A Cross-Lingual Statutory Article Retrieval Dataset for Taiwan Legal Studies

TL;DR

This paper presents a new cross-lingual legal dataset for Taiwan, enabling better retrieval of statutes in multilingual contexts and proposing LLM-based methods to improve cross-lingual legal information access.

Contribution

It introduces a comprehensive cross-lingual legal dataset and baseline methods, addressing translation challenges in multilingual legal retrieval systems.

Findings

Dataset covers all Taiwanese civil, criminal, and administrative laws.

Proposed LLM-based methods improve cross-lingual retrieval accuracy.

Enhances access to legal information for non-native speakers in Taiwan.

Abstract

This paper introduces a cross-lingual statutory article retrieval (SAR) dataset designed to enhance legal information retrieval in multilingual settings. Our dataset features spoken-language-style legal inquiries in English, paired with corresponding Chinese versions and relevant statutes, covering all Taiwanese civil, criminal, and administrative laws. This dataset aims to improve access to legal information for non-native speakers, particularly for foreign nationals in Taiwan. We propose several LLM-based methods as baselines for evaluating retrieval effectiveness, focusing on mitigating translation errors and improving cross-lingual retrieval performance. Our work provides a valuable resource for developing inclusive legal information retrieval systems.