Modelling Legislative Systems into Property Graphs to Enable Advanced Pattern Detection
Andrea Colombo, Anna Bernasconi, Stefano Ceri

TL;DR
This paper introduces a property graph model for legislative systems, enabling advanced pattern detection and efficient querying of complex legal interdependencies, demonstrated through the Italian legislative system using Neo4j.
Contribution
The paper presents a novel approach to model legal texts as property graphs, improving analysis and pattern detection over traditional RDF-based methods.
Findings
Enhanced query efficiency for complex legal interdependencies
Successful implementation in the Italian legislative system
Facilitates comprehensive comparison of legislative complexities
Abstract
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…
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Taxonomy
Topics3D Modeling in Geospatial Applications
