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1 |
+
---
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2 |
+
annotations_creators:
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+
- expert-generated
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4 |
+
language_creators:
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+
- found
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6 |
+
language:
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- en
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8 |
+
license:
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9 |
+
- unknown
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10 |
+
multilinguality:
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11 |
+
- monolingual
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12 |
+
size_categories:
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13 |
+
- 10K<n<100K
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14 |
+
source_datasets:
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15 |
+
- extended|conll2003
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16 |
+
task_categories:
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+
- token-classification
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+
task_ids:
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19 |
+
- named-entity-recognition
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20 |
+
paperswithcode_id: conll
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21 |
+
pretty_name: CoNLL++
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+
train-eval-index:
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23 |
+
- config: conllpp
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24 |
+
task: token-classification
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25 |
+
task_id: entity_extraction
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26 |
+
splits:
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27 |
+
train_split: train
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28 |
+
eval_split: test
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29 |
+
col_mapping:
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30 |
+
tokens: tokens
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31 |
+
ner_tags: tags
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32 |
+
metrics:
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33 |
+
- type: seqeval
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34 |
+
name: seqeval
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35 |
+
dataset_info:
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36 |
+
features:
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37 |
+
- name: id
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38 |
+
dtype: string
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+
- name: tokens
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40 |
+
sequence: string
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41 |
+
- name: pos_tags
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42 |
+
sequence:
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+
class_label:
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+
names:
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45 |
+
0: '"'
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46 |
+
1: ''''''
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47 |
+
2: '#'
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+
3: $
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+
4: (
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5: )
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6: ','
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52 |
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7: .
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+
8: ':'
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9: '``'
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+
10: CC
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11: CD
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+
12: DT
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+
13: EX
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+
14: FW
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15: IN
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16: JJ
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+
17: JJR
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+
18: JJS
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+
19: LS
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20: MD
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+
21: NN
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+
22: NNP
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+
23: NNPS
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+
24: NNS
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+
25: NN|SYM
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26: PDT
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27: POS
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28: PRP
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29: PRP$
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30: RB
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31: RBR
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32: RBS
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33: RP
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+
34: SYM
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+
35: TO
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+
36: UH
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+
37: VB
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+
38: VBD
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+
39: VBG
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+
40: VBN
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+
41: VBP
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+
42: VBZ
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+
43: WDT
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+
44: WP
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+
45: WP$
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+
46: WRB
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+
- name: chunk_tags
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+
sequence:
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94 |
+
class_label:
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95 |
+
names:
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96 |
+
0: O
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97 |
+
1: B-ADJP
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98 |
+
2: I-ADJP
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99 |
+
3: B-ADVP
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100 |
+
4: I-ADVP
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101 |
+
5: B-CONJP
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102 |
+
6: I-CONJP
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103 |
+
7: B-INTJ
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+
8: I-INTJ
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+
9: B-LST
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106 |
+
10: I-LST
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+
11: B-NP
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+
12: I-NP
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109 |
+
13: B-PP
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+
14: I-PP
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+
15: B-PRT
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+
16: I-PRT
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+
17: B-SBAR
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+
18: I-SBAR
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+
19: B-UCP
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116 |
+
20: I-UCP
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117 |
+
21: B-VP
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+
22: I-VP
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+
- name: ner_tags
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+
sequence:
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+
class_label:
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122 |
+
names:
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123 |
+
0: O
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124 |
+
1: B-PER
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+
2: I-PER
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126 |
+
3: B-ORG
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127 |
+
4: I-ORG
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128 |
+
5: B-LOC
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129 |
+
6: I-LOC
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130 |
+
7: B-MISC
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131 |
+
8: I-MISC
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132 |
+
config_name: conllpp
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+
splits:
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134 |
+
- name: train
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135 |
+
num_bytes: 6931393
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136 |
+
num_examples: 14041
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137 |
+
- name: validation
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138 |
+
num_bytes: 1739247
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+
num_examples: 3250
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+
- name: test
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141 |
+
num_bytes: 1582078
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142 |
+
num_examples: 3453
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143 |
+
download_size: 4859600
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144 |
+
dataset_size: 10252718
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+
---
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146 |
+
|
147 |
+
# Dataset Card for "conllpp"
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148 |
+
|
149 |
+
## Table of Contents
|
150 |
+
- [Dataset Description](#dataset-description)
|
151 |
+
- [Dataset Summary](#dataset-summary)
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152 |
+
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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153 |
+
- [Languages](#languages)
|
154 |
+
- [Dataset Structure](#dataset-structure)
|
155 |
+
- [Data Instances](#data-instances)
|
156 |
+
- [Data Fields](#data-fields)
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157 |
+
- [Data Splits](#data-splits)
|
158 |
+
- [Dataset Creation](#dataset-creation)
|
159 |
+
- [Curation Rationale](#curation-rationale)
|
160 |
+
- [Source Data](#source-data)
|
161 |
+
- [Annotations](#annotations)
|
162 |
+
- [Personal and Sensitive Information](#personal-and-sensitive-information)
|
163 |
+
- [Considerations for Using the Data](#considerations-for-using-the-data)
|
164 |
+
- [Social Impact of Dataset](#social-impact-of-dataset)
|
165 |
+
- [Discussion of Biases](#discussion-of-biases)
|
166 |
+
- [Other Known Limitations](#other-known-limitations)
|
167 |
+
- [Additional Information](#additional-information)
|
168 |
+
- [Dataset Curators](#dataset-curators)
|
169 |
+
- [Licensing Information](#licensing-information)
|
170 |
+
- [Citation Information](#citation-information)
|
171 |
+
- [Contributions](#contributions)
|
172 |
+
|
173 |
+
## Dataset Description
|
174 |
+
|
175 |
+
- **Homepage:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
|
176 |
+
- **Repository:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
|
177 |
+
- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1519)
|
178 |
+
- **Leaderboard:**
|
179 |
+
- **Point of Contact:**
|
180 |
+
|
181 |
+
### Dataset Summary
|
182 |
+
|
183 |
+
CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
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184 |
+
have been manually corrected. The training set and development set from CoNLL2003 is included for completeness. One
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185 |
+
correction on the test set for example, is:
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186 |
+
|
187 |
+
```
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188 |
+
{
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189 |
+
"tokens": ["SOCCER", "-", "JAPAN", "GET", "LUCKY", "WIN", ",", "CHINA", "IN", "SURPRISE", "DEFEAT", "."],
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190 |
+
"original_ner_tags_in_conll2003": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-PER", "O", "O", "O", "O"],
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191 |
+
"corrected_ner_tags_in_conllpp": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O"],
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192 |
+
}
|
193 |
+
```
|
194 |
+
|
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+
### Supported Tasks and Leaderboards
|
196 |
+
|
197 |
+
[More Information Needed]
|
198 |
+
|
199 |
+
### Languages
|
200 |
+
|
201 |
+
[More Information Needed]
|
202 |
+
|
203 |
+
## Dataset Structure
|
204 |
+
|
205 |
+
### Data Instances
|
206 |
+
|
207 |
+
#### conllpp
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208 |
+
|
209 |
+
- **Size of downloaded dataset files:** 4.85 MB
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210 |
+
- **Size of the generated dataset:** 10.26 MB
|
211 |
+
- **Total amount of disk used:** 15.11 MB
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212 |
+
|
213 |
+
An example of 'train' looks as follows.
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+
```
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215 |
+
This example was too long and was cropped:
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+
|
217 |
+
{
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218 |
+
"chunk_tags": [11, 12, 12, 21, 13, 11, 11, 21, 13, 11, 12, 13, 11, 21, 22, 11, 12, 17, 11, 21, 17, 11, 12, 12, 21, 22, 22, 13, 11, 0],
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219 |
+
"id": "0",
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220 |
+
"ner_tags": [0, 3, 4, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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+
"pos_tags": [12, 22, 22, 38, 15, 22, 28, 38, 15, 16, 21, 35, 24, 35, 37, 16, 21, 15, 24, 41, 15, 16, 21, 21, 20, 37, 40, 35, 21, 7],
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+
"tokens": ["The", "European", "Commission", "said", "on", "Thursday", "it", "disagreed", "with", "German", "advice", "to", "consumers", "to", "shun", "British", "lamb", "until", "scientists", "determine", "whether", "mad", "cow", "disease", "can", "be", "transmitted", "to", "sheep", "."]
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223 |
+
}
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224 |
+
```
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+
|
226 |
+
### Data Fields
|
227 |
+
|
228 |
+
The data fields are the same among all splits.
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229 |
+
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230 |
+
#### conllpp
|
231 |
+
- `id`: a `string` feature.
|
232 |
+
- `tokens`: a `list` of `string` features.
|
233 |
+
- `pos_tags`: a `list` of classification labels, with possible values including `"` (0), `''` (1), `#` (2), `$` (3), `(` (4).
|
234 |
+
- `chunk_tags`: a `list` of classification labels, with possible values including `O` (0), `B-ADJP` (1), `I-ADJP` (2), `B-ADVP` (3), `I-ADVP` (4).
|
235 |
+
- `ner_tags`: a `list` of classification labels, with possible values including `O` (0), `B-PER` (1), `I-PER` (2), `B-ORG` (3), `I-ORG` (4).
|
236 |
+
|
237 |
+
### Data Splits
|
238 |
+
|
239 |
+
| name |train|validation|test|
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240 |
+
|---------|----:|---------:|---:|
|
241 |
+
|conll2003|14041| 3250|3453|
|
242 |
+
|
243 |
+
## Dataset Creation
|
244 |
+
|
245 |
+
### Curation Rationale
|
246 |
+
|
247 |
+
[More Information Needed]
|
248 |
+
|
249 |
+
### Source Data
|
250 |
+
|
251 |
+
#### Initial Data Collection and Normalization
|
252 |
+
|
253 |
+
[More Information Needed]
|
254 |
+
|
255 |
+
#### Who are the source language producers?
|
256 |
+
|
257 |
+
[More Information Needed]
|
258 |
+
|
259 |
+
### Annotations
|
260 |
+
|
261 |
+
#### Annotation process
|
262 |
+
|
263 |
+
[More Information Needed]
|
264 |
+
|
265 |
+
#### Who are the annotators?
|
266 |
+
|
267 |
+
[More Information Needed]
|
268 |
+
|
269 |
+
### Personal and Sensitive Information
|
270 |
+
|
271 |
+
[More Information Needed]
|
272 |
+
|
273 |
+
## Considerations for Using the Data
|
274 |
+
|
275 |
+
### Social Impact of Dataset
|
276 |
+
|
277 |
+
[More Information Needed]
|
278 |
+
|
279 |
+
### Discussion of Biases
|
280 |
+
|
281 |
+
[More Information Needed]
|
282 |
+
|
283 |
+
### Other Known Limitations
|
284 |
+
|
285 |
+
[More Information Needed]
|
286 |
+
|
287 |
+
## Additional Information
|
288 |
+
|
289 |
+
### Dataset Curators
|
290 |
+
|
291 |
+
[More Information Needed]
|
292 |
+
|
293 |
+
### Licensing Information
|
294 |
+
|
295 |
+
[More Information Needed]
|
296 |
+
|
297 |
+
### Citation Information
|
298 |
+
|
299 |
+
```
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300 |
+
@inproceedings{wang2019crossweigh,
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301 |
+
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
|
302 |
+
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
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303 |
+
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)},
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+
pages={5157--5166},
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+
year={2019}
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+
}
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+
```
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308 |
+
|
309 |
+
### Contributions
|
310 |
+
|
311 |
+
Thanks to [@ZihanWangKi](https://github.com/ZihanWangKi) for adding this dataset.
|