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.
AuTexTification: Model Generated Text Detection IberLEF 2023
- NLP topic: text generation
- Dataset: AuTexTification 2023
- Forum: IberLEF
- Competition: AuTexTification: Automated Text Identification
- Domain: General, Legal, News
- Language(s): Spanish
AuTexTification: Model Generated Text Attribution IberLEF 2023
- NLP topic: text generation
- Dataset: AuTexTification 2023
- Forum: IberLEF
- Competition: AuTexTification: Automated Text Identification
- Domain: General, Legal, News
- Language(s): Spanish
Rest-Mex: Thematic Unsupervised Classification IberLEF 2023
- NLP topic: topic modeling
- Dataset: Rest-Mex 2023 Clustering
- Forum: IberLEF
- Competition: Rest-Mex 2023: Research on Sentiment Analysis Task for Mexican Tourist Texts
- Domain: News
- 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
Entity recognition IberLEF 2019
- NLP topic: information extraction
- Dataset: eHealth-KD 2019
- Forum: IberLEF
- Competition: eHealth-KD 2019: eHealth Knowledge Discovery
- Domain:
- Language(s):
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
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
Classification of political topics IberEVAL 2017
- NLP topic: topic modeling
- Dataset: COSET
- Forum: IberEVAL
- Competition: 1st Classification of Spanish Election Tweets Task
- Domain: Politics
- 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.
