task_categories:
- text-generation
language:
- en
pretty_name: Caselaw Access Project
Caselaw Access Project
Description
This dataset contains 6.7 million cases from the Caselaw Access Project and Court Listener. The Caselaw Access Project consists of nearly 40 million pages of U.S. federal and state court decisions and judges’ opinions from the last 365 years. In addition, Court Listener adds over 900 thousand cases scraped from 479 courts. The Caselaw Access Project and Court Listener source legal data from a wide variety of resources such as the Harvard Law Library, the Law Library of Congress, and the Supreme Court Database. From these sources, we only included documents that were in the public domain. Erroneous OCR errors were further corrected after digitization, and additional post-processing was done to fix formatting and parsing. Code for collecting, processing, and preparing this dataset is available in the common-pile GitHub repo.
Dataset Statistics
| Documents | UTF-8 GB |
|---|---|
| 6,919,240 | 78 |
License Issues
While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see our paper). If you believe you have found an instance of incorrect licensing in this dataset, please start a discussion on this repository.
Other Versions
This is the "raw" version of the Caselaw Access Project dataset. If you are looking for the filtered version used to train Comma v0.1, you can find it here.
Citation
If you use this dataset, please cite:
@article{kandpal2025common,
title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}},
author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray},
journal={arXiv preprint},
year={2025}
}