NQ-retrieval
收藏魔搭社区2025-12-10 更新2025-06-14 收录
下载链接:
https://modelscope.cn/datasets/sentence-transformers/NQ-retrieval
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资源简介:
#NQ-retrieval
This is a nicely formatted version of the [Natural Questions](https://ai.google.com/research/NaturalQuestions/) dataset, formatted to train and evaluate retrieval systems.
Each row contains the following entries:
- **question**: Original question send for Google Search Engine
- **title**: Title of Wikipedia article
- **candidates**: A list with the passages from the original Wikipedia HTML document
- **passage_types**: Types (text, table, list) of the candidate passages
- **long_answers**: IDs which candidate passages where selected as relevant from annotators. Might be empty if no relevant passage has been identified
- **document_url**
#NQ-retrieval
本数据集为规范化处理后的[自然问题(Natural Questions)](https://ai.google.com/research/NaturalQuestions/)数据集版本,专为检索系统的训练与评估构建。
每条数据行包含以下字段:
- **问题(question)**:提交至谷歌搜索引擎(Google Search Engine)的原始查询问题
- **标题(title)**:对应维基百科(Wikipedia)文章的标题
- **候选段落集(candidates)**:源自原始维基百科HTML文档的段落列表
- **段落类型(passage_types)**:候选段落的类型(文本、表格、列表)
- **长答案标注(long_answers)**:标注人员选定的相关候选段落的ID。若未识别出相关段落,则该字段为空
- **文档链接(document_url)**
提供机构:
maas
创建时间:
2025-01-06



