Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Automated Factchecking: Developing an Annotation Schema and
  Benchmark for Consistent Automated Claim Detection   In an effort to assist factcheckers in the process of factchecking, we tackle
the claim detection task, one of the necessary stages prior to determining the
veracity of a claim. It consists of identifying the set of sentences, out of a
long text, deemed capable of being factchecked. This paper is a collaborative
work between Full Fact, an independent factchecking charity, and academic
partners. Leveraging the expertise of professional factcheckers, we develop an
annotation schema and a benchmark for automated claim detection that is more
consistent across time, topics and annotators than previous approaches. Our
annotation schema has been used to crowdsource the annotation of a dataset with
sentences from UK political TV shows. We introduce an approach based on
universal sentence representations to perform the classification, achieving an
F1 score of 0.83, with over 5% relative improvement over the state-of-the-art
methods ClaimBuster and ClaimRank. The system was deployed in production and
received positive user feedback.

3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
2
The categories of this paper are: math