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dc.contributor.author Westera, Matthijs
dc.contributor.author Mayol, Laia
dc.contributor.author Rohde, Hannah
dc.date.accessioned 2021-02-03T11:03:00Z
dc.date.available 2021-02-03T11:03:00Z
dc.date.issued 2020
dc.identifier.citation Westera M, Mayol L, Rohde H. TED-Q: TED talks and the questions they evoke. In: Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the 12th Language Resources and Evaluation Conference; 2020 May 13-15; Marseilles, France. Stroudsburg (PA): ACL; 2020. p. 1118-27.
dc.identifier.uri http://hdl.handle.net/10230/46320
dc.description Comunicació presentada al 12th Language Resources and Evaluation Conference celebrat del 13 al 15 de maig de 2020 de manera virtual.
dc.description.abstract We present a new dataset of TED-talks annotated with the questions they evoke and, where available, the answers to these questions. Evoked questions represent a hitherto mostly unexplored type of linguistic data, which promises to open up important new lines of research, especially related to the Question Under Discussion (QUD)-based approach to discourse structure. In this paper we introduce the method and open the first installment of our data to the public. We summarize and explore the current dataset, illustrate its potential by providing new evidence for the relation between predictability and implicitness – capitalizing on the already existing PDTB-style annotations for the texts we use – and outline its potential for future research. The dataset should be of interest, at its current scale, to researchers on formal and experimental pragmatics, discourse coherence, information structure, discourse expectations and processing. Our data-gathering procedure is designed to scale up, relying on crowdsourcing by non-expert annotators, with its utility for Natural Language Processing in mind (e.g., dialogue systems, conversational question answering).
dc.description.sponsorship This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 715154) and from the Spanish State Research Agency (AEI) and the European Regional Development Fund (FEDER, UE) (project PGC2018-094029-A-I00).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher ACL (Association for Computational Linguistics)
dc.relation.ispartof Calzolari N, Béchet F, Blache P, Choukri K, Cieri C, Declerck T, Goggi S, Isahara H, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors. Proceedings of the 12th Language Resources and Evaluation Conference; 2020 May 13-15; Marseilles, France. Stroudsburg (PA): ACL; 2020. p. 1118-27
dc.rights © ACL, Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.title TED-Q: TED talks and the questions they evoke
dc.type info:eu-repo/semantics/conferenceObject
dc.subject.keyword Discourse structure
dc.subject.keyword Discourse relation
dc.subject.keyword Evoked question
dc.subject.keyword Question under discussion
dc.subject.keyword TED-talks
dc.subject.keyword Crowdsourcing
dc.subject.keyword Implicit connective
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/715154
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-094029-A-I00
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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