View article

Many important aspects of natural language reside beyond the level of a single sentence or clause, at the level of the discourse, including: reference relations such anaphora, notions of topic/focus and foreground/background information as well as rhetorical relations such as CAUSATION or MOTIVATION. This dissertation is concerned with data-driven, machine learning-based methods for the latter-the identification of rhetorical discourse relations between abstract objects, including events, states and propositions. Our focus is specifically on those relations based on the semantic content of their arguments as opposed to the intent of the writer.