conllpp / README.md
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---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|conll2003
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: conll
pretty_name: CoNLL++
train-eval-index:
- config: conllpp
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: pos_tags
sequence:
class_label:
names:
0: '"'
1: ''''''
2: '#'
3: $
4: (
5: )
6: ','
7: .
8: ':'
9: '``'
10: CC
11: CD
12: DT
13: EX
14: FW
15: IN
16: JJ
17: JJR
18: JJS
19: LS
20: MD
21: NN
22: NNP
23: NNPS
24: NNS
25: NN|SYM
26: PDT
27: POS
28: PRP
29: PRP$
30: RB
31: RBR
32: RBS
33: RP
34: SYM
35: TO
36: UH
37: VB
38: VBD
39: VBG
40: VBN
41: VBP
42: VBZ
43: WDT
44: WP
45: WP$
46: WRB
- name: chunk_tags
sequence:
class_label:
names:
0: O
1: B-ADJP
2: I-ADJP
3: B-ADVP
4: I-ADVP
5: B-CONJP
6: I-CONJP
7: B-INTJ
8: I-INTJ
9: B-LST
10: I-LST
11: B-NP
12: I-NP
13: B-PP
14: I-PP
15: B-PRT
16: I-PRT
17: B-SBAR
18: I-SBAR
19: B-UCP
20: I-UCP
21: B-VP
22: I-VP
- name: ner_tags
sequence:
class_label:
names:
0: O
1: B-PER
2: I-PER
3: B-ORG
4: I-ORG
5: B-LOC
6: I-LOC
7: B-MISC
8: I-MISC
config_name: conllpp
splits:
- name: train
num_bytes: 6931393
num_examples: 14041
- name: validation
num_bytes: 1739247
num_examples: 3250
- name: test
num_bytes: 1582078
num_examples: 3453
download_size: 4859600
dataset_size: 10252718
---
# Dataset Card for "conllpp"
## 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:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
- **Repository:** [Github](https://github.com/ZihanWangKi/CrossWeigh)
- **Paper:** [Aclweb](https://www.aclweb.org/anthology/D19-1519)
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
CoNLLpp is a corrected version of the CoNLL2003 NER dataset where labels of 5.38% of the sentences in the test set
have been manually corrected. The training set and development set from CoNLL2003 is included for completeness. One
correction on the test set for example, is:
```
{
"tokens": ["SOCCER", "-", "JAPAN", "GET", "LUCKY", "WIN", ",", "CHINA", "IN", "SURPRISE", "DEFEAT", "."],
"original_ner_tags_in_conll2003": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-PER", "O", "O", "O", "O"],
"corrected_ner_tags_in_conllpp": ["O", "O", "B-LOC", "O", "O", "O", "O", "B-LOC", "O", "O", "O", "O"],
}
```
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
#### conllpp
- **Size of downloaded dataset files:** 4.85 MB
- **Size of the generated dataset:** 10.26 MB
- **Total amount of disk used:** 15.11 MB
An example of 'train' looks as follows.
```
This example was too long and was cropped:
{
"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],
"id": "0",
"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],
"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],
"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", "."]
}
```
### Data Fields
The data fields are the same among all splits.
#### conllpp
- `id`: a `string` feature.
- `tokens`: a `list` of `string` features.
- `pos_tags`: a `list` of classification labels, with possible values including `"` (0), `''` (1), `#` (2), `$` (3), `(` (4).
- `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).
- `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).
### Data Splits
| name |train|validation|test|
|---------|----:|---------:|---:|
|conll2003|14041| 3250|3453|
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### 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
```
@inproceedings{wang2019crossweigh,
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
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)},
pages={5157--5166},
year={2019}
}
```
### Contributions
Thanks to [@ZihanWangKi](https://github.com/ZihanWangKi) for adding this dataset.