We describe our experiments using the DeSR parser in the multilingual and do- main adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incre- mental deterministic Shift/Reduce parsing algorithm, using specific rules to handle non-projective dependencies. For the multi- lingual track we adopted a second order averaged perceptron and performed feature selection to tune a feature model for each language. For the domain adaptation track we applied a tree revision method which learns how to correct the mistakes made by the base parser on the adaptation domain.

Multilingual Dependency Parsing and Domain Adaptation using DeSR

ATTARDI, GIUSEPPE;SIMI, MARIA
2007

Abstract

We describe our experiments using the DeSR parser in the multilingual and do- main adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incre- mental deterministic Shift/Reduce parsing algorithm, using specific rules to handle non-projective dependencies. For the multi- lingual track we adopted a second order averaged perceptron and performed feature selection to tune a feature model for each language. For the domain adaptation track we applied a tree revision method which learns how to correct the mistakes made by the base parser on the adaptation domain.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/187775
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