ULBERT: a domain-adapted BERT model for bilingual information retrieval from Pakistan's constitution.

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Frontiers in Big Data Pub Date : 2025-09-22 eCollection Date: 2025-01-01 DOI:10.3389/fdata.2025.1448785
Qaiser Abbas, Waqas Nawaz, Sadia Niazi, Muhammad Awais
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引用次数: 0

Abstract

Introduction: Navigating legal texts like a national constitution is notoriously difficult due to specialized jargon and complex internal references. For the Constitution of Pakistan, no automated, user-friendly search tool existed to address this challenge. This paper introduces ULBERT, a novel AI-powered information retrieval framework designed to make the constitution accessible to all users, from legal experts to ordinary citizens, in both English and Urdu.

Methods: The system is built around a custom AI model that moves beyond keyword matching to understand the semantic meaning of a user's query. It processes questions in English or Urdu and compares them to the constitutional text, identifying the most relevant passages based on contextual and semantic similarity.

Results: In performance testing, the ULBERT framework proved highly effective. It successfully retrieved the correct constitutional information with an accuracy of 86% for English queries and 73% for Urdu queries.

Discussion: These results demonstrate a significant breakthrough in enhancing the accessibility of foundational legal documents through artificial intelligence. The framework provides an effective and intuitive tool for legal inquiry, empowering a broader audience to understand the Constitution of Pakistan.

导言:浏览像国家宪法这样的法律文本是出了名的困难,因为有专门的术语和复杂的内部参考。对于巴基斯坦宪法,没有自动的、用户友好的搜索工具来解决这一挑战。本文介绍了ULBERT,这是一种新型的人工智能信息检索框架,旨在使从法律专家到普通公民的所有用户都可以使用英语和乌尔都语访问宪法。方法:该系统是围绕一个自定义的人工智能模型构建的,该模型超越了关键字匹配,以理解用户查询的语义。它处理英语或乌尔都语的问题,并将它们与宪法文本进行比较,根据上下文和语义相似性识别出最相关的段落。结果:在性能测试中,ULBERT框架是非常有效的。它成功地检索了正确的宪法信息,英语查询的准确率为86%,乌尔都语查询的准确率为73%。讨论:这些结果表明,人工智能在增强基础法律文件可及性方面取得了重大突破。该框架为法律调查提供了一个有效和直观的工具,使更广泛的受众能够了解巴基斯坦宪法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.20
自引率
3.20%
发文量
122
审稿时长
13 weeks
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