Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K - 100K
License:
File size: 3,422 Bytes
6186068 6531c54 6186068 a1cc0d4 cf9ef57 6186068 cf9ef57 6186068 3d788d0 6186068 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 | ---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: Ontonotes5
configs:
- config_name: ontonotes5
data_files:
- split: train
path: ontonotes5/train-*
- split: validation
path: ontonotes5/validation-*
- split: test
path: ontonotes5/test-*
default: true
dataset_info:
config_name: ontonotes5
features:
- name: tokens
sequence: string
- name: tags
sequence: int32
splits:
- name: train
num_bytes: 13828647
num_examples: 59924
- name: validation
num_bytes: 1874112
num_examples: 8528
- name: test
num_bytes: 1934244
num_examples: 8262
download_size: 4700778
dataset_size: 17637003
---
# 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",
}
``` |