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

@inproceedings{Wang2015BoostingTA,
  title={Boosting Transition-based AMR Parsing with Refined Actions and Auxiliary Analyzers},
  author={Chuan Wang and Nianwen Xue and Sameer Pradhan},
  booktitle={ACL},
  year={2015}
}
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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