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.
Fake news detection IberLEF 2021
- NLP topic: fake news detection
- Dataset: FakeDeS
- Forum: IberLEF
- Competition: FakeDeS: Fake news detection
- Domain: COVID, others
- Language(s): Spanish
Worthiness estimation CLEF 2021
- NLP topic: fake news detection
- Dataset: CheckThat-ES
- Forum: CLEF
- Competition: CheckThat! Lab Task 1 on Check-Worthiness Estimation in Tweets and Political Debates
- Domain: Politics
- Language(s): Spanish, English
Factuality classification IberLEF 2020
- NLP topic: processing factuality
- Dataset: FACT
- Forum: IberLEF
- Competition: FACT 2020: Factuality Analysis and Classification Task
- Domain:
- Language(s): Spanish
Factuality classification IberLEF 2019
- NLP topic: processing factuality
- Dataset: FACT
- Forum: IberLEF
- Competition: FACT: Factuality Analysis and Classification Task,
- Domain:
- 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.
