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 Recognition IberLEF 2023
- NLP topic: (named) entity recognition
- 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
GUA-SPA: Named entity classification IberLEF 2023
- NLP topic: (named) entity recognition
- Dataset: GUA-SPA: Guarani Spanish corpus
- Forum: IberLEF
- Competition: GUA-SPA: Guarani-Spanish Code-Switching Analysis
- Domain: News
- Language(s): Spanish
Monolingual NER Spanish SEMEVAL 2023
- NLP topic: (named) entity recognition
- Dataset: MultiCoNER v2 ES
- Forum: SEMEVAL
- Competition: SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)
- Domain: General
- Language(s): Spanish, English
- NLP topic: (named) entity recognition
- Dataset: MedProcNER/ProcTEMIST corpus 2023
- Forum: CLEF
- Competition: BioASQ 2023: Large-scale Biomedical Semantic Indexing and Question Answering
- Domain: Health
- Language(s): Spanish
Detection of disease mentions in tweets COLING 2022
- NLP topic: (named) entity recognition
- Dataset: SocialDisNER
- Forum: COLING
- Competition: Seventh Social Media Mining for Health Applications
- Domain: Health
- Language(s): Spanish
Named entity recognition CLEF 2022
- NLP topic: (named) entity recognition
- Dataset: DisTEMIST
- Forum: CLEF
- Competition: DisTEMIST at BioASQ: Automatic detection and normalization of diseases from clinical texts
- Domain: Health
- Language(s): Spanish
Named entity recognition SEMEVAL 2022
- NLP topic: (named) entity recognition
- Dataset: MultiCoNER-ES
- Forum: SEMEVAL
- Competition: SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)
- Domain: Diverse
- Language(s): Spanish, English
SpRadIE - Named entity recognition CLEF 2021
- NLP topic: (named) entity recognition
- Dataset: SpRadIE
- Forum: CLEF
- Competition: SpRadIE: A challenge on information extraction from Spanish Radiology Reports
- Domain: Health
- Language(s): Spanish (Argentina)
Entity recognition IberLEF 2021
- NLP topic: (named) entity recognition
- Dataset: eHealth-KD-ES
- Forum: IberLEF
- Competition: eHealth Knowledge Discovery
- Domain: Health
- Language(s): Spanish, English
MEDDOPROF - Named entity recognition IberLEF 2021
- NLP topic: (named) entity recognition
- Dataset: MEDDOPROF
- Forum: IberLEF
- Competition: Recognition, classification and normalization of professions and occupations from medical texts
- Domain: Health
- Language(s): Spanish
Named entity recognition IberLEF 2020
- NLP topic: (named) entity recognition
- Dataset: CAPITEL-NER
- Forum: IberLEF
- Competition: Named entity recognition and Universal Dependency parsing
- 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
Entity classification IberLEF 2019
- NLP topic: (named) entity recognition
- Dataset: MEDDOCAN
- Forum: IberLEF
- Competition: MEDDOCAN: Medical Document Anonymization Track
- Domain: Health
- Language(s): Spanish
DIANN 2018: Disability detection IberEVAL 2018
- NLP topic: (named) entity recognition
- Dataset: DIANN-2018-ES
- Forum: IberEVAL
- Competition: Disability annotation on documents from the biomedical domain (DIANN)
- 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.