irds/mr-tydi_th_train
收藏资源简介：
`mr-tydi/th/train`数据集由ir-datasets包提供，主要用于文本检索任务。该数据集包含3,319个查询（即主题）和3,360个相关评估（qrels）。文档部分需要使用`irds/mr-tydi_th`数据集。用户可以通过Python代码加载查询和相关评估数据，并获取每条记录的详细信息。
The `mr-tydi/th/train` dataset, provided by the ir-datasets package, is primarily designed for text retrieval tasks. This dataset contains 3,319 queries (i.e., topics) and 3,360 relevance judgments (qrels). The document corpus requires the use of the `irds/mr-tydi_th` dataset. Users can load the query and relevance judgment data via Python code, and obtain detailed information for each record.
Dataset Card for mr-tydi/th/train
Overview
- Dataset Name:
mr-tydi/th/train - Provider: ir-datasets package
- Source Datasets:
irds/mr-tydi_th - Task Categories: text-retrieval
Data Details
- Queries: 3,319 topics
- Qrels: 3,360 relevance assessments
- Docs: Available via
irds/mr-tydi_th
Usage Example
python from datasets import load_dataset
queries = load_dataset(irds/mr-tydi_th_train, queries) for record in queries: record # {query_id: ..., text: ...}
qrels = load_dataset(irds/mr-tydi_th_train, qrels) for record in qrels: record # {query_id: ..., doc_id: ..., relevance: ..., iteration: ...}
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} }
