Datasets:
Tasks:
Text Retrieval
ArXiv:
Sean MacAvaney
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- beir_arguana.py +0 -1
README.md
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---
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pretty_name: '`beir/arguana`'
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viewer: false
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---
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# Dataset Card for `beir/arguana`
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The `beir/arguana`
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- `docs` (documents, i.e., the corpus)
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- `queries` (i.e., topics)
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- `qrels`: (relevance assessments)
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Find more information about the dataset [here](https://ir-datasets.com/{dsid.split('/')[0]}#{dsid}).
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## Usage
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```python
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from datasets import load_dataset
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```
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## Citation Information
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---
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pretty_name: '`beir/arguana`'
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viewer: false
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source_datasets: []
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task_categories:
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- text-retrieval
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---
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# Dataset Card for `beir/arguana`
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The `beir/arguana` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
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For more information about the dataset, see the [documentation](https://ir-datasets.com/beir#beir/arguana).
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# Data
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This dataset provides:
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- `docs` (documents, i.e., the corpus); count=8,674
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- `queries` (i.e., topics); count=1,406
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- `qrels`: (relevance assessments); count=1,406
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## Usage
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```python
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from datasets import load_dataset
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docs = load_dataset('irds/beir_arguana', 'docs')
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for record in docs:
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record # {'doc_id': ..., 'text': ..., 'title': ...}
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queries = load_dataset('irds/beir_arguana', 'queries')
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for record in queries:
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record # {'query_id': ..., 'text': ...}
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qrels = load_dataset('irds/beir_arguana', 'qrels')
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for record in qrels:
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record # {'query_id': ..., 'doc_id': ..., 'relevance': ..., 'iteration': ...}
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```
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Note that calling `load_dataset` will download the dataset (or provide access instructions when it's not public) and make a copy of the
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data in 🤗 Dataset format.
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## Citation Information
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beir_arguana.py
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class beir_arguana(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
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DEFAULT_CONFIG_NAME = list(IRDS_ENTITY_TYPES)[0]
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def _info(self):
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return datasets.DatasetInfo(
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class beir_arguana(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [datasets.BuilderConfig(name=e) for e in IRDS_ENTITY_TYPES]
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def _info(self):
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return datasets.DatasetInfo(
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