Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Multilinguality:
monolingual
Size Categories:
1k<10K
ArXiv:
Tags:
License:
| 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](https://github.com/asahi417/tner) | |
| - **Paper:** TBA | |
| - **Dataset:** TweetNER7 | |
| - **Domain:** Twitter | |
| - **Number of Entity:** 7 | |
| ### Dataset Summary | |
| TweeBank NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. | |
| - Entity Types: `corperation`, `creative_work`, `event`, `group`, `location`, `product`, `person` | |
| ## Dataset Structure | |
| ### Data Instances | |
| An example of `train` looks as follows. | |
| ``` | |
| { | |
| } | |
| ``` | |
| ### Label ID | |
| The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/tweetner7/raw/main/dataset/label.json). | |
| ```python | |
| { | |
| "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| | |
| |---------|----:|---------:|---:| | |
| |tweetner7 | 1639| 710 |1201| | |
| ### Citation Information | |
| ``` | |
| TBA | |
| ``` |