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August 22, 2025Open Access

Using Large Language Models for Ontology Development

Key Points

LLMs can significantly reduce the complexity of ontology development processes, making them a valuable tool for engineers in this field.
The case study shows a streamlined approach to creating class hierarchies and defining properties, fostering a more efficient ontology engineering workflow.
Following a modified Ontology Development 101 methodology reveals how LLMs can effectively assist in integrating multiple standards and existing ontologies.
While automation is not fully achievable, LLMs serve as effective assistants, thereby significantly shortening the development time.

Abstract

This paper explores the application of Large Language Models (LLMs) for ontology development, focusing specifically on cloud service ontologies. We demonstrate how LLMs can streamline the ontology development process by following a modified Ontology Development 101 methodology using Perplexity AI. Our case study shows that LLMs can effectively assist in defining scope, identifying existing ontologies, generating class hierarchies, creating properties, and populating instances. The resulting cloud service ontology integrates concepts from multiple standards and existing ontologies. While LLMs cannot fully automate ontology creation, they significantly reduce development time and complexity, serving as valuable assistants in the ontology engineering process.

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