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.
AuTexTification: Model Generated Text Detection IberLEF 2023
- NLP topic: text generation
- Dataset: AuTexTification 2023
- Forum: IberLEF
- Competition: AuTexTification: Automated Text Identification
- Domain: General, Legal, News
- Language(s): Spanish
AuTexTification: Model Generated Text Attribution IberLEF 2023
- NLP topic: text generation
- Dataset: AuTexTification 2023
- Forum: IberLEF
- Competition: AuTexTification: Automated Text Identification
- Domain: General, Legal, News
- Language(s): Spanish
Rest-MEX: Predicting recommendation IberLEF 2022
- NLP topic: recommendation systems
- Dataset: RestMEX-recommendation system
- Forum: IberLEF
- Competition: Rest-Mex en IberLEF 2022: Sistema de Recomendación, Análisis de Sentimiento y Predicción de Semáforo Covid para Textos Turísticos Mexicanos
- Domain: Tourism
- 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 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
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.
