NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoning
arXiv:2607.15776v1 Announce Type: new Abstract: OWL ontologies provide a formal knowledge representation framework that enables semantic reasoning, and have been widely adopted across domains such as healthcare and bioinformatics. In practice, however, real-world ontologies are often incomplete, which pose challenges for reasoning. In this work, we focus on a fundamental subsumption reasoning problem: given an incomplete ontology and a candidate (non-entailed) subsumption, determine whether the ...
arXiv cs.AI
·Hui Yang, Jiaoyan Chen, Yiping Song, Renate Schmidt, Wen Zhang
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