Fact Checking via Evidence Patterns

Fact Checking via Evidence Patterns

Valeria Fionda, Giuseppe PirrĂ²

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 3755-3761. https://doi.org/10.24963/ijcai.2018/522

We tackle fact checking using Knowledge Graphs (KGs) as a source of background knowledge. Our approach leverages the KG schema to generate candidate evidence patterns, that is, schema-level paths that capture the semantics of a target fact in alternative ways. Patterns verified in the data are used to both assemble semantic evidence for a fact and provide a numerical assessment of its truthfulness. We present efficient algorithms to generate and verify evidence patterns, and assemble evidence. We also provide a translation of the core of our algorithms into the SPARQL query language. Not only our approach is faster than the state of the art and offers comparable accuracy, but it can also use any SPARQL-enabled KG.
Keywords:
Multidisciplinary Topics and Applications: Intelligent Database Systems
Multidisciplinary Topics and Applications: AI and the Web