NUMTEMP: A real-world benchmark to verify claims with statistical and
  temporal expressions
Venktesh V Abhijit Anand Avishek Anand Vinay Setty
Automated fact checking has gained immense interest to tackle the growing
misinformation in the digital era. Existing systems primarily focus on
synthetic claims on Wikipedia, and noteworthy progress has also been made on
real-world claims. In this work, we release Numtemp, a diverse, multi-domain
dataset focused exclusively on numerical claims, encompassing temporal,
statistical and diverse aspects with fine-grained metadata and an evidence
collection without leakage. This addresses the challenge of verifying
real-world numerical claims, which are complex and often lack precise
information, not addressed by existing works that mainly focus on synthetic
claims. We evaluate and quantify the limitations of existing solutions for the
task of verifying numerical claims. We also evaluate claim decomposition based
methods, numerical understanding based models and our best baselines achieves a
macro-F1 of 58.32. This demonstrates that Numtemp serves as a challenging
evaluation set for numerical claim verification.