irds/beir_nfcorpus_train

`beir/nfcorpus/train`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2,590条查询（queries）和110,575条相关性评估（qrels）。文档部分需要从`irds/beir_nfcorpus`数据集中获取。数据集的使用示例代码展示了如何通过Python加载查询和相关性评估数据。

原始信息汇总

数据集概述

数据集名称

beir/nfcorpus/train

数据来源

由ir-datasets包提供。

数据内容

• queries: 查询语句，共2,590条。
• qrels: 相关性评估，共110,575条。
• docs: 文档数据，需通过irds/beir_nfcorpus获取。

使用示例

python from datasets import load_dataset

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

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

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 } @article{Thakur2021Beir, title = "BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models", author = "Thakur, Nandan and Reimers, Nils and Rücklé, Andreas and Srivastava, Abhishek and Gurevych, Iryna", journal= "arXiv preprint arXiv:2104.08663", month = "4", year = "2021", url = "https://arxiv.org/abs/2104.08663", }