Show simple item record

dc.contributor.authorThomson, Craig Alexander
dc.contributor.authorReiter, Ehud
dc.date.accessioned2020-12-07T16:23:01Z
dc.date.available2020-12-07T16:23:01Z
dc.date.issued2020-12
dc.identifier.citationThomson , C A & Reiter , E 2020 , ' A Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systems ' , Paper presented at Proceedings of the 13th International Conference on Natural Language Generation , Dublin , Ireland , 15/12/20 - 18/12/20 pp. 158-168 . < https://www.aclweb.org/anthology/2020.inlg-1.22/ >en
dc.identifier.citationconferenceen
dc.identifier.otherPURE: 182839459
dc.identifier.otherPURE UUID: 479a65c1-39fe-4dc1-a075-609ad193f532
dc.identifier.otherORCID: /0000-0002-7548-9504/work/84977771
dc.identifier.urihttps://hdl.handle.net/2164/15469
dc.descriptionAcknowledgements: Many thanks to the Mechanical Turk annotators who participated in our experiment, and also to David Reiter, Tim Daniels, Rodrigo de Oliveira, and Andrew Smith for serving as pilot annotators when we were developing the methodology described in this paper. We would also like to thank Moray Greig for being our basketball domain expert during development. We are also grateful for the very helpful comments on this paper from the anonymous reviewers, the Aberdeen CLAN group, David Howcroft, Clement Rebuffel, and Chris van ´ der Lee. We would also like to thank Sam Wiseman, Ratish Puduppully, and Clement Rebuffel for pro- viding the generated texts from their respective systems. The work presented here is partially funded by the Engineering and Physical Sciences Research Council (EPSRC), which funds Craig Thomson under a National Productivity Investment Fund Doctoral Studentship (EP/R512412/1).en
dc.format.extent11
dc.language.isoeng
dc.relation.ispartofen
dc.rightsMaterials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License https://creativecommons.org/licenses/by/4.0/en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectEngineering and Physical Sciences Research Council (EPSRC)en
dc.subjectEP/R512412/1en
dc.subject.lccQA75en
dc.titleA Gold Standard Methodology for Evaluating Accuracy in Data-To-Text Systemsen
dc.typeConference paperen
dc.contributor.institutionUniversity of Aberdeen.Natural & Computing Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Centre for Health Data Scienceen
dc.contributor.institutionUniversity of Aberdeen.Computer Science and Informaticsen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.urlhttps://www.aclweb.org/anthology/2020.inlg-1.22/en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record