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We unify different broad-coverage semantic parsing tasks under a transduction paradigm, and propose an attention-based neural framework that incrementally builds a meaning representation via a sequence of semantic relations.
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Long short-term memory
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The Syntactic Process
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Deep linguistic analysis for the accurate identification of predicate-argument relations
Yusuke Miyao and Jun’ichi Tsujii. 2004 · 2004
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Incrementality in deterministic dependency parsing
Joakim Nivre. 2004 · 2004
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Discriminant-based MRS banking
Stephan Oepen and Jan Tore Lønning. 2006 · 2006
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Wide-coverage semantic analysis with Boxer
Johan Bos. 2008 · 2008
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Dynamic programming for linear-time incremental parsing
Liang Huang and Kenji Sagae. 2010 · 2010
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DeepBank: A Dynamically Annotated Treebank of the Wall Street
Dan Flickinger, Valia Kordoni, and Zhang Yi. 2012 · 2012
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Announcing Prague Czech-English dependency treebank 2.0
Jan Hajič, Eva Hajičová, Jarmila Panevová, Petr Sgall, Ondřej Bojar, Silvie Cinková, Eva Fučíková, Marie Mikulová, Petr Pajas, Jan Popelka, Jiří Semecký, Jana Šindlerová, Jan Štěpánek, Josef Toman, Zdeňka Urešová, and Zdeněk Žabokrtský. 2012 · 2012
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Universal conceptual cognitive annotation (ucca)
Omri Abend and Ari Rappoport. 2013 · 2013
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Abstract meaning representation for sembanking
Laura Banarescu, Claire Bonial, Shu Cai, Madalina Georgescu, Kira Griffitt, Ulf Hermjakob, Kevin Knight, Philipp Koehn, Martha Palmer, and Nathan Schneider. 2013 · 2013
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Smatch: an evaluation metric for semantic feature structures
Shu Cai and Kevin Knight. 2013 · 2013
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Transition-based dependency parsing with selectional branching
Jinho D. Choi and Andrew McCallum. 2013 · 2013
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Improving efficiency and accuracy in multilingual entity extraction
Joachim Daiber, Max Jakob, Chris Hokamp, and Pablo N. Mendes. 2013 · 2013
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A discriminative graph-based parser for the abstract meaning representation
Jeffrey Flanigan, Sam Thomson, Jaime Carbonell, Chris Dyer, and Noah A. Smith. 2014 · 2014
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SemEval 2014 task 8: Broad-coverage semantic dependency parsing
Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Dan Flickinger, Jan Hajic, Angelina Ivanova, and Yi Zhang. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Lisbon: Evaluating TurboSemanticParser on multiple languages and out-of-domain data
Mariana S. C. Almeida and André F. T. Martins. 2015 · 2015
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Broad-coverage ccg semantic parsing with amr
Yoav Artzi, Kenton Lee, and Luke Zettlemoyer. 2015 · 2015
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Peking: Building semantic dependency graphs with a hybrid parser
Yantao Du, Fan Zhang, Xun Zhang, Weiwei Sun, and Xiaojun Wan. 2015 · 2015
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Transition-based dependency parsing with stack long short-term memory
Chris Dyer, Miguel Ballesteros, Wang Ling, Austin Matthews, and Noah A. Smith. 2015 · 2015
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SemEval 2015 task 18: Broad-coverage semantic dependency parsing
Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Silvie Cinkova, Dan Flickinger, Jan Hajic, and Zdenka Uresova. 2015 · 2015
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A synchronous hyperedge replacement grammar based approach for AMR parsing
Xiaochang Peng, Linfeng Song, and Daniel Gildea. 2015 · 2015
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Parsing english into abstract meaning representation using syntax-based machine translation
Michael Pust, Ulf Hermjakob, Kevin Knight, Daniel Marcu, and Jonathan May. 2015 · 2015
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Neural amr: Sequence-to-sequence models for parsing and generation
Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, and Luke Zettlemoyer. 2017 · 2017
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SemEval-2017 task 9: Abstract meaning representation parsing and generation
Jonathan May and Jay Priyadarshi. 2017 · 2017
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Neural semantic parsing by character-based translation: Experiments with abstract meaning representations
Rik van Noord and Johan Bos. 2017 · 2017
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Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Getting the most out of amr parsing
Chuan Wang and Nianwen Xue. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
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Chuan Wang, Nianwen Xue, and Sameer Pradhan. 2015 · 2015
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RIGA at SemEval-2016 task 8: Impact of Smatch extensions and character-level neural translation on AMR parsing accuracy
Guntis Barzdins and Didzis Gosko. 2016 · 2016
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Deep biaffine attention for neural dependency parsing
Timothy Dozat and Christopher D Manning. 2016 · 2016
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Cmu at semeval-2016 task 8: Graph-based amr parsing with infinite ramp loss
Jeffrey Flanigan, Chris Dyer, Noah A. Smith, and Jaime Carbonell. 2016 · 2016
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Ucl+sheffield at semeval-2016 task 8: Imitation learning for amr parsing with an alpha-bound
James Goodman, Andreas Vlachos, and Jason Naradowsky. 2016 · 2016
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Character-aware neural language models
Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. 2016 · 2016
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SemEval-2016 task 8: Meaning representation parsing
Jonathan May. 2016 · 2016
Cited alongside, same era.
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Simpler but more accurate semantic dependency parsing
Timothy Dozat and Christopher D. Manning. 2018 · 2018
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Better transition-based amr parsing with a refined search space
Zhijiang Guo and Wei Lu. 2018 · 2018
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Multitask parsing across semantic representations
Daniel Hershcovich, Omri Abend, and Ari Rappoport. 2018 · 2018
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Amr parsing as graph prediction with latent alignment
Chunchuan Lyu and Ivan Titov. 2018 · 2018
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Learning joint semantic parsers from disjoint data
Hao Peng, Sam Thomson, Swabha Swayamdipta, and Noah A. Smith. 2018 · 2018
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A neural transition-based approach for semantic dependency graph parsing
Yuxuan Wang, Wanxiang Che, Jiang Guo, and Ting Liu. 2018 · 2018
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Cross-lingual decompositional semantic parsing
Sheng Zhang, Xutai Ma, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. 2018 · 2018
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Core Semantic First: A Top-down Approach for AMR Parsing
Deng Cai and Wai Lam. 2019 · 2019
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SemEval-2019 task 1: Cross-lingual semantic parsing with UCCA
Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, Ari Rappoport, and Omri Abend. 2019 · 2019
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HLT@SUDA at SemEval-2019 task 1: UCCA graph parsing as constituent tree parsing
Wei Jiang, Zhenghua Li, Yu Zhang, and Min Zhang. 2019 · 2019
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Compositional semantic parsing across graphbanks
Matthias Lindemann, Jonas Groschwitz, and Alexander Koller. 2019 · 2019
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Rewarding Smatch: Transition-based AMR parsing with reinforcement learning
Tahira Naseem, Abhishek Shah, Hui Wan, Radu Florian, Salim Roukos, and Miguel Ballesteros. 2019 · 2019
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AMR parsing as sequence-to-graph transduction
Sheng Zhang, Xutai Ma, Kevin Duh, and Benjamin Van Durme. 2019 · 2019
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Deep multitask learning for semantic dependency parsing
Hao Peng, Sam Thomson, and Noah A. Smith. 2017a · 2048
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