Boosting Transition-based AMR Parsing with Refined Actions and Auxiliary Analyzers

Chuan Wang, Nianwen Xue, Sameer Pradhan

Abstract: We report improved AMR parsing results by adding a new action to a transitionbased AMR parser to infer abstract concepts and by incorporating richer features produced by auxiliary analyzers such as a semantic role labeler and a coreference resolver. We report final AMR parsing results that show an improvement of 7% absolute in F1 score over the best previously reported result. Our parser is available at: https://github.com/ Juicechuan/AMRParsing