metadata

annotations_creators:
  - expert-generated
language_creators:
  - machine-generated
language:
  - ru
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - unknown
source_datasets:
  - original
task_categories:
  - structure-prediction
task_ids: []
pretty_name: NRU-HSE
tags:
  - word-segmentation

Dataset Card for NRU-HSE

Table of Contents
Dataset Description
- Dataset Summary
- Languages
Dataset Structure
- Data Instances
- Data Fields
Dataset Creation
Additional Information
- Citation Information
- Contributions

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 and segmentation or identifier and segmentation.
The only difference between hashtag and segmentation or between identifier and segmentation 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.