# 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} } ```