Pitfalls in AI-Generated Ontologies: Strategies for Detection and Mitigation

Ontology driven cross language design smell detection through semantic reasoning

Design smells are structural flaws that, if not detected early, can impair software quality and increase maintenance costs. Traditional detection approaches are language-specific and rely on low-level metrics, making them ineffective for heterogeneous, multilingual systems. This paper presents Ontology-Driven Design De...

Ontology Reuse in LLM-Generated Ontologies: A Comparative Evaluation Framework

From Rule Engines to Ontologies: An OWL 2 DL Approach for Domain-Specific Evaluation Information Systems

The results support the feasibility of ontology-driven generation for static-classification systems, whereas arithmetic risk computation and temporal event processing remain better suited to complementary procedural technologies.

Exploiting Mapping Corpora and Expert Knowledge for LLM-based Schema Mapping Generation

Enhancing Construction Requirements Documents Analytics through Integrating Ontology and Large Language Model

The results demonstrate the feasibility of the proposed framework for producing consistent sentence-level semantic extraction from quality-related construction requirement text and demonstrate how ontology-guided fine-tuning can provide explicit semantic grounding for LLM-based information extraction.

Toward Effective and Reliable LLM Agents via Dynamic Ontology

OaK is presented, an ontology-as-a-kernel framework that dynamically constructs and refines task-oriented ontologies for LLM agents and shows that OaK improves standard LLM agents, strengthens evidence grounding, and boosts the reliability of multi-step reasoning.