Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering

The rise of large language models has opened new avenues for users seeking legal advice. However, users often lack professional legal knowledge, which can lead to questions that omit critical information. This deficiency makes it challenging for traditional legal question-answering systems to accurately identify users' actual needs, often resulting in imprecise or generalized advice. In this work, we develop a legal question-answering system called Intelligent Legal Assistant, which interacts with users to precisely capture their needs. When a user poses a question, the system requests that the user select their geographical location to pinpoint the applicable laws. It then generates clarifying questions and options based on the key information missing from the user's initial question. This allows the user to select and provide the necessary details. Once all necessary information is provided, the system produces an in-depth legal analysis encompassing three aspects: overall conclusion, jurisprudential analysis, and resolution suggestions. More materials of the system can be accessed at https://github.com/RujingYao/Intelligent-Legal-Assistant.

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Publication Details

Published
2025-05-08
DOI
https://doi.org/10.1145/3701716.3715204
Citations
4
Primary Topic
Artificial Intelligence in Law
Type
article
Field-Weighted Citation Impact
34.09
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article

Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering

Rujing Yao, Yiquan Wu, Tong Zhang, Fang Wang et al.
4 citations
Artificial Intelligence in Law
34.09
article

Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering

Rujing Yao, Yiquan Wu, Tong Zhang, Fang Wang, Jiayin Yang, Xiaozhong Liu, Changlong Sun, Yang Wu, Yuting Huang, Xuhui Zhang
article en
4 citations

Abstract

The rise of large language models has opened new avenues for users seeking legal advice. However, users often lack professional legal knowledge, which can lead to questions that omit critical information. This deficiency makes it challenging for traditional legal question-answering systems to accurately identify users' actual needs, often resulting in imprecise or generalized advice. In this work, we develop a legal question-answering system called Intelligent Legal Assistant, which interacts with users to precisely capture their needs. When a user poses a question, the system requests that the user select their geographical location to pinpoint the applicable laws. It then generates clarifying questions and options based on the key information missing from the user's initial question. This allows the user to select and provide the necessary details. Once all necessary information is provided, the system produces an in-depth legal analysis encompassing three aspects: overall conclusion, jurisprudential analysis, and resolution suggestions. More materials of the system can be accessed at https://github.com/RujingYao/Intelligent-Legal-Assistant.

Worcester Polytechnic Institute (US), Nankai University (CN), Zhejiang University (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 0%
Artificial Intelligence in Law
34.09
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