Using Syntactic Dependencies and WordNet Classes for Noun Event Recognition

The goal of this research is to devise a method for recognizing TimeML noun events in a more effective way. TimeML is the most recent annotation scheme for processing the event and temporal expressions in natural language processing fields. In this paper, we argue and demonstrate that the dependencies and the deep-level WordNet classes are useful for recognizing events. We formulate the event recognition problem as a classification task using various features including lexical semantic and dependency-based features. The experimental results show that our proposed method outperforms significantly a state-of-the-art approach. Our analysis of the results demonstrates that the dependencies of direct object and the deep-level WordNet hypernyms play pivotal roles for recognizing noun events.