FoodTaxo: Generating Food Taxonomies with Large Language Models
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915305485238272 |
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| author | Wullschleger, Pascal Zarharan, Majid Daly, Donnacha Pouly, Marc Foster, Jennifer |
| author_facet | Wullschleger, Pascal Zarharan, Majid Daly, Donnacha Pouly, Marc Foster, Jennifer |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_19838 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FoodTaxo: Generating Food Taxonomies with Large Language Models Wullschleger, Pascal Zarharan, Majid Daly, Donnacha Pouly, Marc Foster, Jennifer Computation and Language Artificial Intelligence 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. |
| title | FoodTaxo: Generating Food Taxonomies with Large Language Models |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2505.19838 |