mlsanityData to 7 Oct 2026

Enriching Taxonomies Using Large Language Models

arXiv 2602.22213 ↗First posted 21 Nov 2025cs.IR cs.AI cs.CLcited by 2

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Abstract (arXiv)

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 However, many existing taxonomies suffer from limited coverage and outdated or ambiguous nodes, reducing their effectiveness in knowledge retrieval.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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 8 references that are in the map. First posted on arXiv 21 Nov 2025.

Builds on

5 of 8 references.

References · 5

  1. 2023YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomycited by 37
  2. 2024Are Large Language Models a Good Replacement of Taxonomies?cited by 19
  3. 2022Entity Type Prediction Leveraging Graph Walks and Entity Descriptionscited by 6
  4. 2024Refining Wikidata Taxonomy using Large Language Modelscited by 5
  5. 2024FLAME: Self-Supervised Low-Resource Taxonomy Expansion using Large Language Modelscited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.