Tasks
A task is an activity proposed with the purpose of solving a specific NLP problem, generally within the framework of a competition. Below is information about NLP tasks in Spanish from 2013 to the present.
- NLP topic: text indexing
- Dataset: MESINESP8-L
- Forum: CLEF
- Competition: BioASQ 2021: Large-scale biomedical semantic indexing and question answering
- Domain: Health
- Language(s): Spanish
Entity classification IberLEF 2019
- NLP topic: (named) entity recognition
- Dataset: MEDDOCAN
- Forum: IberLEF
- Competition: MEDDOCAN: Medical Document Anonymization Track
- Domain: Health
- Language(s): Spanish
Sensitive span detection IberLEF 2019
- NLP topic: information extraction
- Dataset: MEDDOCAN
- Forum: IberLEF
- Competition: MEDDOCAN: Medical Document Anonymization Track
- Domain: Health
- Language(s): Spanish
Abbreviation resolution evaluation IberEVAL 2018
- NLP topic: processing abbreviations
- Dataset: BARR2
- Forum: IberEVAL
- Competition: Biomedical Abbreviation Recognition and Resolution 2018
- Domain: Health
- Language(s): Spanish
Abbreviation resolution IberEVAL 2018
- NLP topic: processing abbreviations
- Dataset: SPACCC
- Forum: IberEVAL
- Competition: Second Biomedical Abbreviation Recognition and Resolution (BARR2)
- Domain: Health
- Language(s): Spanish
DIANN 2018: Disability detection IberEVAL 2018
- NLP topic: (named) entity recognition
- Dataset: DIANN-2018-ES
- Forum: IberEVAL
- Competition: Disability annotation on documents from the biomedical domain (DIANN)
- Domain: Health
- Language(s): Spanish
Detecting abbreviation-definition pairs IberEVAL 2018
- NLP topic: processing abbreviations
- Dataset: BARR2
- Forum: IberEVAL
- Competition: Biomedical Abbreviation Recognition and Resolution 2018
- Domain: Health
- Language(s): Spanish
Abbreviation recognition and resolution IberEVAL 2017
- NLP topic: processing abbreviations
- Dataset: BARR
- Forum: IberEVAL
- Competition: Biomedical Abbreviation Recognition and Resolution
- Domain: Health
- Language(s): Spanish
If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.
