Datasets:
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README.md
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- fr
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size_categories:
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- 1M<n<10M
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dataset_info:
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splits:
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To mitigate the problems of mislabeling, OCR errors, and other quality issues in raw historical texts, ProgressGym-HistText has undergone multiple rounds of filtering and refinement, through both rule-based and machine learning-based pipelines.
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We collected historical texts from portions of
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The texts are organized into `.json` files by year, with each year's file containing a list of passages. Each passage is represented as a dictionary, with the fields `creation_year`, `source_dataset`, and `content` being mandatory, and many other metadata fields being optional to include.
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- fr
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size_categories:
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source_datasets:
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- pile-of-law/pile-of-law
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- EEBO
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- Library of Congress
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- Project Gutenberg (Standardized Project Gutenberg Corpus)
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dataset_info:
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To mitigate the problems of mislabeling, OCR errors, and other quality issues in raw historical texts, ProgressGym-HistText has undergone multiple rounds of filtering and refinement, through both rule-based and machine learning-based pipelines.
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We collected historical texts from portions of Library of Congress (Internet Archive), Project Gutenberg (Standardized Project Gutenberg Corpus), Early English Books Online (EEBO), and [Pile of Law](https://huggingface.co/datasets/pile-of-law/pile-of-law), which are public-domain, freely available digital libraries of texts. The dataset encompasses different types of texts: fiction, nonfiction, legal, administrative, religious, and more.
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The texts are organized into `.json` files by year, with each year's file containing a list of passages. Each passage is represented as a dictionary, with the fields `creation_year`, `source_dataset`, and `content` being mandatory, and many other metadata fields being optional to include.
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