Update README.md

README.md

@@ -13,14 +13,16 @@ task_categories:
 - token-classification
 task_ids:
 - named-entity-recognition
-licenses:
-- cc-by-4-0
 ---
 
-# PharmaCoNER Corpus
+# PharmaCoNER
 
 ## Dataset Description
 
+- **Homepage:** [zenodo](https://zenodo.org/record/4270158)
+- **Paper:** [PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track](https://aclanthology.org/D19-5701/)
+- **Point of Contact:** [email protected]
+
 ### Dataset Summary
 
 Manually classified collection of clinical case studies derived from the Spanish Clinical Case Corpus (SPACCC), an open access electronic library that gathers Spanish medical publications from [SciELO](https://scielo.org/).
@@ -37,17 +39,13 @@ This dataset was designed for the PharmaCoNER task, sponsored by [Plan de Impuls
 
 For further information, please visit [the official website](https://temu.bsc.es/pharmaconer/).
 
-## Digital Object Identifier (DOI) and access to dataset files
-
-https://zenodo.org/record/4270158
-
 ### Supported Tasks
 
-Named Entity Recognition
+Named Entity Recognition (NER)
 
 ### Languages
 
-ES - Spanish
+- Spanish (es)
 
 ### Directory Structure
 
@@ -93,9 +91,11 @@ enalapril         S0004-06142006000900008-1  234_243  B-NORMALIZABLES
 
 ### Data Splits
 
-* train:       8,129 sentences
-* validation:  3,787 sentences
-* test:        3,952 sentences
+| Split | Size |
+| ------------- | ------------- |
+| `train`  | 8,129  |
+| `dev`  | 3,787  |
+| `test`  | 3,952  |
 
 ## Dataset Creation
 
@@ -121,7 +121,7 @@ The annotation process of the PharmaCoNER corpus was inspired by previous annota
 
 #### Who are the annotators?
 
- Practicing physicians and medicinal chemistry experts.
+Practicing physicians and medicinal chemistry experts.
 
 ### Personal and Sensitive Information
 
@@ -133,14 +133,8 @@ No personal or sensitive information included.
 
 The Text Mining Unit from Barcelona Supercomputing center.
 
-### Contact
-
-[email protected]
-
 ### Citation Information
 
-If you use these resources in your work, please cite the following paper:
-
 ```bibtex
 @inproceedings{,
     title = "PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track",
@@ -161,6 +155,10 @@ If you use these resources in your work, please cite the following paper:
 }
 ```
 
+### Contact Information
+
+For further information, send an email to [email protected].
+
 ### Funding
 
 This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL.