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: 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
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
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
Entity recognition IberLEF 2019
- NLP topic: information extraction
- Dataset: eHealth-KD 2019
- Forum: IberLEF
- Competition: eHealth-KD 2019: eHealth Knowledge Discovery
- Domain:
- Language(s):
Negation cue identification IberLEF 2019
- NLP topic: processing negation
- Dataset: NEGES
- Forum: IberLEF
- Competition: NEGES 2019 Task: Negation in Spanish
- Domain:
- Language(s): Spanish
Relation extraction IberLEF 2019
- NLP topic: information extraction
- Dataset: eHealth-KD 2019
- Forum: IberLEF
- Competition: eHealth-KD 2019: eHealth Knowledge Discovery
- Domain:
- Language(s): Spanish
Sensitive span detection IberLEF 2019
- NLP topic: information extraction
- Dataset: MEDDOCAN
- Forum: IberLEF
- Competition: MEDDOCAN: Medical Document Anonymization Track
- Domain: Health
- Language(s): Spanish
Hypernym Discovery SEMEVAL 2018
- NLP topic: information extraction
- Dataset: Hypernym corpora-ES
- Forum: SEMEVAL
- Competition: SemEval 2018 Shared Task on Hypernym Discovery
- 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.
