---
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](mailto:gila@darrow.ai)

### Dataset Summary

USClassActions is an English dataset of 3K 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
```python
from datasets import load_dataset
dataset = load_dataset('darrow-ai/USClassActions')
```
### Data Fields
`id`: (**int**) a unique identifier of the document \
`target_text`: (**str**) the complaint text \
`verdict`: (**str**) the outcome of the case \

### 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},
}
```