ABSTRACT Taxonomies organize concepts into broad categories consisting of more specific subcategories. In this study, we explore the use of multiple large language models (LLMs) to construct a domain‐specific taxonomy. We propose a five‐step workflow that combines LLM prompting, taxonomy alignment, and human validation. To test this workflow, we prompted six state‐of‐the‐art LLMs to generate taxonomies with a maximum of two levels and 30 nodes. Although there were structural and syntactic variations, all models produced coherent taxonomies. Our findings suggest that even in the absence of ground truth data to facilitate taxonomy construction, integrating outputs from multiple LLMs can result in a reasonable starting point for a domain‐specific taxonomy. In future work, we plan to complete the remaining steps in our proposed workflow by working with domain experts to verify the combined taxonomies; we will also test the generalizability of this workflow to other domains.
Yoo et al. (2025) studied this question.