TED-Q: TED talks and the questions they evoke

Matthijs Westera, Laia Mayol, Hannah Rohde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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).
Original languageEnglish
Title of host publicationProceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)
EditorsNicoletta Calzolari
PublisherEuropean Language Resources Association (ELRA)
Pages1118‑1127
ISBN (Print)9791095546344
Publication statusPublished - 1 May 2020

Keywords

  • discourse structure
  • discourse relation
  • evoked question
  • question under discussion
  • TED-talks
  • crowdsourcing
  • implicit connective

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