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    NIPS
    2008
    154views Information Technology» more  NIPS 2008»
    Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
    13 years 11 months ago
    Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
    Download  www.cs.cmu.edu
    We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
    Shay B. Cohen, Kevin Gimpel, Noah A. Smith
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    NAACL
    2010
    193views Computational Linguistics» more  NAACL 2010»
    Unsupervised Syntactic Alignment with Inversion Transduction Grammars
    13 years 7 months ago
    Unsupervised Syntactic Alignment with Inversion Transduction Grammars
    Download  www.isi.edu
    Syntactic machine translation systems currently use word alignments to infer syntactic correspondences between the source and target languages. Instead, we propose an unsupervised...
    Adam Pauls, Dan Klein, David Chiang, Kevin Knight
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    NAACL
    2007
    142views Computational Linguistics» more  NAACL 2007»
    Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
    13 years 11 months ago
    Semi-Supervised Learning for Semantic Parsing using Support Vector Machines
    Download  www.cs.utexas.edu
    We present a method for utilizing unannotated sentences to improve a semantic parser which maps natural language (NL) sentences into their formal meaning representations (MRs). Gi...
    Rohit J. Kate, Raymond J. Mooney
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    ACL
    2009
    130views Computational Linguistics» more  ACL 2009»
    Unsupervised Learning of Narrative Schemas and their Participants
    13 years 7 months ago
    Unsupervised Learning of Narrative Schemas and their Participants
    Download  cs.stanford.edu
    We describe an unsupervised system for learning narrative schemas, coherent sequences or sets of events (arrested(POLICE,SUSPECT), convicted( JUDGE, SUSPECT)) whose arguments are ...
    Nathanael Chambers, Dan Jurafsky
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    ACL
    2010
    128views Computational Linguistics» more  ACL 2010»
    Profiting from Mark-Up: Hyper-Text Annotations for Guided Parsing
    13 years 8 months ago
    Profiting from Mark-Up: Hyper-Text Annotations for Guided Parsing
    Download  nlp.stanford.edu
    We show how web mark-up can be used to improve unsupervised dependency parsing. Starting from raw bracketings of four common HTML tags (anchors, bold, italics and underlines), we ...
    Valentin I. Spitkovsky, Daniel Jurafsky, Hiyan Als...
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