irds/antique_test_non-offensive

--- pretty_name: '`antique/test/non-offensive`' viewer: false source_datasets: ['irds/antique'] task_categories: - text-retrieval --- # Dataset Card for `antique/test/non-offensive` The `antique/test/non-offensive` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package. For more information about the dataset, see the [documentation](https://ir-datasets.com/antique#antique/test/non-offensive). # Data This dataset provides: - `queries` (i.e., topics); count=176 - `qrels`: (relevance assessments); count=5,752 - For `docs`, use [`irds/antique`](https://huggingface.co/datasets/irds/antique) ## Usage ```python from datasets import load_dataset queries = load_dataset('irds/antique_test_non-offensive', 'queries') for record in queries: record # {'query_id': ..., 'text': ...} qrels = load_dataset('irds/antique_test_non-offensive', 'qrels') for record in qrels: record # {'query_id': ..., 'doc_id': ..., 'relevance': ...} ``` 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 ``` @inproceedings{Hashemi2020Antique, title={ANTIQUE: A Non-Factoid Question Answering Benchmark}, author={Helia Hashemi and Mohammad Aliannejadi and Hamed Zamani and Bruce Croft}, booktitle={ECIR}, year={2020} } ```

原始信息汇总

数据集概述

数据集名称

antique/test/non-offensive

数据来源

• 源数据集：irds/antique

数据集内容

• queries（查询主题）：共176条
• qrels（相关性评估）：共5,752条
• docs（文档）：使用irds/antique数据集

数据集用途

• 文本检索任务

数据集加载示例

python from datasets import load_dataset

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

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

引用信息

@inproceedings{Hashemi2020Antique, title={ANTIQUE: A Non-Factoid Question Answering Benchmark}, author={Helia Hashemi and Mohammad Aliannejadi and Hamed Zamani and Bruce Croft}, booktitle={ECIR}, year={2020} }