The Role of Generative AI in Competency Question Retrofitting

Competency Questions (CQs) are essential in ontology engineering; they express an ontology’s functional requirements as natural language questions, offer crucial insights into an ontology’s scope and are pivotal for various tasks, e.g. ontology reuse, testing, requirement specification, and pattern definition. Despite their importance, the practice of publishing CQs alongside ontological artefacts is not commonly adopted. We propose an approach based on Generative AI, specifically Large Language Models (LLMs) for retrofitting CQs from existing ontologies and we study how the control parameters in two LLMs (i.e. gpt-3.5-turbo and gpt-4) affect their performance and investigate the interplay between prompts and configuration for retrofitting viable CQs