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.;
(2015)
  • 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)
    acm: TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGES

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
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