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dc.contributor.authorDzendzik, Daria
dc.contributor.authorVogel, Carl
dc.contributor.authorFoster, Jennifer
dc.date.accessioned2021-12-09T14:22:57Z
dc.date.available2021-12-09T14:22:57Z
dc.date.issued2021
dc.date.submitted2021en
dc.identifier.citationDaria Dzendzik, Carl Vogel, Jennifer Foster, 'English Machine Reading Comprehension Datasets: A Survey', Association for Computational Linguistics, 2021en
dc.identifier.otherY
dc.descriptionPUBLISHEDen
dc.description.abstractThis paper surveys 60 English Machine Reading Comprehension datasets, with a view to providing a convenient resource for other researchers interested in this problem. We categorize the datasets according to their question and answer form and compare them across various dimensions including size, vocabulary, data source, method of creation, human performance level, and first question word. Our analysis reveals that Wikipedia is by far the most common data source and that there is a relative lack of why, when, and where questions across datasets.en
dc.format.extent8784-8804en
dc.language.isoenen
dc.publisherAssociation for Computational Linguisticsen
dc.rightsYen
dc.subjectMachine reading comprehensionen
dc.subjectEnglish languageen
dc.subjectData sourcesen
dc.titleEnglish Machine Reading Comprehension Datasets: A Surveyen
dc.title.alternativeProceedings of the 2021 Conference on Empirical Methods in Natural Language Processingen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/vogel
dc.identifier.rssinternalid235461
dc.rights.ecaccessrightsopenAccess
dc.subject.TCDThemeCreative Technologiesen
dc.subject.TCDThemeDigital Engagementen
dc.subject.TCDThemeDigital Humanitiesen
dc.subject.TCDTagComputational Linguisticsen
dc.subject.TCDTagComputational linguisticsen
dc.subject.TCDTagQuestion Answeringen
dc.subject.TCDTagcomputational linguisticsen
dc.subject.TCDTagtext analyticsen
dc.identifier.orcid_id0000-0001-8928-8546
dc.contributor.sponsorScience Foundation Ireland (SFI)en
dc.contributor.sponsorGrantNumber13/RC/2106en
dc.identifier.urihttps://aclanthology.org/2021.emnlp-main.693.pdf
dc.identifier.urihttp://hdl.handle.net/2262/97682


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