2024/10/10 by Morgan Gray, Jaromír Šavelka, Gray, Morgan +5 · 2 citations
Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Law #Computation and Language (cs.CL) #FOS: Computer and information sciences #Law, AI, and Intellectual Property #Legal Education and Practice Innovations
paper · pdf · doi:10.48550/arxiv.2410.07504
openalex publication_date 2024/10/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Factors are a foundational component of legal analysis and computational models of legal reasoning. These factor-based representations enable lawyers, judges, and AI and Law researchers to reason about legal cases. In this paper, we introduce a methodology that leverages large language models (LLMs) to discover lists of factors that effectively represent a legal domain. Our method takes as input raw court opinions and produces a set of factors and associated definitions. We demonstrate that a semi-automated approach, incorporating minimal human involvement, produces factor representations that can predict case outcomes with moderate success, if not yet as well as expert-defined factors can.