From Subsumption to Satisfiability: LLM-Assisted Active Learning for OWL Ontologies

Computer Science > Artificial Intelligence [Submitted on 17 Apr 2026] From Subsumption to Satisfiability: LLM-Assisted Active Learning for OWL Ontologies Haoruo Zhao, Wenshuo Tang, Duncan Guthrie, Michele Sevegnani, David Flynn, Paul Harvey 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 the standard reduction of subsumption to satisfiability in description logics, we reformulate each candidate axiom into its corresponding counter-concept and verbalise it in controlled natural language before presenting it to Large Language Models (LLMs). We introduce LLMs as a third component that provides real-world examples approximating an instance of the counter-concept. This design property ensures that only Type II errors may occur in ontology modelling; in the worst case, these errors merely delay the construction process without introducing inconsistencies. Experimental results on 13 commercial LLMs show that recall, corresponding to Type II errors in our framework, remains stable across several well-established ontologies. Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2604.16672 [cs.AI]   (or arXiv:2604.16672v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2604.16672 Focus to learn more Submission history From: Haoruo Zhao [view email] [v1] Fri, 17 Apr 2026 20:05:30 UTC (576 KB) Access Paper: view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-04 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)