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: text indexing
- Dataset: MedProcNER/ProcTEMIST corpus 2023
- Forum: CLEF
- Competition: BioASQ 2023: Large-scale Biomedical Semantic Indexing and Question Answering
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: PoliticES 2023
- Forum: IberLEF
- Competition: PoliticES: Political ideology detection in Spanish texts
- Domain: Social, Politics
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Depression 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Eating disorders 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Undefined disorder 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Depression 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Undefined disorder 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Depression 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
- NLP topic: profiling
- Dataset: MentalRiskES - Eating disorders 2023
- Forum: IberLEF
- Competition: MentalRiskES: Early detection of mental disorders risk in Spanish
- Domain: Health
- Language(s): Spanish
Author profiling IberLEF 2022
- NLP topic: profiling
- Dataset: PoliticEs
- Forum: IberLEF
- Competition: PoliticEs 2022: Spanish Author Profiling for Political Ideology
- Domain: Politics
- Language(s): Spanish
- 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
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
Diagnosis coding CLEF 2020
- NLP topic: text indexing
- Dataset: CodiEsp
- Forum: CLEF
- Competition: CodiEsp: Clinical Case Coding in Spanish Shared Task (eHealth CLEF 2020)
- Domain:
- Language(s): Spanish
Procedure Coding CLEF 2020
- NLP topic: text indexing
- Dataset: CodiEsp
- Forum: CLEF
- Competition: CodiEsp: Clinical Case Coding in Spanish Shared Task (eHealth CLEF 2020)
- Domain:
- Language(s):
Explainable AI CLEF 2020
- NLP topic: text indexing
- Dataset: CodiEsp
- Forum: CLEF
- Competition: CodiEsp: Clinical Case Coding in Spanish Shared Task (eHealth CLEF 2020)
- Domain:
- Language(s): Spanish
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
Authorship attribution PAN 2018
- NLP topic: profiling
- Dataset: PAN18-Attribution-ES
- Forum: PAN
- Competition: Cross-Domain Authorship Attribution
- Domain: Fiction
- 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.