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A Taxonomy of Real-Life Questions and Answers in Dialogue

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Maxime Amblard
Semantic Analysis of Natural Language
CV
Maria Boritchev
École normale supérieure - Lyon
Marta Carletti
  • Function : Author
  • PersonId : 1052572
Institut des Sciences du Digital, Management et Cognition
Lea Dieudonat
  • Function : Author
  • PersonId : 1052573
Institut des Sciences du Digital, Management et Cognition
Yiting Tsai
  • Function : Author
  • PersonId : 1052574
Institut des Sciences du Digital, Management et Cognition

Abstract

We present a taxonomy of questions and answers based on real-life data extracted from spontaneous dialogue corpora. This classification allowed us to build a fine-grained annotation schema, which we applied to several languages: English, French, Italian and Chinese.

Domains

Cognitive science Linguistics Cognitive science Computer science Computer Science [cs] Document and Text Processing Computer Science [cs] Artificial Intelligence [cs.AI]
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https://hal.inria.fr/hal-02269609

Submitted on : Friday, August 23, 2019-9:50:50 AM

Last modification on : Saturday, June 25, 2022-7:43:55 PM

Long-term archiving on: Friday, January 10, 2020-11:23:32 PM

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hal-02269609 , version 1 (23-08-2019)

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  • HAL Id : hal-02269609 , version 1

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Maxime Amblard, Maria Boritchev, Marta Carletti, Lea Dieudonat, Yiting Tsai. A Taxonomy of Real-Life Questions and Answers in Dialogue. SemDial 2019 - LondonLogue - 23rd Workshop on the semantics and pragmatics of dialogue, Sep 2019, London, United Kingdom. ⟨hal-02269609⟩

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