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.

  • DIPROMATS-ES 2023

    Politics
    Spanish , English
    Published in 2023
    9,591
    Tweets
    text classification

  • GUA-SPA: Guarani Spanish corpus

    News
    Spanish , Spanish (Paraguay) , Guarani
    Published in 2023
    1,500
    News
    code switching detection

  • ClinAIS 2023

    Health
    Spanish
    Published in 2023
    1,038
    Clinical notes
    text classification

  • SMM4H-tweets-es-2022

    Health
    Spanish
    Published in 2022
    20,481
    Tweets
    text classification

  • RestMEX-covid-sempahore

    Health
    Spanish (Mexico)
    Published in 2022
    131,471
    News
    text classification

  • ADoBo

    Spanish
    Published in 2021
    Laws
    text classification

  • MEDDOPROF

    Health
    Spanish
    Published in 2021
    1,844
    Clinical records from journals
    text classification

  • eHealth-KD 2019

    Spanish
    Published in 2019
    1,000
    Health
    information extraction

  • MEDDOCAN

    Health
    Spanish
    Published in 2019
    1,000
    Clinical case reports
    (named) entity recognition, information extraction

  • MLDoc-ES

    News
    Spanish
    Published in 2018
    14,458
    News
    text classification

  • DIANN-2018-ES

    Health
    Spanish
    Published in 2018
    500
    Abstracts scientific articles
    information extraction

  • DIANN-2018-EN

    Health
    English
    Published in 2018
    500
    Abstracts scientific articles
    information extraction

  • Tweets emojis-ES

    Spanish
    Published in 2018
    120,000
    Tweets
    text classification

  • MLDoc-EN

    News
    English
    Published in 2018
    14,458
    News
    text classification

  • Hypernym corpora-ES

    Spanish
    Published in 2018
    2,000
    Words
    information extraction

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.