Datasets:

PlanTL-GOB-ES
/

pharmaconer

Tasks:

Token Classification

Modalities:

Sub-tasks:

named-entity-recognition

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mapama247 commited on Apr 7, 2022

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@@ -26,7 +26,7 @@ Manually classified collection of clinical case studies derived from the Spanish
 The PharmaCoNER corpus contains a total of 396,988 words and 1,000 clinical cases that have been randomly sampled into 3 subsets.
 The training set contains 500 clinical cases, while the development and test sets contain 250 clinical cases each.
 In terms of training examples, this translates to a total of 8130, 3788 and 3953 annotated sentences in each set.
-The original dataset was distributed in [Brat](https://brat.nlplab.org/standoff.html) format.
 The annotation of the entire set of entity mentions was carried out by domain experts.
 It includes the following 4 entity types: NORMALIZABLES, NO_NORMALIZABLES, PROTEINAS and UNCLEAR.

 The PharmaCoNER corpus contains a total of 396,988 words and 1,000 clinical cases that have been randomly sampled into 3 subsets.
 The training set contains 500 clinical cases, while the development and test sets contain 250 clinical cases each.
 In terms of training examples, this translates to a total of 8130, 3788 and 3953 annotated sentences in each set.
+The original dataset is distributed in [Brat](https://brat.nlplab.org/standoff.html) format.
 The annotation of the entire set of entity mentions was carried out by domain experts.
 It includes the following 4 entity types: NORMALIZABLES, NO_NORMALIZABLES, PROTEINAS and UNCLEAR.