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# FactSense Dataset
## Overview
FactSense is the linguistic layer of FactNet that provides multilingual, natural language expressions of facts extracted from Wikipedia pages. Each FactSense instance represents a FactStatement realized in natural text with provenance information.
+ Paper: https://arxiv.org/abs/2602.03417
+ Github: https://github.com/yl-shen/factnet
+ Dataset: https://huggingface.co/collections/openbmb/factnet
## Dataset Format
The dataset contains parquet files with the following key fields:
- `factsense_id`: Unique identifier for the FactSense instance
- `belongs_to_statement_id`: ID of the associated FactStatement
- `language`: Language code (e.g., 'en', 'zh')
- `page_id`: Wikipedia page ID
- `page_title`: Title of the Wikipedia page
- `page_namespace`: Wikipedia namespace
- `match_type`: Type of match (sitelink, sitelink_pagelink, label_based, etc.)
- `sentence`: Text snippet containing the fact mention (limited to 1000 chars)
- `sentence_index`: Position of the sentence in the paragraph/page
- `confidence`: Match confidence score (0.5-0.9)
- `subject_qid`: Subject entity QID
- `property_pid`: Property PID
- `value_qid`: Value entity QID (if applicable)
- `subject_label`: Label used for matching
- `value_label`: Value label used for matching
- `extraction_method`: Extraction strategy version
- `extraction_ts`: Extraction timestamp
## Usage
FactSense instances provide natural language evidence for facts across multiple languages, enabling applications in multilingual fact checking, knowledge-grounded generation, and cross-lingual information retrieval.
## License
This dataset contains text derived from Wikipedia and is available under the CC BY-SA license.
## Citation
```
@article{shen2026factnet,
title={FactNet: A Billion-Scale Knowledge Graph for Multilingual Factual Grounding},
author={Shen, Yingli and Lai, Wen and Zhou, Jie and Zhang, Xueren and Wang, Yudong and Luo, Kangyang and Wang, Shuo and Gao, Ge and Fraser, Alexander and Sun, Maosong},
journal={arXiv preprint arXiv:2602.03417},
year={2026}
}
``` |