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The Project Gutenberg eBook of De Re Metallica, Translated from the First Latin Edition of 1556
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Title: De Re Metallica, Translated from the First Latin Edition of 1556
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Release date: November 14, 2011 [eBook #38015]
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Most recently updated: January 8, 2021
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Credits: Produced by Malcolm Farmer, Stephen H
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Sentoff and the
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Online Distributed Proofreading Team at https://www.pgdp.net
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Biographical Introduction, Annotations and Appendices upon
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the Development of Mining Methods, Metallurgical
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Processes, Geology, Mineralogy & Mining Law
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from the earliest times to the 16th Century
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A
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B
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Stanford University, Member American Institute of Mining Engineers,
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Mining and Metallurgical Society of America, Société des Ingéniéurs
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Civils de France, American Institute of Civil Engineers,
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Fellow Royal Geographical Society, etc., etc.
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A
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B
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Stanford University, Member American Association for the
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Advancement of Science, The National Geographical Society,
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Royal Scottish Geographical Society, etc., etc.
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The inspiration of whose teaching is no less great than his
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contribution to science.
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This New 1950 Edition of DE RE METALLICA is a complete and unchanged
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reprint of the translation published by The Mining Magazine, London, in
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1912
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It has been made available through the kind permission of
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Honorable Herbert C
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Hoover and Mr
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Edgar Rickard, Author and Publisher,
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respectively, of the original volume.
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PRINTED IN THE UNITED STATES OF AMERICA
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here are three objectives in translation of works of this character: to
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give a faithful, literal translation of the author's statements; to give
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these in a manner which will interest the reader; and to preserve, so
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far as is possible, the style of the original text
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The task has been
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doubly difficult in this work because, in using Latin, the author
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availed himself of a medium which had ceased to expand a thousand years
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before his subject had in many particulars come into being; in
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consequence he was in difficulties with a large number of ideas for
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which there were no corresponding words in the vocabulary at his
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command, and instead of adopting into the text his native German terms,
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he coined several hundred Latin expressions to answer his needs
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It is
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upon this rock that most former attempts at translation have been
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wrecked
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Except for a very small number, we believe we have been able to
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discover the intended meaning of such expressions from a study of the
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context, assisted by a very incomplete glossary prepared by the author
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himself, and by an exhaustive investigation into the literature of these
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subjects during the sixteenth and seventeenth centuries
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That discovery
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in this particular has been only gradual and obtained after much labour,
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may be indicated by the fact that the entire text has been
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re-typewritten three times since the original, and some parts more
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often; and further, that the printer's proof has been thrice revised
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We
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have found some English equivalent, more or less satisfactory, for
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practically all such terms, except those of weights, the varieties of
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veins, and a few minerals
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Books Corpus Dataset
Overview
This dataset is a large collection of text lines extracted from free books available on Project Gutenberg. The dataset is primarily composed of literary texts, including classical literature and science fiction. It is designed for training custom language models focused on book-style text generation.
Dataset Structure
- Directory:
data/ - Main corpus file:
books.txt- Contains one sentence or paragraph per line.
- Checkpoint file:
corpus_checkpoint.txt- Keeps track of the last downloaded line to resume interrupted downloads.
Each line in the corpus represents a cleaned sentence or paragraph extracted from the HTML of Project Gutenberg books.
Features
- Large-scale collection with tens of thousands of lines.
- Focus on literary texts, including:
- Science fiction
- Classical literature
- Popular public-domain books
- Cleaned text:
- Removes HTML tags, ads, and metadata
- Splits paragraphs into sentences
- Keeps lines with meaningful length (>30 characters)
Usage
- Clone or download the dataset directory.
- Load the dataset in Python:
with open("data/books.txt", "r", encoding="utf-8") as f:
texts = [line.strip() for line in f if line.strip()]
print(f"Total lines in corpus: {len(texts)}")
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