Dependency parsing with reference to Slovene, Spanish and Swedish

Authors:
Simon Corston-Oliver;Anthony Aue
Affiliations:
Microsoft Research, One Microsoft Way, Redmond, WA;Microsoft Research, One Microsoft Way, Redmond, WA
Venue:
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Year:
2006

Citing 6
Cited 2

A maximum entropy approach to natural language processing

Computational Linguistics
Three new probabilistic models for dependency parsing: an exploration

COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Online large-margin training of dependency parsers

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Multilingual dependency parsing using Bayes Point Machines

HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
CoNLL-X shared task on multilingual dependency parsing

CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Online Bayes point machines

PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining

Dependency parsing of turkish

Computational Linguistics
Predictive text entry using syntax and semantics

IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe a parser used in the CoNLL 2006 Shared Task, "Multingual Dependency Parsing." The parser first identifies syntactic dependencies and then labels those dependencies using a maximum entropy classifier. We consider the impact of feature engineering and the choice of machine learning algorithm, with particular focus on Slovene, Spanish and Swedish.