CAMR at SemEval-2016 task 8: An extended transition-based AMR parser

Chuan Wang, Sameer Pradhan, Nianwen Xue, Xiaoman Pan, Heng Ji

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes CAMR, the transitionbased 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.

Original languageEnglish (US)
Title of host publicationSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PublisherAssociation for Computational Linguistics (ACL)
Pages1173-1178
Number of pages6
ISBN (Electronic)9781941643952
DOIs
StatePublished - 2016
Externally publishedYes
Event10th International Workshop on Semantic Evaluation, SemEval 2016 - San Diego, United States
Duration: Jun 16 2016Jun 17 2016

Publication series

NameSemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings

Conference

Conference10th International Workshop on Semantic Evaluation, SemEval 2016
Country/TerritoryUnited States
CitySan Diego
Period6/16/166/17/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Science Applications

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