构建双语法律检索系统，提升孟加拉警报公报的精准查询能力
LegalRAG: A Hybrid RAG System for Multilingual Legal Information Retrieval
- 融合RAG技术与双语文本处理，优化法律文档检索流程
- 在孟加拉警报公报上实现所有指标超越现有方法
- 适合需要跨语言法律信息检索的研究者与实务人员
自然语言处理与计算语言学技术在多个领域广泛应用，但在法律和监管任务中的应用仍有限。为填补这一空白，我们构建了一个针对孟加拉警察公告（Bangladesh Police Gazettes）的高效双语问答框架，该公告包含英文与孟加拉语文本。本研究采用现代检索增强生成（RAG）管道，提升信息检索与回答生成效果。除传统RAG外，还提出一种改进型RAG方法，显著提升检索性能，从而生成更精确的答案。该系统可高效搜索特定政府法律通告，使法律信息更易获取。我们在孟加拉警察公告的多样化测试集上评估了所提方法与传统RAG系统，结果表明，所提方法在所有评价指标上均持续优于现有方法。
原文摘要 · Abstract (English)
Natural Language Processing (NLP) and computational linguistic techniques are increasingly being applied across various domains, yet their use in legal and regulatory tasks remains limited. To address this gap, we develop an efficient bilingual question-answering framework for regulatory documents, specifically the Bangladesh Police Gazettes, which contain both English and Bangla text. Our approach employs modern Retrieval Augmented Generation (RAG) pipelines to enhance information retrieval and response generation. In addition to conventional RAG pipelines, we propose an advanced RAG-based approach that improves retrieval performance, leading to more precise answers. This system enables efficient searching for specific government legal notices, making legal information more accessible. We evaluate both our proposed and conventional RAG systems on a diverse test set on Bangladesh Police Gazettes, demonstrating that our approach consistently outperforms existing methods across all evaluation metrics.
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