Datasets:
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---
annotations_creators:
- expert-generated
language_creators:
- machine-generated
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
pretty_name: BOUN
size_categories:
- unknown
source_datasets:
- original
task_categories:
- structure-prediction
task_ids:
- structure-prediction-other-word-segmentation
---
# Dataset Card for BOUN
## Dataset Description
- **Repository:** [ardax/hashtag-segmentor](https://github.com/ardax/hashtag-segmentor)
- **Paper:** [Segmenting hashtags using automatically created training data](http://www.lrec-conf.org/proceedings/lrec2016/pdf/708_Paper.pdf)
### Dataset Summary
Automatically segmented 803K SNAP Twitter Data Set hashtags with the heuristic described in the paper "Segmenting hashtags using automatically created training data".
### Languages
English
## Dataset Structure
### Data Instances
```
{
"index": 0,
"hashtag": "BrandThunder",
"segmentation": "Brand Thunder"
}
```
### Data Fields
- `index`: a numerical index.
- `hashtag`: the original hashtag.
- `segmentation`: the gold segmentation for the hashtag.
### Citation Information
```
@inproceedings{celebi2016segmenting,
title={Segmenting hashtags using automatically created training data},
author={Celebi, Arda and {\"O}zg{\"u}r, Arzucan},
booktitle={Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
pages={2981--2985},
year={2016}
}
```
### Contributions
This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github..com/ruanchaves/hashformers) library.
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