<b>DocFEE: A Document-Level Chinese Financial Event Extraction Dataset</b>

<b>DocFEE: A Document-Level Chinese Financial Event Extraction Dataset</b><br><br>DocFEE is a large-scale, document-level dataset designed for financial event extraction in Chinese. It contains ​<b>19,044 annotated documents</b> spanning nine critical financial event types, including <i>Bankruptcy Liquidation</i>, <i>Major Safety Incident</i>, <i>Equity Pledge</i>, and <i>Senior Executive Death</i>, among others. Each document is annotated with ​<b>38 distinct argument types</b> to capture intricate event details, such as dates, amounts, stakeholders, and contextual impacts.The dataset addresses the challenges of document-level event extraction, where events and their arguments may span multiple sentences or exhibit cross-sentence dependencies. On average, documents contain ​<b>1.86 events</b> with a broad event range (<b>960.06</b> <b>characters</b>) and a median document length of<b> 2,277.25</b> <b>characters</b>, reflecting real-world complexity. Key features include fine-grained annotations for diverse financial scenarios, such as tracking shareholder reductions (<i>Reduction Start Date</i>, <i>Shareholder</i>, <i>Reduction Amount</i>) or quantifying losses in <i>Major Asset Loss</i> events (<i>Loss Amount</i>, <i>Other Losses</i>).DocFEE supports research in financial NLP, regulatory compliance, and risk analysis by providing robust, structured data for modeling cross-sentence event relations and argument extraction in long-form texts. Its comprehensive annotations and domain specificity make it a valuable resource for advancing document-level understanding in Chinese financial contexts.<br><br>Please refer to README.pdf for detailed description.