Explainable Fact Checking with Probabilistic Answer Set Programming

Understand

One challenge in fact checking is the ability to improve the transparency of the decision.

• We present a fact checking method that uses reference information in knowledge graphs (KGs) to assess claims and explain its decisions.
• KGs contain a formal representation of knowledge with semantic descriptions of entities and their relationships.
• We exploit such rich semantics to produce interpretable explanations for the fact checking output.