irds/neumarco_ru_train

---
pretty_name: '`neumarco/ru/train`'
viewer: false
source_datasets: ['irds/neumarco_ru']
task_categories:
- text-retrieval
---

# Dataset Card for `neumarco/ru/train`

The `neumarco/ru/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/neumarco#neumarco/ru/train).

# Data

This dataset provides:
- `queries` (i.e., topics); count=808,731
- `qrels`: (relevance assessments); count=532,761
- `docpairs`; count=269,919,004

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

This dataset is used by: [`neumarco_ru_train_judged`](https://huggingface.co/datasets/irds/neumarco_ru_train_judged)

## Usage

```python
from datasets import load_dataset

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

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

docpairs = load_dataset('irds/neumarco_ru_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.

原始信息汇总

数据集概述

数据集名称

neumarco/ru/train

数据来源

• 原始数据集：irds/neumarco_ru

数据内容

• queries：查询主题，数量为808,731
• qrels：相关性评估，数量为532,761
• docpairs：文档对，数量为269,919,004

数据使用

• 用于数据集：neumarco_ru_train_judged

数据加载示例

python from datasets import load_dataset

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

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

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