LePaRD: A Dataset of 4+ Million Examples of Judges Citing Precedents

Anonymous

Abstract: We present the Legal Passage Retrieval Dataset, LePaRD. LePaRD is a massive collection of over 4 million U.S. federal judicial citations to precedent in context. The dataset aims to facilitate work on legal passage retrieval, a challenging practice-oriented legal retrieval and reasoning task. Legal passage retrieval seeks to predict relevant passages from precedential court decisions given the context of a legal argument. We extensively evaluate various retrieval approaches on LePaRD, and find that classification appears to work best. However, we note that legal passage retrieval is a difficult task, and there remains significant room for improvement. By publishing LePaRD, we provide a large-scale and high quality resource to foster further research on legal retrieval. Legal passage retrieval is a practice-oriented NLP task that promises to help expand access to justice by reducing the burden associated with legal research via computational assistance. The LePaRD dataset and code will be made freely available upon publication.

Paper Type: long

Research Area: Special Theme (conference specific)

Contribution Types: Data resources

Languages Studied: English