arXiv:2603.05171cs.CLcs.AI2026-03被引 1

为中文判决书构建可计算的法律论证结构标注规范

Guidelines for the Annotation and Visualization of Legal Argumentation Structures in Chinese Judicial Decisions

  • 划分非命题与命题层级,定义五类论点和五种逻辑关系
  • 提出可视化规则与标注流程,确保数据一致性和可复现性
  • 适合法律AI、司法大数据分析及法律推理建模研究者使用

本文提出一套系统化且可操作的司法判决中法律论证结构标注框架。在元素层面,区分非命题层(包括争议事项与非论证成分)和命题层(包含一般规范判断、具体规范判断、一般事实判断、具体事实判断四类)。在关系层面,定义五种论证关系:支持、攻击、联合、匹配、同一性,用以刻画正向/负向关联、合取推理、规范与事实对应及命题等价。框架还规定了基本与嵌套结构的形式表达规则与可视化惯例,并建立标准化标注流程与一致性控制机制,保障标注数据的可复现性与可靠性。该指南通过清晰的概念模型、形式化规则与实践流程,支持大规模司法推理分析,推动法律论证挖掘、法律推理计算建模及AI辅助法律分析的发展。

原文摘要 · Abstract (English)

This Guideline presents a systematic and operationalizable annotation framework for representing legal argumentation structures in judicial decisions. Grounded in theories of legal reasoning and argumentation, the framework aims to reveal the logical organization of judicial reasoning and provide a reliable foundation for computational analysis. At the element level, the Guideline distinguishes between the non-propositional layer and the propositional layer. The non-propositional layer consists of two elements: Issue and Non-argumentative Component. At the propositional level, the Guideline defines four proposition types: General Normative Judgment, Particular Normative Judgment, General Factual Judgment, and Particular Factual Judgment. At the relational level, five relation types are defined to represent argumentative structures: Support, Attack, Joint, Match, and Identity. These relations capture positive and negative argumentative connections, conjunctive reasoning structures, correspondences between legal norms and case facts, and identity or semantic equivalence between propositions. The Guideline further specifies formal representation rules and visualization conventions for both basic and nested structures, enabling consistent visualization of complex argumentation patterns. In addition, it establishes a standardized annotation workflow and consistency control mechanisms to ensure the reproducibility and reliability of annotated data. By providing a clear conceptual model, formal representation rules, and practical annotation procedures, this Guideline supports large-scale analysis of judicial reasoning and future research in legal argument mining, computational modeling of legal reasoning, and AI-assisted legal analysis.

法律AI论证结构司法大数据标注规范

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