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Since ChatGPT offers detailed responses without justifications, and erroneousfacts even for popular persons, events and places, in this paper we present anovel pipeline that retrieves the response of ChatGPT in RDF and tries tovalidate the ChatGPT facts using one or more RDF Knowledge Graphs (KGs). Tothis end we leverage DBpedia and LODsyndesis (an aggregated Knowledge Graphthat contains 2 billion triples from 400 RDF KGs of many domains) and shortsentence embeddings, and introduce an algorithm that returns the more relevanttriple(s) accompanied by their provenance and a confidence score. This enablesthe validation of ChatGPT responses and their enrichment with justificationsand provenance. To evaluate this service (such services in general), we createan evaluation benchmark that includes 2,000 ChatGPT facts; specifically 1,000facts for famous Greek Persons, 500 facts for popular Greek Places, and 500facts for Events related to Greece. The facts were manually labelled(approximately 73% of ChatGPT facts were correct and 27% of facts wereerroneous). The results are promising; indicatively for the whole benchmark, wemanaged to verify the 85.3% of the correct facts of ChatGPT and to find thecorrect answer for the 58% of the erroneous ChatGPT facts.

Validating ChatGPT Facts through RDF Knowledge Graphs and Sentence Similarity