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--- |
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pretty_name: '`kilt/codec`' |
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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 `kilt/codec` |
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The `kilt/codec` 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/kilt#kilt/codec). |
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# Data |
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This dataset provides: |
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- `queries` (i.e., topics); count=42 |
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- `qrels`: (relevance assessments); count=11,323 |
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## Usage |
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```python |
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from datasets import load_dataset |
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queries = load_dataset('irds/kilt_codec', 'queries') |
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for record in queries: |
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record # {'query_id': ..., 'query': ..., 'domain': ..., 'guidelines': ...} |
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qrels = load_dataset('irds/kilt_codec', '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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``` |
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@inproceedings{mackie2022codec, |
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title={CODEC: Complex Document and Entity Collection}, |
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author={Mackie, Iain and Owoicho, Paul and Gemmell, Carlos and Fischer, Sophie and MacAvaney, Sean and Dalton, Jeffery}, |
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booktitle={Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval}, |
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year={2022} |
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} |
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``` |
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