metadata

language:
  - en
bigbio_language:
  - English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: MEDIQA RQE
homepage: https://sites.google.com/view/mediqa2019
bigbio_pubmed: false
bigbio_public: true
bigbio_tasks:
  - TEXT_PAIRS_CLASSIFICATION

Dataset Card for MEDIQA RQE

Dataset Description

Homepage: https://sites.google.com/view/mediqa2019
Pubmed: False
Public: True
Tasks: Text Pairs Classification

The MEDIQA challenge is an ACL-BioNLP 2019 shared task aiming to attract further research efforts in Natural Language Inference (NLI), Recognizing Question Entailment (RQE), and their applications in medical Question Answering (QA). Mailing List: https://groups.google.com/forum/#!forum/bionlp-mediqa

The objective of the RQE task is to identify entailment between two questions in the context of QA. We use the following definition of question entailment: “a question A entails a question B if every answer to B is also a complete or partial answer to A” [1] [1] A. Ben Abacha & D. Demner-Fushman. “Recognizing Question Entailment for Medical Question Answering”. AMIA 2016.

Citation Information

@inproceedings{MEDIQA2019,
  author    = {Asma {Ben Abacha} and Chaitanya Shivade and Dina Demner{-}Fushman},
  title     = {Overview of the MEDIQA 2019 Shared Task on Textual Inference, Question Entailment and Question Answering},
  booktitle = {ACL-BioNLP 2019},
  year      = {2019}
}