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Large Language Models (LLMs) can assist with tasks such as terminology extraction, concept discovery, taxonomy construction, relationship identification, ontology documentation, and ontology alignment, significantly accelerating the development of semantic models. At the same time, AI-generated ontologies often contain conceptual inconsistencies, incorrect abstractions, hidden assumptions, and other modeling errors that require careful human review. This hands-on tutorial explores how generative AI can be effectively integrated into the ontology engineering lifecycle. 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