ATT1: Temporal Annotation Using Big Windows and Rich Syntactic and Semantic Features

Abstract In this paper we present the results of experiments comparing (a) rich syntactic and semantic feature sets and (b) big context windows, for the TempEval time expression and event segmentation and classification tasks. We show that it is possible for models using only lexical features to approach the performance of models using rich syntactic and semantic feature sets