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We present a deep neural architecture that parses sentences into three semantic dependency graph formalisms.
The expression of a tensor or a polyadic as a sum of products
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John Blitzer, Ryan McDonald, and Fernando Pereira. 2006 · 2006
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Yusuke Miyao. 2006 · 2006
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SemEval’07 task 19: Frame semantic structure extraction
Collin Baker, Michael Ellsworth, and Katrin Erk. 2007 · 2007
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Experiments with a higher-order projective dependency parser
Xavier Carreras. 2007 · 2007
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Hal Daumé III. 2007 · 2007
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Andriy Mnih and Geoffrey Hinton. 2007 · 2007
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Ronan Collobert and Jason Weston. 2008 · 2008
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Dependency parsing by belief propagation
David Smith and Jason Eisner. 2008 · 2008
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The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies
Mihai Surdeanu, Richard Johansson, Adam Meyers, Lluís Màrquez, and Joakim Nivre. 2008 · 2008
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Tamara G. Kolda and Brett W. Bader. 2009 · 2009
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Concise integer linear programming formulations for dependency parsing
André F. T. Martins, Noah Smith, and Eric Xing. 2009 · 2009
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Dual decomposition for parsing with non-projective head automata
Terry Koo, Alexander M. Rush, Michael Collins, Tommi Jaakkola, and David Sontag. 2010 · 2010
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André F. T. Martins, Noah A. Smith, Pedro M. Q. Aguiar, and Mário A. T. Figueiredo. 2011 · 2011
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Daniel Flickinger, Yi Zhang, and Valia Kordoni. 2012 · 2012
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Alex Graves. 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
Greed is good if randomized: New inference for dependency parsing
Yuan Zhang, Tao Lei, Regina Barzilay, and Tommi S. Jaakkola. 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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Natural language understanding with distributed representation
Kyunghyun Cho. 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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Semantic role labeling with neural network factors
Nicholas FitzGerald, Oscar Täckström, Kuzman Ganchev, and Dipanjan Das. 2015 · 2015
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Generating sequences with recurrent neural networks
Alex Graves. 2013 · 2013
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Multi-lingual joint parsing of syntactic and semantic dependencies with a latent variable model
James Henderson, Paola Merlo, Ivan Titov, and Gabriele Musillo. 2013 · 2013
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Training parsers on incompatible treebanks
Richard Johansson. 2013 · 2013
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Scaling semantic parsers with on-the-fly ontology matching
Tom Kwiatkowski, Eunsol Choi, Yoav Artzi, and Luke S. Zettlemoyer. 2013 · 2013
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Joint arc-factored parsing of syntactic and semantic dependencies
Xavier Lluís, Xavier Carreras, and Lluís Màrquez. 2013 · 2013
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Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. 2015 · 2015
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Turku: Semantic dependency parsing as a sequence classification
Jenna Kanerva, Juhani Luotolahti, and Filip Ginter. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Frame-semantic role labeling with heterogeneous annotations
Meghana Kshirsagar, Sam Thomson, Nathan Schneider, Jaime Carbonell, Noah A. Smith, and Chris Dyer. 2015 · 2015
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SemEval 2015 task 18: Broad-coverage semantic dependency parsing
Stephan Oepen, Marco Kuhlmann, Yusuke Miyao, Daniel Zeman, Silvie Cinková, Dan Flickinger, Jan Hajič, and Zdeňka Urešová. 2015 · 2015
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An effective neural network model for graph-based dependency parsing
Wenzhe Pei, Tao Ge, and Baobao Chang. 2015 · 2015
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Template kernels for dependency parsing
Hillel Taub-Tabib, Yoav Goldberg, and Amir Globerson. 2015 · 2015
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Many languages, one parser
Waleed Ammar, George Mulcaire, Miguel Ballesteros, Chris Dyer, and Noah Smith. 2016 · 2016
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Jiang Guo, Wanxiang Che, Haifeng Wang, and Ting Liu. 2016 · 2016
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Frustratingly easy neural domain adaptation
Young-Bum Kim, Karl Stratos, and Ruhi Sarikaya. 2016 · 2016
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Simple and accurate dependency parsing using bidirectional LSTM feature representations
Eliyahu Kiperwasser and Yoav Goldberg. 2016 · 2016
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Distilling an ensemble of greedy dependency parsers into one MST parser
Adhiguna Kuncoro, Miguel Ballesteros, Lingpeng Kong, Chris Dyer, and Noah A. Smith. 2016 · 2016
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Neural probabilistic model for non-projective MST parsing
Xuezhe Ma and Eduard Hovy. 2016 · 2016
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Deep multi-task learning with low level tasks supervised at lower layers
Anders Søgaard and Yoav Goldberg. 2016 · 2016
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Greedy, joint syntactic-semantic parsing with stack LSTMs
Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer, and Noah A. Smith. 2016 · 2016
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Graph-based dependency parsing with bidirectional LSTM
Wenhui Wang and Baobao Chang. 2016 · 2016
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Transition-based parsing for deep dependency structures
Xun Zhang, Yantao Du, Weiwei Sun, and Xiaojun Wan. 2016 · 2016
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Stack-propagation: Improved representation learning for syntax
Yuan Zhang and David Weiss. 2016 · 2016
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Deep biaffine attention for neural dependency parsing
Timothy Dozat and Christopher D. Manning. 2017 · 2017
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