dc.contributor.author | Dzendzik, Daria | |
dc.contributor.author | Vogel, Carl | |
dc.contributor.author | Foster, Jennifer | |
dc.date.accessioned | 2021-12-09T14:22:57Z | |
dc.date.available | 2021-12-09T14:22:57Z | |
dc.date.issued | 2021 | |
dc.date.submitted | 2021 | en |
dc.identifier.citation | Daria Dzendzik, Carl Vogel, Jennifer Foster, 'English Machine Reading Comprehension Datasets: A Survey', Association for Computational Linguistics, 2021 | en |
dc.identifier.other | Y | |
dc.description | PUBLISHED | en |
dc.description.abstract | This 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.extent | 8784-8804 | en |
dc.language.iso | en | en |
dc.publisher | Association for Computational Linguistics | en |
dc.rights | Y | en |
dc.subject | Machine reading comprehension | en |
dc.subject | English language | en |
dc.subject | Data sources | en |
dc.title | English Machine Reading Comprehension Datasets: A Survey | en |
dc.title.alternative | Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing | en |
dc.type | Conference Paper | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/vogel | |
dc.identifier.rssinternalid | 235461 | |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTheme | Creative Technologies | en |
dc.subject.TCDTheme | Digital Engagement | en |
dc.subject.TCDTheme | Digital Humanities | en |
dc.subject.TCDTag | Computational Linguistics | en |
dc.subject.TCDTag | Computational linguistics | en |
dc.subject.TCDTag | Question Answering | en |
dc.subject.TCDTag | computational linguistics | en |
dc.subject.TCDTag | text analytics | en |
dc.identifier.orcid_id | 0000-0001-8928-8546 | |
dc.contributor.sponsor | Science Foundation Ireland (SFI) | en |
dc.contributor.sponsorGrantNumber | 13/RC/2106 | en |
dc.identifier.uri | https://aclanthology.org/2021.emnlp-main.693.pdf | |
dc.identifier.uri | http://hdl.handle.net/2262/97682 | |