annotations_creators:
- expert-generated
language_creators:
- machine-generated
language:
- ru
license:
- unknown
multilinguality:
- monolingual
pretty_name: NRU-HSE
size_categories:
- unknown
source_datasets:
- original
task_categories:
- structure-prediction
task_ids:
- structure-prediction-other-word-segmentation
Dataset Card for NRU-HSE
Table of Contents
Dataset Description
- Repository: glushkovato/hashtag_segmentation
- Paper: Char-RNN and Active Learning for Hashtag Segmentation
Dataset Summary
Real hashtags collected from several pages about civil services on vk.com (a Russian social network) and then segmented manually.
Languages
Russian
Dataset Structure
Data Instances
{
"index": 0,
"hashtag": "ЁлкаВЗазеркалье",
"segmentation": "Ёлка В Зазеркалье"
}
Data Fields
index
: a numerical index.hashtag
: the original hashtag.segmentation
: the gold segmentation for the hashtag.
Dataset Creation
All hashtag segmentation and identifier splitting datasets on this profile have the same basic fields:
hashtag
andsegmentation
oridentifier
andsegmentation
.The only difference between
hashtag
andsegmentation
or betweenidentifier
andsegmentation
are the whitespace characters. Spell checking, expanding abbreviations or correcting characters to uppercase go into other fields.There is always whitespace between an alphanumeric character and a sequence of any special characters ( such as
_
,:
,~
).If there are any annotations for named entity recognition and other token classification tasks, they are given in a
spans
field.
Additional Information
Citation Information
@article{glushkova2019char,
title={Char-RNN and Active Learning for Hashtag Segmentation},
author={Glushkova, Taisiya and Artemova, Ekaterina},
journal={arXiv preprint arXiv:1911.03270},
year={2019}
}
Contributions
This dataset was added by @ruanchaves while developing the hashformers library.