Labeled pseudo-projective dependency parsing with support vector machines

Joakim Nivre; Johan Hall; Jens Nilsson; Gülşen Eryiǧit; Svetoslav Marinov

Labeled pseudo-projective dependency parsing with support vector machines

Joakim Nivre^*, Johan Hall, Jens Nilsson, Gülşen Eryiǧit, Svetoslav Marinov

^*Corresponding author for this work

Department of Artificial Intelligence and Data Engineering

Research output: Contribution to conference › Paper › peer-review

155 Citations (Scopus)

Abstract

We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.

Original language	English
Publication status	Published - 2006
Event	10th Conference on Computational Natural Language Learning, CoNLL-X - New York, NY, United States Duration: 8 Jun 2006 → 9 Jun 2006

Conference

Conference	10th Conference on Computational Natural Language Learning, CoNLL-X
Country/Territory	United States
City	New York, NY
Period	8/06/06 → 9/06/06

Cite this

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title = "Labeled pseudo-projective dependency parsing with support vector machines",

abstract = "We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.",

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T1 - Labeled pseudo-projective dependency parsing with support vector machines

AU - Nivre, Joakim

AU - Hall, Johan

AU - Nilsson, Jens

AU - Eryiǧit, Gülşen

AU - Marinov, Svetoslav

PY - 2006

Y1 - 2006

N2 - We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.

AB - We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.

UR - http://www.scopus.com/inward/record.url?scp=84862271629&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84862271629

T2 - 10th Conference on Computational Natural Language Learning, CoNLL-X

Y2 - 8 June 2006 through 9 June 2006

ER -

Labeled pseudo-projective dependency parsing with support vector machines

Abstract

Conference

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