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.
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)
Irony detection IberLEF 2019
- NLP topic: processing humor
- Dataset: IDAT-SP-EU, IDAT-SP-MEX, IDAT-SP-CUBA
- Forum: IberLEF
- Competition: Irony Detection in Spanish Variants
- Domain:
- Language(s): Spanish (Cuba), Spanish (Mexico), Spanish (Spain)
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)
Humor detection IberLEF 2019
- NLP topic: processing humor
- Dataset: HAHA
- Forum: IberLEF
- Competition: HAHA 2019: Humor Analysis based on Human Annotation
- 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)
Sentiment valence regression SEMEVAL 2018
- NLP topic: sentiment analysis
- Dataset: Affect in Tweets-ES
- Forum: SEMEVAL
- Competition: SemEval-2018 Task 1: Affect in Tweets
- Domain:
- Language(s): Spanish, English
Stance detection IberEVAL 2018
- NLP topic: sentiment analysis
- Dataset: The TW-1O Referendum corpus - ES
- Forum: IberEVAL
- Competition: Multimodal Stance Detection in Tweets on Catalan #1Oct Referendum
- Domain:
- Language(s): Spanish
Sentiment valence classification SEMEVAL 2018
- NLP topic: sentiment analysis
- Dataset: Affect in Tweets-ES
- Forum: SEMEVAL
- Competition: SemEval-2018 Task 1: Affect in Tweets
- Domain:
- Language(s): Spanish, English
Emotion intensity regression SEMEVAL 2018
- NLP topic: sentiment analysis
- Dataset: Affect in Tweets-ES
- Forum: SEMEVAL
- Competition: SemEval-2018 Task 1: Affect in Tweets
- Domain:
- Language(s): Spanish, English
Humor detection IberEVAL 2018
- NLP topic: processing humor
- Dataset: HAHA
- Forum: IberEVAL
- Competition: Humor Analysis based on Human Annotation (HAHA)
- Domain:
- Language(s): Spanish
Emotion classification SEMEVAL 2018
- NLP topic: sentiment analysis
- Dataset: Affect in Tweets-ES
- Forum: SEMEVAL
- Competition: SemEval-2018 Task 1: Affect in Tweets
- Domain:
- Language(s): Spanish, English
Emotion intensity classification SEMEVAL 2018
- NLP topic: sentiment analysis
- Dataset: Affect in Tweets-ES
- Forum: SEMEVAL
- Competition: SemEval-2018 Task 1: Affect in Tweets
- Domain:
- Language(s): Spanish, English
Humor rating IberEVAL 2018
- NLP topic: processing humor
- Dataset: HAHA
- Forum: IberEVAL
- Competition: Humor Analysis based on Human Annotation (HAHA)
- Domain:
- Language(s): Spanish
Pagination
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.