README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - found
languages:
  - en
licenses:
  - 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++

Dataset Card for "conllpp"

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: Github
• Repository: Github
• Paper: Aclweb
• 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

We show detailed information for up to 5 configurations of the dataset.

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

[More Information Needed]

Contributions

Thanks to @ZihanWangKi for adding this dataset.