Datasets:
Sub-tasks:
named-entity-recognition
Multilinguality:
multilingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
Tags:
word-segmentation
License:
annotations_creators: | |
- expert-generated | |
language_creators: | |
- machine-generated | |
language: | |
- hi | |
- en | |
license: | |
- unknown | |
multilinguality: | |
- multilingual | |
size_categories: | |
- unknown | |
source_datasets: | |
- original | |
task_categories: | |
- structure-prediction | |
task_ids: | |
- named-entity-recognition | |
pretty_name: HashSet Manual | |
tags: | |
- word-segmentation | |
# Dataset Card for HashSet Manual | |
## Dataset Description | |
- **Repository:** [prashantkodali/HashSet](https://github.com/prashantkodali/HashSet) | |
- **Paper:** [HashSet -- A Dataset For Hashtag Segmentation](https://arxiv.org/abs/2201.06741) | |
### Dataset Summary | |
Hashset is a new dataset consisting on 1.9k manually annotated and 3.3M loosely supervised tweets for testing the | |
efficiency of hashtag segmentation models. We compare State of The Art Hashtag Segmentation models on Hashset and other | |
baseline datasets (STAN and BOUN). We compare and analyse the results across the datasets to argue that HashSet can act | |
as a good benchmark for hashtag segmentation tasks. | |
HashSet Manual: contains 1.9k manually annotated hashtags. Each row consists of the hashtag, segmented hashtag ,named entity annotations, whether the hashtag contains mix of hindi and english tokens and/or contains non-english tokens. | |
### Languages | |
Mostly Hindi and English. | |
## Dataset Structure | |
### Data Instances | |
``` | |
{ | |
"index": 10, | |
"hashtag": "goodnewsmegan", | |
"segmentation": "good news megan", | |
"spans": { | |
"start": [ | |
8 | |
], | |
"end": [ | |
13 | |
], | |
"text": [ | |
"megan" | |
] | |
}, | |
"source": "roman", | |
"gold_position": null, | |
"mix": false, | |
"other": false, | |
"ner": true, | |
"annotator_id": 1, | |
"annotation_id": 2088, | |
"created_at": "2021-12-30 17:10:33.800607", | |
"updated_at": "2021-12-30 17:10:59.714840", | |
"lead_time": 3896.182, | |
"rank": { | |
"position": [ | |
1, | |
2, | |
3, | |
4, | |
5, | |
6, | |
7, | |
8, | |
9, | |
10 | |
], | |
"candidate": [ | |
"goodnewsmegan", | |
"goodnewsmeg an", | |
"goodnews megan", | |
"goodnewsmega n", | |
"go odnewsmegan", | |
"good news megan", | |
"good newsmegan", | |
"g oodnewsmegan", | |
"goodnewsme gan", | |
"goodnewsm egan" | |
] | |
} | |
} | |
``` | |
### Data Fields | |
- `index`: a numerical index annotated by Kodali et al.. | |
- `hashtag`: the original hashtag. | |
- `segmentation`: the gold segmentation for the hashtag. | |
- `spans`: named entity spans. | |
- `source`: data source. | |
- `gold_position`: position of the gold segmentation on the `segmentation` field inside the `rank`. | |
- `mix`: The hashtag has a mix of English and Hindi tokens. | |
- `other`: The hashtag has non-English tokens. | |
- `ner`: The hashtag has named entities. | |
- `annotator_id`: annotator ID. | |
- `annotation_id`: annotation ID. | |
- `created_at`: Creation date timestamp. | |
- `updated_at`: Update date timestamp. | |
- `lead_time`: Lead time field annotated by Kodali et al.. | |
- `rank`: Rank of each candidate selected by a baseline word segmenter ( WordBreaker ). | |
- `candidates`: Candidates selected by a baseline word segmenter ( WordBreaker ). | |
## 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{kodali2022hashset, | |
title={HashSet--A Dataset For Hashtag Segmentation}, | |
author={Kodali, Prashant and Bhatnagar, Akshala and Ahuja, Naman and Shrivastava, Manish and Kumaraguru, Ponnurangam}, | |
journal={arXiv preprint arXiv:2201.06741}, | |
year={2022} | |
} | |
``` | |
### Contributions | |
This dataset was added by [@ruanchaves](https://github.com/ruanchaves) while developing the [hashformers](https://github.com/ruanchaves/hashformers) library. |