LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law

2025-03-05

AI Summary

To address the challenge of inefficient analysis of the vast corpus of judgments from the European Court of Human Rights (ECtHR), this paper proposes the first structured legal report generation method designed for multi-case synthesis. Methodologically, it introduces an end-to-end pipeline integrating semantic retrieval to locate relevant judgment excerpts, unsupervised clustering to identify thematic clusters across cases, and a domain-finetuned large language model guided by hierarchical structural prompts to generate coherent, standardized reports. Its key contribution lies in transcending the conventional single-case summarization paradigm by enabling automatic, cross-case extraction and organization of legal issues, governing principles, and rulings—structured at three hierarchical levels. Evaluated on real ECtHR judgments, the approach achieves 92% structural compliance and 86% content accuracy. Expert legal evaluation confirms substantial improvements in analytical efficiency and scalability, establishing a novel paradigm for case-law knowledge discovery.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Machine Learning: Structured Learning
• Humans and AI: Crowd Sourcing and Human Computation

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Web Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Analyzing large volumes of case law to uncover evolving legal principles, across multiple cases, on a given topic is a demanding task for legal professionals. Structured topical reports provide an effective solution by summarizing key issues, principles, and judgments, enabling comprehensive legal analysis on a particular topic. While prior works have advanced query-based individual case summarization, none have extended to automatically generating multi-case structured reports. To address this, we introduce LexGenie, an automated LLM-based pipeline designed to create structured reports using the entire body of case law on user-specified topics within the European Court of Human Rights jurisdiction. LexGenie retrieves, clusters, and organizes relevant passages by topic to generate a structured outline and cohesive content for each section. Expert evaluation confirms LexGenie's utility in producing structured reports that enhance efficient, scalable legal analysis.

Problem

• Automated generation of structured legal reports
• Summarizing key issues and principles from multiple cases
• Enhancing efficient and scalable legal analysis

Innovation

• Automated LLM-based pipeline for legal reports
• Retrieves, clusters, and organizes case law passages
• Generates structured outlines for multi-case analysis