datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ProfNER_corpus_NER
Description
Gold standard annotations for profession detection in Spanish COVID-19 tweets
The entire corpus contains 10,000 annotated tweets. It has been split into training, validation, and test (60-20-20). The current version contains the training and development set of the shared task with Gold Standard annotations. In addition, it contains the unannotated test, and background sets will be released.
For Named Entity Recognition, profession detection, annotations are distributed… See the full description on the dataset page: https://huggingface.co/datasets/Biomedical-TeMU/ProfNER_corpus_NER.bioleaflets-biomedical-ner
Dataset Card for BioLeaflets Dataset
Dataset Summary
BioLeaflets is a biomedical dataset for Data2Text generation. It is a corpus of 1,336 package leaflets of medicines authorised in Europe, which were obtained by scraping the European Medicines Agency (EMA) website.
Package leaflets are included in the packaging of medicinal products and contain information to help patients use the product safely and appropriately.
This dataset comprises the large majority (∼ 90%) of… See the full description on the dataset page: https://huggingface.co/datasets/ruslan/bioleaflets-biomedical-ner.chinese_biomedical_NER_dataset
1 Source
Source: https://github.com/alibaba-research/ChineseBLUE
2 Definition of the tagset
tag_set = [
'B_手术',
'I_疾病和诊断',
'B_症状',
'I_解剖部位',
'I_药物',
'B_影像检查',
'B_药物',
'B_疾病和诊断',
'I_影像检查',
'I_手术',
'B_解剖部位',
'O',
'B_实验室检验',
'I_症状',
'I_实验室检验'
]
tag2id = lambda tag: tag_set.index(tag)
id2tag = lambda id: tag_set[id]
3 Citation
To use this dataset in your work please cite:
Ningyu Zhang, Qianghuai Jia, Kangping Yin, Liang Dong, Feng Gao, Nengwei Hua.… See the full description on the dataset page: https://huggingface.co/datasets/Adapting/chinese_biomedical_NER_dataset.MACCROBAT_biomedical_ner
MACCROBAT-biomedical-ner
This data is the same data from here, the only difference is that it has been converted into the Huggingface dataset format. So it can be easily loaded and can be used wherever need.
To convert from the orginal format to huggingface dataset format, followed the following steps (To know in more detail look at the create_dataset.py file):
Read corresponding *.txt and *.ann file.
Used pandas to convert the *.ann file into dataframe.
After converting into… See the full description on the dataset page: https://huggingface.co/datasets/singh-aditya/MACCROBAT_biomedical_ner.biomedical-ner
Dataset Card for "biomedical-ner"
More Information needed
bioBERT-ner-biomedical-text
Dataset Card for "bioBERT-ner-biomedical-text"
More Information needed