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

  • MedProcNER/ProcTEMIST corpus 2023

    Health
    Spanish
    Published in 2023
    1,000
    Clinical notes
    (named) entity recognition

  • MEDDOPLACE Corpus: Gold Standard annotations for Medical Documents Place-related Content Extraction

    Health
    Spanish
    Published in 2023
    1,000
    Clinical notes
    (named) entity recognition

  • MultiCoNER v2 ES

    General
    Spanish
    Published in 2023
    264,207
    Wiki sentences Questions Search queries
    (named) entity recognition

  • MultiCoNER-ES

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

  • SocialDisNER

    Health
    Spanish
    Published in 2022
    9,500
    Tweets
    (named) entity recognition

  • LivingNER

    Health
    Spanish
    Published in 2022
    1,850
    Clinical case reports
    (named) entity recognition

  • DisTEMIST

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

  • SpRadIE

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

  • CAPITEL-NER

    Spanish
    Published in 2020
    News
    (named) entity recognition

  • CAPITEL-UD

    Spanish
    Published in 2020
    News
    parsing

  • NEGES

    Spanish
    Published in 2019
    400
    Reviews
    sentiment analysis, processing negation

  • MEDDOCAN

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

  • CoNLL-UD2.2-ES

    Spanish
    Published in 2018
    445,000
    Documents
    parsing

  • UD2.0-es

    Spanish
    Published in 2017
    parsing

  • CoNL-2009-ES

    Spanish
    Published in 2009
    16,054
    parsing

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.