Our idea of selecting a finite set of representative feature values for each event mention is based on a heuristic approach that is used after running the mIBP generative process.
by considering the event mention y t , f m one of the feature values that characterizes y t , q m the number of times f m was selected for all mentions during mIBP, and v t a threshold variable for y t such that v t ∼ Uniform(1, max{q m | F m t = 1}), we define the finite set of feature values B t corresponding to the observation y t as: A pictorial representation of this idea is illustrated in Figure 4, where only the feature values f m with the corresponding counts q m above the threshold indicated by v t are selected in B t .