irds/mmarco_v2_es_train

---
pretty_name: '`mmarco/v2/es/train`'
viewer: false
source_datasets: ['irds/mmarco_v2_es']
task_categories:
- text-retrieval
---

# Dataset Card for `mmarco/v2/es/train`

The `mmarco/v2/es/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/mmarco#mmarco/v2/es/train).

# Data

This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=39,780,811

- For `docs`, use [`irds/mmarco_v2_es`](https://huggingface.co/datasets/irds/mmarco_v2_es)

## Usage

```python
from datasets import load_dataset

queries = load_dataset('irds/mmarco_v2_es_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}

qrels = load_dataset('irds/mmarco_v2_es_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}

docpairs = load_dataset('irds/mmarco_v2_es_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}

```

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

```
@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}
```

---
pretty_name: '`mmarco/v2/es/train`'
viewer: 禁用
source_datasets: ['irds/mmarco_v2_es']
task_categories:
- 文本检索
---

# `mmarco/v2/es/train` 数据集卡片

本`mmarco/v2/es/train`数据集由[ir-datasets](https://ir-datasets.com/)工具包提供。如需了解该数据集的更多详情，请参阅[官方文档](https://ir-datasets.com/mmarco#mmarco/v2/es/train)。

# 数据

本数据集包含以下内容：
- `queries`（即查询主题）：共计808,731条
- `qrels`（相关性标注）：共计532,761条
- `docpairs`：共计39,780,811条
- 如需获取`docs`数据，请使用 [`irds/mmarco_v2_es`](https://huggingface.co/datasets/irds/mmarco_v2_es) 数据集

## 使用方法

python
from datasets import load_dataset

queries = load_dataset('irds/mmarco_v2_es_train', 'queries')
for record in queries:
record # {'query_id': ..., 'text': ...}

qrels = load_dataset('irds/mmarco_v2_es_train', 'qrels')
for record in qrels:
record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}

docpairs = load_dataset('irds/mmarco_v2_es_train', 'docpairs')
for record in docpairs:
record # {'query_id': ..., 'doc_id_a': ..., 'doc_id_b': ...}

请注意，调用`load_dataset`函数将自动下载该数据集（若数据集未公开，则会提供获取指引），并将数据转换为🤗数据集格式进行存储。

## 引用信息

@article{Bonifacio2021MMarco,
title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset},
author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira},
year={2021},
journal={arXiv:2108.13897}
}

原始信息汇总

数据集卡片 mmarco/v2/es/train

数据集概述

mmarco/v2/es/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 808,731
• qrels（相关性评估）；数量为 532,761
• docpairs；数量为 39,780,811

对于 docs，请使用 irds/mmarco_v2_es。

使用方法

以下是加载和使用数据集的示例代码： python from datasets import load_dataset

queries = load_dataset(irds/mmarco_v2_es_train, queries) for record in queries: record # {query_id: ..., text: ...}

qrels = load_dataset(irds/mmarco_v2_es_train, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ..., iteration: ...}

docpairs = load_dataset(irds/mmarco_v2_es_train, docpairs) for record in docpairs: record # {query_id: ..., doc_id_a: ..., doc_id_b: ...}

引用信息

@article{Bonifacio2021MMarco, title={{mMARCO}: A Multilingual Version of {MS MARCO} Passage Ranking Dataset}, author={Luiz Henrique Bonifacio and Israel Campiotti and Roberto Lotufo and Rodrigo Nogueira}, year={2021}, journal={arXiv:2108.13897} }