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--- |
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annotations_creators: |
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- no-annotation |
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language: |
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- zh |
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- en |
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license: |
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- apache-2.0 |
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pretty_name: CSL |
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size_categories: |
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- 100K<n<1M |
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source_datasets: |
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- extended|csl |
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tags: [] |
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task_categories: |
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- text-retrieval |
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task_ids: |
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- document-retrieval |
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--- |
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|
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# Dataset Card for CSL |
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## Dataset Description |
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CSL is the Chinese Scientific Literature Dataset. |
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- **Paper:** https://aclanthology.org/2022.coling-1.344 |
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- **Repository:** https://github.com/ydli-ai/CSL |
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### Dataset Summary |
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The dataset contains titles, abstracts, keywords of papers written in Chinese from several academic fields. |
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### Languages |
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- Chinese |
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- English (translation) |
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## Dataset Structure |
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### Data Instances |
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| Split | Documents | |
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|-----------------|----------:| |
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| `csl` | 396k | |
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| `en_translation`| 396k | |
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### Data Fields |
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- `doc_id`: unique identifier for this document |
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- `title`: title of the paper |
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- `abstract`: abstract of the paper |
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- `keywords`: keywords associated with the paper |
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- `category`: the broad category of the paper |
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- `category_eng`: English translaction of the broad category (e.g., Engineering) |
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- `discipline`: academic discipline of the paper |
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- `discipline_eng`: English translation of the academic discipline (e.g., Agricultural Engineering) |
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The `en_translation` contains documents translated from Google Translation service. |
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All text are in English, so the fields `category_eng` and `discipline_eng` are omitted. |
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## Dataset Usage |
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Using 🤗 Datasets: |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset('neuclir/csl')['csl'] |
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``` |
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## License & Citation |
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This dataset is based off the [Chinese Scientific Literature Dataset](https://github.com/ydli-ai/CSL) under Apache 2.0. |
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The primay change is the addition of `doc_id`s, English translactions of the category and discipline descriptions by a native speaker, |
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and basic de-duplication. Code that performed this modification is avalable in [this repository](https://github.com/NeuCLIR/csl-preprocess). |
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If you use this data, please cite: |
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``` |
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@inproceedings{li-etal-2022-csl, |
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title = "{CSL}: A Large-scale {C}hinese Scientific Literature Dataset", |
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author = "Li, Yudong and |
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Zhang, Yuqing and |
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Zhao, Zhe and |
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Shen, Linlin and |
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Liu, Weijie and |
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Mao, Weiquan and |
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Zhang, Hui", |
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booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", |
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month = oct, |
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year = "2022", |
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address = "Gyeongju, Republic of Korea", |
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publisher = "International Committee on Computational Linguistics", |
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url = "https://aclanthology.org/2022.coling-1.344", |
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pages = "3917--3923", |
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} |
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``` |
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