

# Dataset Card for GENETAG

## Dataset Description

- **Homepage:** https://github.com/openbiocorpora/genetag
- **Pubmed:** True
- **Public:** True
- **Tasks:** NER


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 = {}
}

```

multilinguality:monolingual language:en license:other region:us
{"language": ["en"], "license": "other", "multilinguality": "monolingual", "pretty_name": "GENETAG", "bigbio_language": ["English"], "bigbio_license_shortname": "NCBI_LICENSE", "homepage": "https://github.com/openbiocorpora/genetag", "bigbio_pubmed": true, "bigbio_public": true, "bigbio_tasks": ["NAMED_ENTITY_RECOGNITION"]}
TAGS
#multilinguality-monolingual #language-English #license-other #region-us 



# Dataset Card for GENETAG

## Dataset Description

- Homepage: URL
- Pubmed: True
- Public: True
- Tasks: NER


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..







# Dataset Card for GENETAG ## Dataset Description

- Homepage: URL
- Pubmed: True
- Public: True
- Tasks: NER


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..
TAGS
#multilinguality-monolingual #language-English #license-other #region-us 
 # Dataset Card for GENETAG ## Dataset Description

- Homepage: URL
- Pubmed: True
- Public: True
- Tasks: NER


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..
passage: TAGS
#multilinguality-monolingual #language-English #license-other #region-us 
# Dataset Card for GENETAG## Dataset Description

- Homepage: URL
- Pubmed: True
- Public: True
- Tasks: NER


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..