annotations_creators:
- other
language_creators:
- found
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- ga
- hr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
license:
- cc-by-4.0
multilinguality:
- multilingual
size_categories:
- 1K<n<100K
source_datasets:
- original
task_categories:
- token-classification
- text-classification
task_ids:
- multi-class-classification
- multi-label-classification
- named-entity-recognition
- topic-classification
pretty_name: 'LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding'
tags:
- named-entity-recognition-and-classification
- judgement-prediction
Dataset Card for LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: Joel Niklaus
Dataset Summary
The dataset consists of 11 diverse multilingual legal NLU tasks. 6 tasks have one single configuration and 5 tasks have two or three configurations. This leads to a total of 18 tasks (8 single-label text classification tasks, 5 multi-label text classification tasks and 5 token-classification tasks).
Supported Tasks and Leaderboards
The dataset supports the tasks of text classification and token classification. In detail, we support the folliwing tasks and configurations:
task | task type | configurations | link |
---|---|---|---|
Brazilian Court Decisions | Judgment Prediction | (judgment, unanimity) | joelito/brazilian_court_decisions |
Swiss Judgment Prediction | Judgment Prediction | default | joelito/swiss_judgment_prediction |
German Argument Mining | Argument Mining | default | joelito/german_argument_mining |
Greek Legal Code | Topic Classification | (volume, chapter, subject) | greek_legal_code |
Online Terms of Service | Unfairness Classification | (unfairness level, claus topic) | online_terms_of_service |
Covid 19 Emergency Event | Event Classification | default | covid19_emergency_event |
MultiEURLEX | Topic Classification | (level 1, level 2, level 3) | multi_eurlex |
LeNER BR | Named Entity Recognition | default | lener_br |
LegalNERo | Named Entity Recognition | default | legalnero |
Greek Legal NER | Named Entity Recognition | default | greek_legal_ner |
MAPA | Named Entity Recognition | (coarse, fine) | mapa |
Languages
The following languages are supported: bg , cs , da, de, el, en, es, et, fi, fr, ga, hr, hu, it, lt, lv, mt, nl, pl, pt, ro, sk, sl, sv
Dataset Structure
Data Instances
The file format is jsonl and three data splits are present for each configuration (train, validation and test).
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
TODO add citation
Contributions
Thanks to @JoelNiklaus for adding this dataset.