Ontology Semantic Disambiguation by LLM
Résumé
Within the BPP project, a combination of statistics and word n-gram extraction enabled the creation of a bilingual (French/English) ontology in the field of e-recruitment. The produced dataset was of good quality, but it still contained errors. In this paper, we present an approach that explores the use of large language models (LLMs) to automate the validation and enrichment of ontologies and knowledge graphs. Starting with a naive prompt and using small language models (SLMs), we tested various approaches, including zero-shot, few-shot, chain-of-thought (CoT) reasoning, and self-consistency (SC) decoding. The preliminary results are encouraging, demonstrating the ability of LLMs to make complex distinctions and to evaluate the relationships derived from our ontology finely
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