Transition-Based Dependency Parsing with Stack Long Short-Term Memory

Conference object, Preprint English OPEN
Dyer, Chris; Ballesteros, Miguel; Ling, W; Matthews, A; Smith, Noah A.;
  • Publisher: Association for Computational Linguistics
  • Related identifiers: doi: 10.3115/v1/p15-1033
  • Subject: Computer Science - Computation and Language | Lingüística computacional | Computer Science - Neural and Evolutionary Computing | Computer Science - Learning | Tractament del llenguatge natural (Informàtica)

We propose a technique for learning representations of parser states in transition-based dependency parsers. Our primary innovation is a new control structure for sequence-to-sequence neural networks---the stack LSTM. Like the conventional stack data structures used in ... View more
  • References (37)
    37 references, page 1 of 4

    [Graves et al.2014] Alex Graves, Greg Wayne, and Ivo Danihelka. 2014. Neural Turing machines. CoRR, abs/1410.5401.

    [Grefenstette et al.2014] Edward Grefenstette, Karl Moritz Hermann, Georgiana Dinu, and Phil Blunsom. 2014. New directions in vector space models of meaning. ACL Tutorial.

    [Henderson2004] James Henderson. 2004. Discriminative training of a neural network discriminative parser. In Proc. ACL.

    [Hermann and Blunsom2013] Karl Moritz Hermann and Phil Blunsom. 2013. The role of syntax in vector space models of compositional semantics. In Proc. ACL.

    [Hochreiter and Schmidhuber1997] Sepp Hochreiter and Ju¨rgen Schmidhuber. 1997. Long short-term memory. Neural Computation, 9(8):1735-1780.

    [Huang and Chiang2008] Liang Huang and David Chiang. 2008. Forest reranking: Discriminative parsing with non-local features. In Proc. ACL.

    [Le and Zuidema2014] Phong Le and Willem Zuidema. 2014. Inside-outside recursive neural network model for dependency parsing. In Proc. EMNLP.

    [Ling et al.2015] Wang Ling, Chris Dyer, Alan Black, and Isabel Trancoso. 2015. Two/too simple adaptations of word2vec for syntax problems. In Proc. NAACL.

    [Martins et al.2010] Andre´ F. T. Martins, Noah A. Smith, Eric P. Xing, Pedro M. Q. Aguiar, and Ma´rio A. T. Figueiredo. 2010. Turboparsers: Dependency parsing by approximate variational inference. In Proc. EMNLP.

    [Mayberry and Miikkulainen1999] Marshall R. Mayberry and Risto Miikkulainen. 1999. SARDSRN: A neural network shift-reduce parser. In Proc. IJCAI.

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