OAEI-LLM-T: A TBox Benchmark Dataset for Understanding LLM Hallucinations in Ontology Matching Systems

Qiang, Zhangcheng

arXiv.org Artificial Intelligence 

Hallucinations are inevitable in downstream tasks using large language models (LLMs). While addressing hallucinations becomes a substantial challenge for LLM-based ontology matching (OM) systems, we introduce a new benchmark dataset called OAEI-LLM-T. The dataset evolves from the TBox (i.e. schema-matching) datasets in the Ontology Alignment Evaluation Initiative (OAEI), capturing hallucinations of different LLMs performing OM tasks. These OM-specific hallucinations are carefully classified into two primary categories and six sub-categories. We showcase the usefulness of the dataset in constructing the LLM leaderboard and fine-tuning foundational LLMs for LLM-based OM systems.

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