Which States Can Be Changed by Which Events?

摘要

We present a method for finding (STATE, EVENT) pairs where EVENT can change STATE. For example, the event "realize" can put an end to the states "be unaware", "be confused", and "be happy"; while it can rarely affect "being hungry". We extract these pairs from a large corpus using a fixed set of syntactic dependency patterns. We then apply a supervised Machine Learning algorithm to clean the results using syntactic and collocational features, achieving a precision of 78% and a recall of 90%. We observe 3 different relations between states and events that change them and present a method for using Mechanical Turk to differentiate between these relations.