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

  • DisTEMIST

    Health
    Spanish
    Published in 2022
    1,000
    Clinical cases
    entity linking, (named) entity recognition

  • ADoBo

    Spanish
    Published in 2021
    Laws
    text classification

  • MEDDOPROF

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

  • SpRadIE

    Health
    Spanish (Argentina)
    Published in 2021
    513
    Radiology reports
    (named) entity recognition

  • CAPITEL-NER

    Spanish
    Published in 2020
    News
    (named) entity recognition

  • 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

  • Tweets emojis-ES

    Spanish
    Published in 2018
    120,000
    Tweets
    text classification

  • MLDoc-EN

    News
    English
    Published in 2018
    14,458
    News
    text classification

  • RepLab-2014-Reputation

    Finance
    Spanish
    Published in 2014
    48,705
    Tweets
    text classification

  • RepLab-2014-Profiling

    Finance
    Spanish
    Published in 2014
    48,705
    Tweets
    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.