Lexical Event Ordering with an Edge-Factored Model

Extensive lexical knowledge is necessary for temporal analysis and planning tasks. We ad-dress in this paper a lexical setting that al-lows for the straightforward incorporation of rich features and structural constraints. We ex-plore a lexical event ordering task, namely de-termining the likely temporal order of events based solely on the identity of their predi-cates and arguments. We propose an “edge-factored ” model for the task that decomposes over the edges of the event graph. We learn it using the structured perceptron. As lexi-cal tasks require large amounts of text, we do not attempt manual annotation and instead use the textual order of events in a domain where this order is aligned with their temporal order, namely cooking recipes.