Pitfalls in AI-Generated Ontologies: Strategies for Detection and Mitigation
This paper introduces a complementary set of ontology pitfalls targeting patterns that are not necessary produced by human ontology engineers but commonly arise from LLM-assisted ontology generation, including semantic redundancies, hierarchy conflicts, and property modeling artifacts.
Pasquale Lisena, J. Plu, Oscar Moreno Escobar et al.
· 0 citations