Modeling the Diachronic Evolution of Legal Norms: An LRMoo-Based, Component-Level, Event-Centric Approach to Legal Knowledge Graphs
Researchers have developed a new method for modeling the temporal evolution of legal norms, crucial for AI applications that require precise historical legal data. This approach uses the LRMoo ontology to create a structured pattern for versioning legal texts at a component level. By formalizing legislative amendments as events, the system allows for the exact reconstruction of any legal document as it existed on a specific date, providing a verifiable foundation for legal knowledge graphs and trustworthy AI in the legal domain. AI
IMPACT Provides a deterministic foundation for trustworthy legal AI by enabling precise historical reconstruction of legal texts.