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

نویسندگان

  • Chuan Wang
  • Nianwen Xue
  • Sameer Pradhan
چکیده

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

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تاریخ انتشار 2015