|
--- |
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annotations_creators: |
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- no-annotation |
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language_creators: |
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- found |
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language: |
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- en |
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license: |
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- cc-by-nc-sa-4.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 1M<n<10M |
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source_datasets: |
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- extended |
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task_categories: |
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- text-generation |
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- fill-mask |
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task_ids: |
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- language-modeling |
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- masked-language-modeling |
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pretty_name: LexFiles |
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configs: |
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- eu_legislation |
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- eu_court_cases |
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- uk_legislation |
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- uk_court_cases |
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- us_legislation |
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- us_court_cases |
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- us_contracts |
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- canadian_legislation |
|
- canadian_court_cases |
|
- indian_court_cases |
|
--- |
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|
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# Dataset Card for "LexFiles" |
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|
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Dataset Specifications](#supported-tasks-and-leaderboards) |
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|
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## Dataset Description |
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|
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- **Homepage:** https://github.com/coastalcph/lexlms |
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- **Repository:** https://github.com/coastalcph/lexlms |
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- **Paper:** https://arxiv.org/abs/xxx |
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- **Point of Contact:** [Ilias Chalkidis](mailto:[email protected]) |
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|
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### Dataset Summary |
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|
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The LeXFiles is a new diverse English multinational legal corpus that we created including 11 distinct sub-corpora that cover legislation and case law from 6 primarily English-speaking legal systems (EU, CoE, Canada, US, UK, India). |
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The corpus contains approx. 19 billion tokens. In comparison, the "Pile of Law" corpus released by Hendersons et al. (2022) comprises 32 billion in total, where the majority (26/30) of sub-corpora come from the United States of America (USA), hence the corpus as a whole is biased towards the US legal system in general, and the federal or state jurisdiction in particular, to a significant extent. |
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### Dataset Specifications |
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|
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| Corpus | Corpus alias | Documents | Tokens | Pct. | Sampl. (a=0.5) | Sampl. (a=0.2) | |
|
|-----------------------------------|----------------------|-----------|--------|--------|----------------|----------------| |
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| EU Legislation | `eu-legislation` | 93.7K | 233.7M | 1.2% | 5.0% | 8.0% | |
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| EU Court Decisions | `eu-court-cases` | 29.8K | 178.5M | 0.9% | 4.3% | 7.6% | |
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| ECtHR Decisions | `ecthr-cases` | 12.5K | 78.5M | 0.4% | 2.9% | 6.5% | |
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| UK Legislation | `uk-legislation` | 52.5K | 143.6M | 0.7% | 3.9% | 7.3% | |
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| UK Court Decisions | `uk-court-cases` | 47K | 368.4M | 1.9% | 6.2% | 8.8% | |
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| Indian Court Decisions | `indian-court-cases` | 34.8K | 111.6M | 0.6% | 3.4% | 6.9% | |
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| Canadian Legislation | `canadian-legislation` | 6K | 33.5M | 0.2% | 1.9% | 5.5% | |
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| Canadian Court Decisions | `canadian-court-cases` | 11.3K | 33.1M | 0.2% | 1.8% | 5.4% | |
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| U.S. Court Decisions [1] | `court-listener` | 4.6M | 11.4B | 59.2% | 34.7% | 17.5% | |
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| U.S. Legislation | `us-legislation` | 518 | 1.4B | 7.4% | 12.3% | 11.5% | |
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| U.S. Contracts | `us-contracts` | 622K | 5.3B | 27.3% | 23.6% | 15.0% | |
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| Total | `lexlms/lexfiles` | 5.8M | 18.8B | 100% | 100% | 100% | |
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[1] We consider only U.S. Court Decisions from 1965 onwards (cf. post Civil Rights Act), as a hard threshold for cases relying on severely out-dated and in many cases harmful law standards. The rest of the corpora include more recent documents. |
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[2] Sampling (Sampl.) ratios are computed following the exponential sampling introduced by Lample et al. (2019). |
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Additional corpora not considered for pre-training, since they do not represent factual legal knowledge. |
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|
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| Corpus | Corpus alias | Documents | Tokens | |
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|----------------------------------------|------------------------|-----------|--------| |
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| Legal web pages from C4 | `legal-c4` | 284K | 340M | |
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### Citation |
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|
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[*Ilias Chalkidis\*, Nicolas Garneau\*, Catalina E.C. Goanta, Daniel Martin Katz, and Anders Søgaard.* |
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*LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development.* |
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*2022. In the Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada.*](https://aclanthology.org/xxx/) |
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``` |
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@inproceedings{chalkidis-garneau-etal-2023-lexlms, |
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title = {{LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development}}, |
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author = "Chalkidis*, Ilias and |
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Garneau*, Nicolas and |
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Goanta, Catalina and |
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Katz, Daniel Martin and |
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Søgaard, Anders", |
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booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics", |
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month = june, |
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year = "2023", |
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address = "Toronto, Canada", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/xxx", |
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} |
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``` |
