Datasets:

tranthaihoa
/

vifactcheck

language:
  - vi
license: mit
task_categories:
  - text-classification
  - question-answering
task_ids:
  - natural-language-inference
  - fact-checking
  - fact-checking-retrieval
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
pretty_name: ViFactCheck
arxiv: 2412.15308
tags:
  - fact-checking
  - vietnamese
  - NLP
  - misinformation
  - fake-news
  - claim-verification
  - natural-language-inference
  - low-resource
  - news
  - benchmark
  - AAAI
  - AAAI-25
  - multi-domain
  - evidence-retrieval

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

Field	Type	Description
`Statement`	`string`	The claim to be verified (in Vietnamese)
`Context`	`string`	Full article context from which the claim was derived
`Evidence`	`string`	Annotated gold evidence snippet(s) supporting the label
`Topic`	`string`	News domain/topic (12 categories, see below)
`Author`	`string`	Source newspaper (one of 9 licensed outlets)
`Url`	`string`	URL of the original news article
`labels`	`int64`	Fact-checking label: `0` = Supported, `1` = Refuted, `2` = NEI
`annotation_id`	`int64`	Unique annotation identifier
`index`	`int64`	Original dataset index

Label Distribution

Label	ID	Meaning
Supported	`0`	The context/evidence supports the claim
Refuted	`1`	The context/evidence contradicts the claim
NEI	`2`	Not Enough Information to verify the claim

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=NEI

import 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.