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  ### Dataset Summary
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- This dataset comprises of open-domain question-answer pairs obtained from extracting 100K FAQ URLs from C4 dataset. Please refer to the original [`paper`](https://arxiv.org/abs/1910.10683) and [`dataset card`](https://huggingface.co/datasets/c4) for more details.
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  You can load C4-FAQs as follows:
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  ```python
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  ### Curation Rationale
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- [More Information Needed]
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- ### Source Data
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- #### Initial Data Collection and Normalization
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- #### Who are the source language producers?
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- ### Annotations
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- #### Annotation process
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- #### Who are the annotators?
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- ### Personal and Sensitive Information
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- ## Considerations for Using the Data
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- ### Social Impact of Dataset
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- ### Discussion of Biases
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- ### Other Known Limitations
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  ## Additional Information
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  ### Dataset Curators
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  ### Licensing Information
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  ### Citation Information
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- ### Contributions
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- Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.
 
 
 
 
 
 
 
 
 
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  ### Dataset Summary
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+ This dataset comprises of open-domain question-answer pairs obtained from extracting 150K FAQ URLs from C4 dataset. Please refer to the original [`paper`](https://arxiv.org/abs/1910.10683) and [`dataset card`](https://huggingface.co/datasets/c4) for more details.
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  You can load C4-FAQs as follows:
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  ```python
 
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  ### Curation Rationale
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+ The dataset was curated to create end-to-end Question Generation pipelines. A large amount of open-source models use [`SQuAD`](https://huggingface.co/datasets/squad) dataset to create answer-agnostic question generation models. While the questions are valid, they often are short factoid in nature. This dataset is curated from FAQs of websites, which are generally hand-crafted and can be used to further improve generated question quality.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Additional Information
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  ### Dataset Curators
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+ Original data by [Common Crawl](https://commoncrawl.org/).
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  ### Licensing Information
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+ The original dataset was released under the terms of ODC-BY. By using this, you are also bound by the Common Crawl terms of use in respect of the content contained in the dataset.
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  ### Citation Information
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+ If you use this dataset, I would love to hear about it! Reach out on GitHub, twitter or shoot me an email.
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+ To cite the original `c4` dataset:
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+ ```bibtex
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+ @article{2019t5,
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+ author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
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+ title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
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+ journal = {arXiv e-prints},
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+ year = {2019},
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+ archivePrefix = {arXiv},
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+ eprint = {1910.10683},
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+ }
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+ ```