Trends in Parsing Technology

Dependency Parsing, Domain Adaptation, and Deep Parsing


ISBN: 978-90-481-9351-6 (Print) 978-90-481-9352-3 (Online)

Table of contents (16 chapters)

  1. Front Matter

    Pages i-ix

  2. Chapter

    Pages 1-17

    Current Trends in Parsing Technology

  3. Chapter

    Pages 19-33

    Single Malt or Blended? A Study in Multilingual Parser Optimization

  4. Chapter

    Pages 35-55

    A Latent Variable Model for Generative Dependency Parsing

  5. Chapter

    Pages 57-68

    Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles

  6. Chapter

    Pages 69-86

    Dependency Parsing Using Global Features

  7. Chapter

    Pages 87-104

    Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information

  8. Chapter

    Pages 105-120

    Strictly Lexicalised Dependency Parsing

  9. Chapter

    Pages 121-150

    Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length

  10. Chapter

    Pages 151-167

    Corrective Dependency Parsing

  11. Chapter

    Pages 169-182

    Inducing Lexicalised PCFGs with Latent Heads

  12. Chapter

    Pages 183-200

    Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy

  13. Chapter

    Pages 201-222

    Are Very Large Context-Free Grammars Tractable?

  14. Chapter

    Pages 223-241

    Efficiency in Unification-Based N-Best Parsing

  15. Chapter

    Pages 243-256

    HPSG Parsing with a Supertagger

  16. Chapter

    Pages 257-275

    Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaptation of an HPSG Parser

  17. Chapter

    Pages 277-291

    Semi-supervised Training of a Statistical Parser from Unlabeled Partially-Bracketed Data

  18. Back Matter

    Pages 293-297