Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K<n<100K
License:
| 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:** 4.63 MB | |
| - **Size of the generated dataset:** 9.78 MB | |
| - **Total amount of disk used:** 14.41 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. |