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 Attribution 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 Detection IberLEF 2023
- NLP topic: text generation
- Dataset: AuTexTification 2023
- Forum: IberLEF
- Competition: AuTexTification: Automated Text Identification
- Domain: General, Legal, News
- 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
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
- 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.
