Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approach
Automatically generating formal ontologies from unstructured natural language remains a central challenge in knowledge engineering. While large language models (LLMs) show promise, it remains unclear which architectural design choices drive generation quality and why current approaches fail. We present a controlled experimental study using domain-specific insurance contracts to investigate these questions. We first establish a single-agent LLM baseline, identifying key failure modes such as poor Ontology Design Pattern compliance, structural redundancy, and ineffective iterative repair. We then introduce a multi-agent architecture that decomposes ontology construction into four artifact-d...
| Authors | Abid Talukder, Maruf Ahmed Mridul, Oshani Seneviratne |
|---|---|
| Primary category | cs.AI |
| Published | 25 April 2026 |
| Last updated at source | 25 April 2026 |
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