We present a method for discovering abstract event classes in biographies, based on a probabilistic latent-variable model. Taking as input timestamped text, we exploit latent correlations among events to learn a set of event classes (such as BORN, GRADUATES HIGH SCHOOL, and BECOMES CITIZEN), along with the typical times in a person’s life when those events occur. In a quantitative evaluation at...
