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