OntoExtend framework uses LLMs for scalable ontology extension

Researchers have developed OntoExtend, a novel framework designed to streamline the process of ontology extension using Large Language Models (LLMs). This system leverages retrieval-augmented generation (RAG) to propose extensions based on specific requirements, framed as competency questions. Evaluations on two distinct use cases, including the Onto-DESIDE project and an industrial ontology from Bosch, indicate that OntoExtend effectively generates ontology fragments with minimal structural issues and high functional accuracy, serving as a valuable drafting assistant for ontology engineers. AI

IMPACT This framework could significantly speed up the development and maintenance of knowledge bases by automating parts of the ontology extension process.

RANK_REASON The item is a research paper detailing a new framework for ontology extension using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• Bosch
• Hugging Face
• LLMs
• Mohammad Javad Saeedizade
• Onto-DESIDE
• OntoExtend
• retrieval-augmented generation

• paper
• product

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