five

irds/mr-tydi_sw

收藏
Hugging Face2023-01-05 更新2024-03-04 收录
下载链接:
https://hf-mirror.com/datasets/irds/mr-tydi_sw
下载链接
链接失效反馈
官方服务:
资源简介:
--- pretty_name: '`mr-tydi/sw`' viewer: false source_datasets: [] task_categories: - text-retrieval --- # Dataset Card for `mr-tydi/sw` The `mr-tydi/sw` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/mr-tydi#mr-tydi/sw). # Data This dataset provides: - `docs` (documents, i.e., the corpus); count=136,689 - `queries` (i.e., topics); count=3,271 - `qrels`: (relevance assessments); count=3,767 This dataset is used by: [`mr-tydi_sw_dev`](https://huggingface.co/datasets/irds/mr-tydi_sw_dev), [`mr-tydi_sw_test`](https://huggingface.co/datasets/irds/mr-tydi_sw_test), [`mr-tydi_sw_train`](https://huggingface.co/datasets/irds/mr-tydi_sw_train) ## Usage ```python from datasets import load_dataset docs = load_dataset('irds/mr-tydi_sw', 'docs') for record in docs: record # {'doc_id': ..., 'text': ...} queries = load_dataset('irds/mr-tydi_sw', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/mr-tydi_sw', '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{Zhang2021MrTyDi, title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin}, year={2021}, journal={arXiv:2108.08787}, } @article{Clark2020TyDiQa, title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}, year={2020}, journal={Transactions of the Association for Computational Linguistics} } ```
提供机构:
irds
原始信息汇总

数据集卡片 mr-tydi/sw

数据集概述

mr-tydi/sw 数据集由 ir-datasets 包提供。

数据内容

  • 文档 (docs): 包含 136,689 个文档。
  • 查询 (queries): 包含 3,271 个查询。
  • 相关性评估 (qrels): 包含 3,767 个相关性评估。

使用方法

以下是使用 datasets 库加载数据集的示例代码:

python from datasets import load_dataset

docs = load_dataset(irds/mr-tydi_sw, docs) for record in docs: record # {doc_id: ..., text: ...}

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

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

引用信息

@article{Zhang2021MrTyDi, title={{Mr. TyDi}: A Multi-lingual Benchmark for Dense Retrieval}, author={Xinyu Zhang and Xueguang Ma and Peng Shi and Jimmy Lin}, year={2021}, journal={arXiv:2108.08787}, } @article{Clark2020TyDiQa, title={{TyDi QA}: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages}, author={Jonathan H. Clark and Eunsol Choi and Michael Collins and Dan Garrette and Tom Kwiatkowski and Vitaly Nikolaev and Jennimaria Palomaki}, year={2020}, journal={Transactions of the Association for Computational Linguistics} }

5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作