[
"Seol_Ki-Hyeon",
"team",
"Incheon_United_FC"
],
[
"Seol_Ki-Hyeon",
"team",
"Reading_F.C."
],
[
"Shrek",
"film_release_region",
"Colombia"
],
[
"Shrek",
"film_release_region",
"Kuwait"
],
[
"Shutter_Island",
"film_format",
"35_mm_film"
],
[
"Shutter_Island",
"genre",
"Psychological_thriller"
],
[
"Signs",
"film_release_region",
"Colombia"
],
[
"Signs",
"film_release_region",
"Kuwait"
],
[
"Summit_Entertainment",
"film",
"Fair_Game"
],
[
"Summit_Entertainment",
"film",
"Memento"
],
[
"Summit_Entertainment",
"film",
"PS,_I_Love_You"
],
[
"Summit_Entertainment",
"film",
"The_Beaver"
],
[
"Summit_Entertainment",
"film",
"The_Ghost_Writer"
],
[
"Summit_Entertainment",
"film",
"The_Three_Musketeers"
],
[
"Summit_Entertainment",
"film",
"Twilight"
],
[
"Summit_Entertainment",
"industry",
"Film"
],
[
"Summit_Entertainment",
"nominated_for",
"The_Ghost_Writer"
],
[
"Summit_Entertainment",
"nominated_for",
"The_Hurt_Locker"
],
[
"Sunset_Boulevard",
"film_release_region",
"Uruguay"
],
[
"Super_8",
"film_release_region",
"Colombia"
],
[
"Super_8",
"film_release_region",
"Kuwait"
],
[
"Super_8",
"film_release_region",
"Uruguay"
],
[
"Taken",
"film_release_region",
"Colombia"
],
[
"Taken",
"film_release_region",
"Uruguay"
],
[
"Taken",
"genre",
"Psychological_thriller"
],
[
"The_Avengers",
"film_release_region",
"Colombia"
],
[
"The_Avengers",
"film_release_region",
"Kuwait"
],
[
"The_Avengers",
"film_release_region",
"Uruguay"
],
[
"The_Beaver",
"film_release_region",
"Kuwait"
],
[
"The_Beaver",
"film_release_region",
"Uruguay"
],
[
"The_Butterfly_Effect",
"genre",
"Psychological_thriller"
],
[
"The_Cabin_in_the_Woods",
"film_format",
"35_mm_film"
],
[
"The_Cabin_in_the_Woods",
"film_release_region",
"Colombia"
],
[
"The_Clearing",
"film_release_region",
"Kuwait"
],
[
"The_Dark_Knight",
"film_format",
"35_mm_film"
],
[
"The_Dark_Knight",
"film_release_region",
"Colombia"
],
[
"The_Dark_Knight",
"film_release_region",
"Kuwait"
],
[
"The_Dark_Knight",
"film_release_region",
"Slovakia"
],
[
"The_Dark_Knight",
"film_release_region",
"Uruguay"
],
[
"The_Devil's_Double",
"film_format",
"35_mm_film"
],
[
"The_Devil's_Double",
"film_regional_debut_venue",
"Toronto"
],
[
"The_Expendables",
"film_release_region",
"Kuwait"
],
[
"The_Expendables",
"film_release_region",
"Slovakia"
],
[
"The_Expendables",
"film_release_region",
"Uruguay"
],
[
"The_Ghost_Writer",
"genre",
"Psychological_thriller"
],
[
"The_Hunger_Games",
"film_release_region",
"Colombia"
],
[
"The_Hunger_Games",
"film_release_region",
"Kuwait"
],
[
"The_Hunger_Games",
"film_release_region",
"Slovakia"
],
[
"The_Hunger_Games",
"film_release_region",
"Uruguay"
],
[
"The_Hurt_Locker",
"award_honor_award",
"Broadcast_Film_Critics_Association_Award_for_Best_Film"
],
[
"The_Hurt_Locker",
"award_winner",
"Guy_Pearce"
],
[
"The_Hurt_Locker",
"award_winner",
"Summit_Entertainment"
],
[
"The_Hurt_Locker",
"production_companies",
"Summit_Entertainment"
],
[
"The_Sixth_Sense",
"genre",
"Psychological_thriller"
],
[
"The_Talented_Mr._Ripley",
"film_format",
"35_mm_film"
],
[
"The_Talented_Mr._Ripley",
"genre",
"Psychological_thriller"
],
[
"The_Three_Musketeers",
"film_release_region",
"Kuwait"
],
[
"The_Whistleblower",
"film_format",
"35_mm_film"
],
[
"The_Whistleblower",
"film_regional_debut_venue",
"Toronto_International_Film_Festival"
],
[
"The_Whistleblower",
"film_release_region",
"Uruguay"
],
[
"Toronto",
"contains",
"Ryerson_University"
],
[
"Toronto",
"contains",
"University_of_Toronto"
],
[
"Transformers",
"film_release_region",
"Colombia"
],
[
"Transformers",
"film_release_region",
"Kuwait"
],
[
"Transformers",
"film_release_region",
"Slovakia"
],
[
"Transformers:_Dark_of_the_Moon",
"film_release_region",
"Colombia"
],
[
"Transformers:_Dark_of_the_Moon",
"film_release_region",
"Kuwait"
],
[
"Twilight",
"film_release_region",
"Colombia"
],
[
"Twilight",
"film_release_region",
"Kuwait"
],
[
"Twilight",
"film_release_region",
"Slovakia"
],
[
"Twilight",
"film_release_region",
"Uruguay"
],
[
"Twilight",
"production_companies",
"Summit_Entertainment"
],
[
"University_of_Toronto",
"campuses",
"University_of_Toronto"
],
[
"University_of_Toronto",
"citytown",
"Toronto"
],
[
"University_of_Toronto",
"colors",
"Blue"
],
[
"University_of_Toronto",
"major_field_of_study",
"Acting"
],
[
"University_of_Toronto",
"student",
"David_Cronenberg"
],
[
"University_of_Toronto",
"student",
"Donald_Sutherland"
],
[
"University_of_Toronto",
"student",
"Lorne_Michaels"
],
[
"X-Men_Origins:_Wolverine",
"film_release_region",
"Colombia"
],
[
"X-Men_Origins:_Wolverine",
"film_release_region",
"Kuwait"
],
[
"X-Men_Origins:_Wolverine",
"film_release_region",
"Slovakia"
],
[
"X-Men_Origins:_Wolverine",
"film_release_region",
"Uruguay"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12443, 61st_Primetime_Emmy_Awards
730, Alan_Alda
4565, An_Early_Frost
13228, And_the_Band_Played_On
12497, Backstairs_at_the_White_House
10122, Beau_Bridges
170, Ben_Kingsley
5995, Chief_of_police-GB
8227, Danny_Glover
1709, Dennis_Quaid
6341, Don_Cheadle
7101, Hallmark_Hall_of_Fame
273, Ian_McKellen
10251, Independent_Spirit_Award_for_Best_Male_Lead
508, Into_the_West
13471, James_Woods
13373, Kevin_Bacon
2549, Kevin_Spacey
5469, Laurence_Fishburne
11097, Matthew_Modine
2574, NBC
3448, New_York
8813, Nick_Nolte
5848, Paul_Giamatti
137, Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie
2505, Randy_Quaid
1707, Robert_Duvall
169, Stanley_Tucci
13862, The_Biggest_Loser
10214, Theodore_Roosevelt
2401, Tom_Wilkinson
306, William_H._Macy
5693, Woody_Harrelson
src, edge_attr, dst
12443, award_winner, 2574
730, acted_in, 13228
730, award, 137
730, nominated_for, 13228
4565, award_winner, 2574
170, award, 10251
170, award, 137
8227, award, 137
1709, award, 10251
1709, award, 137
6341, award, 10251
6341, award, 137
7101, award_winner, 2574
273, acted_in, 13228
273, award, 137
273, nominated_for, 13228
10251, award_winner, 8227
10251, award_winner, 1709
10251, award_winner, 273
10251, award_winner, 13471
10251, award_winner, 5848
10251, award_winner, 1707
10251, award_winner, 2401
10251, award_winner, 306
508, actor, 10122
508, actor, 11097
13471, award, 10251
13373, award, 10251
13373, award, 137
2549, award, 10251
2549, award, 137
5469, award, 10251
5469, award, 137
11097, acted_in, 13228
11097, award, 10251
11097, award, 137
11097, nominated_for, 13228
2574, nominated_for, 13862
2574, program, 4565
2574, program, 12497
2574, program, 7101
2574, state_province_region, 3448
8813, award, 10251
8813, award, 137
5848, award, 10251
5848, award, 137
137, award_winner, 10122
137, award_winner, 13471
137, award_winner, 5848
137, award_winner, 1707
137, award_winner, 306
137, ceremony, 12443
137, nominated_for, 4565
137, nominated_for, 13228
137, nominated_for, 12497
137, nominated_for, 7101
2505, award, 10251
2505, award, 137
1707, award, 10251
169, award, 10251
169, award, 137
10214, jurisdiction_of_office, 3448
10214, profession, 5995
2401, award, 137
306, award, 10251
5693, award, 10251
5693, award, 137
Question: In what context are Chief_of_police-GB, Matthew_Modine, and The_Biggest_Loser connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Chief_of_police-GB",
"Matthew_Modine",
"The_Biggest_Loser"
],
"valid_edges": [
[
"61st_Primetime_Emmy_Awards",
"award_winner",
"NBC"
],
[
"Alan_Alda",
"acted_in",
"And_the_Band_Played_On"
],
[
"Alan_Alda",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Alan_Alda",
"nominated_for",
"And_the_Band_Played_On"
],
[
"An_Early_Frost",
"award_winner",
"NBC"
],
[
"Ben_Kingsley",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Ben_Kingsley",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Danny_Glover",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Dennis_Quaid",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Dennis_Quaid",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Don_Cheadle",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Don_Cheadle",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Hallmark_Hall_of_Fame",
"award_winner",
"NBC"
],
[
"Ian_McKellen",
"acted_in",
"And_the_Band_Played_On"
],
[
"Ian_McKellen",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Ian_McKellen",
"nominated_for",
"And_the_Band_Played_On"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Danny_Glover"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Dennis_Quaid"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Ian_McKellen"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"James_Woods"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Paul_Giamatti"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Robert_Duvall"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"Tom_Wilkinson"
],
[
"Independent_Spirit_Award_for_Best_Male_Lead",
"award_winner",
"William_H._Macy"
],
[
"Into_the_West",
"actor",
"Beau_Bridges"
],
[
"Into_the_West",
"actor",
"Matthew_Modine"
],
[
"James_Woods",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Kevin_Bacon",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Kevin_Bacon",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Kevin_Spacey",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Kevin_Spacey",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Laurence_Fishburne",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Laurence_Fishburne",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Matthew_Modine",
"acted_in",
"And_the_Band_Played_On"
],
[
"Matthew_Modine",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Matthew_Modine",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Matthew_Modine",
"nominated_for",
"And_the_Band_Played_On"
],
[
"NBC",
"nominated_for",
"The_Biggest_Loser"
],
[
"NBC",
"program",
"An_Early_Frost"
],
[
"NBC",
"program",
"Backstairs_at_the_White_House"
],
[
"NBC",
"program",
"Hallmark_Hall_of_Fame"
],
[
"NBC",
"state_province_region",
"New_York"
],
[
"Nick_Nolte",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Nick_Nolte",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Paul_Giamatti",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Paul_Giamatti",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"Beau_Bridges"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"James_Woods"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"Paul_Giamatti"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"Robert_Duvall"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"award_winner",
"William_H._Macy"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"ceremony",
"61st_Primetime_Emmy_Awards"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"nominated_for",
"An_Early_Frost"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"nominated_for",
"And_the_Band_Played_On"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"nominated_for",
"Backstairs_at_the_White_House"
],
[
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie",
"nominated_for",
"Hallmark_Hall_of_Fame"
],
[
"Randy_Quaid",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Randy_Quaid",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Robert_Duvall",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Stanley_Tucci",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Stanley_Tucci",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"Theodore_Roosevelt",
"jurisdiction_of_office",
"New_York"
],
[
"Theodore_Roosevelt",
"profession",
"Chief_of_police-GB"
],
[
"Tom_Wilkinson",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
],
[
"William_H._Macy",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Woody_Harrelson",
"award",
"Independent_Spirit_Award_for_Best_Male_Lead"
],
[
"Woody_Harrelson",
"award",
"Primetime_Emmy_Award_for_Outstanding_Lead_Actor_-_Miniseries_or_a_Movie"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
12828, 11th_Satellite_Awards
3991, American_Broadcasting_Company
12525, Bewitched
7947, Chandra_Wilson
5207, Dunfermline
1607, Ellen_Pompeo
6460, Eric_Dane
11598, Grey's_Anatomy
10201, Isaiah_Washington
11691, James_Pickens_Jr.
13904, Justin_Chambers
1662, Kate_Walsh
5140, Katherine_Heigl
8854, Patrick_Dempsey
8370, Sandra_Oh
10271, Sara_Ramirez
5929, Scotland
7023, T._R._Knight
7387, Traffic
src, edge_attr, dst
12828, award_winner, 3991
12828, award_winner, 11691
12828, award_winner, 1662
3991, nominated_for, 11598
3991, program, 12525
3991, program, 11598
7947, award_nominee, 11691
7947, award_nominee, 1662
7947, award_winner, 11691
7947, award_winner, 1662
7947, participant, 1662
1607, award_nominee, 11691
1607, award_nominee, 1662
1607, award_winner, 11691
1607, award_winner, 1662
6460, award_nominee, 11691
6460, award_nominee, 1662
6460, award_winner, 11691
6460, award_winner, 1662
11598, actor, 11691
11598, actor, 1662
11598, award_winner, 11691
11598, award_winner, 1662
10201, award_nominee, 11691
10201, award_nominee, 1662
10201, award_winner, 11691
10201, award_winner, 1662
11691, acted_in, 7387
11691, award_nominee, 7947
11691, award_nominee, 6460
11691, award_nominee, 10201
11691, award_nominee, 13904
11691, award_nominee, 5140
11691, award_nominee, 8854
11691, award_nominee, 8370
11691, award_nominee, 10271
11691, award_winner, 7947
11691, award_winner, 1607
11691, award_winner, 6460
11691, award_winner, 10201
11691, award_winner, 13904
11691, award_winner, 5140
11691, award_winner, 8854
11691, award_winner, 8370
11691, award_winner, 10271
11691, award_winner, 7023
11691, nominated_for, 11598
13904, award_nominee, 11691
13904, award_nominee, 1662
13904, award_winner, 11691
13904, award_winner, 1662
13904, participant, 1662
1662, acted_in, 12525
1662, award_nominee, 7947
1662, award_nominee, 6460
1662, award_nominee, 10201
1662, award_nominee, 5140
1662, award_nominee, 8854
1662, award_nominee, 10271
1662, award_nominee, 7023
1662, award_winner, 7947
1662, award_winner, 1607
1662, award_winner, 6460
1662, award_winner, 11691
1662, award_winner, 13904
1662, award_winner, 5140
1662, award_winner, 8854
1662, award_winner, 7023
1662, participant, 7947
1662, participant, 10271
1662, participant, 7023
5140, award_nominee, 11691
5140, award_nominee, 1662
5140, award_winner, 11691
5140, award_winner, 1662
8854, award_nominee, 11691
8854, award_nominee, 1662
8854, award_winner, 11691
8854, award_winner, 1662
8370, award_nominee, 11691
8370, award_winner, 11691
8370, award_winner, 1662
10271, award_nominee, 11691
10271, award_nominee, 1662
10271, award_winner, 1662
5929, contains, 5207
5929, vacationer, 8854
7023, award_nominee, 11691
7023, award_nominee, 1662
7023, award_winner, 11691
7023, award_winner, 1662
Question: How are Bewitched, Dunfermline, and Traffic related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Bewitched",
"Dunfermline",
"Traffic"
],
"valid_edges": [
[
"11th_Satellite_Awards",
"award_winner",
"American_Broadcasting_Company"
],
[
"11th_Satellite_Awards",
"award_winner",
"James_Pickens_Jr."
],
[
"11th_Satellite_Awards",
"award_winner",
"Kate_Walsh"
],
[
"American_Broadcasting_Company",
"nominated_for",
"Grey's_Anatomy"
],
[
"American_Broadcasting_Company",
"program",
"Bewitched"
],
[
"American_Broadcasting_Company",
"program",
"Grey's_Anatomy"
],
[
"Chandra_Wilson",
"award_nominee",
"James_Pickens_Jr."
],
[
"Chandra_Wilson",
"award_nominee",
"Kate_Walsh"
],
[
"Chandra_Wilson",
"award_winner",
"James_Pickens_Jr."
],
[
"Chandra_Wilson",
"award_winner",
"Kate_Walsh"
],
[
"Chandra_Wilson",
"participant",
"Kate_Walsh"
],
[
"Ellen_Pompeo",
"award_nominee",
"James_Pickens_Jr."
],
[
"Ellen_Pompeo",
"award_nominee",
"Kate_Walsh"
],
[
"Ellen_Pompeo",
"award_winner",
"James_Pickens_Jr."
],
[
"Ellen_Pompeo",
"award_winner",
"Kate_Walsh"
],
[
"Eric_Dane",
"award_nominee",
"James_Pickens_Jr."
],
[
"Eric_Dane",
"award_nominee",
"Kate_Walsh"
],
[
"Eric_Dane",
"award_winner",
"James_Pickens_Jr."
],
[
"Eric_Dane",
"award_winner",
"Kate_Walsh"
],
[
"Grey's_Anatomy",
"actor",
"James_Pickens_Jr."
],
[
"Grey's_Anatomy",
"actor",
"Kate_Walsh"
],
[
"Grey's_Anatomy",
"award_winner",
"James_Pickens_Jr."
],
[
"Grey's_Anatomy",
"award_winner",
"Kate_Walsh"
],
[
"Isaiah_Washington",
"award_nominee",
"James_Pickens_Jr."
],
[
"Isaiah_Washington",
"award_nominee",
"Kate_Walsh"
],
[
"Isaiah_Washington",
"award_winner",
"James_Pickens_Jr."
],
[
"Isaiah_Washington",
"award_winner",
"Kate_Walsh"
],
[
"James_Pickens_Jr.",
"acted_in",
"Traffic"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Chandra_Wilson"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Eric_Dane"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Isaiah_Washington"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Justin_Chambers"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Katherine_Heigl"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Patrick_Dempsey"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Sandra_Oh"
],
[
"James_Pickens_Jr.",
"award_nominee",
"Sara_Ramirez"
],
[
"James_Pickens_Jr.",
"award_winner",
"Chandra_Wilson"
],
[
"James_Pickens_Jr.",
"award_winner",
"Ellen_Pompeo"
],
[
"James_Pickens_Jr.",
"award_winner",
"Eric_Dane"
],
[
"James_Pickens_Jr.",
"award_winner",
"Isaiah_Washington"
],
[
"James_Pickens_Jr.",
"award_winner",
"Justin_Chambers"
],
[
"James_Pickens_Jr.",
"award_winner",
"Katherine_Heigl"
],
[
"James_Pickens_Jr.",
"award_winner",
"Patrick_Dempsey"
],
[
"James_Pickens_Jr.",
"award_winner",
"Sandra_Oh"
],
[
"James_Pickens_Jr.",
"award_winner",
"Sara_Ramirez"
],
[
"James_Pickens_Jr.",
"award_winner",
"T._R._Knight"
],
[
"James_Pickens_Jr.",
"nominated_for",
"Grey's_Anatomy"
],
[
"Justin_Chambers",
"award_nominee",
"James_Pickens_Jr."
],
[
"Justin_Chambers",
"award_nominee",
"Kate_Walsh"
],
[
"Justin_Chambers",
"award_winner",
"James_Pickens_Jr."
],
[
"Justin_Chambers",
"award_winner",
"Kate_Walsh"
],
[
"Justin_Chambers",
"participant",
"Kate_Walsh"
],
[
"Kate_Walsh",
"acted_in",
"Bewitched"
],
[
"Kate_Walsh",
"award_nominee",
"Chandra_Wilson"
],
[
"Kate_Walsh",
"award_nominee",
"Eric_Dane"
],
[
"Kate_Walsh",
"award_nominee",
"Isaiah_Washington"
],
[
"Kate_Walsh",
"award_nominee",
"Katherine_Heigl"
],
[
"Kate_Walsh",
"award_nominee",
"Patrick_Dempsey"
],
[
"Kate_Walsh",
"award_nominee",
"Sara_Ramirez"
],
[
"Kate_Walsh",
"award_nominee",
"T._R._Knight"
],
[
"Kate_Walsh",
"award_winner",
"Chandra_Wilson"
],
[
"Kate_Walsh",
"award_winner",
"Ellen_Pompeo"
],
[
"Kate_Walsh",
"award_winner",
"Eric_Dane"
],
[
"Kate_Walsh",
"award_winner",
"James_Pickens_Jr."
],
[
"Kate_Walsh",
"award_winner",
"Justin_Chambers"
],
[
"Kate_Walsh",
"award_winner",
"Katherine_Heigl"
],
[
"Kate_Walsh",
"award_winner",
"Patrick_Dempsey"
],
[
"Kate_Walsh",
"award_winner",
"T._R._Knight"
],
[
"Kate_Walsh",
"participant",
"Chandra_Wilson"
],
[
"Kate_Walsh",
"participant",
"Sara_Ramirez"
],
[
"Kate_Walsh",
"participant",
"T._R._Knight"
],
[
"Katherine_Heigl",
"award_nominee",
"James_Pickens_Jr."
],
[
"Katherine_Heigl",
"award_nominee",
"Kate_Walsh"
],
[
"Katherine_Heigl",
"award_winner",
"James_Pickens_Jr."
],
[
"Katherine_Heigl",
"award_winner",
"Kate_Walsh"
],
[
"Patrick_Dempsey",
"award_nominee",
"James_Pickens_Jr."
],
[
"Patrick_Dempsey",
"award_nominee",
"Kate_Walsh"
],
[
"Patrick_Dempsey",
"award_winner",
"James_Pickens_Jr."
],
[
"Patrick_Dempsey",
"award_winner",
"Kate_Walsh"
],
[
"Sandra_Oh",
"award_nominee",
"James_Pickens_Jr."
],
[
"Sandra_Oh",
"award_winner",
"James_Pickens_Jr."
],
[
"Sandra_Oh",
"award_winner",
"Kate_Walsh"
],
[
"Sara_Ramirez",
"award_nominee",
"James_Pickens_Jr."
],
[
"Sara_Ramirez",
"award_nominee",
"Kate_Walsh"
],
[
"Sara_Ramirez",
"award_winner",
"Kate_Walsh"
],
[
"Scotland",
"contains",
"Dunfermline"
],
[
"Scotland",
"vacationer",
"Patrick_Dempsey"
],
[
"T._R._Knight",
"award_nominee",
"James_Pickens_Jr."
],
[
"T._R._Knight",
"award_nominee",
"Kate_Walsh"
],
[
"T._R._Knight",
"award_winner",
"James_Pickens_Jr."
],
[
"T._R._Knight",
"award_winner",
"Kate_Walsh"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
87, 2009_Toronto_International_Film_Festival
11170, 2010_Berlin_International_Film_Festival
6394, Adaptation
10329, Adult_Swim
7401, American_Dad!
5946, American_Psycho
3206, Away_from_Her
13459, Berlin
10731, Black_comedy
14223, Cartoon_Network
6416, Catch-22
140, Civil_engineer
9389, Corpse_Bride
6310, Election
10181, Family_Guy
4530, Fight_Club
9870, Hot_Fuzz
12870, Islam
6790, Kid_vs._Kat
3833, Lionsgate_Entertainment
11978, M*A*S*H
13994, Mary_and_Max
2277, Matt_Stone
10118, Mike_Henry
5494, Network
7653, Nine
13032, Oh!_What_a_Lovely_War
8626, Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)
45, Primetime_Emmy_Award_for_Outstanding_Short-format_Animation
11725, Robot_Chicken
4261, Satire
12307, Scrooged
6872, Seth_Green
3509, Seth_MacFarlane
10042, Sitcom
10762, South_Park
5998, South_Park:_Bigger,_Longer_&_Uncut
5449, SpongeBob_SquarePants
5554, Stop_motion
3948, Team_America:_World_Police
1732, Thank_You_for_Smoking
6705, The_Boondocks
4731, The_Cable_Guy
1122, The_Cleveland_Show
6800, The_Stepford_Wives
11888, The_Weinstein_Company
8880, The_White_Ribbon
13924, Weeds
8351, Yasser_Arafat
10800, Youth_in_Revolt
src, edge_attr, dst
11170, locations, 13459
6394, genre, 10731
6394, genre, 4261
10329, program, 11725
10329, program, 6705
7401, genre, 10731
7401, genre, 4261
7401, genre, 10042
5946, genre, 10731
5946, genre, 4261
3206, film_festivals, 11170
13459, religion, 12870
10731, genre, 10731
14223, program, 6790
14223, program, 11725
14223, titles, 11725
14223, titles, 6705
6416, genre, 10731
6416, genre, 4261
9389, genre, 10731
9389, genre, 5554
6310, genre, 10731
6310, genre, 4261
10181, actor, 6872
10181, genre, 10731
10181, genre, 4261
10181, genre, 10042
4530, genre, 10731
4530, genre, 4261
9870, genre, 10731
9870, genre, 4261
6790, genre, 10731
6790, genre, 10042
3833, film, 3206
11978, genre, 10731
11978, genre, 4261
11978, genre, 10042
13994, genre, 10731
13994, genre, 5554
2277, award, 8626
10118, award_nominee, 3509
10118, program, 10181
10118, program, 1122
5494, genre, 10731
5494, genre, 4261
7653, award_winner, 11888
7653, film_festivals, 11170
13032, genre, 10731
13032, genre, 4261
8626, award_winner, 2277
8626, nominated_for, 7401
8626, nominated_for, 11725
8626, nominated_for, 10762
8626, nominated_for, 5449
45, award_winner, 6872
45, nominated_for, 11725
45, nominated_for, 5449
11725, actor, 10118
11725, actor, 6872
11725, award_honor_award, 45
11725, award_winner, 6872
11725, genre, 10731
11725, genre, 4261
11725, genre, 10042
11725, genre, 5554
12307, genre, 10731
12307, genre, 4261
6872, award, 8626
6872, award, 45
6872, award_nominee, 2277
6872, nominated_for, 11725
6872, nominated_for, 10762
6872, organizations_founded, 10329
6872, program, 11725
6872, tv_program, 11725
3509, award, 8626
3509, award_nominee, 10118
10762, award_honor_award, 8626
10762, genre, 10731
10762, genre, 4261
10762, genre, 10042
5998, genre, 10731
5998, genre, 4261
5449, genre, 10731
5449, genre, 4261
5449, genre, 10042
3948, genre, 10731
3948, genre, 4261
1732, genre, 10731
1732, genre, 4261
6705, genre, 10731
6705, genre, 4261
6705, genre, 10042
4731, genre, 10731
4731, genre, 4261
1122, actor, 10118
1122, genre, 10731
1122, genre, 4261
1122, genre, 10042
6800, genre, 10731
6800, genre, 4261
11888, film, 7653
11888, film, 10800
8880, film_festivals, 87
8880, film_festivals, 11170
13924, genre, 10731
13924, genre, 4261
8351, profession, 140
8351, religion, 12870
10800, film_festivals, 87
10800, film_festivals, 11170
10800, genre, 10731
10800, production_companies, 3833
Question: In what context are 2010_Berlin_International_Film_Festival, Civil_engineer, and Robot_Chicken connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"2010_Berlin_International_Film_Festival",
"Civil_engineer",
"Robot_Chicken"
],
"valid_edges": [
[
"2010_Berlin_International_Film_Festival",
"locations",
"Berlin"
],
[
"Adaptation",
"genre",
"Black_comedy"
],
[
"Adaptation",
"genre",
"Satire"
],
[
"Adult_Swim",
"program",
"Robot_Chicken"
],
[
"Adult_Swim",
"program",
"The_Boondocks"
],
[
"American_Dad!",
"genre",
"Black_comedy"
],
[
"American_Dad!",
"genre",
"Satire"
],
[
"American_Dad!",
"genre",
"Sitcom"
],
[
"American_Psycho",
"genre",
"Black_comedy"
],
[
"American_Psycho",
"genre",
"Satire"
],
[
"Away_from_Her",
"film_festivals",
"2010_Berlin_International_Film_Festival"
],
[
"Berlin",
"religion",
"Islam"
],
[
"Black_comedy",
"genre",
"Black_comedy"
],
[
"Cartoon_Network",
"program",
"Kid_vs._Kat"
],
[
"Cartoon_Network",
"program",
"Robot_Chicken"
],
[
"Cartoon_Network",
"titles",
"Robot_Chicken"
],
[
"Cartoon_Network",
"titles",
"The_Boondocks"
],
[
"Catch-22",
"genre",
"Black_comedy"
],
[
"Catch-22",
"genre",
"Satire"
],
[
"Corpse_Bride",
"genre",
"Black_comedy"
],
[
"Corpse_Bride",
"genre",
"Stop_motion"
],
[
"Election",
"genre",
"Black_comedy"
],
[
"Election",
"genre",
"Satire"
],
[
"Family_Guy",
"actor",
"Seth_Green"
],
[
"Family_Guy",
"genre",
"Black_comedy"
],
[
"Family_Guy",
"genre",
"Satire"
],
[
"Family_Guy",
"genre",
"Sitcom"
],
[
"Fight_Club",
"genre",
"Black_comedy"
],
[
"Fight_Club",
"genre",
"Satire"
],
[
"Hot_Fuzz",
"genre",
"Black_comedy"
],
[
"Hot_Fuzz",
"genre",
"Satire"
],
[
"Kid_vs._Kat",
"genre",
"Black_comedy"
],
[
"Kid_vs._Kat",
"genre",
"Sitcom"
],
[
"Lionsgate_Entertainment",
"film",
"Away_from_Her"
],
[
"M*A*S*H",
"genre",
"Black_comedy"
],
[
"M*A*S*H",
"genre",
"Satire"
],
[
"M*A*S*H",
"genre",
"Sitcom"
],
[
"Mary_and_Max",
"genre",
"Black_comedy"
],
[
"Mary_and_Max",
"genre",
"Stop_motion"
],
[
"Matt_Stone",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Mike_Henry",
"award_nominee",
"Seth_MacFarlane"
],
[
"Mike_Henry",
"program",
"Family_Guy"
],
[
"Mike_Henry",
"program",
"The_Cleveland_Show"
],
[
"Network",
"genre",
"Black_comedy"
],
[
"Network",
"genre",
"Satire"
],
[
"Nine",
"award_winner",
"The_Weinstein_Company"
],
[
"Nine",
"film_festivals",
"2010_Berlin_International_Film_Festival"
],
[
"Oh!_What_a_Lovely_War",
"genre",
"Black_comedy"
],
[
"Oh!_What_a_Lovely_War",
"genre",
"Satire"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"award_winner",
"Matt_Stone"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"American_Dad!"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"Robot_Chicken"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"South_Park"
],
[
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"award_winner",
"Seth_Green"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"nominated_for",
"Robot_Chicken"
],
[
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation",
"nominated_for",
"SpongeBob_SquarePants"
],
[
"Robot_Chicken",
"actor",
"Mike_Henry"
],
[
"Robot_Chicken",
"actor",
"Seth_Green"
],
[
"Robot_Chicken",
"award_honor_award",
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation"
],
[
"Robot_Chicken",
"award_winner",
"Seth_Green"
],
[
"Robot_Chicken",
"genre",
"Black_comedy"
],
[
"Robot_Chicken",
"genre",
"Satire"
],
[
"Robot_Chicken",
"genre",
"Sitcom"
],
[
"Robot_Chicken",
"genre",
"Stop_motion"
],
[
"Scrooged",
"genre",
"Black_comedy"
],
[
"Scrooged",
"genre",
"Satire"
],
[
"Seth_Green",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Seth_Green",
"award",
"Primetime_Emmy_Award_for_Outstanding_Short-format_Animation"
],
[
"Seth_Green",
"award_nominee",
"Matt_Stone"
],
[
"Seth_Green",
"nominated_for",
"Robot_Chicken"
],
[
"Seth_Green",
"nominated_for",
"South_Park"
],
[
"Seth_Green",
"organizations_founded",
"Adult_Swim"
],
[
"Seth_Green",
"program",
"Robot_Chicken"
],
[
"Seth_Green",
"tv_program",
"Robot_Chicken"
],
[
"Seth_MacFarlane",
"award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"Seth_MacFarlane",
"award_nominee",
"Mike_Henry"
],
[
"South_Park",
"award_honor_award",
"Primetime_Emmy_Award_for_Outstanding_Animated_Program_(for_Programming_Less_Than_One_Hour)"
],
[
"South_Park",
"genre",
"Black_comedy"
],
[
"South_Park",
"genre",
"Satire"
],
[
"South_Park",
"genre",
"Sitcom"
],
[
"South_Park:_Bigger,_Longer_&_Uncut",
"genre",
"Black_comedy"
],
[
"South_Park:_Bigger,_Longer_&_Uncut",
"genre",
"Satire"
],
[
"SpongeBob_SquarePants",
"genre",
"Black_comedy"
],
[
"SpongeBob_SquarePants",
"genre",
"Satire"
],
[
"SpongeBob_SquarePants",
"genre",
"Sitcom"
],
[
"Team_America:_World_Police",
"genre",
"Black_comedy"
],
[
"Team_America:_World_Police",
"genre",
"Satire"
],
[
"Thank_You_for_Smoking",
"genre",
"Black_comedy"
],
[
"Thank_You_for_Smoking",
"genre",
"Satire"
],
[
"The_Boondocks",
"genre",
"Black_comedy"
],
[
"The_Boondocks",
"genre",
"Satire"
],
[
"The_Boondocks",
"genre",
"Sitcom"
],
[
"The_Cable_Guy",
"genre",
"Black_comedy"
],
[
"The_Cable_Guy",
"genre",
"Satire"
],
[
"The_Cleveland_Show",
"actor",
"Mike_Henry"
],
[
"The_Cleveland_Show",
"genre",
"Black_comedy"
],
[
"The_Cleveland_Show",
"genre",
"Satire"
],
[
"The_Cleveland_Show",
"genre",
"Sitcom"
],
[
"The_Stepford_Wives",
"genre",
"Black_comedy"
],
[
"The_Stepford_Wives",
"genre",
"Satire"
],
[
"The_Weinstein_Company",
"film",
"Nine"
],
[
"The_Weinstein_Company",
"film",
"Youth_in_Revolt"
],
[
"The_White_Ribbon",
"film_festivals",
"2009_Toronto_International_Film_Festival"
],
[
"The_White_Ribbon",
"film_festivals",
"2010_Berlin_International_Film_Festival"
],
[
"Weeds",
"genre",
"Black_comedy"
],
[
"Weeds",
"genre",
"Satire"
],
[
"Yasser_Arafat",
"profession",
"Civil_engineer"
],
[
"Yasser_Arafat",
"religion",
"Islam"
],
[
"Youth_in_Revolt",
"film_festivals",
"2009_Toronto_International_Film_Festival"
],
[
"Youth_in_Revolt",
"film_festivals",
"2010_Berlin_International_Film_Festival"
],
[
"Youth_in_Revolt",
"genre",
"Black_comedy"
],
[
"Youth_in_Revolt",
"production_companies",
"Lionsgate_Entertainment"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
4235, 12th_Satellite_Awards
5250, 1952_Summer_Olympics
926, 2012
4161, Agatha_Christie
3669, Alan_Moore
2190, Albert_Wolsky
3821, Aldous_Huxley
9618, Americas
2908, Andes
10288, Artistic_gymnastics
3079, Austin_Powers:_Goldmember
14123, Back_to_the_Future
12546, Back_to_the_Future_Part_II
2804, Back_to_the_Future_Part_III
7858, Bahrain
1128, Bolivia
10817, Bronze_medal
5139, C._S._Lewis
12938, Carnegie_Medal_in_Literature
10741, Carolina_RailHawks
3022, Charles_Dickens
12800, Chris_Nurse
1038, Christopher_Hitchens
5918, Click
3986, Clive_Barker
10502, Cloud_Atlas
10659, Colleen_Atwood
7411, Crouching_Tiger,_Hidden_Dragon
4159, Curse_of_the_Golden_Flower
11628, Cycling
1013, Dean_Koontz
9479, Edgar_Allan_Poe
3334, English_people
314, Exeter_College,_Oxford
9096, Fast_Five
10198, Fencing
2074, Fiction
13463, Franz_Kafka
8393, From_Hell
9088, G._K._Chesterton
12368, Gene_Wolfe
5701, Gold_medal
58, Grant_Morrison
3031, Guatemala
498, Guyana
13074, H._G._Wells
11379, H._P._Lovecraft
13331, Harry_Potter_and_the_Chamber_of_Secrets
8058, Harry_Potter_and_the_Goblet_of_Fire
10188, Harry_Potter_and_the_Half-Blood_Prince
9497, Harry_Potter_and_the_Order_of_the_Phoenix
8887, Harry_Potter_and_the_Philosopher's_Stone
2822, Harry_Potter_and_the_Prisoner_of_Azkaban
3671, Herman_Melville
3809, House_of_Flying_Daggers
2646, Hulk
10842, Indiana_Jones_and_the_Kingdom_of_the_Crystal_Skull
13696, Iron_Man
12099, Iron_Man_2
8319, J._K._Rowling
3579, J._R._R._Tolkien
623, Jean_Cocteau
11806, John_Milton
1400, Jonathan_Swift
12994, Jorge_Luis_Borges
3980, Judo
6708, Latin_America
12139, Locus_Award_for_Best_Fantasy_Novel
6042, Locus_Award_for_Best_Science_Fiction_Novel
4119, Marit_Allen
7025, Milena_Canonero
6899, Modern_pentathlon
3632, Moulin_Rouge!
11536, Nebula_Award_for_Best_Short_Story
1972, Neil_Gaiman
7653, Nine
113, Nobel_Prize_in_Literature
8594, North_America-US
10455, Oscar_Wilde
11369, Panama
1498, Paraguay
7505, Paul_Auster
1935, Philip_Pullman
10744, Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl
5184, Planet_of_the_Apes
4108, Pleasantville
9985, Poet
7734, Prometheus_Hall_of_Fame_Award
4331, Red_Cliff
4869, Republic
10889, Richard_Taylor
424, Road_cycling
13947, Robert_E._Howard
4514, Robert_Louis_Stevenson
767, Rowing
3834, Rudyard_Kipling
9777, Sailing
7442, Sandy_Powell
57, Satellite_Award_for_Best_Costume_Design
13584, Saturn_Award_for_Best_Costume
11241, Sherlock_Holmes
5910, Sherlock_Holmes:_A_Game_of_Shadows
3506, Signs
6332, Silver_medal
6778, Sleepy_Hollow
14036, South_America
6525, Spirited_Away
8596, Star_Wars_Episode_II:_Attack_of_the_Clones
6829, Stephen_King
5102, Syd_Barrett
8475, T._S._Eliot
10860, Table_tennis
5418, The_Chronicles_of_Narnia:_Prince_Caspian
2906, The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe
13897, The_Chronicles_of_Narnia:_The_Voyage_of_the_Dawn_Treader
1409, The_Golden_Compass
8079, The_League_of_Extraordinary_Gentlemen
5178, The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring
6040, The_Phantom_of_the_Opera
12895, Thomas_Pynchon
4766, Unitary_state
2977, University_of_Oxford
4882, Ursula_K._Le_Guin
11139, Uruguay
1600, V_for_Vendetta
41, Venezuela
5238, Viggo_Mortensen
13832, Visual_Effects_Art_Director
3087, W._H._Auden
9253, Watchmen
10728, William_Blake
13174, William_Morris
8169, William_S._Burroughs
13284, William_Shakespeare
6951, World_Fantasy_Award_for_Best_Novel
8336, World_Fantasy_Award_for_Best_Novella
4674, World_Trade_Organization
src, edge_attr, dst
4235, award_winner, 5238
5250, participating_countries, 3031
5250, participating_countries, 11139
5250, participating_countries, 41
926, film_release_region, 3031
926, film_release_region, 11369
926, film_release_region, 11139
926, film_release_region, 41
4161, influenced_by, 9088
4161, profession, 9985
3669, award, 6042
3669, award, 7734
3669, award, 8336
3669, influenced_by, 3986
3669, influenced_by, 9479
3669, influenced_by, 13074
3669, influenced_by, 11379
3669, influenced_by, 12895
3669, influenced_by, 10728
3669, influenced_by, 8169
3669, peers, 58
2190, award, 57
2190, award, 13584
3821, award, 113
3821, influenced_by, 3022
3821, influenced_by, 13074
3821, influenced_by, 10728
9618, contains, 1128
9618, contains, 3031
9618, contains, 11369
9618, contains, 11139
9618, contains, 41
10288, country, 3031
10288, country, 41
14123, genre, 2074
12546, genre, 2074
2804, genre, 2074
7858, medal, 10817
7858, medal, 5701
1128, adjoins, 1498
1128, form_of_government, 4869
1128, form_of_government, 4766
1128, partially_contains, 2908
5139, award, 7734
5139, friend, 3579
5139, influenced_by, 9088
5139, influenced_by, 13074
5139, influenced_by, 3579
5139, influenced_by, 11806
5139, influenced_by, 10728
5139, influenced_by, 13174
12938, award_winner, 5139
12938, award_winner, 1935
12800, nationality, 498
12800, team, 10741
1038, influenced_by, 3821
1038, influenced_by, 12994
5918, film_release_region, 11369
5918, film_release_region, 41
3986, award, 12139
3986, award, 8336
3986, influenced_by, 9479
3986, influenced_by, 11379
3986, influenced_by, 623
3986, influenced_by, 6829
3986, influenced_by, 10728
3986, influenced_by, 8169
10502, film_crew_role, 13832
10659, award, 57
10659, award, 13584
7411, film_release_region, 41
4159, award_honor_award, 13584
11628, country, 3031
11628, country, 41
1013, influenced_by, 5139
1013, influenced_by, 9088
1013, profession, 9985
9479, profession, 9985
3334, people, 3669
3334, people, 3022
3334, people, 3986
3334, people, 3579
3334, people, 4119
3334, people, 1972
3334, people, 3087
3334, people, 10728
3334, people, 13284
314, student, 3579
314, student, 1935
9096, film_release_region, 11369
9096, film_release_region, 41
10198, country, 11369
10198, country, 41
13463, influenced_by, 9088
8393, story_by, 3669
9088, award, 113
9088, influenced_by, 3022
9088, influenced_by, 4514
9088, influenced_by, 10728
12368, influenced_by, 9088
12368, influenced_by, 3579
12368, influenced_by, 12994
58, influenced_by, 3669
58, influenced_by, 12994
58, peers, 3669
3031, form_of_government, 4766
3031, medal, 6332
3031, olympics, 5250
498, adjoins, 41
11379, profession, 9985
13331, genre, 2074
8058, genre, 2074
10188, genre, 2074
9497, film_crew_role, 13832
9497, genre, 2074
8887, genre, 2074
2822, genre, 2074
3671, influenced_by, 11806
3671, profession, 9985
3809, film_release_region, 11139
3809, film_release_region, 41
2646, film_crew_role, 13832
2646, film_release_region, 7858
2646, film_release_region, 11369
10842, award_honor_award, 13584
10842, film_crew_role, 13832
13696, film_crew_role, 13832
13696, film_release_region, 11369
13696, film_release_region, 11139
13696, film_release_region, 41
13696, genre, 2074
12099, film_release_region, 7858
12099, film_release_region, 11369
12099, film_release_region, 11139
12099, genre, 2074
8319, influenced_by, 5139
8319, influenced_by, 9088
3579, award, 12139
3579, award, 7734
3579, friend, 5139
3579, influenced_by, 9088
3579, influenced_by, 13947
3579, influenced_by, 13174
3579, peers, 5139
623, profession, 9985
11806, influenced_by, 13284
11806, profession, 9985
1400, profession, 9985
12994, award, 11536
12994, influenced_by, 9479
12994, influenced_by, 13463
12994, influenced_by, 9088
12994, influenced_by, 13074
12994, influenced_by, 11379
12994, influenced_by, 3671
12994, influenced_by, 1400
12994, influenced_by, 10455
12994, influenced_by, 4514
12994, influenced_by, 3834
12994, influenced_by, 10728
12994, influenced_by, 13284
12994, location_of_ceremony, 1498
12994, profession, 9985
3980, country, 1128
3980, country, 3031
3980, country, 11369
3980, country, 11139
3980, country, 41
6708, contains, 1128
6708, contains, 3031
6708, contains, 11369
6708, contains, 41
12139, award_winner, 3579
12139, disciplines_or_subjects, 2074
6042, disciplines_or_subjects, 2074
4119, award, 57
4119, award, 13584
7025, award, 57
7025, award, 13584
6899, country, 3031
6899, country, 41
3632, award_honor_award, 57
11536, disciplines_or_subjects, 2074
1972, influenced_by, 3669
1972, influenced_by, 5139
1972, influenced_by, 3986
1972, influenced_by, 9088
1972, influenced_by, 3579
1972, influenced_by, 12994
8594, contains, 3031
8594, contains, 11369
8594, countries_within, 3031
8594, countries_within, 11369
10455, profession, 9985
11369, form_of_government, 4766
11369, medal, 10817
11369, medal, 5701
1498, adjoins, 1128
7505, influenced_by, 12994
7505, profession, 9985
1935, award, 12938
1935, award, 12139
1935, award, 6951
1935, influenced_by, 11806
1935, influenced_by, 10728
10744, award_honor_award, 13584
10744, film_release_region, 7858
10744, film_release_region, 11369
10744, film_release_region, 11139
10744, film_release_region, 41
7734, award_winner, 3669
7734, award_winner, 3579
7734, disciplines_or_subjects, 2074
10889, award, 57
10889, award, 13584
10889, nominated_for, 5178
424, country, 3031
424, country, 11139
424, country, 41
13947, influenced_by, 9088
4514, profession, 9985
767, country, 11139
767, country, 41
3834, profession, 9985
9777, country, 3031
9777, country, 11139
9777, country, 41
7442, award, 57
7442, award, 13584
57, ceremony, 4235
57, nominated_for, 3079
57, nominated_for, 10502
57, nominated_for, 7411
57, nominated_for, 4159
57, nominated_for, 8393
57, nominated_for, 8058
57, nominated_for, 3809
57, nominated_for, 7653
57, nominated_for, 10744
57, nominated_for, 5184
57, nominated_for, 4108
57, nominated_for, 4331
57, nominated_for, 6778
57, nominated_for, 8596
57, nominated_for, 5178
57, nominated_for, 6040
13584, award_winner, 10659
13584, award_winner, 10889
13584, award_winner, 7442
13584, nominated_for, 3079
13584, nominated_for, 14123
13584, nominated_for, 12546
13584, nominated_for, 2804
13584, nominated_for, 7411
13584, nominated_for, 8393
13584, nominated_for, 13331
13584, nominated_for, 8058
13584, nominated_for, 10188
13584, nominated_for, 9497
13584, nominated_for, 8887
13584, nominated_for, 2822
13584, nominated_for, 3809
13584, nominated_for, 3632
13584, nominated_for, 7653
13584, nominated_for, 10744
13584, nominated_for, 5184
13584, nominated_for, 4108
13584, nominated_for, 4331
13584, nominated_for, 11241
13584, nominated_for, 5910
13584, nominated_for, 6778
13584, nominated_for, 5418
13584, nominated_for, 2906
13584, nominated_for, 1409
13584, nominated_for, 8079
13584, nominated_for, 5178
13584, nominated_for, 6040
13584, nominated_for, 1600
13584, nominated_for, 9253
11241, film_crew_role, 13832
11241, film_release_region, 7858
11241, film_release_region, 11369
5910, film_release_region, 11369
3506, film_release_region, 11369
3506, film_release_region, 41
6778, film_crew_role, 13832
14036, contains, 1128
14036, contains, 11139
14036, contains, 41
6525, film_release_region, 7858
6525, film_release_region, 11369
6525, film_release_region, 41
8596, film_crew_role, 13832
6829, influenced_by, 3579
5102, influenced_by, 5139
5102, influenced_by, 3579
8475, influenced_by, 9088
8475, influenced_by, 11806
8475, profession, 9985
10860, country, 1128
10860, country, 41
5418, film_crew_role, 13832
5418, story_by, 5139
2906, award_honor_award, 13584
2906, crewmember, 10889
2906, film_crew_role, 13832
2906, story_by, 5139
13897, film_crew_role, 13832
13897, story_by, 5139
1409, film_crew_role, 13832
1409, film_release_region, 11369
1409, film_release_region, 41
1409, story_by, 1935
8079, film_crew_role, 13832
8079, story_by, 3669
5178, award_winner, 10889
5178, costume_design_by, 10889
5178, crewmember, 10889
5178, film_crew_role, 13832
5178, film_release_region, 7858
5178, film_release_region, 1128
5178, film_release_region, 3031
5178, film_release_region, 11369
5178, film_release_region, 11139
5178, film_release_region, 41
5178, genre, 2074
5178, story_by, 3579
12895, influenced_by, 12994
2977, student, 3821
2977, student, 5139
2977, student, 3579
2977, student, 1935
4882, influenced_by, 3579
4882, influenced_by, 12994
11139, form_of_government, 4869
11139, form_of_government, 4766
11139, medal, 10817
11139, medal, 6332
11139, olympics, 5250
1600, film_release_region, 11369
1600, story_by, 3669
41, adjoins, 498
41, form_of_government, 4869
41, medal, 10817
41, medal, 5701
41, medal, 6332
41, olympics, 5250
41, partially_contains, 2908
5238, acted_in, 5178
5238, location, 14036
5238, location, 41
5238, nominated_for, 5178
5238, profession, 9985
3087, profession, 9985
9253, film_crew_role, 13832
9253, story_by, 3669
10728, influenced_by, 11806
10728, profession, 9985
13284, profession, 9985
6951, disciplines_or_subjects, 2074
8336, disciplines_or_subjects, 2074
4674, member_states, 7858
4674, member_states, 1128
4674, member_states, 3031
4674, member_states, 11369
4674, member_states, 11139
4674, member_states, 41
Question: How are Carolina_RailHawks, The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring, and William_Blake related?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Carolina_RailHawks",
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"William_Blake"
],
"valid_edges": [
[
"12th_Satellite_Awards",
"award_winner",
"Viggo_Mortensen"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Guatemala"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Uruguay"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Venezuela"
],
[
"2012",
"film_release_region",
"Guatemala"
],
[
"2012",
"film_release_region",
"Panama"
],
[
"2012",
"film_release_region",
"Uruguay"
],
[
"2012",
"film_release_region",
"Venezuela"
],
[
"Agatha_Christie",
"influenced_by",
"G._K._Chesterton"
],
[
"Agatha_Christie",
"profession",
"Poet"
],
[
"Alan_Moore",
"award",
"Locus_Award_for_Best_Science_Fiction_Novel"
],
[
"Alan_Moore",
"award",
"Prometheus_Hall_of_Fame_Award"
],
[
"Alan_Moore",
"award",
"World_Fantasy_Award_for_Best_Novella"
],
[
"Alan_Moore",
"influenced_by",
"Clive_Barker"
],
[
"Alan_Moore",
"influenced_by",
"Edgar_Allan_Poe"
],
[
"Alan_Moore",
"influenced_by",
"H._G._Wells"
],
[
"Alan_Moore",
"influenced_by",
"H._P._Lovecraft"
],
[
"Alan_Moore",
"influenced_by",
"Thomas_Pynchon"
],
[
"Alan_Moore",
"influenced_by",
"William_Blake"
],
[
"Alan_Moore",
"influenced_by",
"William_S._Burroughs"
],
[
"Alan_Moore",
"peers",
"Grant_Morrison"
],
[
"Albert_Wolsky",
"award",
"Satellite_Award_for_Best_Costume_Design"
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],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Order_of_the_Phoenix"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Philosopher's_Stone"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Harry_Potter_and_the_Prisoner_of_Azkaban"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"House_of_Flying_Daggers"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Moulin_Rouge!"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Nine"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Pirates_of_the_Caribbean:_The_Curse_of_the_Black_Pearl"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Planet_of_the_Apes"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Pleasantville"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Red_Cliff"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Sherlock_Holmes"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Sherlock_Holmes:_A_Game_of_Shadows"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Sleepy_Hollow"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Chronicles_of_Narnia:_Prince_Caspian"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Golden_Compass"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_League_of_Extraordinary_Gentlemen"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"The_Phantom_of_the_Opera"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"V_for_Vendetta"
],
[
"Saturn_Award_for_Best_Costume",
"nominated_for",
"Watchmen"
],
[
"Sherlock_Holmes",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"Sherlock_Holmes",
"film_release_region",
"Bahrain"
],
[
"Sherlock_Holmes",
"film_release_region",
"Panama"
],
[
"Sherlock_Holmes:_A_Game_of_Shadows",
"film_release_region",
"Panama"
],
[
"Signs",
"film_release_region",
"Panama"
],
[
"Signs",
"film_release_region",
"Venezuela"
],
[
"Sleepy_Hollow",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"South_America",
"contains",
"Bolivia"
],
[
"South_America",
"contains",
"Uruguay"
],
[
"South_America",
"contains",
"Venezuela"
],
[
"Spirited_Away",
"film_release_region",
"Bahrain"
],
[
"Spirited_Away",
"film_release_region",
"Panama"
],
[
"Spirited_Away",
"film_release_region",
"Venezuela"
],
[
"Star_Wars_Episode_II:_Attack_of_the_Clones",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"Stephen_King",
"influenced_by",
"J._R._R._Tolkien"
],
[
"Syd_Barrett",
"influenced_by",
"C._S._Lewis"
],
[
"Syd_Barrett",
"influenced_by",
"J._R._R._Tolkien"
],
[
"T._S._Eliot",
"influenced_by",
"G._K._Chesterton"
],
[
"T._S._Eliot",
"influenced_by",
"John_Milton"
],
[
"T._S._Eliot",
"profession",
"Poet"
],
[
"Table_tennis",
"country",
"Bolivia"
],
[
"Table_tennis",
"country",
"Venezuela"
],
[
"The_Chronicles_of_Narnia:_Prince_Caspian",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_Chronicles_of_Narnia:_Prince_Caspian",
"story_by",
"C._S._Lewis"
],
[
"The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe",
"award_honor_award",
"Saturn_Award_for_Best_Costume"
],
[
"The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe",
"crewmember",
"Richard_Taylor"
],
[
"The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_Chronicles_of_Narnia:_The_Lion,_the_Witch_and_the_Wardrobe",
"story_by",
"C._S._Lewis"
],
[
"The_Chronicles_of_Narnia:_The_Voyage_of_the_Dawn_Treader",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_Chronicles_of_Narnia:_The_Voyage_of_the_Dawn_Treader",
"story_by",
"C._S._Lewis"
],
[
"The_Golden_Compass",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_Golden_Compass",
"film_release_region",
"Panama"
],
[
"The_Golden_Compass",
"film_release_region",
"Venezuela"
],
[
"The_Golden_Compass",
"story_by",
"Philip_Pullman"
],
[
"The_League_of_Extraordinary_Gentlemen",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_League_of_Extraordinary_Gentlemen",
"story_by",
"Alan_Moore"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"award_winner",
"Richard_Taylor"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"costume_design_by",
"Richard_Taylor"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"crewmember",
"Richard_Taylor"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Bahrain"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Bolivia"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Guatemala"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Panama"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Uruguay"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"film_release_region",
"Venezuela"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"genre",
"Fiction"
],
[
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring",
"story_by",
"J._R._R._Tolkien"
],
[
"Thomas_Pynchon",
"influenced_by",
"Jorge_Luis_Borges"
],
[
"University_of_Oxford",
"student",
"Aldous_Huxley"
],
[
"University_of_Oxford",
"student",
"C._S._Lewis"
],
[
"University_of_Oxford",
"student",
"J._R._R._Tolkien"
],
[
"University_of_Oxford",
"student",
"Philip_Pullman"
],
[
"Ursula_K._Le_Guin",
"influenced_by",
"J._R._R._Tolkien"
],
[
"Ursula_K._Le_Guin",
"influenced_by",
"Jorge_Luis_Borges"
],
[
"Uruguay",
"form_of_government",
"Republic"
],
[
"Uruguay",
"form_of_government",
"Unitary_state"
],
[
"Uruguay",
"medal",
"Bronze_medal"
],
[
"Uruguay",
"medal",
"Silver_medal"
],
[
"Uruguay",
"olympics",
"1952_Summer_Olympics"
],
[
"V_for_Vendetta",
"film_release_region",
"Panama"
],
[
"V_for_Vendetta",
"story_by",
"Alan_Moore"
],
[
"Venezuela",
"adjoins",
"Guyana"
],
[
"Venezuela",
"form_of_government",
"Republic"
],
[
"Venezuela",
"medal",
"Bronze_medal"
],
[
"Venezuela",
"medal",
"Gold_medal"
],
[
"Venezuela",
"medal",
"Silver_medal"
],
[
"Venezuela",
"olympics",
"1952_Summer_Olympics"
],
[
"Venezuela",
"partially_contains",
"Andes"
],
[
"Viggo_Mortensen",
"acted_in",
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring"
],
[
"Viggo_Mortensen",
"location",
"South_America"
],
[
"Viggo_Mortensen",
"location",
"Venezuela"
],
[
"Viggo_Mortensen",
"nominated_for",
"The_Lord_of_the_Rings:_The_Fellowship_of_the_Ring"
],
[
"Viggo_Mortensen",
"profession",
"Poet"
],
[
"W._H._Auden",
"profession",
"Poet"
],
[
"Watchmen",
"film_crew_role",
"Visual_Effects_Art_Director"
],
[
"Watchmen",
"story_by",
"Alan_Moore"
],
[
"William_Blake",
"influenced_by",
"John_Milton"
],
[
"William_Blake",
"profession",
"Poet"
],
[
"William_Shakespeare",
"profession",
"Poet"
],
[
"World_Fantasy_Award_for_Best_Novel",
"disciplines_or_subjects",
"Fiction"
],
[
"World_Fantasy_Award_for_Best_Novella",
"disciplines_or_subjects",
"Fiction"
],
[
"World_Trade_Organization",
"member_states",
"Bahrain"
],
[
"World_Trade_Organization",
"member_states",
"Bolivia"
],
[
"World_Trade_Organization",
"member_states",
"Guatemala"
],
[
"World_Trade_Organization",
"member_states",
"Panama"
],
[
"World_Trade_Organization",
"member_states",
"Uruguay"
],
[
"World_Trade_Organization",
"member_states",
"Venezuela"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
7898, 1900_Summer_Olympics
3309, 1908_Summer_Olympics
7962, 1912_Summer_Olympics
9784, 1920_Summer_Olympics
4416, 1924_Summer_Olympics
7085, 1928_Summer_Olympics
11367, 1936_Summer_Olympics
11590, 1948_Summer_Olympics
5250, 1952_Summer_Olympics
12466, 1956_Summer_Olympics
5561, 1960_Summer_Olympics
8933, 1964_Summer_Olympics
2827, 1968_Summer_Olympics
7928, 1972_Summer_Olympics
4549, 1976_Summer_Olympics
680, 1980_Summer_Olympics
6985, 1984_Summer_Olympics
4829, 1988_Summer_Olympics
7439, 1992_Summer_Olympics
6286, 1996_Summer_Olympics
5468, 2000_Summer_Olympics
1970, 2004_Summer_Olympics
5259, 2008_Summer_Olympics
446, 2012_Summer_Olympics
10565, Australia
5282, Australia_national_association_football_team
9704, Black_Robe
7647, Brazil
11678, Canada
7754, Canada_men's_national_soccer_team
5715, Defender
14063, Exeter_City_F.C.
10308, Football
230, France
3252, Germany
10624, KwaZulu-Natal
3605, Mexico
7327, Netherlands
8723, New_Zealand
12212, Poland
10977, South_Africa
7771, South_Africa_national_football_team
src, edge_attr, dst
7898, participating_countries, 10565
7898, participating_countries, 11678
9784, participating_countries, 11678
11367, participating_countries, 10565
11367, participating_countries, 11678
11367, participating_countries, 10977
5250, participating_countries, 10565
5250, participating_countries, 11678
5468, participating_countries, 10565
1970, participating_countries, 10565
5259, participating_countries, 10565
5259, participating_countries, 11678
446, participating_countries, 10565
10565, adjoins, 8723
10565, combatants, 7647
10565, combatants, 11678
10565, combatants, 3252
10565, combatants, 3605
10565, combatants, 7327
10565, combatants, 8723
10565, combatants, 12212
10565, film_country, 10565
10565, film_country, 8723
10565, olympics, 7898
10565, olympics, 9784
10565, olympics, 4416
10565, olympics, 7085
10565, olympics, 11367
10565, olympics, 11590
10565, olympics, 5250
10565, olympics, 12466
10565, olympics, 5561
10565, olympics, 8933
10565, olympics, 2827
10565, olympics, 7928
10565, olympics, 4549
10565, olympics, 680
10565, olympics, 6985
10565, olympics, 4829
10565, olympics, 7439
10565, olympics, 6286
10565, olympics, 5468
10565, olympics, 1970
10565, olympics, 5259
10565, olympics, 446
10565, teams, 5282
5282, position, 5715
9704, film_country, 10565
9704, film_country, 11678
7647, combatants, 11678
7647, combatants, 10977
7647, film_release_region, 10565
11678, combatants, 10565
11678, combatants, 7647
11678, combatants, 3252
11678, combatants, 3605
11678, combatants, 8723
11678, combatants, 12212
11678, combatants, 10977
11678, olympics, 7898
11678, olympics, 3309
11678, olympics, 7962
11678, olympics, 9784
11678, olympics, 4416
11678, olympics, 7085
11678, olympics, 11367
11678, olympics, 11590
11678, olympics, 5250
11678, olympics, 12466
11678, olympics, 8933
11678, olympics, 2827
11678, olympics, 7928
11678, olympics, 4549
11678, olympics, 680
11678, olympics, 6985
11678, olympics, 4829
11678, olympics, 7439
11678, olympics, 6286
11678, olympics, 5468
11678, olympics, 1970
11678, olympics, 5259
11678, olympics, 446
11678, teams, 7754
7754, football_roster_position, 5715
7754, position, 5715
5715, team, 5282
5715, team, 7754
5715, team, 14063
5715, team, 7771
14063, football_roster_position, 5715
14063, position, 5715
10308, country, 10565
10308, country, 11678
10308, country, 10977
230, combatants, 10565
230, combatants, 11678
230, combatants, 10977
3252, combatants, 10565
3252, combatants, 11678
10624, administrative_parent, 10977
10624, country, 10977
3605, combatants, 10565
3605, combatants, 11678
3605, combatants, 10977
7327, combatants, 10565
7327, combatants, 11678
7327, combatants, 10977
8723, adjoins, 10565
8723, combatants, 10565
8723, combatants, 11678
8723, combatants, 10977
8723, exported_to, 10565
12212, combatants, 10565
12212, combatants, 11678
12212, combatants, 10977
10977, combatants, 10565
10977, combatants, 7647
10977, combatants, 11678
10977, combatants, 230
10977, combatants, 3252
10977, combatants, 3605
10977, combatants, 7327
10977, combatants, 12212
10977, contains, 10624
10977, olympics, 3309
10977, olympics, 7962
10977, olympics, 9784
10977, olympics, 4416
10977, olympics, 7085
10977, olympics, 11367
10977, olympics, 11590
10977, olympics, 5250
10977, olympics, 12466
10977, olympics, 5561
10977, olympics, 7439
10977, olympics, 6286
10977, olympics, 5468
10977, olympics, 1970
10977, olympics, 5259
10977, olympics, 446
10977, teams, 7771
7771, football_roster_position, 5715
7771, position, 5715
Question: In what context are Black_Robe, Exeter_City_F.C., and KwaZulu-Natal connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Black_Robe",
"Exeter_City_F.C.",
"KwaZulu-Natal"
],
"valid_edges": [
[
"1900_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"1900_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1920_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1936_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"1936_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"1936_Summer_Olympics",
"participating_countries",
"South_Africa"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"1952_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"2000_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"2004_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"2008_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"2008_Summer_Olympics",
"participating_countries",
"Canada"
],
[
"2012_Summer_Olympics",
"participating_countries",
"Australia"
],
[
"Australia",
"adjoins",
"New_Zealand"
],
[
"Australia",
"combatants",
"Brazil"
],
[
"Australia",
"combatants",
"Canada"
],
[
"Australia",
"combatants",
"Germany"
],
[
"Australia",
"combatants",
"Mexico"
],
[
"Australia",
"combatants",
"Netherlands"
],
[
"Australia",
"combatants",
"New_Zealand"
],
[
"Australia",
"combatants",
"Poland"
],
[
"Australia",
"film_country",
"Australia"
],
[
"Australia",
"film_country",
"New_Zealand"
],
[
"Australia",
"olympics",
"1900_Summer_Olympics"
],
[
"Australia",
"olympics",
"1920_Summer_Olympics"
],
[
"Australia",
"olympics",
"1924_Summer_Olympics"
],
[
"Australia",
"olympics",
"1928_Summer_Olympics"
],
[
"Australia",
"olympics",
"1936_Summer_Olympics"
],
[
"Australia",
"olympics",
"1948_Summer_Olympics"
],
[
"Australia",
"olympics",
"1952_Summer_Olympics"
],
[
"Australia",
"olympics",
"1956_Summer_Olympics"
],
[
"Australia",
"olympics",
"1960_Summer_Olympics"
],
[
"Australia",
"olympics",
"1964_Summer_Olympics"
],
[
"Australia",
"olympics",
"1968_Summer_Olympics"
],
[
"Australia",
"olympics",
"1972_Summer_Olympics"
],
[
"Australia",
"olympics",
"1976_Summer_Olympics"
],
[
"Australia",
"olympics",
"1980_Summer_Olympics"
],
[
"Australia",
"olympics",
"1984_Summer_Olympics"
],
[
"Australia",
"olympics",
"1988_Summer_Olympics"
],
[
"Australia",
"olympics",
"1992_Summer_Olympics"
],
[
"Australia",
"olympics",
"1996_Summer_Olympics"
],
[
"Australia",
"olympics",
"2000_Summer_Olympics"
],
[
"Australia",
"olympics",
"2004_Summer_Olympics"
],
[
"Australia",
"olympics",
"2008_Summer_Olympics"
],
[
"Australia",
"olympics",
"2012_Summer_Olympics"
],
[
"Australia",
"teams",
"Australia_national_association_football_team"
],
[
"Australia_national_association_football_team",
"position",
"Defender"
],
[
"Black_Robe",
"film_country",
"Australia"
],
[
"Black_Robe",
"film_country",
"Canada"
],
[
"Brazil",
"combatants",
"Canada"
],
[
"Brazil",
"combatants",
"South_Africa"
],
[
"Brazil",
"film_release_region",
"Australia"
],
[
"Canada",
"combatants",
"Australia"
],
[
"Canada",
"combatants",
"Brazil"
],
[
"Canada",
"combatants",
"Germany"
],
[
"Canada",
"combatants",
"Mexico"
],
[
"Canada",
"combatants",
"New_Zealand"
],
[
"Canada",
"combatants",
"Poland"
],
[
"Canada",
"combatants",
"South_Africa"
],
[
"Canada",
"olympics",
"1900_Summer_Olympics"
],
[
"Canada",
"olympics",
"1908_Summer_Olympics"
],
[
"Canada",
"olympics",
"1912_Summer_Olympics"
],
[
"Canada",
"olympics",
"1920_Summer_Olympics"
],
[
"Canada",
"olympics",
"1924_Summer_Olympics"
],
[
"Canada",
"olympics",
"1928_Summer_Olympics"
],
[
"Canada",
"olympics",
"1936_Summer_Olympics"
],
[
"Canada",
"olympics",
"1948_Summer_Olympics"
],
[
"Canada",
"olympics",
"1952_Summer_Olympics"
],
[
"Canada",
"olympics",
"1956_Summer_Olympics"
],
[
"Canada",
"olympics",
"1964_Summer_Olympics"
],
[
"Canada",
"olympics",
"1968_Summer_Olympics"
],
[
"Canada",
"olympics",
"1972_Summer_Olympics"
],
[
"Canada",
"olympics",
"1976_Summer_Olympics"
],
[
"Canada",
"olympics",
"1980_Summer_Olympics"
],
[
"Canada",
"olympics",
"1984_Summer_Olympics"
],
[
"Canada",
"olympics",
"1988_Summer_Olympics"
],
[
"Canada",
"olympics",
"1992_Summer_Olympics"
],
[
"Canada",
"olympics",
"1996_Summer_Olympics"
],
[
"Canada",
"olympics",
"2000_Summer_Olympics"
],
[
"Canada",
"olympics",
"2004_Summer_Olympics"
],
[
"Canada",
"olympics",
"2008_Summer_Olympics"
],
[
"Canada",
"olympics",
"2012_Summer_Olympics"
],
[
"Canada",
"teams",
"Canada_men's_national_soccer_team"
],
[
"Canada_men's_national_soccer_team",
"football_roster_position",
"Defender"
],
[
"Canada_men's_national_soccer_team",
"position",
"Defender"
],
[
"Defender",
"team",
"Australia_national_association_football_team"
],
[
"Defender",
"team",
"Canada_men's_national_soccer_team"
],
[
"Defender",
"team",
"Exeter_City_F.C."
],
[
"Defender",
"team",
"South_Africa_national_football_team"
],
[
"Exeter_City_F.C.",
"football_roster_position",
"Defender"
],
[
"Exeter_City_F.C.",
"position",
"Defender"
],
[
"Football",
"country",
"Australia"
],
[
"Football",
"country",
"Canada"
],
[
"Football",
"country",
"South_Africa"
],
[
"France",
"combatants",
"Australia"
],
[
"France",
"combatants",
"Canada"
],
[
"France",
"combatants",
"South_Africa"
],
[
"Germany",
"combatants",
"Australia"
],
[
"Germany",
"combatants",
"Canada"
],
[
"KwaZulu-Natal",
"administrative_parent",
"South_Africa"
],
[
"KwaZulu-Natal",
"country",
"South_Africa"
],
[
"Mexico",
"combatants",
"Australia"
],
[
"Mexico",
"combatants",
"Canada"
],
[
"Mexico",
"combatants",
"South_Africa"
],
[
"Netherlands",
"combatants",
"Australia"
],
[
"Netherlands",
"combatants",
"Canada"
],
[
"Netherlands",
"combatants",
"South_Africa"
],
[
"New_Zealand",
"adjoins",
"Australia"
],
[
"New_Zealand",
"combatants",
"Australia"
],
[
"New_Zealand",
"combatants",
"Canada"
],
[
"New_Zealand",
"combatants",
"South_Africa"
],
[
"New_Zealand",
"exported_to",
"Australia"
],
[
"Poland",
"combatants",
"Australia"
],
[
"Poland",
"combatants",
"Canada"
],
[
"Poland",
"combatants",
"South_Africa"
],
[
"South_Africa",
"combatants",
"Australia"
],
[
"South_Africa",
"combatants",
"Brazil"
],
[
"South_Africa",
"combatants",
"Canada"
],
[
"South_Africa",
"combatants",
"France"
],
[
"South_Africa",
"combatants",
"Germany"
],
[
"South_Africa",
"combatants",
"Mexico"
],
[
"South_Africa",
"combatants",
"Netherlands"
],
[
"South_Africa",
"combatants",
"Poland"
],
[
"South_Africa",
"contains",
"KwaZulu-Natal"
],
[
"South_Africa",
"olympics",
"1908_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1912_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1920_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1924_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1928_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1936_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1948_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1952_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1956_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1960_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1992_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"1996_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"2000_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"2004_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"2008_Summer_Olympics"
],
[
"South_Africa",
"olympics",
"2012_Summer_Olympics"
],
[
"South_Africa",
"teams",
"South_Africa_national_football_team"
],
[
"South_Africa_national_football_team",
"football_roster_position",
"Defender"
],
[
"South_Africa_national_football_team",
"position",
"Defender"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
835, ADO_Den_Haag
8553, AZ
1098, Athletic_Bilbao
3801, Bohemian_F.C.
406, CFR_Cluj
6188, Chelsea_F.C.
12077, Chicago_Fire_Soccer_Club
2692, Clube_de_Regatas_do_Flamengo
392, Collingwood_Football_Club
2850, De_Graafschap
8952, Droylsden_F.C.
240, FC_Barcelona
3090, FC_Groningen
7533, FC_Levadia_Tallinn
13412, FC_Unirea_Urziceni
13098, FC_Utrecht
12719, FC_Zenit_Saint_Petersburg
2842, Feyenoord
12127, Forward
13450, Galatasaray_S.K.
7110, Heracles_Almelo
0, Liverpool_F.C.
1695, NAC_Breda
1938, Official_Website
11708, Olympique_de_Marseille
12035, Panionios_G.S.S.
5879, Roda_JC_Kerkrade
13029, Rugrats
8999, SC_Heerenveen
12909, Salavat_Yulaev_Ufa
5065, Shamrock_Rovers_F.C.
3395, Sociedade_Esportiva_Palmeiras
988, Sparta_Rotterdam
453, Vitesse
11193, Willem_II
4294, Windows_Vista
src, edge_attr, dst
835, football_roster_position, 12127
835, position, 12127
835, webpage_category, 1938
8553, position, 12127
8553, webpage_category, 1938
1098, position, 12127
1098, webpage_category, 1938
3801, football_roster_position, 12127
3801, position, 12127
3801, webpage_category, 1938
406, football_roster_position, 12127
406, position, 12127
406, webpage_category, 1938
6188, football_roster_position, 12127
6188, webpage_category, 1938
12077, football_roster_position, 12127
12077, position, 12127
12077, webpage_category, 1938
2692, football_roster_position, 12127
2692, position, 12127
2692, webpage_category, 1938
392, webpage_category, 1938
2850, position, 12127
2850, webpage_category, 1938
8952, football_roster_position, 12127
8952, position, 12127
8952, webpage_category, 1938
240, position, 12127
240, webpage_category, 1938
3090, football_roster_position, 12127
3090, position, 12127
3090, webpage_category, 1938
7533, football_roster_position, 12127
7533, position, 12127
7533, webpage_category, 1938
13412, football_roster_position, 12127
13412, position, 12127
13412, webpage_category, 1938
13098, football_roster_position, 12127
13098, position, 12127
13098, webpage_category, 1938
12719, football_roster_position, 12127
12719, webpage_category, 1938
2842, football_roster_position, 12127
2842, webpage_category, 1938
12127, team, 8553
12127, team, 1098
12127, team, 3801
12127, team, 406
12127, team, 6188
12127, team, 12077
12127, team, 2692
12127, team, 392
12127, team, 2850
12127, team, 8952
12127, team, 3090
12127, team, 7533
12127, team, 13412
12127, team, 13098
12127, team, 12719
12127, team, 2842
12127, team, 13450
12127, team, 7110
12127, team, 0
12127, team, 11708
12127, team, 12035
12127, team, 5879
12127, team, 12909
12127, team, 5065
12127, team, 3395
12127, team, 453
12127, team, 11193
13450, webpage_category, 1938
7110, football_roster_position, 12127
7110, webpage_category, 1938
0, football_roster_position, 12127
0, position, 12127
0, webpage_category, 1938
1695, football_roster_position, 12127
1695, position, 12127
1695, webpage_category, 1938
11708, football_roster_position, 12127
11708, position, 12127
11708, webpage_category, 1938
12035, football_roster_position, 12127
12035, position, 12127
5879, football_roster_position, 12127
5879, position, 12127
5879, webpage_category, 1938
13029, webpage_category, 1938
8999, position, 12127
8999, webpage_category, 1938
12909, hockey_position, 12127
12909, webpage_category, 1938
5065, football_roster_position, 12127
5065, position, 12127
5065, webpage_category, 1938
3395, football_roster_position, 12127
3395, position, 12127
3395, webpage_category, 1938
988, football_roster_position, 12127
988, position, 12127
988, webpage_category, 1938
453, football_roster_position, 12127
453, position, 12127
453, webpage_category, 1938
11193, football_roster_position, 12127
11193, position, 12127
11193, webpage_category, 1938
4294, webpage_category, 1938
Question: For what reason are Panionios_G.S.S., Rugrats, and Windows_Vista associated?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Panionios_G.S.S.",
"Rugrats",
"Windows_Vista"
],
"valid_edges": [
[
"ADO_Den_Haag",
"football_roster_position",
"Forward"
],
[
"ADO_Den_Haag",
"position",
"Forward"
],
[
"ADO_Den_Haag",
"webpage_category",
"Official_Website"
],
[
"AZ",
"position",
"Forward"
],
[
"AZ",
"webpage_category",
"Official_Website"
],
[
"Athletic_Bilbao",
"position",
"Forward"
],
[
"Athletic_Bilbao",
"webpage_category",
"Official_Website"
],
[
"Bohemian_F.C.",
"football_roster_position",
"Forward"
],
[
"Bohemian_F.C.",
"position",
"Forward"
],
[
"Bohemian_F.C.",
"webpage_category",
"Official_Website"
],
[
"CFR_Cluj",
"football_roster_position",
"Forward"
],
[
"CFR_Cluj",
"position",
"Forward"
],
[
"CFR_Cluj",
"webpage_category",
"Official_Website"
],
[
"Chelsea_F.C.",
"football_roster_position",
"Forward"
],
[
"Chelsea_F.C.",
"webpage_category",
"Official_Website"
],
[
"Chicago_Fire_Soccer_Club",
"football_roster_position",
"Forward"
],
[
"Chicago_Fire_Soccer_Club",
"position",
"Forward"
],
[
"Chicago_Fire_Soccer_Club",
"webpage_category",
"Official_Website"
],
[
"Clube_de_Regatas_do_Flamengo",
"football_roster_position",
"Forward"
],
[
"Clube_de_Regatas_do_Flamengo",
"position",
"Forward"
],
[
"Clube_de_Regatas_do_Flamengo",
"webpage_category",
"Official_Website"
],
[
"Collingwood_Football_Club",
"webpage_category",
"Official_Website"
],
[
"De_Graafschap",
"position",
"Forward"
],
[
"De_Graafschap",
"webpage_category",
"Official_Website"
],
[
"Droylsden_F.C.",
"football_roster_position",
"Forward"
],
[
"Droylsden_F.C.",
"position",
"Forward"
],
[
"Droylsden_F.C.",
"webpage_category",
"Official_Website"
],
[
"FC_Barcelona",
"position",
"Forward"
],
[
"FC_Barcelona",
"webpage_category",
"Official_Website"
],
[
"FC_Groningen",
"football_roster_position",
"Forward"
],
[
"FC_Groningen",
"position",
"Forward"
],
[
"FC_Groningen",
"webpage_category",
"Official_Website"
],
[
"FC_Levadia_Tallinn",
"football_roster_position",
"Forward"
],
[
"FC_Levadia_Tallinn",
"position",
"Forward"
],
[
"FC_Levadia_Tallinn",
"webpage_category",
"Official_Website"
],
[
"FC_Unirea_Urziceni",
"football_roster_position",
"Forward"
],
[
"FC_Unirea_Urziceni",
"position",
"Forward"
],
[
"FC_Unirea_Urziceni",
"webpage_category",
"Official_Website"
],
[
"FC_Utrecht",
"football_roster_position",
"Forward"
],
[
"FC_Utrecht",
"position",
"Forward"
],
[
"FC_Utrecht",
"webpage_category",
"Official_Website"
],
[
"FC_Zenit_Saint_Petersburg",
"football_roster_position",
"Forward"
],
[
"FC_Zenit_Saint_Petersburg",
"webpage_category",
"Official_Website"
],
[
"Feyenoord",
"football_roster_position",
"Forward"
],
[
"Feyenoord",
"webpage_category",
"Official_Website"
],
[
"Forward",
"team",
"AZ"
],
[
"Forward",
"team",
"Athletic_Bilbao"
],
[
"Forward",
"team",
"Bohemian_F.C."
],
[
"Forward",
"team",
"CFR_Cluj"
],
[
"Forward",
"team",
"Chelsea_F.C."
],
[
"Forward",
"team",
"Chicago_Fire_Soccer_Club"
],
[
"Forward",
"team",
"Clube_de_Regatas_do_Flamengo"
],
[
"Forward",
"team",
"Collingwood_Football_Club"
],
[
"Forward",
"team",
"De_Graafschap"
],
[
"Forward",
"team",
"Droylsden_F.C."
],
[
"Forward",
"team",
"FC_Groningen"
],
[
"Forward",
"team",
"FC_Levadia_Tallinn"
],
[
"Forward",
"team",
"FC_Unirea_Urziceni"
],
[
"Forward",
"team",
"FC_Utrecht"
],
[
"Forward",
"team",
"FC_Zenit_Saint_Petersburg"
],
[
"Forward",
"team",
"Feyenoord"
],
[
"Forward",
"team",
"Galatasaray_S.K."
],
[
"Forward",
"team",
"Heracles_Almelo"
],
[
"Forward",
"team",
"Liverpool_F.C."
],
[
"Forward",
"team",
"Olympique_de_Marseille"
],
[
"Forward",
"team",
"Panionios_G.S.S."
],
[
"Forward",
"team",
"Roda_JC_Kerkrade"
],
[
"Forward",
"team",
"Salavat_Yulaev_Ufa"
],
[
"Forward",
"team",
"Shamrock_Rovers_F.C."
],
[
"Forward",
"team",
"Sociedade_Esportiva_Palmeiras"
],
[
"Forward",
"team",
"Vitesse"
],
[
"Forward",
"team",
"Willem_II"
],
[
"Galatasaray_S.K.",
"webpage_category",
"Official_Website"
],
[
"Heracles_Almelo",
"football_roster_position",
"Forward"
],
[
"Heracles_Almelo",
"webpage_category",
"Official_Website"
],
[
"Liverpool_F.C.",
"football_roster_position",
"Forward"
],
[
"Liverpool_F.C.",
"position",
"Forward"
],
[
"Liverpool_F.C.",
"webpage_category",
"Official_Website"
],
[
"NAC_Breda",
"football_roster_position",
"Forward"
],
[
"NAC_Breda",
"position",
"Forward"
],
[
"NAC_Breda",
"webpage_category",
"Official_Website"
],
[
"Olympique_de_Marseille",
"football_roster_position",
"Forward"
],
[
"Olympique_de_Marseille",
"position",
"Forward"
],
[
"Olympique_de_Marseille",
"webpage_category",
"Official_Website"
],
[
"Panionios_G.S.S.",
"football_roster_position",
"Forward"
],
[
"Panionios_G.S.S.",
"position",
"Forward"
],
[
"Roda_JC_Kerkrade",
"football_roster_position",
"Forward"
],
[
"Roda_JC_Kerkrade",
"position",
"Forward"
],
[
"Roda_JC_Kerkrade",
"webpage_category",
"Official_Website"
],
[
"Rugrats",
"webpage_category",
"Official_Website"
],
[
"SC_Heerenveen",
"position",
"Forward"
],
[
"SC_Heerenveen",
"webpage_category",
"Official_Website"
],
[
"Salavat_Yulaev_Ufa",
"hockey_position",
"Forward"
],
[
"Salavat_Yulaev_Ufa",
"webpage_category",
"Official_Website"
],
[
"Shamrock_Rovers_F.C.",
"football_roster_position",
"Forward"
],
[
"Shamrock_Rovers_F.C.",
"position",
"Forward"
],
[
"Shamrock_Rovers_F.C.",
"webpage_category",
"Official_Website"
],
[
"Sociedade_Esportiva_Palmeiras",
"football_roster_position",
"Forward"
],
[
"Sociedade_Esportiva_Palmeiras",
"position",
"Forward"
],
[
"Sociedade_Esportiva_Palmeiras",
"webpage_category",
"Official_Website"
],
[
"Sparta_Rotterdam",
"football_roster_position",
"Forward"
],
[
"Sparta_Rotterdam",
"position",
"Forward"
],
[
"Sparta_Rotterdam",
"webpage_category",
"Official_Website"
],
[
"Vitesse",
"football_roster_position",
"Forward"
],
[
"Vitesse",
"position",
"Forward"
],
[
"Vitesse",
"webpage_category",
"Official_Website"
],
[
"Willem_II",
"football_roster_position",
"Forward"
],
[
"Willem_II",
"position",
"Forward"
],
[
"Willem_II",
"webpage_category",
"Official_Website"
],
[
"Windows_Vista",
"webpage_category",
"Official_Website"
]
]
}
|
FB15k-237
|
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 β no extra text):
PATH:
("subject"|predicate|"object")
...
END
Rules
- Use only listed edges; do NOT invent edges.
- Map IDs β 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
10677, Antonio_Banderas
9070, Computer_Animation
4874, EX_Machina
6303, Joely_Richardson
6485, John_Swasey
9289, Melanie_Griffith
176, Robert_Englund
13885, Royal_Academy_of_Dramatic_Art
13667, Shining_Through
2877, Shrek_Forever_After
7791, Swedish_American
src, edge_attr, dst
10677, acted_in, 2877
10677, participant, 9289
10677, spouse, 9289
4874, actor, 6485
4874, genre, 9070
6303, acted_in, 13667
9289, acted_in, 13667
9289, nominated_for, 13667
9289, participant, 10677
9289, spouse, 10677
13885, student, 6303
13885, student, 176
13667, award_winner, 9289
2877, genre, 9070
7791, people, 9289
7791, people, 176
Question: In what context are Antonio_Banderas, John_Swasey, and Royal_Academy_of_Dramatic_Art connected?
Your output must be ONLY the PATH block.
|
graph_path
|
{
"style": "rule"
}
|
{
"entities": [
"Antonio_Banderas",
"John_Swasey",
"Royal_Academy_of_Dramatic_Art"
],
"valid_edges": [
[
"Antonio_Banderas",
"acted_in",
"Shrek_Forever_After"
],
[
"Antonio_Banderas",
"participant",
"Melanie_Griffith"
],
[
"Antonio_Banderas",
"spouse",
"Melanie_Griffith"
],
[
"EX_Machina",
"actor",
"John_Swasey"
],
[
"EX_Machina",
"genre",
"Computer_Animation"
],
[
"Joely_Richardson",
"acted_in",
"Shining_Through"
],
[
"Melanie_Griffith",
"acted_in",
"Shining_Through"
],
[
"Melanie_Griffith",
"nominated_for",
"Shining_Through"
],
[
"Melanie_Griffith",
"participant",
"Antonio_Banderas"
],
[
"Melanie_Griffith",
"spouse",
"Antonio_Banderas"
],
[
"Royal_Academy_of_Dramatic_Art",
"student",
"Joely_Richardson"
],
[
"Royal_Academy_of_Dramatic_Art",
"student",
"Robert_Englund"
],
[
"Shining_Through",
"award_winner",
"Melanie_Griffith"
],
[
"Shrek_Forever_After",
"genre",
"Computer_Animation"
],
[
"Swedish_American",
"people",
"Melanie_Griffith"
],
[
"Swedish_American",
"people",
"Robert_Englund"
]
]
}
|
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