metadata

language:
  - es
tags:
  - biomedical
  - clinical
  - spanish
multilinguality:
  - monolingual
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
license:
  - cc-by-4.0
pretty_name: SocialDisNER
train-eval-index:
  - task: token-classification
    task_id: token_classification
    splits:
      train_split: train
      eval_split: test
    metrics:
      - type: f1
        name: f1

SocialDisNER

This is a third party reupload of the SocialDisNER dataset.

This dataset is part of a benchmark in the paper TODO.

Citation Information

TODO

Citation Information of the original dataset

@inproceedings{gasco-sanchez-etal-2022-socialdisner,
    title = "The {S}ocial{D}is{NER} shared task on detection of disease mentions in health-relevant content from social media: methods, evaluation, guidelines and corpora",
    author = "Gasco S{'a}nchez, Luis  and
      Estrada Zavala, Darryl  and
      Farr{'e}-Maduell, Eul{\`a}lia  and
      Lima-L{'o}pez, Salvador  and
      Miranda-Escalada, Antonio  and
      Krallinger, Martin",
    booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {\&} Shared Task",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.smm4h-1.48",
    pages = "182--189",
}