将法律作品映射到语义网，实现可验证的法律知识图谱基础
Legal Knowledge Graph Foundations, Part I: URI-Addressable Abstract Works (LRMoo F1 to schema.org)
- 用schema.org标准逐属性映射法律作品实体，构建机器可读描述
- 基于巴西联邦法律数据，通过JSON-LD生成带稳定URN标识的结构化信息
- 为法律知识图谱提供可追溯、可验证的底层锚点，适合法律信息化研究者
基于国际图联图书馆参考模型（LRMoo）的事件中心化法律规范演变形式化模型，本文解决了将该模型基础实体——抽象法律作品（F1）发布到语义网的第一步。我们提出了LRMoo F1作品到广泛采用的schema.org/Legislation词汇表的逐属性映射方案。以Normas.leg.br门户中的巴西联邦立法为实际案例，展示了如何通过JSON-LD创建可互操作、机器可读的描述，重点包括稳定URN标识符、核心元数据和规范关系。这种结构化映射为每项法律规范建立了稳定的、可通过URI访问的锚点，形成可验证的“事实基准”。它为后续模型层（如时间版本表达式和内部组件）的构建提供了必要且可互操作的基础。通过连接正式本体与网络原生标准，本工作为构建确定性、可靠的法律知识图谱（LKGs）铺平道路，克服了纯概率模型的局限。
原文摘要 · Abstract (English)
Building upon a formal, event-centric model for the diachronic evolution of legal norms grounded in the IFLA Library Reference Model (LRMoo), this paper addresses the essential first step of publishing this model's foundational entity-the abstract legal Work (F1)-on the Semantic Web. We propose a detailed, property-by-property mapping of the LRMoo F1 Work to the widely adopted schema.org/Legislation vocabulary. Using Brazilian federal legislation from the Normas.leg.br portal as a practical case study, we demonstrate how to create interoperable, machine-readable descriptions via JSON-LD, focusing on stable URN identifiers, core metadata, and norm relationships. This structured mapping establishes a stable, URI-addressable anchor for each legal norm, creating a verifiable "ground truth". It provides the essential, interoperable foundation upon which subsequent layers of the model, such as temporal versions (Expressions) and internal components, can be built. By bridging formal ontology with web-native standards, this work paves the way for building deterministic and reliable Legal Knowledge Graphs (LKGs), overcoming the limitations of purely probabilistic models.
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