We propose a framework for analyzing episodic conversational activities in terms of expressed relationships between the participants and utterance content. We test the hypothesis that linguistic features which express such properties, e.g. tense, aspect, and person deixis, are a useful basis for automatic intentional discourse segmentation. We present a novel algorithm and test our hypothesis on a set of intentionally segmented conversational monologues. Our algorithm performs better than a simple baseline and as well as or better than well-known lexical-semantic segmentation methods.