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@@ -1,3 +1,110 @@
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- ---
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- license: odc-by
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: odc-by
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+ tags:
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+ - 文档解析
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+ - 文档智能
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+ - OCR Bench
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+ - Doc Parsing
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+ - OCR
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+ - pdf
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+ - markdown
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+ ---
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+
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+ DocParsingBench是一个包含1400张图片的文档智能测评数据集,系统性地采集并标注了来自真实业务流程的文档样本,首次系统性总结企业高频的文档元素,涵盖金融、法律、科研、工业、教育五大领域。
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+
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+ [![Hugging Face](https://img.shields.io/badge/🤗%20Hugging%20Face-SmartDoc--Industry-blue)](https://)
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+ [![License](https://img.shields.io/badge/License-ODC--BY-blue)](LICENSE)
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+ [![Version](https://img.shields.io/badge/Version-1.0.0-orange)]()
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+
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+
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+ ---
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+ ## 🆕 最新资讯
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+
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+ **[2026.03.09]** DocParsingBench v1.0 正式发布!首个**面向真实行业场景**的智能文档解析数据集,涵盖金融、法律、科研、工业、教育五大领域。现已上线 Hugging Face!🔥🔥🔥
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+
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+ ---
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+
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+ ## 🎯 核心亮点
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+
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+ ### ✅ 1. 五大真实行业场景
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+
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+ 我们系统性地采集并标注了来自**真实业务流程**的文档样本,保留了**扫描噪声、印章遮挡、模糊字符**:
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+
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+ | 行业 | 文档类型 | 场景特征 |
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+ |------|---------|---------|
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+ | **金融** | 券商研报、上市公司财报、招股说明书 | 多栏报表、带印章的PDF扫描件、复杂表格 |
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+ | **法律** | 法律文书、合同条款、行业标准规范 | 页眉页脚规范化、脚注密集、参考文献交叉引用 |
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+ | **科研** | 学术论文、编程教材、专利全文 | 双栏/三栏混合、公式密集、代码段、化学式 |
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+ | **工业制造** | 操作SOP、表格单据 | 扫描件模糊、手写填空项、二维码/条形码 |
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+ | **教育** | 书籍教材、英文、化学、数学 | 化学结构式、化学反应式、选择题选项、填空空白 |
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+
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+
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+ ### ✅ 2. 复杂版面全覆盖
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+
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+ - **单栏**:教材、法律文书
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+ - **双栏**:学术论文、部分研报
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+ - **三栏及以上**:券商财报、数据报表
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+ - **混合布局**:图文混排、表格跨栏、侧边栏嵌套
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+
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+ ---
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+
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+ ## 📊 数据构成
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+
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+ | 维度 | 分类 |
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+ |------|------|
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+ | **总样本量** | 1400页 |
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+ | **语言** | 中文、英文、中英混合|
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+ | **行业分布** | 金融 / 法律 / 科研 / 工业 / 教育 |
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+ | **版面分布** | 单栏 / 双栏 / 三栏 / 混合 |
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+ | **标注格式** | Markdown
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+ | **化学标注** | 采用 [SoMarkdown](https://github.com/SoMarkAI/SoMarkDown) 规范,将 SMILES 与 LaTeX 结合进行表达,可完整渲染化学结构式
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+
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+ ---
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+
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+ ## 🏗️ 数据处理与标注理念
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+ - **坚持全人工标注**,因为文档解析的“正确答案”不该是模型猜出来的。因为我们在实践中发现:模型预标注的误差会被标注员“惯性接受”。标注员面对已有markdown结果时,倾向于微调而非重画,导致模型错误被固化。每一根框线,都是一笔一笔画出来的;每一个字都是通过键盘输入的。这不是效率最高的方式,但这是质量最高的方式。
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+ - 这是本项目投入时间最长的环节。我们为每一类文档元素制定了详细的边界判定规则,逐类试标、迭代、定稿。
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+ - 每一类规范都经过3轮以上试标+全员培训+一致性测试,确保不同标注员对同一页面的判定差异<5%。累计退回重标批次6轮,标注-复核工时比1 : 0.8
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+
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+
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+ ## 📈 评测基准(待发布)
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+
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+ 我们同期发布的DocParsingBench**行业文档解析评测基准**欢迎社区参与评测!📊
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+
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+
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+ ## ❤️ 致谢
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+
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+ 这是一个需要极大耐心的工作。一个复杂页面的化学式+表格混排,可能耗时数小时;一次边界分歧导致的整批次退回,意味着数百小时的重来。每一页标注的背后,都是人眼对文档结构的理解,是人手对markdown的确认。感谢所有标注团队的坚持。
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+
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+ 同时感谢 [SoMarkdown](https://github.com/SoMarkAI/SoMarkDown) 项目提供的化学结构式标注规范,使我们能够用精确表达大模型可读的化学内容。
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+
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+ ---
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+
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+ ## 📖 引用
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+
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+ 如果您在研究中使用了DocParsingBench,请按如下格式引用:
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+
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+ ```bibtex
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+ @misc{DocParsingBench-2026,
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+ title={DocParsingBench},
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+ author={SoMark},
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+ year={2026},
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+ publisher={Hugging Face,ModelScope},
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+ howpublished={\url{https://modelscope.cn/datasets/SoMark/DocParsingBench}}
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+ }
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+ ```
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+
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+ ---
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+
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+ ## 📜 许可证
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+
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+ 本项目采用 **ODC-BY (Open Data Commons Attribution License)** 许可证,开放学术研究和商业应用。
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+
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+ ---
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+ > 🌟 如果您觉得这个数据集有价值,欢迎在 modelscope/Hugging Face 上给我们 ⭐!
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+
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+
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+ #### 下载方法
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+ :modelscope-code[]{type="sdk"}
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+ :modelscope-code[]{type="git"}
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+
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