迈向人工智能法律智能的新推理语法：以《梅塞莱法典》作为其语义协议
Towards a New Grammar of Reasoning for Artificial Legal Intelligence and the Mecelle as Its Semantic Protocol
浏览论文内容
中文总结 AI 辅助
本文针对传统法律实践的认知与方法论危机，提出以《梅塞莱法典》语义协议为核心的本体动态框架，指出法律推理不可简化为数据处理，需结合神经符号系统等技术解决法律挑战，为AI时代法律推理提供新范式。
中文摘要 AI 辅助
本文结合人工智能带来的机遇与约束，探讨了传统法律实践长期存在的认知与方法论危机。针对该危机，本文提出了一种基于本体论的框架，名为《梅塞莱法典》（Mecellem）语义协议。分析聚焦于法律内部维持规范一致性与适应不断变化的社会和制度条件之间的结构性张力，阐明了为何仅基于法典编纂、实证主义系统化或诸如计量法学（jurimetrics）这类定量方法的路径是不够的。本文主张，法律推理不能被简化为数据检索或统计模式识别。相反，它基于意义具有语境依赖性这一前提，必须通过本体论定义的实体类别和差异化的知识层进行动态重构。在此视角下，《梅塞莱法典》将法律重新概念化为一种本体动态架构，沿本体论、认识论和方法论的相互关联轴构建，而非固定的规则体系。从计量法学向语义协议的转变不仅是技术层面的转变，更是法律知识基础的变革。本文进一步指出，神经符号系统、知识图谱和智能体人工智能只有嵌入此类本体动态框架，才能有效解决持续存在的法律挑战。通过将法律理解为持续形成的领域而非完成的理性整体，《梅塞莱法典》在人类与机器层面均推进了一种语境敏感、可审计且一致的法律意义生产模型，为人工智能时代重新思考法律推理提供了全面框架。
英文摘要
This article examines the enduring epistemic and methodological crisis of traditional legal practice in light of the opportunities and constraints introduced by artificial intelligence. It proposes an ontologically grounded framework termed the Mecellem semantic protocol as a response to this crisis. The analysis focuses on the structural tension within law between maintaining normative coherence and adapting to evolving social and institutional conditions, and shows why approaches based solely on codification, positivist systematization, or quantitative methods such as jurimetrics are insufficient. The article argues that legal reasoning cannot be reduced to data retrieval or statistical pattern recognition. Instead, it is grounded in the premise that meaning is context-dependent and must be dynamically reconstructed through ontologically defined entity categories and differentiated layers of knowledge. Within this perspective, Mecellem reconceptualizes law not as a fixed system of rules, but as an ontodynamic architecture structured along the interconnected axes of ontology, epistemology, and methodology. The transition from jurimetrics to a semantic protocol is presented not merely as a technical shift, but as a transformation in the foundations of legal knowledge. The article further argues that neurosymbolic systems, knowledge graphs, and agentic artificial intelligence can effectively address persistent legal challenges only when embedded within such an ontodynamic framework. By understanding law as a domain of ongoing formation rather than a completed rational totality, Mecellem advances a context-sensitive, auditable, and coherent model for legal meaning production at both human and machine levels, offering a comprehensive framework for rethinking legal reasoning in the age of artificial intelligence.
发表机构
- NewMind AI
机构由 AI 辅助整理，请以论文原文为准。
