Similarity or deeper understanding?: analyzing the TED-Q dataset of evoked questions

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• dc.contributor.author Westera, Matthijs
• dc.contributor.author Amidei, Jacopo
• dc.contributor.author Mayol, Laia
• dc.date.accessioned 2021-02-03T11:03:04Z
• dc.date.available 2021-02-03T11:03:04Z
• dc.date.issued 2020
• dc.description Comunicació presentada al 28th International Conference on Computational Linguistics celebrat del 8 al 13 de desembre de 2020 de manera virtual.
• dc.description.abstract We take a close look at a recent dataset of TED-talks annotated with the questions they implicitly evoke, TED-Q (Westera et al., 2020). We test to what extent the relation between a discourse and the questions it evokes is merely one of similarity or association, as opposed to deeper semantic/pragmatic interpretation. We do so by turning the TED-Q dataset into a binary classification task, constructing an analogous task from explicit questions we extract from the BookCorpus (Zhu et al., 2015), and fitting a BERT-based classifier alongside models based on different notions of similarity. The BERT-based classifier, achieving close to human performance, outperforms all similarity-based models, suggesting that there is more to identifying true evoked questions than plain similarity.en
• 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.identifier.citation Westera M, Amidei J, Mayol L. Similarity or deeper understanding?: analyzing the TED-Q dataset of evoked questions. In: Scott D, Bel N, Zong C, editors. Proceedings of the 28th International Conference on Computational Linguistics; 2020 Dec 8-13; Barcelona, Spain. Stroudsburg (PA): ACL; 2020. p. 5004-12.
• dc.identifier.uri http://hdl.handle.net/10230/46321
• dc.language.iso eng
• dc.publisher ACL (Association for Computational Linguistics)
• dc.relation.ispartof Scott D, Bel N, Zong C, editors. Proceedings of the 28th International Conference on Computational Linguistics; 2020 Dec 8-13; Barcelona, Spain. Stroudsburg (PA): ACL; 2020. p. 5004-12
• 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 © ACL, Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/)
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.title Similarity or deeper understanding?: analyzing the TED-Q dataset of evoked questionsen
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion