neyugntuan/vifactcheck
ViFactCheck: A Multi-Domain Vietnamese News Fact-Checking Benchmark Dataset Summary ViFactCheck is the first publicly available benchmark dataset for multi-domain news fact-checking in Vietnamese. It contains 7,232 human-annotated claim–evidence pairs sourced from nine reputable Vietnamese online news outlets, spanning 12 diverse topics. Each entry pairs a claim with its full article context and annotated evidence, labeled as Supported, Refuted, or Not Enough… See the full description on the dataset page: https://huggingface.co/datasets/neyugntuan/vifactcheck.
ViFactCheck: A Multi-Domain Vietnamese News Fact-Checking Benchmark
Dataset Summary
ViFactCheck is the first publicly available benchmark dataset for multi-domain news fact-checking in Vietnamese. It contains 7,232 human-annotated claim–evidence pairs sourced from nine reputable Vietnamese online news outlets, spanning 12 diverse topics. Each entry pairs a claim with its full article context and annotated evidence, labeled as Supported, Refuted, or Not Enough Information (NEI).
Dataset Structure
Data Fields
Label Distribution
Topics Covered (12 Domains)
The dataset spans 12 diverse Vietnamese news domains including: Politics, Law & Justice, Business & Economics, Education, Urban Affairs, Sports, Youth & Society, Culture, Environment, Health, Technology, and Entertainment.
Usage
from datasets import load_dataset
dataset = load_dataset("tranthaihoa/vifactcheck")
# Access splits
train = dataset["train"]
dev = dataset["dev"]
test = dataset["test"]
# Example entry
print(train[0]["Statement"]) # The claim (Vietnamese)
print(train[0]["Evidence"]) # Gold evidence
print(train[0]["labels"]) # 0=Supported, 1=Refuted, 2=NEIimport pandas as pd
df = pd.read_parquet("hf://datasets/tranthaihoa/vifactcheck/default/train-00000-of-00001.parquet")Citation
If you use ViFactCheck in your research, please cite:
@inproceedings{tran2025vifactcheck,
title = {ViFactCheck: A New Benchmark Dataset and Methods for Multi-Domain News Fact-Checking in Vietnamese},
author = {Tran, Thai Hoa and Tran, Quang Duy and Tran, Khanh Quoc and Nguyen, Kiet Van},
booktitle = {Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25)},
pages = {308--316},
year = {2025},
publisher = {AAAI Press}
}📧 Contact: {khanhtq,kietnv}@uit.edu.vn
This research was supported by the Scientific Research Support Fund of VNUHCM-University of Information Technology.
