X-Fact: A New Benchmark Dataset for Multilingual Fact Checking

Ashim Gupta and Vivek Srikumar

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL), 2021.

Abstract

In this work, we introduce X-FACT: the largest publicly available multilingual dataset for factual verification of naturally existing real-world claims. The dataset contains short statements in 25 languages and is labeled for veracity by expert fact-checkers. The dataset includes a multilingual evaluation benchmark that measures both out-of-domain generalization, and zero-shot capabilities of the multilingual models. Using state-of-the-art multilingual transformer-based models, we develop several automated fact-checking models that, along with textual claims, make use of additional metadata and evidence from news stories retrieved using a search engine. Empirically, our best model attains an F-score of around 40%, suggesting that our dataset is a challenging benchmark for evaluation of multilingual fact-checking models.

Bib Entry

@inproceedings{gupta2021x-fact,
  author = {Gupta, Ashim and Srikumar, Vivek},
  title = {{X-Fact: A New Benchmark Dataset for Multilingual Fact Checking}},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL)},
  year = {2021}
}

Vivek Srikumar