Trends in Parsing Technology

1. Current Trends in Parsing Technology
Paola Merlo, Harry Bunt, Joakim Nivre

2. Single Malt or Blended? A Study in Multilingual Parser Optimization
Johan Hall, Jens Nilsson, Joakim Nivre

3. A Latent Variable Model for Generative Dependency Parsing
Ivan Titov, James Henderson

4. Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles
Kenji Sagae, Jun-ichi Tsujii

5. Dependency Parsing Using Global Features
Tetsuji Nakagawa

6. Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information
Massimiliano Ciaramita, Giuseppe Attardi

7. Strictly Lexicalised Dependency Parsing
Qin Iris Wang, Dale Schuurmans, Dekang Lin

8. Favor Short Dependencies: Parsing with Soft and Hard Constraints on Dependency Length
Jason Eisner, Noah A. Smith

9. Corrective Dependency Parsing
Keith Hall, Václav Novák

10. Inducing Lexicalised PCFGs with Latent Heads
Detlef Prescher

11. Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy
Gertjan Noord

12. Are Very Large Context-Free Grammars Tractable?
Pierre Boullier, Benoît Sagot

13. Efficiency in Unification-Based N-Best Parsing
Yi Zhang, Stephan Oepen, John Carroll

14. HPSG Parsing with a Supertagger
Takashi Ninomiya, Takuya Matsuzaki, Yusuke Miyao, Yoshimasa Tsuruoka, Jun-ichi Tsujii

15. Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaptation of an HPSG Parser
Tadayoshi Hara, Yusuke Miyao, Jun-ichi Tsujii

16. Semi-supervised Training of a Statistical Parser from Unlabeled Partially-Bracketed Data
Rebecca Watson, Ted Briscoe, John Carroll

Keywords: Linguistics, Computational Linguistics, Language Translation and Linguistics