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.
GUA-SPA: Spanish code classification IberLEF 2023
- NLP topic: code switching detection
- Dataset: GUA-SPA: Guarani Spanish corpus
- Forum: IberLEF
- Competition: GUA-SPA: Guarani-Spanish Code-Switching Analysis
- Domain: News
- Language(s): Spanish
FinancES: Financial targeted sentiment analysis IberLEF 2023
- NLP topic: sentiment analysis
- Dataset: FinancES 2023
- Forum: IberLEF
- Competition: FinancES: Financial Targeted Sentiment Analysis in Spanish
- Domain: Finance
- Language(s): Spanish
- NLP topic: sentiment analysis
- Dataset: FinancES 2023
- Forum: IberLEF
- Competition: FinancES: Financial Targeted Sentiment Analysis in Spanish
- Domain: Finance
- Language(s): Spanish
- NLP topic: sentiment analysis
- Dataset: Rest-Mex 2023 Sentiment
- Forum: IberLEF
- Competition: Rest-Mex 2023: Research on Sentiment Analysis Task for Mexican Tourist Texts
- Domain: Tourism
- Language(s): Spanish
Polarity classification IberLEF 2021
- NLP topic: sentiment analysis
- Dataset: RestMEX-SA
- Forum: IberLEF
- Competition: RestMEX: Recommendation System for Text Mexican Tourism
- Domain: Tourism
- Language(s): Spanish (Mexico)
Stance detection IberLEF 2021
- NLP topic: sentiment analysis
- Dataset: VaxxStance-ES
- Forum: IberLEF
- Competition: Stance detection about vaccines
- Domain: Health
- Language(s): Spanish
Emotion classification IberLEF 2021
- NLP topic: sentiment analysis
- Dataset: EmoEventEs
- Forum: IberLEF
- Competition: EmoEvalEs: Emotion detection
- Domain:
- Language(s): Spanish
General polarity at three levels IberLEF 2020
- NLP topic: sentiment analysis
- Dataset: InterTASS 2020
- Forum: IberLEF
- Competition: Semantic Analysis at SEPLN (TASS)
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: InterTASS-SP, InterTASS-MEX, InterTASS-CR, InterTASS-PE, InterTASS-URU
- Forum: IberLEF
- Competition: TASS: Sentiment Analysis Task at SEPLN
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: NEGES
- Forum: IberLEF
- Competition: NEGES 2019 Task: Negation in Spanish
- Domain:
- Language(s): Spanish
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: InterTASS-SP, InterTASS-MEX, InterTASS-CR, InterTASS-PE, InterTASS-URU
- Forum: IberLEF
- Competition: TASS: Sentiment Analysis Task at SEPLN
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: InterTASS-SP, InterTASS-MEX, InterTASS-CR, InterTASS-PE, InterTASS-URU
- Forum: IberLEF
- Competition: TASS: Sentiment Analysis Task at SEPLN
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: InterTASS-SP, InterTASS-MEX, InterTASS-CR, InterTASS-PE, InterTASS-URU
- Forum: IberLEF
- Competition: TASS: Sentiment Analysis Task at SEPLN
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
Polarity classification IberLEF 2019
- NLP topic: sentiment analysis
- Dataset: InterTASS-SP, InterTASS-MEX, InterTASS-CR, InterTASS-PE, InterTASS-URU
- Forum: IberLEF
- Competition: TASS: Sentiment Analysis Task at SEPLN
- Domain:
- Language(s): Spanish (Costa Rica), Spanish (Mexico), Spanish (Peru), Spanish (Spain), Spanish (Uruguay)
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.