Maximum spanning tree algorithm for non-projective labeled dependency parsing

Authors:
Nobuyuki Shimizu
Affiliations:
State University of New York at Albany, Albany, NY
Venue:
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Year:
2006

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Abstract

Following (McDonald et al., 2005), we present an application of a maximum spanning tree algorithm for a directed graph to non-projective labeled dependency parsing. Using a variant of the voted perceptron (Collins, 2002; Collins and Roark, 2004; Crammer and Singer, 2003), we discriminatively trained our parser in an on-line fashion. After just one epoch of training, we were generally able to attain average results in the CoNLL 2006 Shared Task.