FoodTaxo: Generating Food Taxonomies with Large Language Models

Pascal Wullschleger, Majid Zarharan, Donnacha Daly, Marc Pouly, Jennifer Foster


Abstract
We investigate the utility of Large Language Models for automated taxonomy generation and completion specifically applied to taxonomies from the food technology industry. We explore the extent to which taxonomies can be completed from a seed taxonomy or generated without a seed from a set of known concepts, in an iterative fashion using recent prompting techniques.Experiments on five taxonomies using an open-source LLM (Llama-3), while promising, point to the difficulty of correctly placing inner nodes.
Anthology ID:
2025.acl-industry.55
Volume:
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Georg Rehm, Yunyao Li
Venue:
ACL
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Publisher:
Association for Computational Linguistics
Note:
Pages:
784–803
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URL:
https://preview.aclanthology.org/landing_page/2025.acl-industry.55/
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Cite (ACL):
Pascal Wullschleger, Majid Zarharan, Donnacha Daly, Marc Pouly, and Jennifer Foster. 2025. FoodTaxo: Generating Food Taxonomies with Large Language Models. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track), pages 784–803, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
FoodTaxo: Generating Food Taxonomies with Large Language Models (Wullschleger et al., ACL 2025)
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PDF:
https://preview.aclanthology.org/landing_page/2025.acl-industry.55.pdf