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When we communicate with other humans, we do not simply generate a sequenceof words. Rather, we use our cognitive state (beliefs, desires, intentions) andour model of the audience's cognitive state to create utterances that affectthe audience's cognitive state in the intended manner. An important part ofcognitive state is the common ground, which is the content the speakerbelieves, and the speaker believes the audience believes, and so on. While muchattention has been paid to common ground in cognitive science, there has notbeen much work in natural language processing. In this paper, we introduce anew annotation and corpus to capture common ground. We then describe someinitial experiments extracting propositions from dialog and tracking theirstatus in the common ground from the perspective of each speaker.

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