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 8130, 3788 and 3953 annotated sentences in each set.
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The original dataset
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The annotation of the entire set of entity mentions was carried out by domain experts.
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It includes the following 4 entity types: NORMALIZABLES, NO_NORMALIZABLES, PROTEINAS and UNCLEAR.
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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 8130, 3788 and 3953 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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It includes the following 4 entity types: NORMALIZABLES, NO_NORMALIZABLES, PROTEINAS and UNCLEAR.
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