Automating IRAC Analysis in Malaysian Contract Law using a Semi-Structured Knowledge Base

Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon, Zhuang Li, Adnan Trakic
6/19/2024
cs.CL

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Abstract

The effectiveness of Large Language Models (LLMs) in legal reasoning is often limited due to the unique legal terminologies and the necessity for highly specialized knowledge. These limitations highlight the need for high-quality data tailored for complex legal reasoning tasks. This paper introduces LegalSemi, a benchmark specifically curated for legal scenario analysis. LegalSemi comprises 54 legal scenarios, each rigorously annotated by legal experts, based on the comprehensive IRAC (Issue, Rule, Application, Conclusion) framework from Malaysian Contract Law. In addition, LegalSemi is accompanied by a structured knowledge base (SKE). A series of experiments were conducted to assess the usefulness of LegalSemi for IRAC analysis. The experimental results demonstrate the effectiveness of incorporating the SKE for issue identification, rule retrieval, application and conclusion generation using four different LLMs.

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Cite this paper

@article{kang2024automating,
  title  = {Automating IRAC Analysis in Malaysian Contract Law using a Semi-Structured Knowledge Base},
  author = {Xiaoxi Kang and Lizhen Qu and Lay-Ki Soon and Zhuang Li and Adnan Trakic},
  year   = {2024},
  eprint = {2406.13217},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.13217v2}
}

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