Explainable fact checking with probabilistic answer set programming

Papotti, Paolo

A challenge in fact checking is the ability to provide explanations for the claim validation. We present a computational method that uses reference information to verify claims and explain its assessments. Our solution exploits existing formal representation of knowledge to generate interpretable explanations for the fact checking decisions.


Type:
Talk
City:
Paris
Date:
2019-10-28
Department:
Data Science
Eurecom Ref:
6047
Copyright:
© EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in and is available at :
See also:

PERMALINK : https://www.eurecom.fr/publication/6047