irds/nfcorpus_dev_nontopic

`nfcorpus/dev/nontopic`数据集由ir-datasets包提供，主要用于文本检索任务。该数据集包含144个查询（queries）和4,353个相关性评估（qrels）。文档部分需要从`irds/nfcorpus`数据集中获取。数据集的使用示例代码展示了如何加载查询和相关性评估数据。

The `nfcorpus/dev/nontopic` dataset is provided by the ir-datasets package and is primarily used for text retrieval tasks. It contains 144 queries and 4,353 relevance judgments (qrels). The document corpus needs to be obtained from the `irds/nfcorpus` dataset. A sample usage code is provided to demonstrate how to load the queries and relevance judgment data.

原始信息汇总

数据集概述

数据集名称

nfcorpus/dev/nontopic

数据来源

• 源数据集：irds/nfcorpus

任务类别

• 文本检索

数据内容

• queries（查询，即主题）：数量=144
• qrels（相关性评估）：数量=4,353
• docs（文档）：使用irds/nfcorpus数据集

使用示例

python from datasets import load_dataset

queries = load_dataset(irds/nfcorpus_dev_nontopic, queries) for record in queries: record # {query_id: ..., text: ...}

qrels = load_dataset(irds/nfcorpus_dev_nontopic, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ...}

引用信息

@inproceedings{Boteva2016Nfcorpus, title="A Full-Text Learning to Rank Dataset for Medical Information Retrieval", author = "Vera Boteva and Demian Gholipour and Artem Sokolov and Stefan Riezler", booktitle = "Proceedings of the European Conference on Information Retrieval ({ECIR})", location = "Padova, Italy", publisher = "Springer", year = 2016 }