Abstract
This paper describes CAMR, the transition-based parser that we use in the SemEval-2016 Meaning Representation Parsing task. The
main contribution of this paper is a description of the additional sources of information that we use as features in the parsing model to
further boost its performance. We start with our existing AMR parser and experiment with three sets of new features: 1) rich named entities, 2) a verbalization list, 3) semantic role labels. We also use the RPI Wikifier to wikify the concepts in the AMR graph. Our parser
achieves a Smatch F-score of 62% on the official blind test set.