Communication Dans Un Congrès Année : 2025

Enriching Taxonomies using Large Language Models

Résumé

Taxonomies play a vital role in structuring and categorising information across domains. However, many existing taxonomies suffer from limited coverage and outdated or ambiguous nodes, reducing their effectiveness in knowledge retrieval. To address this, we present Taxoria, a novel taxonomy enrichment pipeline that leverages Large Language Models (LLMs) to enhance a given taxonomy. Unlike approaches that extract internal LLM taxonomies, Taxoria uses an existing taxonomy as a seed and prompts an LLM to propose candidate nodes for enrichment. These candidates are then validated to mitigate hallucinations and ensure semantic relevance before integration. The final output includes an enriched taxonomy with provenance tracking and visualisation of the final merged taxonomy for analysis.

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hal-05173197 , version 1 (21-07-2025)

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  • HAL Id : hal-05173197 , version 1

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Zeinab Ghamlouch, Mehwish Alam. Enriching Taxonomies using Large Language Models. ECAI 2025 - 28th European Conference on Artificial Intelligence (Demo Track), Oct 2025, Bologna, Italy. ⟨hal-05173197⟩
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