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CesarCEOAI/PubMedQA

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Hugging Face2026-03-17 更新2026-03-29 收录
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--- annotations_creators: - expert-generated - machine-generated language_creators: - expert-generated language: - en license: - mit multilinguality: - monolingual size_categories: - 100K<n<1M - 10K<n<100K - 1K<n<10K source_datasets: - original task_categories: - question-answering task_ids: - multiple-choice-qa paperswithcode_id: pubmedqa pretty_name: PubMedQA config_names: - pqa_artificial - pqa_labeled - pqa_unlabeled dataset_info: - config_name: pqa_artificial features: - name: pubid dtype: int32 - name: question dtype: string - name: context sequence: - name: contexts dtype: string - name: labels dtype: string - name: meshes dtype: string - name: long_answer dtype: string - name: final_decision dtype: string splits: - name: train num_bytes: 443501057 num_examples: 211269 download_size: 233411194 dataset_size: 443501057 - config_name: pqa_labeled features: - name: pubid dtype: int32 - name: question dtype: string - name: context sequence: - name: contexts dtype: string - name: labels dtype: string - name: meshes dtype: string - name: reasoning_required_pred dtype: string - name: reasoning_free_pred dtype: string - name: long_answer dtype: string - name: final_decision dtype: string splits: - name: train num_bytes: 2088898 num_examples: 1000 download_size: 1075513 dataset_size: 2088898 - config_name: pqa_unlabeled features: - name: pubid dtype: int32 - name: question dtype: string - name: context sequence: - name: contexts dtype: string - name: labels dtype: string - name: meshes dtype: string - name: long_answer dtype: string splits: - name: train num_bytes: 125922964 num_examples: 61249 download_size: 66010017 dataset_size: 125922964 configs: - config_name: pqa_artificial data_files: - split: train path: pqa_artificial/train-* - config_name: pqa_labeled data_files: - split: train path: pqa_labeled/train-* - config_name: pqa_unlabeled data_files: - split: train path: pqa_unlabeled/train-* --- # Dataset Card for [Dataset Name] ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [PubMedQA homepage](https://pubmedqa.github.io/ ) - **Repository:** [PubMedQA repository](https://github.com/pubmedqa/pubmedqa) - **Paper:** [PubMedQA: A Dataset for Biomedical Research Question Answering](https://arxiv.org/abs/1909.06146) - **Leaderboard:** [PubMedQA: Leaderboard](https://pubmedqa.github.io/) ### Dataset Summary The task of PubMedQA is to answer research questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial fibrillation after coronary artery bypass grafting?) using the corresponding abstracts. ### Supported Tasks and Leaderboards The official leaderboard is available at: https://pubmedqa.github.io/. 500 questions in the `pqa_labeled` are used as the test set. They can be found at https://github.com/pubmedqa/pubmedqa. ### Languages English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@tuner007](https://github.com/tuner007) for adding this dataset.

注释生成者: - 专家生成 - 机器生成 语言生成者: - 专家生成 语言: - 英语(en) 许可证: - MIT协议 多语言属性: - 单语言 规模类别: - 10万<样本数<100万 - 1万<样本数<10万 - 1千<样本数<1万 源数据集: - 原始数据集 任务类别: - 问答 任务子类型: - 多选问答(multiple-choice-qa) PaperWithCode标识:pubmedqa 规范名称:PubMedQA 配置名称: - pqa_artificial - pqa_labeled - pqa_unlabeled 数据集信息: - 配置名称:pqa_artificial 字段特征: - 字段名:pubid 数据类型:int32 - 字段名:question 数据类型:字符串 - 字段名:context 类型为序列,包含子字段: - 字段名:contexts 数据类型:字符串 - 字段名:labels 数据类型:字符串 - 字段名:meshes 数据类型:字符串 - 字段名:long_answer 数据类型:字符串 - 字段名:final_decision 数据类型:字符串 数据分割: - 分割名称:train 数据字节数:443501057 样本数量:211269 下载大小:233411194 数据集总大小:443501057 - 配置名称:pqa_labeled 字段特征: - 字段名:pubid 数据类型:int32 - 字段名:question 数据类型:字符串 - 字段名:context 类型为序列,包含子字段: - 字段名:contexts 数据类型:字符串 - 字段名:labels 数据类型:字符串 - 字段名:meshes 数据类型:字符串 - 字段名:reasoning_required_pred 数据类型:字符串 - 字段名:reasoning_free_pred 数据类型:字符串 - 字段名:long_answer 数据类型:字符串 - 字段名:final_decision 数据类型:字符串 数据分割: - 分割名称:train 数据字节数:2088898 样本数量:1000 下载大小:1075513 数据集总大小:2088898 - 配置名称:pqa_unlabeled 字段特征: - 字段名:pubid 数据类型:int32 - 字段名:question 数据类型:字符串 - 字段名:context 类型为序列,包含子字段: - 字段名:contexts 数据类型:字符串 - 字段名:labels 数据类型:字符串 - 字段名:meshes 数据类型:字符串 - 字段名:long_answer 数据类型:字符串 数据分割: - 分割名称:train 数据字节数:125922964 样本数量:61249 下载大小:66010017 数据集总大小:125922964 配置项: - 配置名称:pqa_artificial 数据文件: - 分割:train 路径:pqa_artificial/train-* - 配置名称:pqa_labeled 数据文件: - 分割:train 路径:pqa_labeled/train-* - 配置名称:pqa_unlabeled 数据文件: - 分割:train 路径:pqa_unlabeled/train-* # PubMedQA 数据集卡片 ## 目录 - [数据集概述](#dataset-description) - [数据集摘要](#dataset-summary) - [支持任务与排行榜](#supported-tasks-and-leaderboards) - [语言](#languages) - [数据集结构](#dataset-structure) - [数据实例](#data-instances) - [数据字段](#data-fields) - [数据分割](#data-splits) - [数据集构建](#dataset-creation) - [构建依据](#curation-rationale) - [源数据](#source-data) - [注释](#annotations) - [个人与敏感信息](#personal-and-sensitive-information) - [数据集使用注意事项](#considerations-for-using-the-data) - [数据集的社会影响](#social-impact-of-dataset) - [偏差讨论](#discussion-of-biases) - [其他已知局限性](#other-known-limitations) - [附加信息](#additional-information) - [数据集维护者](#dataset-curators) - [许可证信息](#licensing-information) - [引用信息](#citation-information) - [贡献](#contributions) ## 数据集概述 - **主页:** [PubMedQA 官方主页](https://pubmedqa.github.io/) - **代码仓库:** [PubMedQA 代码仓库](https://github.com/pubmedqa/pubmedqa) - **论文:** [《PubMedQA:一款生物医学研究问答数据集》](https://arxiv.org/abs/1909.06146) - **排行榜:** [PubMedQA 官方排行榜](https://pubmedqa.github.io/) ### 数据集摘要 PubMedQA 的任务是基于对应学术论文摘要,以“是/否/不确定”三种形式回答生物医学研究问题(示例:术前他汀类药物是否会降低冠状动脉搭桥术后的心房颤动发生率?)。 ### 支持任务与排行榜 官方排行榜地址为:https://pubmedqa.github.io/。`pqa_labeled` 配置中的500条问题被用作测试集,可从 https://github.com/pubmedqa/pubmedqa 获取该测试集。 ### 语言 英语 ## 数据集结构 ### 数据实例 [需补充更多信息] ### 数据字段 [需补充更多信息] ### 数据分割 [需补充更多信息] ## 数据集构建 ### 构建依据 [需补充更多信息] ### 源数据 #### 初始数据收集与标准化 [需补充更多信息] #### 源语言生成者是谁? [需补充更多信息] ### 注释 #### 注释流程 [需补充更多信息] #### 注释者是谁? [需补充更多信息] ### 个人与敏感信息 [需补充更多信息] ## 数据集使用注意事项 ### 数据集的社会影响 [需补充更多信息] ### 偏差讨论 [需补充更多信息] ### 其他已知局限性 [需补充更多信息] ## 附加信息 ### 数据集维护者 [需补充更多信息] ### 许可证信息 [需补充更多信息] ### 引用信息 [需补充更多信息] ### 贡献 感谢 [@tuner007](https://github.com/tuner007) 提交本数据集。
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