irds/beir_hotpotqa_train

---
pretty_name: '`beir/hotpotqa/train`'
viewer: false
source_datasets: ['irds/beir_hotpotqa']
task_categories:
- text-retrieval
---

# Dataset Card for `beir/hotpotqa/train`

The `beir/hotpotqa/train` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/beir#beir/hotpotqa/train).

# Data

This dataset provides:
- `queries` (i.e., topics); count=85,000
- `qrels`: (relevance assessments); count=170,000

- For `docs`, use [`irds/beir_hotpotqa`](https://huggingface.co/datasets/irds/beir_hotpotqa)

## Usage

```python
from datasets import load_dataset

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

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

```

Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
data in 🤗 Dataset format.

## Citation Information

```
@inproceedings{Yang2018Hotpotqa,
title = "{H}otpot{QA}: A Dataset for Diverse, Explainable Multi-hop Question Answering",
author = "Yang, Zhilin and
Qi, Peng and
Zhang, Saizheng and
Bengio, Yoshua and
Cohen, William and
Salakhutdinov, Ruslan and
Manning, Christopher D.",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/D18-1259",
doi = "10.18653/v1/D18-1259",
pages = "2369--2380"
}
@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",
}
```

原始信息汇总

数据集卡片 beir/hotpotqa/train

数据集概述

beir/hotpotqa/train 数据集由 ir-datasets 包提供。

数据内容

该数据集包含以下内容：

• queries（即主题）：数量为 85,000
• qrels（相关性评估）：数量为 170,000

对于 docs，请使用 irds/beir_hotpotqa。

使用方法

以下是加载和使用该数据集的示例代码：

python from datasets import load_dataset

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

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

引用信息

@inproceedings{Yang2018Hotpotqa, title = "{H}otpot{QA}: A Dataset for Diverse, Explainable Multi-hop Question Answering", author = "Yang, Zhilin and Qi, Peng and Zhang, Saizheng and Bengio, Yoshua and Cohen, William and Salakhutdinov, Ruslan and Manning, Christopher D.", booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing", month = oct # "-" # nov, year = "2018", address = "Brussels, Belgium", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/D18-1259", doi = "10.18653/v1/D18-1259", pages = "2369--2380" } @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", }

搜集汇总

背景与挑战

背景概述

该数据集是BEIR基准中HotpotQA的训练集部分，专门用于文本检索任务，包含85,000个查询和170,000个相关性评估，支持多跳问答和信息检索模型的零样本评估。数据集基于HotpotQA研究，旨在提供多样化和可解释的问答数据，以促进信息检索技术的发展。