Legislative systems face growing complexity due to the ever-increasing number of laws and intricate interdependencies between them. Traditional methods of storing and analyzing legal systems, mainly based on RDF, struggle with this complexity, hindering efficient knowledge discovery, as required by domain experts. In this paper, we propose to model legislation into a property graph, where edges represent citations, modifications, and abrogations between laws and their articles or attachments, both represented as nodes and edges with properties. As a practical use case, we implement the model in the Italian legislative system. First, we describe our approach to extracting knowledge from legal texts. To this aim, we leverage the recently internationally adopted XML law standard, Akoma Ntoso, to parse and identify entities, relationships and properties. Next, we describe the model and the schema implemented using Neo4j, the market-leading graph database management system. The schema is designed to capture the structure and hierarchy of laws, together with their interdependencies. We show how such a property graph enables an efficient answer to complex and relevant queries previously impractical on raw text. By leveraging other implementations of the Akoma Ntoso standard and the proposed property graph approach, we are confident that this work will facilitate a comprehensive comparison of legislative systems and their complexities.

翻译：由于法律数量不断增加且法律间存在复杂的相互依赖关系，立法系统面临日益增长的系统复杂性。传统基于RDF的法律系统存储与分析方法难以应对这种复杂性，阻碍了领域专家所需的高效知识发现。本文提出将立法体系建模为属性图，其中边表示法律条文及其附件之间的引用、修改与废止关系，这些实体均被表示为带属性的节点和边。我们以意大利立法系统为实际案例实现了该模型。首先阐述了从法律文本中提取知识的方法，通过运用国际最新采用的XML法律标准Akoma Ntoso来解析和识别实体、关系及属性。随后详细说明了基于市场领先的图数据库管理系统Neo4j实现的模型与架构，该架构旨在捕获法律的结构层次及其相互依赖关系。我们展示了此类属性图如何高效解答先前在原始文本上难以处理的复杂相关查询。通过结合Akoma Ntoso标准的其他实施方案与所提出的属性图方法，我们确信这项工作将促进立法系统及其复杂性的全面比较研究。