English

A Statutory Article Retrieval Dataset in French

Computation and Language 2022-03-16 v2

Abstract

Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal question. While recent advances in natural language processing have sparked considerable interest in many legal tasks, statutory article retrieval remains primarily untouched due to the scarcity of large-scale and high-quality annotated datasets. To address this bottleneck, we introduce the Belgian Statutory Article Retrieval Dataset (BSARD), which consists of 1,100+ French native legal questions labeled by experienced jurists with relevant articles from a corpus of 22,600+ Belgian law articles. Using BSARD, we benchmark several state-of-the-art retrieval approaches, including lexical and dense architectures, both in zero-shot and supervised setups. We find that fine-tuned dense retrieval models significantly outperform other systems. Our best performing baseline achieves 74.8% R@100, which is promising for the feasibility of the task and indicates there is still room for improvement. By the specificity of the domain and addressed task, BSARD presents a unique challenge problem for future research on legal information retrieval. Our dataset and source code are publicly available.

Cite

@article{arxiv.2108.11792,
  title  = {A Statutory Article Retrieval Dataset in French},
  author = {Antoine Louis and Gerasimos Spanakis},
  journal= {arXiv preprint arXiv:2108.11792},
  year   = {2022}
}

Comments

ACL 2022. Code and dataset are available at https://github.com/maastrichtlawtech/bsard

R2 v1 2026-06-24T05:26:34.057Z