ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source

Fuente: arXiv
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Autores principales: Le, Hung Tuan, To, Long Truong, Nguyen, Manh Trong, Van Nguyen, Kiet
Formato: Preprint
Publicado: 2024
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author Le, Hung Tuan
To, Long Truong
Nguyen, Manh Trong
Van Nguyen, Kiet
author_facet Le, Hung Tuan
To, Long Truong
Nguyen, Manh Trong
Van Nguyen, Kiet
contents Fact-checking is essential due to the explosion of misinformation in the media ecosystem. Although false information exists in every language and country, most research to solve the problem mainly concentrated on huge communities like English and Chinese. Low-resource languages like Vietnamese are necessary to explore corpora and models for fact verification. To bridge this gap, we construct ViWikiFC, the first manual annotated open-domain corpus for Vietnamese Wikipedia Fact Checking more than 20K claims generated by converting evidence sentences extracted from Wikipedia articles. We analyze our corpus through many linguistic aspects, from the new dependency rate, the new n-gram rate, and the new word rate. We conducted various experiments for Vietnamese fact-checking, including evidence retrieval and verdict prediction. BM25 and InfoXLM (Large) achieved the best results in two tasks, with BM25 achieving an accuracy of 88.30% for SUPPORTS, 86.93% for REFUTES, and only 56.67% for the NEI label in the evidence retrieval task, InfoXLM (Large) achieved an F1 score of 86.51%. Furthermore, we also conducted a pipeline approach, which only achieved a strict accuracy of 67.00% when using InfoXLM (Large) and BM25. These results demonstrate that our dataset is challenging for the Vietnamese language model in fact-checking tasks.
format Preprint
id arxiv_https___arxiv_org_abs_2405_07615
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source
Le, Hung Tuan
To, Long Truong
Nguyen, Manh Trong
Van Nguyen, Kiet
Computation and Language
Fact-checking is essential due to the explosion of misinformation in the media ecosystem. Although false information exists in every language and country, most research to solve the problem mainly concentrated on huge communities like English and Chinese. Low-resource languages like Vietnamese are necessary to explore corpora and models for fact verification. To bridge this gap, we construct ViWikiFC, the first manual annotated open-domain corpus for Vietnamese Wikipedia Fact Checking more than 20K claims generated by converting evidence sentences extracted from Wikipedia articles. We analyze our corpus through many linguistic aspects, from the new dependency rate, the new n-gram rate, and the new word rate. We conducted various experiments for Vietnamese fact-checking, including evidence retrieval and verdict prediction. BM25 and InfoXLM (Large) achieved the best results in two tasks, with BM25 achieving an accuracy of 88.30% for SUPPORTS, 86.93% for REFUTES, and only 56.67% for the NEI label in the evidence retrieval task, InfoXLM (Large) achieved an F1 score of 86.51%. Furthermore, we also conducted a pipeline approach, which only achieved a strict accuracy of 67.00% when using InfoXLM (Large) and BM25. These results demonstrate that our dataset is challenging for the Vietnamese language model in fact-checking tasks.
title ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source
topic Computation and Language
url https://arxiv.org/abs/2405.07615