We tackle fact checking using Knowledge Graphs. (KGs) as a source of background knowledge. Our approach leverages the KG schema to generate can- didate evidence ...

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 ...

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 ...

This work tackles fact checking using Knowledge Graphs as a source of background knowledge by leveraging the KG schema to generate candidate evidence ...

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 ...

Nov 16, 2023 · In this study, we introduce a "Relevant Evidence Detection" (RED) module to discern whether each piece of evidence is relevant, to support or refute the claim.

Oct 26, 2023 · This study examined four fact checkers (Snopes, PolitiFact, Logically, and the Australian Associated Press FactCheck) using a data-driven approach.

Automated fact checking is a task in the domain of Natural Language Pro- cessing that deals with the verification of claims using evidence. Fact checking is.

We identify leaked evidence snippets using patterns for their source URLs or contained phrases. A complete list of all used patterns is given in Appendix B.2).

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 ...