FEVER 20222, 5th Fact Extraction and VERification Workshop, co-located with ACL 2022, 26 May 2022, Dublin, Ireland
Computational fact-checking aims at supporting the verification process of textual claims
by exploiting trustworthy sources. However, there are large classes of complex claims that
cannot be automatically verified, for instance those related to temporal reasoning. To this
aim, in this work, we focus on the verification of economic claims against time series sources. Starting from given textual claims in natural language, we propose a neural machine translation approach to produce respective queries expressed in a recently proposed temporal fragment of the Datalog language. The adopted deep neural approach shows promising preliminary results for the translation of 10 categories of claims extracted from real use cases.
Copyright ACL. Personal use of this material is permitted. The definitive version of this paper was published in FEVER 20222, 5th Fact Extraction and VERification Workshop, co-located with ACL 2022, 26 May 2022, Dublin, Ireland and is available at :