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arXiv · 2510.13839

Meronymic Ontology Extraction via Large Language Models

Dekai Zhang·Simone Conia·Antonio Rago
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Abstract

Ontologies have become essential in today's digital age as a way of organising the vast amount of readily available unstructured text. In providing formal structure to this information, ontologies have immense value and application across various domains, e.g., e-commerce, where countless product listings necessitate proper product organisation. However, the manual construction of these ontologies is a time-consuming, expensive and laborious process. In this paper, we harness the recent advancements in large language models (LLMs) to develop a fully-automated method of extracting product ontologies, in the form of meronymies, from raw review texts. We demonstrate that the ontologies produced by our method surpass an existing, BERT-based baseline when evaluating using an LLM-as-a-judge. Our investigation provides the groundwork for LLMs to be used more generally in (product or otherwise) ontology extraction.

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Dekai Zhang, Simone Conia, Antonio Rago. 2025-10-11. Meronymic Ontology Extraction via Large Language Models. https://arxiv.org/abs/2510.13839

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