Datasets:
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README.md
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---
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---
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annotations_creators:
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- machine-generated
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language_creators:
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- machine-generated
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languages:
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- en-IN
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licenses:
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- unknown
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multilinguality:
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- monolingual
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pretty_name: HashSet Distant Sampled
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size_categories:
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- unknown
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source_datasets:
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- original
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task_categories:
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- structure-prediction
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task_ids:
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- structure-prediction-other-word-segmentation
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---
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# Dataset Card for HashSet Distant Sampled
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## Dataset Description
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- **Repository:** [prashantkodali/HashSet](https://github.com/prashantkodali/HashSet)
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- **Paper:** [HashSet -- A Dataset For Hashtag Segmentation](https://arxiv.org/abs/2201.06741)
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### Dataset Summary
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Hashset is a new dataset consisiting on 1.9k manually annotated and 3.3M loosely supervised tweets for testing the
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efficiency of hashtag segmentation models. We compare State of The Art Hashtag Segmentation models on Hashset and other
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baseline datasets (STAN and BOUN). We compare and analyse the results across the datasets to argue that HashSet can act
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as a good benchmark for hashtag segmentation tasks.
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HashSet Distant: 3.3M loosely collected camel cased hashtags containing hashtag and their segmentation.
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HashSet Distant Sampled is a sample of 20,000 camel cased hashtags from the HashSet Distant dataset.
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### Languages
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Indian English.
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## Dataset Structure
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### Data Instances
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```
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{
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'index': 282559,
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'hashtag': 'Youth4Nation',
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'segmentation': 'Youth 4 Nation'
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}
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```
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### Citation Information
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```
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@article{kodali2022hashset,
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title={HashSet--A Dataset For Hashtag Segmentation},
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author={Kodali, Prashant and Bhatnagar, Akshala and Ahuja, Naman and Shrivastava, Manish and Kumaraguru, Ponnurangam},
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journal={arXiv preprint arXiv:2201.06741},
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year={2022}
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}
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```
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### Contributions
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This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github..com/ruanchaves/hashformers) library.
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