In this paper, we present a formal approach to compositional processing of questions and answers in the Schizophrenia and Language, Analysis and Modeling corpus [1]. We address dialogue lexicality issues starting from the formal definitions of so-called Düsseldorf Frame Semantics given in [2]. We introduce a view of dialogues as compositions of negotiation phases that can be studied separately one from another while linked by a common dialogue context (accessible to all participants of a dialogue).
The present study proposes an annotation scheme for classifying the content and discourse contribution of question-answer pairs. We propose detailed guidelines for using the scheme and apply them to dialogues in English, Spanish, and Dutch. Finally, we report on initial machine learning experiments for automatic annotation.
We present Dialogues in Games (DinG), a corpus of manual transcriptions of real-life, oral, spontaneous multi-party dialogues between French-speaking players of the board game Catan. Our objective is to make available a quality resource for French, composed of long dialogues, to facilitate their study in the style of (Asher et al., 2016). In a general dialogue setting, participants share personal information, which makes it impossible to disseminate the resource freely and openly. In DinG, the attention of the participants is focused on the game, which prevents them from talking about themselves. In addition, we are conducting a study on the nature of the questions in dialogue, through annotation (Cruz Blandon et al., 2019), in order to develop more natural automatic dialogue systems.
This paper introduces a formal model of dialogue based on insights and ideas developed by Jonathan Ginzburg in [11]. This model, which is logic based, takes advantage of inquisitive semantics [4], which allows to model both declarative and interrogative sentences in a uniform way. It appeals to ideas derived from classical epistemic logic in order to model the knowledge states of the dialogue participants, and includes a context-updating mechanisms based on the type-theoretic dynamic logic developed in [15].
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