OTAR3088/Cellfinder-cleaned_CoNLL

Dataset Card for CellFinder CoNLL

This data was processed into the CoNLL format, following a direct download of a Humboldt university of Berlin resource.

For clarity, this is the same data is in OTAR3088/CellFinder-cleaned_BRAT, in another format.

Dataset Details

Dataset Description

From data source https://www.informatik.hu-berlin.de/de/forschung/gebiete/wbi/resources/cellfinder/, this data is described as follows:

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The first version of our corpus is composed of 10 full text documents containing more than 2,100 sentences, 65,000 tokens and 5,200 annotations for entities. The corpus has been annotated with six types of entities (anatomical parts, cell components, cell lines, cell types, genes/protein and species) with an overall inter-annotator agreement around 80%.

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• Curated by: [More Information Needed]
• Funded by [optional]: [More Information Needed]
• Shared by [optional]: [More Information Needed]
• Language(s) (NLP): [More Information Needed]
• License: [More Information Needed]

Dataset Sources

• Link: https://www.informatik.hu-berlin.de/de/forschung/gebiete/wbi/resources/cellfinder/
• Paper: Mariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf Leser. Annotating and evaluating text for stem cell research. Third Workshop on Building and Evaluation Resources for Biomedical Text Mining (BioTxtM 2012) at Language Resources and Evaluation (LREC) 2012.

Uses

We utilised this dataset to train a NER model to annotate the entity types detailed by the authors of this dataset.

In turn this data became part of a larger dataset for our group.

We copied this format of the data to our huggingface project for easier ingestion into our NER-model production pipeline.

Dataset Structure

This data is stored in the ConLL format, with each article, identified through it's PMCID, annotated via a .conll file.

Annotations appear as shown in the following example:

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of O

human B-Species

embryonic I-CellType

stem I-CellType

cell I-CellType

(hESC) O

lines O

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With terms annotated in the IOB format - Beginning, Inside, Outside

Recommendations

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

Citation

Mariana Neves, Alexander Damaschun, Andreas Kurtz, Ulf Leser. Annotating and evaluating text for stem cell research. Third Workshop on Building and Evaluation Resources for Biomedical Text Mining (BioTxtM 2012) at Language Resources and Evaluation (LREC) 2012.

Dataset Card Authors

Christine Withers - https://huggingface.co/christine-withers

Dataset Card Contact

Christine Withers - https://huggingface.co/christine-withers