Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K<n<100K
License:
albertvillanova
HF staff
Convert dataset sizes from base 2 to base 10 in the dataset card (#2)
3e60128
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. |