license: gpl-3.0
Dataset Description
- Homepage: https://www.darrow.ai/
- Repository: https://github.com/darrow-labs/ClassActionPrediction
- Paper: https://arxiv.org/abs/2110.
- Leaderboard: N/A
- Point of Contact: Gila Hayat
Dataset Summary
USClassActions is an English dataset of 200 complaints from the US Federal Court with the respective binarized judgment outcome (Win/Lose). The dataset poses a challenging text classification task. We are happy to share this dataset in order to promote robustness and fairness studies on the critical area of legal NLP.
Data Instances
from datasets import load_dataset
dataset = load_dataset('darrow-ai/USClassActionOutcomes_ExpertsAnnotations')
Data Fields
id: (int) a unique identifier of the document origin_label : (str) the outcome of the case target_text: (str) the facts of the case annotator_prediction : (str) annotators predictions of the case outcome based on the target_text annotator_confidence : (str) the annotator's level of confidence in his outcome prediction \
Curation Rationale
The dataset was curated by Darrow.ai (2022).
Citation Information
Gil Semo, Dor Bernsohn, Ben Hagag, Gila Hayat, and Joel Niklaus ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the US Proceedings of the 2022 Natural Legal Language Processing Workshop. Abu Dhabi. 2022
@InProceedings{darrow-niklaus-2022-uscp,
author = {Semo, Gil
and Bernsohn, Dor
and Stürmer, Matthias
and Hagag, Ben
and Hayat, Gila
and Niklaus, Joel},
title = {ClassActionPrediction: A Challenging Benchmark for Legal Judgment Prediction of Class Action Cases in the US},
booktitle = {Proceedings of the 2022 Natural Legal Language Processing Workshop},
year = {2022},
location = {Abu Dhabi},
}