Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
Chinese
Size:
< 1K
License:
File size: 5,277 Bytes
41c9ff7 09d8aa4 41c9ff7 e521aee 41c9ff7 7c56cb0 41c9ff7 09d8aa4 41c9ff7 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- zh
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: nlp-model-tune
pretty_name: NER Model Tune
train-eval-index:
- config: default
task: token-classification
task_id: entity_extraction
splits:
train_split: train
eval_split: test
col_mapping:
tokens: tokens
ner_tags: tags
metrics:
- type: seqeval
name: seqeval
dataset_info:
features:
- name: id
dtype: string
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O,
'1': B-CARDINAL,
'2': B-DATE,
'3': B-EVENT,
'4': B-FAC,
'5': B-GPE,
'6': B-LANGUAGE,
'7': B-LAW,
'8': B-LOC,
'9': B-MONEY,
'10': B-NORP,
'11': B-ORDINAL,
'12': B-ORG,
'13': B-PERCENT,
'14': B-PERSON,
'15': B-PRODUCT,
'16': B-QUANTITY,
'17': B-TIME,
'18': B-WORK_OF_ART,
'19': I-CARDINAL,
'20': I-DATE,
'21': I-EVENT,
'22': I-FAC,
'23': I-GPE,
'24': I-LANGUAGE,
'25': I-LAW,
'26': I-LOC,
'27': I-MONEY,
'28': I-NORP,
'29': I-ORDINAL,
'30': I-ORG,
'31': I-PERCENT,
'32': I-PERSON,
'33': I-PRODUCT,
'34': I-QUANTITY,
'35': I-TIME,
'36': I-WORK_OF_ART,
'37': E-CARDINAL,
'38': E-DATE,
'39': E-EVENT,
'40': E-FAC,
'41': E-GPE,
'42': E-LANGUAGE,
'43': E-LAW,
'44': E-LOC,
'45': E-MONEY,
'46': E-NORP,
'47': E-ORDINAL,
'48': E-ORG,
'49': E-PERCENT,
'50': E-PERSON,
'51': E-PRODUCT,
'52': E-QUANTITY,
'53': E-TIME,
'54': E-WORK_OF_ART,
'55': S-CARDINAL,
'56': S-DATE,
'57': S-EVENT,
'58': S-FAC,
'59': S-GPE,
'60': S-LANGUAGE,
'61': S-LAW,
'62': S-LOC,
'63': S-MONEY,
'64': S-NORP,
'65': S-ORDINAL,
'66': S-ORG,
'67': S-PERCENT,
'68': S-PERSON,
'69': S-PRODUCT,
'70': S-QUANTITY,
'71': S-TIME,
'72': S-WORK_OF_ART
splits:
- name: train
num_bytes: 568
num_examples: 1
download_size: 568
dataset_size: 568
---
# Dataset Card for "NER Model Tune"
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** None
- **Repository:** https://huggingface.co/datasets/ayuhamaro/nlp-model-tune
- **Paper:** [More Information Needed]
- **Leaderboard:** [If the dataset supports an active leaderboard, add link here]()
- **Point of Contact:** [More Information Needed]
### Dataset Summary
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
[More Information Needed]
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
[More Information Needed]
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions |