Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
100K - 1M
ArXiv:
License:
metadata
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1k<10K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: TweetNER7
Dataset Card for "tner/tweetner7"
Dataset Description
- Repository: T-NER
- Paper: TBA
- Dataset: TweetNER7
- Domain: Twitter
- Number of Entity: 7
Dataset Summary
TweeBank NER dataset formatted in a part of TNER project.
- Entity Types:
corperation
,creative_work
,event
,group
,location
,product
,person
Dataset Structure
Data Instances
An example of train
looks as follows.
{
'tokens': ['Morning', '5km', 'run', 'with', '{{USERNAME}}', 'for', 'breast', 'cancer', 'awareness', '#', 'pinkoctober', '#', 'breastcancerawareness', '#', 'zalorafit', '#', 'zalorafitxbnwrc', '@', 'The', 'Central', 'Park', ',', 'Desa', 'Parkcity', '{{URL}}'],
'tags': [14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 2, 14, 2, 14, 14, 14, 14, 14, 14, 4, 11, 11, 11, 11, 14],
'id': '1183344337016381440',
'date': '2019-10-13'
}
Label ID
The label2id dictionary can be found at here.
{
"B-corporation": 0,
"B-creative_work": 1,
"B-event": 2,
"B-group": 3,
"B-location": 4,
"B-person": 5,
"B-product": 6,
"I-corporation": 7,
"I-creative_work": 8,
"I-event": 9,
"I-group": 10,
"I-location": 11,
"I-person": 12,
"I-product": 13,
"O": 14
}
Data Splits
name | train | validation | test | train_2020 | validation_2020 | test_2020 | train_2021 | validation_2021 | test_2021 | extra_2020 | extra_2021 |
---|---|---|---|---|---|---|---|---|---|---|---|
tweetner7 | 4616 | 576 | 2807 | 4616 | 576 | 576 | 2495 | 310 | 2807 | 87880 | 93594 |
Citation Information
TBA