Datasets

Below is information about Spanish textual data sets created with the goal of solving NLP tasks. In this case, these are collections of texts, generally enriched with annotations.

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Year

  • SQUAD-SQAC 2024 ES

    Diverse
    Spanish
    Published in 2024
    110
    Scientific papers
    question answering

  • JOKER 2023 ES

    Social
    Spanish , English
    Published in 2023
    4,235
    Tweets
    hate detection

  • EXIST-2023-ES

    Social
    Spanish , English
    Published in 2023
    4,653
    Tweets
    hate detection

  • PoliticES 2023

    Social, Politics
    Spanish
    Published in 2023
    2,797
    Tweets
    profiling

  • HUHU 2023

    Social
    Spanish
    Published in 2023
    3,449
    Tweets
    processing humor

  • HOPE-ES 2023

    Social
    Spanish
    Published in 2023
    2,062
    Tweets
    hate detection

  • HOMO-MEX 2023

    Social
    Spanish (Mexico)
    Published in 2023
    11,000
    Tweets
    hate detection

  • DA-VINCIS 2023

    Social
    Spanish (Mexico)
    Published in 2023
    4,731
    Tweets
    processing events

  • MultiCoNER-ES

    Diverse
    Spanish
    Published in 2022
    233,987
    Wikipedia Questions Search queries
    (named) entity recognition

  • DA-VINCIS

    Social
    Spanish (Mexico)
    Published in 2022
    5,453
    Tweets
    processing events

  • FakeDeS

    COVID, others
    Spanish
    Published in 2021
    1,633
    News
    fake news detection

  • PAN-AP-2021-ES

    Social
    Spanish
    Published in 2021
    300
    Tweets
    hate detection

  • Spanish Fake News Corpus

    Diverse
    Spanish (Mexico)
    Published in 2020
    971
    News
    fake news detection

  • mSpRL

    Diverse
    Spanish , English
    Published in 2017
    1,213
    Images, textual descriptions
    semantic role labeling

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.