A Hohfeldian Knowledge Base for LLM-Assisted Legal Information Retrieval in Marine Biodiversity Law
Abstract
Governance of marine genetic resources is fragmented across overlapping treaties, creating uncertainty about which obligations apply in specific situations. We address this by mapping treaty provisions into a normative structure based on Hohfelds framework, the Hohfeld-Structured Normative Knowledge Base (HSNKB), and by constructing a dataset of 15 fact-pattern questions with expert gold answers. We evaluate four recent large language models (LLMs) on retrieving rows that contain the relevant rules to answer the fact-pattern questions. The results indicate that reasoning LLMs achieved modest precision and middling recall. Hohfeldian representations help avoid false positives, but improving recall without degrading precision remains an open problem for cross-treaty retrieval.
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