Datasets:
Tasks:
Token Classification
Modalities:
Text
Sub-tasks:
named-entity-recognition
Languages:
Spanish
Size:
10K - 100K
License:
File size: 2,975 Bytes
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---
annotations_creators:
- expert-generated
languages:
- es
multilinguality:
- monolingual
task_categories:
- text-classification
- multi-label-text-classification
task_ids:
- named-entity-recognition
---
# PharmaCoNER Corpus
## BibTeX citation
If you use these resources in your work, please cite the following paper:
```bibtex
TO DO
```
## Digital Object Identifier (DOI) and access to dataset files
https://zenodo.org/record/4270158#.YTnXP0MzY0F
## Introduction
TO DO: This is a dataset for Named Entity Recognition (NER) from...
### Supported Tasks and Leaderboards
Named Entities Recognition, Language Model
### Languages
ES - Spanish
### Directory structure
* pharmaconer.py
* dev.conll
* test.conll
* train.conll
* README.md
## Dataset Structure
### Data Instances
Three four-column files, one for each split.
### Data Fields
Every file has four columns:
* 1st column: Word form or punctuation symbol
* 2nd column: Original BRAT file name
* 3rd column: Spans
* 4th column: IOB tag
### Example:
<pre>
La S0004-06142006000900008-1 123_125 O
paciente S0004-06142006000900008-1 126_134 O
tenía S0004-06142006000900008-1 135_140 O
antecedentes S0004-06142006000900008-1 141_153 O
de S0004-06142006000900008-1 154_156 O
hipotiroidismo S0004-06142006000900008-1 157_171 O
, S0004-06142006000900008-1 171_172 O
hipertensión S0004-06142006000900008-1 173_185 O
arterial S0004-06142006000900008-1 186_194 O
en S0004-06142006000900008-1 195_197 O
tratamiento S0004-06142006000900008-1 198_209 O
habitual S0004-06142006000900008-1 210_218 O
con S0004-06142006000900008-1 219-222 O
atenolol S0004-06142006000900008-1 223_231 B-NORMALIZABLES
y S0004-06142006000900008-1 232_233 O
enalapril S0004-06142006000900008-1 234_243 B-NORMALIZABLES
</pre>
### Data Splits
* train: 8,074 tokens
* development: 3,764 tokens
* test: 3,931 tokens
## Dataset Creation
### Methodology
TO DO
### Curation Rationale
For compatibility with similar datasets in other languages, we followed as close as possible existing curation guidelines.
### Source Data
#### Initial Data Collection and Normalization
TO DO
#### Who are the source language producers?
TO DO
### Annotations
#### Annotation process
TO DO
#### Who are the annotators?
TO DO
### Dataset Curators
TO DO: Martin?
### Personal and Sensitive Information
No personal or sensitive information included.
## Contact
TO DO: Casimiro?
## License
<a rel="license" href="https://creativecommons.org/licenses/by/4.0/"><img alt="Attribution 4.0 International License" style="border-width:0" src="https://chriszabriskie.com/img/cc-by.png" width="100"/></a><br />This work is licensed under a <a rel="license" href="https://creativecommons.org/licenses/by/4.0/">Attribution 4.0 International License</a>. |