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- ---
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- license: cc-by-4.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-4.0
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+ ---
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+ ---
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+ # Dataset Card for Dataset Name
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+
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+ <!-- Provide a quick summary of the dataset. -->
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+ This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
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+ ## Dataset Details
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+ ### Dataset Description
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+ <!-- Provide a longer summary of what this dataset is. -->
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+ # CleanComedy
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+ Humour generation is a challenging task in natural language processing due to limited resources and the quality of existing datasets. Available humour language resources often suffer from toxicity and duplication, limiting their effectiveness for training robust models. In this paper, we present CleanComedy, a specialised, partially annotated corpus, which includes jokes in English and Russian languages. The dataset is a filtered collection of existing sources, where toxic jokes and duplicates are removed with various algorithmic filters. The end quality of the dataset is validated with human assessment. We also present subjective human humour score annotation for 1,000 Russian and 1,000 English jokes providing detailed, ethical and comprehensive dataset for humour detection and generation tasks.
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+ - **Curated by:** Dmitry Vikhorev, Daria Galimzianova, Svetlana Gorovaia, Elizaveta Zhemchuzhina, Ivan P. Yamshchikov
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+ - **Language(s) (NLP):** English, Russian
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+ - **License:** CC-BY-4.0
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+
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+ ### Dataset Sources [optional]
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+
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+ <!-- Provide the basic links for the dataset. -->
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+ - **Repository:** (https://github.com/gorovuha/CleanComedy)
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+ - **Paper [optional]:** [CleanComedy: Creating Friendly Humor through Generative Techniques](https://arxiv.org/pdf/2412.09203)
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+
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+ ## Dataset Structure
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+ <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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+ ### CleanComedy English
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+ Ethical filtered jokes with 2-scale score
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+ 44,481 instances
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+
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+ ### CleanComedy English Gold
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+ Ethical filtered jokes with human humour 5-scale score
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+ 1,000 instances
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+ ### CleanComedy Russian
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+ Ethical filtered jokes with 2-scale score
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+ 40,926 instances
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+
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+ ### CleanComedy Russian Gold
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+ Ethical filtered jokes with human humour 5-scale score
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+ 1,000 instances
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+ **BibTeX:**
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+ @misc{vikhorev2024cleancomedycreatingfriendlyhumor,
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+ title={CleanComedy: Creating Friendly Humor through Generative Techniques},
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+ author={Dmitry Vikhorev and Daria Galimzianova and Svetlana Gorovaia and Elizaveta Zhemchuzhina and Ivan P. Yamshchikov},
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+ year={2024},
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+ eprint={2412.09203},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2412.09203},
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+ }