lexlms/legal_lama

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",
}