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        <title>Better Transition-Based AMR Parsing with a Refined Search Space</title>
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        <namePart type="given">Zhijiang</namePart>
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            <namePart type="given">Ellen</namePart>
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            <namePart type="given">David</namePart>
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            <namePart type="given">Jun’ichi</namePart>
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    <abstract>This paper introduces a simple yet effective transition-based system for Abstract Meaning Representation (AMR) parsing. We argue that a well-defined search space involved in a transition system is crucial for building an effective parser. We propose to conduct the search in a refined search space based on a new compact AMR graph and an improved oracle. Our end-to-end parser achieves the state-of-the-art performance on various datasets with minimal additional information.</abstract>
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    <identifier type="doi">10.18653/v1/D18-1198</identifier>
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%0 Conference Proceedings
%T Better Transition-Based AMR Parsing with a Refined Search Space
%A Guo, Zhijiang
%A Lu, Wei
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F guo-lu-2018-better
%X This paper introduces a simple yet effective transition-based system for Abstract Meaning Representation (AMR) parsing. We argue that a well-defined search space involved in a transition system is crucial for building an effective parser. We propose to conduct the search in a refined search space based on a new compact AMR graph and an improved oracle. Our end-to-end parser achieves the state-of-the-art performance on various datasets with minimal additional information.
%R 10.18653/v1/D18-1198
%U https://aclanthology.org/D18-1198
%U https://doi.org/10.18653/v1/D18-1198
%P 1712-1722

Markdown (Informal)

[Better Transition-Based AMR Parsing with a Refined Search Space](https://aclanthology.org/D18-1198) (Guo & Lu, EMNLP 2018)

• Better Transition-Based AMR Parsing with a Refined Search Space (Guo & Lu, EMNLP 2018)

ACL

• Zhijiang Guo and Wei Lu. 2018. Better Transition-Based AMR Parsing with a Refined Search Space. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 1712–1722, Brussels, Belgium. Association for Computational Linguistics.