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Datasets:
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RyokoAI_CNNovel125K

Tasks:
Text Classification
Text Generation
Modalities:
Text
Formats:
json
Languages:
Chinese
Size:
1K - 10K
Tags:
novel
training
Libraries:
Datasets
Dask
License:
Dataset card Viewer Files Community
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README.md DELETED
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- ---
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- license: apache-2.0
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- language:
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- - zh
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- tags:
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- - novel
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- - training
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- task_categories:
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- - text-classification
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- - text-generation
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- pretty_name: CNNovel125K
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- size_categories:
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- - 100K<n<1M
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- duplicated_from: RyokoAI/CNNovel125K
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- ---
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-
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- # Dataset Card for CNNovel125K
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-
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- *The BigKnow2022 dataset and its subsets are not yet complete. Not all information here may be accurate or accessible.*
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-
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- ## Dataset Description
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-
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- - **Homepage:** (TODO)
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- - **Repository:** <https://github.com/RyokoAI/BigKnow2022>
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- - **Paper:** N/A
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- - **Leaderboard:** N/A
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- - **Point of Contact:** Ronsor/undeleted <ronsor@ronsor.com>
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-
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- ### Dataset Summary
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-
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- CNNovel125K is a dataset composed of approximately 125,000 novels downloaded from the Chinese novel hosting site <http://ibiquw.com>.
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-
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- ### Supported Tasks and Leaderboards
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-
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- This dataset is primarily intended for unsupervised training of text generation models; however, it may be useful for other purposes.
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-
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- * text-classification
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- * text-generation
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-
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- ### Languages
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-
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- * Simplified Chinese
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-
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- ## Dataset Structure
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-
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- ### Data Instances
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-
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- ```json
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- {
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- "text": "\n------------\n\n全部章节\n\n\n------------\n\n第一章 她肯定做梦呢！\n\n HT国际大酒店总统套房。\n\n 清晨的第一缕阳光照射进圣地亚哥地板上，洒落在凌乱的床单上，突然地，床上睡的正熟的人睁开眼睛，
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- 猛然惊醒！\n\n ...",
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- "meta": {
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- "subset": "cnnovel.ibiquw",
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- "id": "100067",
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- "q": 0.9,
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- "lang": "zh_cn",
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- "title": "为爱入局：嫁给秦先生",
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- "author": "奥德萨"
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- }
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- }
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- {
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- "text": "\n------------\n\n全部章节\n\n\n------------\n\n第1章：出狱就大婚\n\n 凉城第一监狱，大门缓缓打开，秦峰仰起头，贪婪的呼吸了一口空气。\n\n 三年了，终于又闻到了自由的味道。\n\n 他回过头，看着目
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- 送他出来的那群人道：...",
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- "meta": {
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- "subset": "cnnovel.ibiquw",
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- "id": "100059",
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- "q": 0.9,
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- "lang": "zh_cn",
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- "title": "绝世弃婿",
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- "author": "绷带怪"
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- }
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- }
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- ```
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-
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- ### Data Fields
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-
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- * `text`: the actual novel text, all chapters
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- * `meta`: entry metadata
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- * `subset`: dataset tag: `cnnovel.ibiquw`
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- * `id`: novel ID
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- * `q`: quality score, fixed at 0.9
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- * `lang`: always `zh_cn` (Simplified Chinese)
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- * `title`: novel title
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- * `author`: novel author
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-
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- ### Data Splits
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-
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- No splitting of the data was performed.
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-
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- ## Dataset Creation
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-
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- ### Curation Rationale
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-
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- TODO
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-
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- ### Source Data
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-
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- #### Initial Data Collection and Normalization
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-
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- TODO
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-
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- #### Who are the source language producers?
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-
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- The authors of each novel.
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-
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- ### Annotations
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-
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- #### Annotation process
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-
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- Titles were collected alongside the novel text and IDs.
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-
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- #### Who are the annotators?
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-
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- There were no human annotators.
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-
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- ### Personal and Sensitive Information
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-
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- The dataset contains only works of fiction, and we do not believe it contains any PII.
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-
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- ## Considerations for Using the Data
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-
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- ### Social Impact of Dataset
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-
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- This dataset is intended to be useful for anyone who wishes to train a model to generate "more entertaining" content in Chinese.
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- It may also be useful for other languages depending on your language model.
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-
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- ### Discussion of Biases
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-
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- This dataset is composed of fictional works by various authors. Because of this fact, the contents of this dataset will reflect
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- the biases of those authors. Beware of stereotypes.
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-
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- ### Other Known Limitations
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-
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- N/A
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-
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- ## Additional Information
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-
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- ### Dataset Curators
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-
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- Ronsor Labs
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-
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- ### Licensing Information
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-
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- Apache 2.0, for all parts of which Ronsor Labs or the Ryoko AI Production Committee may be considered authors. All other material is
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- distributed under fair use principles.
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-
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- ### Citation Information
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-
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- ```
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- @misc{ryokoai2023-bigknow2022,
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- title = {BigKnow2022: Bringing Language Models Up to Speed},
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- author = {Ronsor},
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- year = {2023},
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- howpublished = {\url{https://github.com/RyokoAI/BigKnow2022}},
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- }
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- ```
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-
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- ### Contributions
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-
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- Thanks to @ronsor (GH) for gathering this dataset.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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