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.

Filter by
Year

  • DIPROMATS-ES 2023

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

  • European Clinical Case Corpus (Spanish part)

    Health
    Spanish
    Published in 2023
    161
    Clinical cases
    relation extraction

  • 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

  • eHealth-KD-ES

    Health
    Spanish
    Published in 2021
    1,800
    News Encyclopedia entries Scientific papers
    relation extraction

  • 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

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.