Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
Spanish
Size:
10K - 100K
License:
Update README.md
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README.md
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The PharmaCoNER corpus contains a total of 396,988 words and 1,000 clinical cases that have been randomly sampled into 3 subsets.
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The training set contains 500 clinical cases, while the development and test sets contain 250 clinical cases each.
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In terms of training examples, this translates to a total of
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The original dataset is distributed in [Brat](https://brat.nlplab.org/standoff.html) format.
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The annotation of the entire set of entity mentions was carried out by domain experts.
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### Data Splits
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* train: 8,
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* validation: 3,
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* test: 3,
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## Dataset Creation
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The PharmaCoNER corpus contains a total of 396,988 words and 1,000 clinical cases that have been randomly sampled into 3 subsets.
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The training set contains 500 clinical cases, while the development and test sets contain 250 clinical cases each.
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In terms of training examples, this translates to a total of 8129, 3787 and 3952 annotated sentences in each set.
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The original dataset is distributed in [Brat](https://brat.nlplab.org/standoff.html) format.
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The annotation of the entire set of entity mentions was carried out by domain experts.
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### Data Splits
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* train: 8,129 sentences
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* validation: 3,787 sentences
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* test: 3,952 sentences
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## Dataset Creation
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