An LLM-empowered General Workflow for Legal Case Analysis: A Case Study on Elderly Laborer Protection

The emergence of LLMs has revolutionized the field of legal case analysis. Exist-ing research primarily focuses on specific issues, e.g., legal view generation and case retrieval, neglecting the universal ability of legal semantic features within texts to address multiple issues. In this paper, we develop a novel general work-flow utilizing LLMs for diverse legal case analysis tasks, uncovering implicit in-formation in the legal case datasets. Specifically, the workflow involves three steps: 1 legal experts first define a fine-grained elements framework for legal cases 2 LLMs then extract these elements from documents and convert them into structured tables, aiming to capture special meaningful information contained in the document 3 various questions of interest to legal experts can be ad-dressed by selecting and analyzing relevant elements. Benefiting from LLMs' knowledge and ability in understanding and processing text, element annotation becomes scalable, allowing our workflow to handle general legal intelligence tasks. We validate the feasibility and effectiveness of our workflow on the Elder-ly Laborer Protection issue as a case study, exploring the factors affecting judg-ment outcomes from a causal perspective. Our fine-grained legal case dataset at the document level annotated by legal experts and easy-to-use workflow tools are available at https: anonymous.4open.science' LegalCaseAnalysis-814F .