Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Tags:
License:
| language: | |
| - en | |
| license: | |
| - other | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| pretty_name: Ontonotes5 | |
| # Dataset Card for "tner/ontonotes5" | |
| ## Dataset Description | |
| - **Repository:** [T-NER](https://github.com/asahi417/tner) | |
| - **Paper:** [https://aclanthology.org/N06-2015/](https://aclanthology.org/N06-2015/) | |
| - **Dataset:** Ontonotes5 | |
| - **Domain:** News | |
| - **Number of Entity:** 8 | |
| ### Dataset Summary | |
| Ontonotes5 NER dataset formatted in a part of [TNER](https://github.com/asahi417/tner) project. | |
| - Entity Types: `CARDINAL`, `DATE`, `PERSON`, `NORP`, `GPE`, `LAW`, `PERCENT`, `ORDINAL`, `MONEY`, `WORK_OF_ART`, `FAC`, `TIME`, `QUANTITY`, `PRODUCT`, `LANGUAGE`, `ORG`, `LOC`, `EVENT` | |
| ## Dataset Structure | |
| ### Data Instances | |
| An example of `train` looks as follows. | |
| ``` | |
| { | |
| 'tags': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 5, 0, 0, 0, 0, 11, 12, 12, 12, 12, 0, 0, 7, 0, 0, 0, 0, 0], | |
| 'tokens': ['``', 'It', "'s", 'very', 'costly', 'and', 'time', '-', 'consuming', ',', "''", 'says', 'Phil', 'Rosen', ',', 'a', 'partner', 'in', 'Fleet', '&', 'Leasing', 'Management', 'Inc.', ',', 'a', 'Boston', 'car', '-', 'leasing', 'company', '.'] | |
| } | |
| ``` | |
| ### Label ID | |
| The label2id dictionary can be found at [here](https://huggingface.co/datasets/tner/onotonotes5/raw/main/dataset/label.json). | |
| ```python | |
| { | |
| "O": 0, | |
| "B-CARDINAL": 1, | |
| "B-DATE": 2, | |
| "I-DATE": 3, | |
| "B-PERSON": 4, | |
| "I-PERSON": 5, | |
| "B-NORP": 6, | |
| "B-GPE": 7, | |
| "I-GPE": 8, | |
| "B-LAW": 9, | |
| "I-LAW": 10, | |
| "B-ORG": 11, | |
| "I-ORG": 12, | |
| "B-PERCENT": 13, | |
| "I-PERCENT": 14, | |
| "B-ORDINAL": 15, | |
| "B-MONEY": 16, | |
| "I-MONEY": 17, | |
| "B-WORK_OF_ART": 18, | |
| "I-WORK_OF_ART": 19, | |
| "B-FAC": 20, | |
| "B-TIME": 21, | |
| "I-CARDINAL": 22, | |
| "B-LOC": 23, | |
| "B-QUANTITY": 24, | |
| "I-QUANTITY": 25, | |
| "I-NORP": 26, | |
| "I-LOC": 27, | |
| "B-PRODUCT": 28, | |
| "I-TIME": 29, | |
| "B-EVENT": 30, | |
| "I-EVENT": 31, | |
| "I-FAC": 32, | |
| "B-LANGUAGE": 33, | |
| "I-PRODUCT": 34, | |
| "I-ORDINAL": 35, | |
| "I-LANGUAGE": 36 | |
| } | |
| ``` | |
| ### Data Splits | |
| | name |train|validation|test| | |
| |---------|----:|---------:|---:| | |
| |ontonotes5|59924| 8528|8262| | |
| ### Citation Information | |
| ``` | |
| @inproceedings{hovy-etal-2006-ontonotes, | |
| title = "{O}nto{N}otes: The 90{\%} Solution", | |
| author = "Hovy, Eduard and | |
| Marcus, Mitchell and | |
| Palmer, Martha and | |
| Ramshaw, Lance and | |
| Weischedel, Ralph", | |
| booktitle = "Proceedings of the Human Language Technology Conference of the {NAACL}, Companion Volume: Short Papers", | |
| month = jun, | |
| year = "2006", | |
| address = "New York City, USA", | |
| publisher = "Association for Computational Linguistics", | |
| url = "https://aclanthology.org/N06-2015", | |
| pages = "57--60", | |
| } | |
| ``` |