@inproceedings{210bc78691b4447baf01cb61856a1410,
title = "Enriching Taxonomies Using Large Language Models",
abstract = "Taxonomies play a vital role in structuring and categorizing 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 However, many existing taxonomies suffer from limited coverage and outdated or ambiguous nodes, reducing their effectiveness in knowledge retrieval.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 visualization of the final merged taxonomy for analysis.",
author = "Zeinab Ghamlouch and Mehwish Alam",
note = "Publisher Copyright: {\textcopyright} 2025 The Authors.; 28th European Conference on Artificial Intelligence, ECAI 2025, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025 ; Conference date: 25-10-2025 Through 30-10-2025",
year = "2025",
month = oct,
day = "21",
doi = "10.3233/FAIA251441",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "5147--5150",
editor = "Ines Lynce and Nello Murano and Mauro Vallati and Serena Villata and Federico Chesani and Michela Milano and Andrea Omicini and Mehdi Dastani",
booktitle = "ECAI 2025 - 28th European Conference on Artificial Intelligence, including 14th Conference on Prestigious Applications of Intelligent Systems, PAIS 2025 - Proceedings",
}