English

The Case for Claim Difficulty Assessment in Automatic Fact Checking

Computation and Language 2022-02-08 v2 Artificial Intelligence Information Retrieval

Abstract

Fact-checking is the process of evaluating the veracity of claims (i.e., purported facts). In this opinion piece, we raise an issue that has received little attention in prior work -- that some claims are far more difficult to fact-check than others. We discuss the implications this has for both practical fact-checking and research on automated fact-checking, including task formulation and dataset design. We report a manual analysis undertaken to explore factors underlying varying claim difficulty and identify several distinct types of difficulty. We motivate this new claim difficulty prediction task as beneficial to both automated fact-checking and practical fact-checking organizations.

Keywords

Cite

@article{arxiv.2109.09689,
  title  = {The Case for Claim Difficulty Assessment in Automatic Fact Checking},
  author = {Prakhar Singh and Anubrata Das and Junyi Jessy Li and Matthew Lease},
  journal= {arXiv preprint arXiv:2109.09689},
  year   = {2022}
}
R2 v1 2026-06-24T06:09:04.720Z