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.
MEDDOPLACE: Location Entity Classification IberLEF 2023
- NLP topic: entity linking
- Dataset: MEDDOPLACE Corpus: Gold Standard annotations for Medical Documents Place-related Content Extraction
- Forum: IberLEF
- Competition: MEDDOPLACE: MEDical DOcument PLAce-related Content Extraction
- 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
- 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: entity linking
- 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: 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
DisTEMIST 2022: Entity linking CLEF 2022
- NLP topic: entity linking
- Dataset: DisTEMIST
- Forum: CLEF
- Competition: DisTEMIST at BioASQ: Automatic detection and normalization of diseases from clinical texts
- 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
Universal dependency parsing IberLEF 2020
- NLP topic: parsing
- Dataset: CAPITEL-UD
- Forum: IberLEF
- Competition: Named entity recognition and Universal Dependency parsing
- 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
- NLP topic: parsing
- Dataset: CoNLL-UD2.2-ES
- Forum: CoNLL
- Competition: CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
- Domain:
- Language(s): Spanish, English
Universal dependency parsing CoNLL 2017
- NLP topic: parsing
- Dataset: UD2.0-es
- Forum: CoNLL
- Competition: CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
- Domain:
- Language(s): Spanish, English
- NLP topic: parsing
- Dataset: CoNL-2009-ES
- Forum: CoNLL
- Competition: CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages
- 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.
