Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
ArXiv:
License:
File size: 2,124 Bytes
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---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1k<10K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: TweeBank NER
---
# Dataset Card for "tner/tweebank_ner"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tner)
- **Paper:** [https://arxiv.org/abs/2201.07281](https://arxiv.org/abs/2201.07281)
- **Dataset:** TweeBank NER
- **Domain:** Twitter
- **Number of Entity:** 4
### Dataset Summary
TweeBank NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project.
- Entity Types: `LOC`, `MISC`, `PER`, `ORG`
## Dataset Structure
### Data Instances
An example of `train` looks as follows.
```
{
'tokens': ['RT', '@USER2362', ':', 'Farmall', 'Heart', 'Of', 'The', 'Holidays', 'Tabletop', 'Christmas', 'Tree', 'With', 'Lights', 'And', 'Motion', 'URL1087', '#Holiday', '#Gifts'],
'tags': [8, 8, 8, 2, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8]
}
```
### Label ID
The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/tweebank_ner/raw/main/dataset/label.json).
```python
{
"B-LOC": 0,
"B-MISC": 1,
"B-ORG": 2,
"B-PER": 3,
"I-LOC": 4,
"I-MISC": 5,
"I-ORG": 6,
"I-PER": 7,
"O": 8
}
```
### Data Splits
| name |train|validation|test|
|---------|----:|---------:|---:|
|tweebank_ner | 1639| 710 |1201|
### Citation Information
```
@article{DBLP:journals/corr/abs-2201-07281,
author = {Hang Jiang and
Yining Hua and
Doug Beeferman and
Deb Roy},
title = {Annotating the Tweebank Corpus on Named Entity Recognition and Building
{NLP} Models for Social Media Analysis},
journal = {CoRR},
volume = {abs/2201.07281},
year = {2022},
url = {https://arxiv.org/abs/2201.07281},
eprinttype = {arXiv},
eprint = {2201.07281},
timestamp = {Fri, 21 Jan 2022 13:57:15 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2201-07281.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
``` |