Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations

Magdalena Markowska, Mohammad Taghizadeh, Adil Soubki, Seyed Abolghasem Mirroshandel, Owen Rambow

Submission Type: Regular Long Paper

Submission Track: Resources and Evaluation

Submission Track 2: Discourse and Pragmatics

Keywords: Common Ground, Belief Extraction, Corpus Construction, Cognitive state, T5 Language Model

TL;DR: We introduce a new corpus for common ground in conversations, and describe initial experiments.

Abstract: When we communicate with other humans, we do not simply generate a sequence of words. Rather, we use our cognitive state (beliefs, desires, intentions) and our model of the audience’s cognitive state to create utterances that affect the audience’s cognitive state in the intended manner. An important part of cognitive state is the common ground, which is the content the speaker believes, and the speaker believes the audience believes, and so on. While much attention has been paid to common ground in cognitive science, there has not been much work in natural language processing. In this paper, we introduce a new annotation and corpus to capture common ground. We then describe some initial experiments extracting propositions from dialog and tracking their status in the common ground from the perspective of each speaker.

Submission Number: 2190