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Semantic role labeling (SRL) is an NLP task involving the assignment of predicate arguments to types, called semantic roles.
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Automatic labeling of semantic roles
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The NomBank project: An interim report
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Unsupervised semantic role labelling
Robert S. Swier and Suzanne Stevenson. 2004 · 2004
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The proposition bank: An annotated corpus of semantic roles
Martha Palmer, Daniel Gildea, and Paul Kingsbury. 2005 · 2005
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The SALSA corpus: a German corpus resource for lexical semantics
Aljoscha Burchardt, Katrin Erk, Anette Frank, Andrea Kowalski, Sebastian Padó, and Manfred Pinkal. 2006 · 2006
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Using semantic roles to improve question answering
Dan Shen and Mirella Lapata. 2007 · 2007
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Semantic role labeling for protein transport predicates
Steven Bethard, Zhiyong Lu, James H. Martin, and Lawrence Hunter. 2008 · 2008
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The New York Times Annotated Corpus LDC2008T19
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The CoNLL-2009 shared task: Syntactic and semantic dependencies in multiple languages
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Cross-lingual annotation projection for semantic roles
Sebastian Padó and Mirella Lapata. 2009 · 2009
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Semlink: Linking propbank, verbnet and framenet
Martha Palmer. 2009 · 2009
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Unsupervised induction of semantic roles
Joel Lang and Mirella Lapata. 2010 · 2010
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A latent Dirichlet allocation method for selectional preferences
Alan Ritter, Mausam, and Oren Etzioni. 2010 · 2010
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Unsupervised semantic role induction via split-merge clustering
Joel Lang and Mirella Lapata. 2011 · 2011
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Scaling up automatic cross-lingual semantic role annotation
Lonneke van der Plas, Paola Merlo, and James Henderson. 2011 · 2011
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Data point selection for cross-language adaptation of dependency parsers
Anders Søgaard. 2011 · 2011
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Collective nominal semantic role labeling for tweets
Xiaohua Liu, Zhongyang Fu, Xiangyang Zhou, Furu Wei, and Ming Zhou. 2012 · 2012
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A Bayesian approach to unsupervised semantic role induction
Ivan Titov and Alexandre Klementiev. 2012 · 2012
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Robust morphological tagging with word representations
Thomas Müller and Hinrich Schuetze. 2015 · 2015
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Unsupervised induction of semantic roles within a reconstruction-error minimization framework
Ivan Titov and Ehsan Khoddam. 2015 · 2015
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Order matters: Sequence to sequence for sets
Oriol Vinyals, Samy Bengio, and Manjunath Kudlur. 2015 · 2015
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Distributed representations for unsupervised semantic role labeling
Kristian Woodsend and Mirella Lapata. 2015 · 2015
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Deep semantic role labeling: What works and what’s next
Luheng He, Kenton Lee, Mike Lewis, and Luke Zettlemoyer. 2017 · 2017
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Categorical reparameterization with gumbel-softmax
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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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Cross-lingual transfer of semantic role labeling models
Mikhail Kozhevnikov and Ivan Titov. 2013 · 2013
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Modeling semantic relations expressed by prepositions
Vivek Srikumar and Dan Roth. 2013 · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2014 · 2014
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Semi-supervised learning with deep generative models
Durk P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling. 2014 · 2014
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Eric Jang, Shixiang Gu, and Ben Poole. 2017 · 2017
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The concrete distribution: A continuous relaxation of discrete random variables
Chris J Maddison, Andriy Mnih, and Yee Whye Teh. 2017 · 2017
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Encoding sentences with graph convolutional networks for semantic role labeling
Diego Marcheggiani and Ivan Titov. 2017 · 2017
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Variational autoencoder for semi-supervised text classification
Weidi Xu, Haoze Sun, Chao Deng, and Ying Tan. 2017 · 2017
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Multi-space variational encoder-decoders for semi-supervised labeled sequence transduction
Chunting Zhou and Graham Neubig. 2017 · 2017
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Variational sequential labelers for semi-supervised learning
Mingda Chen, Qingming Tang, Karen Livescu, and Kevin Gimpel. 2018 · 2018
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AllenNLP: A deep semantic natural language processing platform
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer. 2018 · 2018
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Exploiting semantics in neural machine translation with graph convolutional networks
Diego Marcheggiani, Joost Bastings, and Ivan Titov. 2018 · 2018
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Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Cross-lingual transfer of semantic roles: From raw text to semantic roles
Maryam Aminian, Mohammad Sadegh Rasooli, and Mona Diab. 2019 · 2019
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