Datasets:
Sub-tasks:
masked-language-modeling
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
extended
ArXiv:
License:
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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
@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",
}
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