An Extensible Framework for Verification of Numerical Claims

EACL 2017  ·  James Thorne, Andreas Vlachos ·

In this paper we present our automated fact checking system demonstration which we developed in order to participate in the Fast and Furious Fact Check challenge. We focused on simple numerical claims such as {``}population of Germany in 2015 was 80 million{''} which comprised a quarter of the test instances in the challenge, achieving 68{\%} accuracy. Our system extends previous work on semantic parsing and claim identification to handle temporal expressions and knowledge bases consisting of multiple tables, while relying solely on automatically generated training data. We demonstrate the extensible nature of our system by evaluating it on relations used in previous work. We make our system publicly available so that it can be used and extended by the community.

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