Multilingual Dependency Parsing and Domain Adaptation using DeSR
Year: 2007
Type: conference-paper
Abstract: We describe our experiments using the DeSR parser in the multilingual and domain adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incremental deterministic Shift/Reduce parsing algorithm, using specific rules to handle non-projective dependencies. For the multilingual 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 ethod which learns how to correct the mistakes made by the base parser on the adaptation domain.
Authors: Giuseppe Attardi, Felice Dell’Orletta⋄, Maria Simi, Atanas Chanev, Massimiliano Ciaramita
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W59145111