  The explosion of misinformation spreading in the media ecosystem urges for
automated fact-checking. While misinformation spans both geographic and
linguistic boundaries, most work in the field has focused on English. Datasets
and tools available in other languages, such as Chinese, are limited. In order
to bridge this gap, we construct CHEF, the first CHinese Evidence-based
Fact-checking dataset of 10K real-world claims. The dataset covers multiple
domains, ranging from politics to public health, and provides annotated
evidence retrieved from the Internet. Further, we develop established baselines
and a novel approach that is able to model the evidence retrieval as a latent
variable, allowing jointly training with the veracity prediction model in an
end-to-end fashion. Extensive experiments show that CHEF will provide a
challenging testbed for the development of fact-checking systems designed to
retrieve and reason over non-English claims.
