Verifying RDF Triples Using LLMs with Traceable Arguments: A Method for Large-Scale Knowledge Graph Validation

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A new technique has been developed for using Large Language Models (LLMs) to verify RDF triples in knowledge graphs, focusing on traceable reasoning. By matching RDF triples with externally sourced texts, the approach aims to ensure accuracy and reliability, crucial in fields like biosciences. The method showed an 88% accuracy rate but had a lower recall at 44%, indicating the necessity for human supervision. The strategy was tested on the BioRED dataset and illustrated practical applications with Wikidata, showcasing its potential for scalable, high-precision verification.