NLL2FR 2025: International Workshop on Translating Natural Legal Language into Formal Representation

As legal systems increasingly intersect with digital technologies, the formal representation of legal norms has become essential. Structured knowledge representation provides a rigorous foundation for modeling legal reasoning and supports practical applications such as automated compliance checking, legal advisory tools, and normative reasoning in autonomous systems like self-driving cars and AI-driven legal decision-making. While many rigorous frameworks for legal knowledge representation and reasoning have shown great potential, they often assume that legal knowledge can already be expressed in formal languages. In reality, however, most legal rules and case descriptions are written in natural language, creating a significant gap between natural legal language and formal representations. Recent advances in natural language processing—particularly those driven by large language models—have led to promising applications in AI and Law, including legal information retrieval, summarization, and information extraction. NLL2FR2025 aims to bring together researchers and practitioners interested in bridging this gap between natural legal language and formal representations. Our interest extends beyond the translation of natural language rules into logical formulae to include the formalization of legal cases described in natural language.

This conference invites submissions addressing, though not exclusively, the following areas: knowledge representation, legal text formalization, legal argumentation and factor extraction and artificial intelligence and law.