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: hate detection
- Dataset: MeOffendES
- Forum: IberLEF
- Competition: MeOffendES: Detection of offensive language
- Domain:
- Language(s):
Sexism classification IberLEF 2021
- NLP topic: hate detection
- Dataset: EXIST-2021-ES
- Forum: IberLEF
- Competition: EXIST: Sexism detection in Twitter
- Domain:
- Language(s): Spanish, English
Detection of toxicity IberLEF 2021
- NLP topic: hate detection
- Dataset: NewsCom-TOX
- Forum: IberLEF
- Competition: DETOXIS: Detection of toxicity
- Domain:
- Language(s):
- 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
Contextual classification of offensive comments IberLEF 2021
- NLP topic: hate detection
- Dataset: MeOffendES
- Forum: IberLEF
- Competition: MeOffendES: Detection of offensive language
- Domain:
- Language(s): Spanish
Detection of toxicity level IberLEF 2021
- NLP topic: hate detection
- Dataset: NewsCom-TOX
- Forum: IberLEF
- Competition: DETOXIS: Detection of toxicity
- Domain:
- Language(s):
Automatic indexing of clinical trials CLEF 2021
- 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
Non-contextual classification of offensive comments IberLEF 2021
- NLP topic: hate detection
- Dataset: MeOffendES
- Forum: IberLEF
- Competition: MeOffendES: Detection of offensive language
- Domain:
- Language(s): Spanish
Sexism identification IberLEF 2021
- NLP topic: hate detection
- Dataset: EXIST-2021-ES
- Forum: IberLEF
- Competition: EXIST: Sexism detection in Twitter
- Domain:
- Language(s): Spanish, English
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.
