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Meronymic Ontology Extraction via Large Language Models

arXiv 2510.13839 ↗First posted 11 Oct 2025cs.CL cs.AIcited by 0

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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

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  4. 2024Humans or LLMs as the Judge? A Study on Judgement Biasescited by 314
  5. 2024Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoderscited by 213
  6. 2023Grammar-Constrained Decoding for Structured NLP Tasks without Finetuningcited by 186
  7. 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
  8. 2025Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineeringcited by 64
  9. 2022Generative Knowledge Graph Construction: A Reviewcited by 49
  10. 2021Automatic Product Ontology Extraction from Textual Reviewscited by 2

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