
# WPS - Chinese Simile

## Dataset Description

- **Paper:** [Writing Polishment with Simile: Task, Dataset and A Neural Approach](https://arxiv.org/abs/2012.08117)

## Dataset Summary

Chinese Simile (CS) Dataset

This dataset is constructed and based on the online free-access fictions that are tagged with sci-fi, urban novel, love story, youth, etc.

All similes are extracted by rich regular expression, and the extraction precision is estimated as 92% by labelling 500 random extracted samples. Further data filtering as well as processing is truly encouraged!

The data split in paper is as follows (You could find more details in the paper):

Train	Dev	Test
5,485,721	2,500	2,500

For the details of this dataset, we refer you to the original [paper](https://arxiv.org/abs/2012.08117).

Metadata in **Creative Language Toolkit ([CLTK](https://github.com/liyucheng09/cltk))**:
- CL Type: Simile
- Task Type: Detection, Generation
- Size: 5M
- Created time: 2021
- Language: zh

### Citation Information

If you find this dataset helpful, please cite:

```
@inproceedings{Zhang2020WritingPW,
  title={Writing Polishment with Simile: Task, Dataset and A Neural Approach},
  author={Jiayi Zhang and Z. Cui and Xiaoqiang Xia and Ya-Long Guo and Yanran Li and Chen Wei and Jianwei Cui},
  booktitle={AAAI},
  year={2021}
}
```

### Contributions

If you have any queries, please open an issue or direct your queries to [mail](mailto:yucheng.li@surrey.ac.uk).
license:cc-by-2.0 arxiv:2012.08117 region:us
{"license": "cc-by-2.0"}
TAGS
#license-cc-by-2.0 #arxiv-2012.08117 #region-us 


# WPS - Chinese Simile

## Dataset Description

- Paper: Writing Polishment with Simile: Task, Dataset and A Neural Approach

## Dataset Summary

Chinese Simile (CS) Dataset

This dataset is constructed and based on the online free-access fictions that are tagged with sci-fi, urban novel, love story, youth, etc.

All similes are extracted by rich regular expression, and the extraction precision is estimated as 92% by labelling 500 random extracted samples. Further data filtering as well as processing is truly encouraged!

The data split in paper is as follows (You could find more details in the paper):

Train	Dev	Test
5,485,721	2,500	2,500

For the details of this dataset, we refer you to the original paper.

Metadata in Creative Language Toolkit (CLTK):
- CL Type: Simile
- Task Type: Detection, Generation
- Size: 5M
- Created time: 2021
- Language: zh



If you find this dataset helpful, please cite:



### Contributions

If you have any queries, please open an issue or direct your queries to mail.
# WPS - Chinese Simile ## Dataset Description

- Paper: Writing Polishment with Simile: Task, Dataset and A Neural Approach ## Dataset Summary

Chinese Simile (CS) Dataset

This dataset is constructed and based on the online free-access fictions that are tagged with sci-fi, urban novel, love story, youth, etc.

All similes are extracted by rich regular expression, and the extraction precision is estimated as 92% by labelling 500 random extracted samples. Further data filtering as well as processing is truly encouraged!

The data split in paper is as follows (You could find more details in the paper):

Train	Dev	Test
5,485,721	2,500	2,500

For the details of this dataset, we refer you to the original paper.

Metadata in Creative Language Toolkit (CLTK):
- CL Type: Simile
- Task Type: Detection, Generation
- Size: 5M
- Created time: 2021
- Language: zh



If you find this dataset helpful, please cite: ### Contributions

If you have any queries, please open an issue or direct your queries to mail.
TAGS
#license-cc-by-2.0 #arxiv-2012.08117 #region-us 
 # WPS - Chinese Simile ## Dataset Description

- Paper: Writing Polishment with Simile: Task, Dataset and A Neural Approach ## Dataset Summary

Chinese Simile (CS) Dataset

This dataset is constructed and based on the online free-access fictions that are tagged with sci-fi, urban novel, love story, youth, etc.

All similes are extracted by rich regular expression, and the extraction precision is estimated as 92% by labelling 500 random extracted samples. Further data filtering as well as processing is truly encouraged!

The data split in paper is as follows (You could find more details in the paper):

Train	Dev	Test
5,485,721	2,500	2,500

For the details of this dataset, we refer you to the original paper.

Metadata in Creative Language Toolkit (CLTK):
- CL Type: Simile
- Task Type: Detection, Generation
- Size: 5M
- Created time: 2021
- Language: zh



If you find this dataset helpful, please cite: ### Contributions

If you have any queries, please open an issue or direct your queries to mail.
passage: TAGS
#license-cc-by-2.0 #arxiv-2012.08117 #region-us 
# WPS - Chinese Simile## Dataset Description

- Paper: Writing Polishment with Simile: Task, Dataset and A Neural Approach## Dataset Summary

Chinese Simile (CS) Dataset

This dataset is constructed and based on the online free-access fictions that are tagged with sci-fi, urban novel, love story, youth, etc.

All similes are extracted by rich regular expression, and the extraction precision is estimated as 92% by labelling 500 random extracted samples. Further data filtering as well as processing is truly encouraged!

The data split in paper is as follows (You could find more details in the paper):

Train	Dev	Test
5,485,721	2,500	2,500

For the details of this dataset, we refer you to the original paper.

Metadata in Creative Language Toolkit (CLTK):
- CL Type: Simile
- Task Type: Detection, Generation
- Size: 5M
- Created time: 2021
- Language: zh



If you find this dataset helpful, please cite:### Contributions

If you have any queries, please open an issue or direct your queries to mail.