Fact-checking with explanations

Abstract

We present an approach for automated fact-checking, given a trusted knowledge base and a natural language text. The FACE (FAct Checker with Explanations) system is capable of extracting the knowledge behind the sentences, and decide what is entailed in the trusted sources and what is in conflict with them, providing also explanations and counter speeches in English. The system also specifies the provenance of each of its argument, thus it can be traced back to the source of the information.Description logic representation of the input is obtained using the FRED machine reader, which is further improved by detecting and handling translation patterns. The obtained ontology is aligned to the knowledge base using the WordNet database in a custom algorithm, then entailment and conflict detection is performed with the Hermit reasoner, through which we obtain the explanations and counter speeches which are verbalized to Attempto Controlled English.The fact checker is demonstrated on Covid-19 related sentences, however it is domain independent, and can be used with other knowledge bases as well.