Update README.md

README.md

@@ -14,11 +14,41 @@ task_ids:
 
 # PharmaCoNER Corpus
 
+This dataset is designed for the PharmaCoNER task, sponsored by Plan de Impulso de las Tecnologías del Lenguaje (Plan TL).
+
+It is a 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 (Scientific Electronic Library Online).
+
+The annotation of the entire set of entity mentions was carried out by medicinal chemistry experts and 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 was distributed in Brat format (https://brat.nlplab.org/standoff.html).
+
+For further information, please visit https://temu.bsc.es/pharmaconer/ or send an email to [email protected]
+
 ## BibTeX  citation
 If you use these resources in your work, please cite the following paper:
 
 ```bibtex
-TO DO
+@inproceedings{,
+    title = "PharmaCoNER: Pharmacological Substances, Compounds and proteins Named Entity Recognition track",
+    author = "Gonzalez-Agirre, Aitor  and
+      Marimon, Montserrat  and
+      Intxaurrondo, Ander  and
+      Rabal, Obdulia  and
+      Villegas, Marta  and
+      Krallinger, Martin",
+    booktitle = "Proceedings of The 5th Workshop on BioNLP Open Shared Tasks",
+    month = nov,
+    year = "2019",
+    address = "Hong Kong, China",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/D19-5701",
+    doi = "10.18653/v1/D19-5701",
+    pages = "1--10",
+    abstract = "",
+}
 ```
 
 ## Digital Object Identifier (DOI) and access to dataset files
@@ -125,7 +155,7 @@ No personal or sensitive information included.
 
 ## Contact
 
-TO DO: Casimiro?
+[email protected]
 
 ## License