# Specific Domain Ontology Construction Using Large Language Models

arXiv: https://arxiv.org/abs/2606.20691 · HTML: https://mlsanity.com/paper/2606.20691/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 7 references that are in the map.
- First posted on arXiv 14 Jun 2026.

## Builds on (most cited first, 1 of 1)

- [A Short Review for Ontology Learning: Stride to Large Language Models Trend](https://mlsanity.com/paper/2404.14991/) (2024)

## Abstract (arXiv)

Ontologies are useful structures to organize and maintain information that can be understood both by humans and systems. However, since their manual crafting is a laborious task, many specific domains lack reference ontologies. The outstanding ability for understanding natural language demonstrated by the Large Language Models (LLMs) has motivated their application to aid on a variety of fields, including on ontology development. This work presents the experimentation with a technique that uses LLMs in the role of domain experts to build conceptual hierarchies for a given initial concept. Twenty ontologies automatically constructed for the domain of the Brazilian maritime territory (a.k.a the Blue Amazon) using GPT-3.5 and GPT-4 were then evaluated by human experts. The models were able to construct overall coherent conceptualizations of the domain, but none of the outputs was completely satisfactory as a representation of the context without refinement.