|
--- |
|
annotations_creators: |
|
- no-annotation |
|
language: |
|
- zh |
|
language_creators: |
|
- found |
|
license: |
|
- apache-2.0 |
|
pretty_name: CSL |
|
size_categories: |
|
- 1M<n<10M |
|
source_datasets: |
|
- extended|csl |
|
tags: [] |
|
task_categories: |
|
- text-retrieval |
|
task_ids: |
|
- document-retrieval |
|
--- |
|
|
|
# Dataset Card for CSL |
|
|
|
## Dataset Description |
|
|
|
CSL is the Chinese Scientific Literature Dataset. |
|
|
|
- **Paper:** https://aclanthology.org/2022.coling-1.344 |
|
- **Repository:** https://github.com/ydli-ai/CSL |
|
|
|
### Dataset Summary |
|
|
|
The dataset contains titles, abstracts, keywords of papers written in Chinese from several academic fields. |
|
|
|
### Languages |
|
|
|
- Chinese |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
| Split | Documents | |
|
|-----------------|----------:| |
|
| `csl` | 396k | |
|
|
|
### Data Fields |
|
- `id`: unique identifier for this document |
|
- `cc_file`: source file from connon crawl |
|
- `time`: extracted date/time from article |
|
- `title`: title extracted from article |
|
- `text`: extracted article body |
|
- `url`: source URL |
|
|
|
## Dataset Usage |
|
|
|
Using 🤗 Datasets: |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
dataset = load_dataset('neuclir/csl')['csl'] |
|
``` |
|
|
|
## License & Citation |
|
|
|
This dataset is based off the [Chinese Scientific Literature Dataset](https://github.com/ydli-ai/CSL) under Apache 2.0. |
|
The primay change is the addition of English translactions of the category and discipline descriptions by a native speaker. |
|
|
|
If you use this data, please cite: |
|
|
|
``` |
|
@inproceedings{li-etal-2022-csl, |
|
title = "{CSL}: A Large-scale {C}hinese Scientific Literature Dataset", |
|
author = "Li, Yudong and |
|
Zhang, Yuqing and |
|
Zhao, Zhe and |
|
Shen, Linlin and |
|
Liu, Weijie and |
|
Mao, Weiquan and |
|
Zhang, Hui", |
|
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", |
|
month = oct, |
|
year = "2022", |
|
address = "Gyeongju, Republic of Korea", |
|
publisher = "International Committee on Computational Linguistics", |
|
url = "https://aclanthology.org/2022.coling-1.344", |
|
pages = "3917--3923", |
|
} |
|
``` |
|
|