The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider removing the loading script and relying on automated data support (you can use convert_to_parquet from the datasets library). If this is not possible, please open a discussion for direct help.

Dataset Card for "LegalLAMA"

Dataset Summary

LegalLAMA is a diverse probing benchmark suite comprising 8 sub-tasks that aims to assess the acquaintance of legal knowledge that PLMs acquired in pre-training.

Dataset Specifications

Corpus Corpus alias Examples Avg. Tokens Labels
Criminal Code Sections (Canada) canadian_sections 321 72 144
Legal Terminology (EU) cjeu_term 2,127 164 23
Contractual Section Titles (US) contract_sections 1,527 85 20
Contract Types (US) contract_types 1,089 150 15
ECHR Articles (CoE) ecthr_articles 5,072 69 13
Legal Terminology (CoE) ecthr_terms 6,803 97 250
Crime Charges (US) us_crimes 4,518 118 59
Legal Terminology (US) us_terms 5,829 308 7

Usage

Load a specific sub-corpus, given the corpus alias, as presented above.

from datasets import load_dataset
dataset = load_dataset('lexlms/legal_lama', name='ecthr_terms')

Citation

Ilias Chalkidis*, Nicolas Garneau*, Catalina E.C. Goanta, Daniel Martin Katz, and Anders Søgaard. LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development. 2022. In the Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada.

@inproceedings{chalkidis-etal-2023-lexfiles,
    title = "{L}e{XF}iles and {L}egal{LAMA}: Facilitating {E}nglish Multinational Legal Language Model Development",
    author = "Chalkidis, Ilias  and
      Garneau, Nicolas  and
      Goanta, Catalina  and
      Katz, Daniel  and
      S{\o}gaard, Anders",
    booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.acl-long.865",
    pages = "15513--15535",
}
Downloads last month
590