irds/lotte_technology_test_search

---
pretty_name: '`lotte/technology/test/search`'
viewer: false
source_datasets: ['irds/lotte_technology_test']
task_categories:
- text-retrieval
---

# Dataset Card for `lotte/technology/test/search`

The `lotte/technology/test/search` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/lotte#lotte/technology/test/search).

# Data

This dataset provides:
- `queries` (i.e., topics); count=596
- `qrels`: (relevance assessments); count=2,045

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

## Usage

```python
from datasets import load_dataset

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

qrels = load_dataset('irds/lotte_technology_test_search', '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

```
@article{Santhanam2021ColBERTv2,
title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia",
journal= "arXiv preprint arXiv:2112.01488",
year = "2021",
url = "https://arxiv.org/abs/2112.01488"
}
```

原始信息汇总

数据集卡片 lotte/technology/test/search

数据集概述

lotte/technology/test/search 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 596
• qrels（相关性评估）：数量为 2,045

对于 docs，请使用 irds/lotte_technology_test。

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/lotte_technology_test_search, queries) for record in queries: record # {query_id: ..., text: ...}

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

注意：调用 load_dataset 将下载数据集（或提供非公开数据集的访问指令），并在 🤗 数据集格式中创建数据的副本。

引用信息

@article{Santhanam2021ColBERTv2, title = "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction", author = "Keshav Santhanam and Omar Khattab and Jon Saad-Falcon and Christopher Potts and Matei Zaharia", journal= "arXiv preprint arXiv:2112.01488", year = "2021", url = "https://arxiv.org/abs/2112.01488" }