Meronymic Ontology Extraction via Large Language Models
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 22 references that are in the map. First posted on arXiv 11 Oct 2025.
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References · 10
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2016Enriching Word Vectors with Subword Informationcited by 1,578
- 2024Humans or LLMs as the Judge? A Study on Judgement Biasescited by 314
- 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 213
- 2023Grammar-Constrained Decoding for Structured NLP Tasks without Finetuningcited by 186
- 2024An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Model is not a General Substitute for GPT-4cited by 90
- 2025Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineeringcited by 64
- 2022Generative Knowledge Graph Construction: A Reviewcited by 49
- 2021Automatic Product Ontology Extraction from Textual Reviewscited by 2
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