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We present a system developed for the
CoNLL-2009 Shared Task (Hajic et al., 2009).
We extend the Carreras (2007) parser to
jointly annotate syntactic and semantic dependencies.
This state-of-the-art parser factorizes
the built tree in second-order factors. We
include semantic dependencies in the factors
and extend their score function to combine
syntactic and semantic scores. The parser is
coupled with an on-line averaged perceptron
(Collins, 2002) as the learning method. Our
averaged results for all seven languages are
71.49 macro F1, 79.11 LAS and 63.06 semantic
CitationLluis, X.; Bott, S.; Màrquez, L. A second-order joint Eisner model for syntactic and semantic dependency parsing. A: Conference on Natural Language Learning. "Thirteenth Conference on Computational Natural Language Learning (CoNLL 2009)". 2009, p. 79-84.
A Second-Order Joint Eisner Model for Syntactic and Semantic Dependency Parsing
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