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Dataset Card for GENETAG
Named entity recognition (NER) is an important first step for text mining the biomedical literature. Evaluating the performance of biomedical NER systems is impossible without a standardized test corpus. The annotation of such a corpus for gene/protein name NER is a difficult process due to the complexity of gene/protein names. We describe the construction and annotation of GENETAG, a corpus of 20K MEDLINE® sentences for gene/protein NER. 15K GENETAG sentences were used for the BioCreAtIvE Task 1A Competition..
Citation Information
@article{Tanabe2005,
author = {Lorraine Tanabe and Natalie Xie and Lynne H Thom and Wayne Matten and W John Wilbur},
title = {{GENETAG}: a tagged corpus for gene/protein named entity recognition},
journal = {{BMC} Bioinformatics},
volume = {6},
year = {2005},
url = {https://doi.org/10.1186/1471-2105-6-S1-S3},
doi = {10.1186/1471-2105-6-s1-s3},
biburl = {},
bibsource = {}
}
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Homepage:
github.com
Pubmed:
True
Public:
True
Tasks:
NER
Size of downloaded dataset files:
36.6 MB
Size of the auto-converted Parquet files:
13.7 MB
Number of rows:
60,000