AI Research
From Subsumption to Satisfiability: LLM-Assisted Active Learning for OWL Ontologies
Bridging formal ontologies and LLMs to automate membership queries without compromising logical integrity.
In active learning, membership queries (MQs) allow a learner to pose questions to a teacher, such as ''Is every apple a fruit?'', to which the teacher responds correctly with yes or no. These MQs can be viewed as subsumption tests with respect to the target ontology. Inspired by ...
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ArXiv CS.AI
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ArXiv CS.AI
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This research bridge the gap between formal logic and generative AI by utilizing LLMs to accelerate the verification of complex ontology structures. It minimizes human cognitive load while ensuring that machine-generated errors remain benign and non-corruptive to the final knowledge model.
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