Dataset Card for JNLPBA

Dataset Summary

The data came from the GENIA version 3.02 corpus (Kim et al., 2003). This was formed from a controlled search on MEDLINE using the MeSH terms human, blood cells and transcription factors. From this search 2,000 abstracts were selected and hand annotated according to a small taxonomy of 48 classes based on a chemical classification. Among the classes, 36 terminal classes were used to annotate the GENIA corpus.

Supported Tasks and Leaderboards

NER

Languages

English

Dataset Structure

Data Instances

{ 'id': '1', 'tokens': ['IL-2', 'gene', 'expression', 'and', 'NF-kappa', 'B', 'activation', 'through', 'CD28', 'requires', 'reactive', 'oxygen', 'production', 'by', '5-lipoxygenase', '.'], 'ner_tags': [1, 2, 0, 0, 9, 10, 0, 0, 9, 0, 0, 0, 0, 0, 9, 0], }

Data Fields

• id: Sentence identifier.
• tokens: Array of tokens composing a sentence.
• ner_tags: Array of tags, where 0 indicates no bio-entity mentioned, 1 signals the first token of a bio-entity and 2 the subsequent bio-entity tokens.

Data Splits

Train samples: 37094 Validation samples: 7714

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@inproceedings{collier-kim-2004-introduction, title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}", author = "Collier, Nigel and Kim, Jin-Dong", booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B}io{NLP})", month = aug # " 28th and 29th", year = "2004", address = "Geneva, Switzerland", publisher = "COLING", url = "https://aclanthology.org/W04-1213", pages = "73--78", }

Contributions

Thanks to @edugp for adding this dataset.