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:
| annotations_creators: | |
| - no-annotation | |
| language_creators: | |
| - found | |
| language: | |
| - en | |
| license: | |
| - cc-by-nc-sa-4.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - extended | |
| task_categories: | |
| - text-generation | |
| - fill-mask | |
| task_ids: | |
| - masked-language-modeling | |
| pretty_name: LegalLAMA | |
| tags: | |
| - legal | |
| - law | |
| # Dataset Card for "LegalLAMA" | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Dataset Specifications](#supported-tasks-and-leaderboards) | |
| ## Dataset Description | |
| - **Homepage:** https://github.com/coastalcph/lexlms | |
| - **Repository:** https://github.com/coastalcph/lexlms | |
| - **Paper:** https://arxiv.org/abs/2305.07507 | |
| - **Point of Contact:** [Ilias Chalkidis](mailto:ilias.chalkidis@di.ku.dk) | |
| ### 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. | |
| ```python | |
| 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.*](https://aclanthology.org/2023.acl-long.865/) | |
| ``` | |
| @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", | |
| } | |
| ``` |