Improving data-driven dependency parsing using large-scale LFG grammars

  title={Improving data-driven dependency parsing using large-scale LFG grammars},
  author={Lilja \Ovrelid and Jonas Kuhn and Kathrin Spreyer},
This paper presents experiments which combine a grammar-driven and a datadriven parser. We show how the conversion of LFG output to dependency representation allows for a technique of parser stacking, whereby the output of the grammar-driven parser supplies features for a data-driven dependency parser. We evaluate on English and German and show significant improvements stemming from the proposed dependency structure as well as various other, deep linguistic features derived from the respective… CONTINUE READING
Highly Cited
This paper has 41 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Explore Further: Topics Discussed in This Paper


Publications citing this paper.
Showing 1-10 of 20 extracted citations

Human Language Technology. Challenges for Computer Science and Linguistics

Lecture Notes in Computer Science • 2013
View 10 Excerpts
Highly Influenced


Publications referenced by this paper.
Showing 1-9 of 9 references

Tiger : Linguistic interpretation of a German corpus

Esther Knig, Wolfgang Lezius, Christian Rohrer, George Smith
Research on Language and Computation • 2004

Tiger: Linguistic interpretation of a German

Hans Uszkoreit

Building a large annotated corpus for English : The Penn treebank

Joakim Nivre, Ryan McDonald
Computational Linguistics • 1993

CoNLL 2007 Shared Task on Dependency Parsing

Ronald Kaplan, Richard Crouch, John T. Maxwell, Mark Johnson

Similar Papers

Loading similar papers…