A joint model for parsing syntactic and semantic dependencies

Authors:
Xavier Lluís;Lluís Màrquez
Affiliations:
Technical University of Catalonia (UPC);Technical University of Catalonia (UPC)
Venue:
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Year:
2008

Citing 7
Cited 6

Three new probabilistic models for dependency parsing: an exploration

COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms

EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Online large-margin training of dependency parsers

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semantic role labeling via integer linear programming inference

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Projective dependency parsing with perceptron

CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies

CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Combination strategies for semantic role labeling

Journal of Artificial Intelligence Research

The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies

CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
A second-order joint eisner model for syntactic and semantic dependency parsing

CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Multilingual syntactic-semantic dependency parsing with three-stage approximate max-margin linear models

CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Online graph planarisation for synchronous parsing of semantic and syntactic dependencies

IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Statistical bistratal dependency parsing

EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Multilingual joint parsing of syntactic and semantic dependencies with a latent variable model

Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a system that jointly parses syntactic and semantic dependencies, presented at the CoNLL-2008 shared task (Surdeanu et al., 2008). It combines online Peceptron learning (Collins, 2002) with a parsing model based on the Eisner algorithm (Eisner, 1996), extended so as to jointly assign syntactic and semantic labels. Overall results are 78.11 global F1, 85.84 LAS, 70.35 semantic F1. Official results for the shared task (63.29 global F1; 71.95 LAS; 54.52 semantic F1) were significantly lower due to bugs present at submission time.