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.
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
Fake news detection IberLEF 2021
- NLP topic: fake news detection
- Dataset: FakeDeS
- Forum: IberLEF
- Competition: FakeDeS: Fake news detection
- Domain: COVID, others
- Language(s): Spanish
Worthiness estimation CLEF 2021
- NLP topic: fake news detection
- Dataset: CheckThat-ES
- Forum: CLEF
- Competition: CheckThat! Lab Task 1 on Check-Worthiness Estimation in Tweets and Political Debates
- Domain: Politics
- Language(s): Spanish, English
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
Entity recognition IberLEF 2019
- NLP topic: information extraction
- Dataset: eHealth-KD 2019
- Forum: IberLEF
- Competition: eHealth-KD 2019: eHealth Knowledge Discovery
- Domain:
- Language(s):
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.
