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

  • 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

  • MEDDOCAN

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

  • mSpRL

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

  • M-WeP-NaD-2017

    Spanish , English
    Published in 2017
    10,420
    Web pages
    information retrieval

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.