Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
1K - 10K
ArXiv:
License:
| 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} | |
| } | |
| ``` |