用生成式AI构建法国最高法院上诉案知识图谱，助力法律数据结构化分析
Knowledge Graphs Construction from Criminal Court Appeals: Insights from the French Cassation Court
- 基于领域本体与生成式AI，将法院判决文本转为结构化知识图谱
- 构建了首个针对法国最高法院上诉案的专用数据集与本体
- 适合法律人工智能、司法大数据分析的研究者使用
尽管关注度日益提升，如何准确可靠地将非结构化数据（如法院判决）转化为结构化形式仍是挑战。近年来，生成式AI在语言建模中的进展使得文本向知识图谱的转换成为可能，为分析与建模开辟了新路径。本文提出一种从法国最高法院上诉案件中构建知识图谱的框架，包含一个领域特定的本体及衍生数据集，为法律数据的结构化表示与分析提供了基础。
原文摘要 · Abstract (English)
Despite growing interest, accurately and reliably representing unstructured data, such as court decisions, in a structured form, remains a challenge. Recent advancements in generative AI applied to language modeling enabled the transformation of text into knowledge graphs, unlocking new opportunities for analysis and modeling. This paper presents a framework for constructing knowledge graphs from appeals to the French Cassation Court. The framework includes a domain-specific ontology and a derived dataset, offering a foundation for structured legal data representation and analysis.
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