Create README.md

README.md

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+# FactNet 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.
+
+## 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}
+}
+```