  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.
