--- name: announcement-layout-parsing-805b5bd72d20 description: 用于公告结构拆分的公告版式解析原子 skill，适用于通用行业文档解析场景。 --- # 公告版式解析 Skill ## 数据来源 本 Skill 支持多种公告文档输入格式，核心数据来源包括： ### 1. 公告文档类型 - **PDF格式**：上市公司公告PDF文档 - **Word格式**：公告Word文档 - **HTML格式**：交易所网站公告页面 - **图片格式**：扫描版公告图片 ### 2. 公告内容类型 - **定期报告**：年报、半年报、季报 - **临时公告**：重大事项公告、权益变动公告 - **监管公告**：监管问询、行政处罚公告 - **交易公告**：停复牌公告、交易异常波动公告 ### 3. 文档特征 - **语言类型**：中文、英文 - **版式类型**：标准版式、复杂版式、扫描版式 - **文档大小**：小文档（<5MB）、大文档（>5MB） ### 4. 数据格式要求 - **文件路径**：本地文件路径或网络文件URL - **文件编码**：UTF-8、GBK、GB2312等 - **文件权限**：需要读取权限 > 说明：本 Skill 不包含文档采集功能，需要用户提供公告文档文件。建议文档格式规范，以便进行准确的版式解析。 --- ## 功能 本 Skill 提供全面的公告版式解析能力，涵盖多种解析功能： ### 1. 公告结构识别 - **公告标题识别**：识别公告标题和公告类型 - **公告编号识别**：识别公告编号和发布机构 - **公告日期识别**：识别公告发布日期和生效日期 - **公告主体识别**：识别公告正文主体内容 ### 2. 章节结构解析 - **章节层级识别**：识别公告的章节层级结构 - **章节标题提取**：提取各级章节标题 - **章节内容提取**：提取各章节的具体内容 - **章节定位**：记录章节在文档中的位置 ### 3. 表格识别 - **财务表格识别**：识别财务报表相关表格 - **数据表格识别**：识别数据统计表格 - **表格结构解析**：解析表格的行列结构 - **表格内容提取**：提取表格的具体数据 ### 4. 关键信息提取 - **公司信息提取**：提取公司名称、股票代码等信息 - **关键日期提取**：提取重要日期和时间节点 - **金额信息提取**：提取涉及金额和数值信息 - **关联方信息提取**：提取关联方和交易对手信息 ### 5. 版式还原 - **版式结构还原**：尽可能还原公告的原始版式 - **格式信息保留**：保留字体、字号等格式信息 - **布局信息记录**：记录页面布局和元素位置 ### 6. 高级处理功能 - **OCR识别**：对扫描版公告进行OCR识别 - **多语言识别**：识别公告中的多语言内容 - **结构化输出**：输出结构化的公告内容 --- ## 使用示例 ### 输出示例 ```json { "document_info": { "filename": "announcement.pdf", "file_size": 512000, "page_count": 10, "language": "zh-CN", "announcement_type": "重大事项公告" }, "header": { "title": "关于重大资产重组的公告", "announcement_number": "2024-001", "company_name": "示例股份有限公司", "stock_code": "000001", "publish_date": "2024-03-15", "publish_org": "上海证券交易所" }, "structure": { "sections": [ { "level": 1, "title": "一、交易概述", "content": "交易概述内容...", "page": 1 }, { "level": 1, "title": "二、交易对方基本情况", "content": "交易对方基本情况...", "page": 2 } ] }, "tables": [ { "table_id": 1, "type": "financial_table", "position": { "page": 5, "section": "三、交易标的基本情况" }, "rows": 8, "columns": 4, "data": [ ["项目", "2024年", "2023年", "2022年"], ["营业收入", "1000", "900", "800"] ] } ], "key_information": { "company_name": "示例股份有限公司", "stock_code": "000001", "transaction_amount": 500000000, "transaction_date": "2024-03-20", "related_parties": ["关联公司A", "关联公司B"] } } ``` --- ## 注意事项与限制 ### 1. 文档格式要求 - 支持标准公告格式文档 - 复杂版式可能影响解析准确性 - 扫描版公告需要OCR功能支持 ### 2. 解析准确性 - 标准版式公告解析准确率较高 - 非标准版式可能影响结构识别 - OCR识别准确率受图片质量影响 ### 3. 性能考虑 - 大文档处理可能需要较长时间 - 内存占用与文档大小成正比 - 建议对超大文档进行分页处理 ### 4. 版式差异 - 不同交易所公告版式可能不同 - 需要适配不同版式的解析规则 - 新版式可能需要更新解析规则 ### 5. 使用限制 - 本 Skill 不包含文档编辑功能 - 解析结果需要人工复核 - 受保护文档可能无法解析 --- ## 参考资料 - 见 references/ 目录中的相关文档，包括： - 公告版式解析方法手册 - 公告结构识别算法说明 - OCR识别使用指南 - 性能优化指南 ## License - 本 skill 代码部分采用 MIT License，详见 `LICENSE` 文件 - 依赖与运行环境以 `requirements.txt` 为准 - 文档内容采用 CC BY 4.0 许可 --- Source attribution: aifinlab Original project: https://github.com/aifinlab/FinClaw/blob/9e62862d1412157fa03ffd1f0b74969dcf0ed66c/skills/announcement-layout-parsing/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. 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