LREC 2006 - Proceedings sorted by papers

Title	MaltParser: A Data-Driven Parser-Generator for Dependency Parsing
Authors	J. Nivre, J. Hall, J. Nilsson
Abstract	We introduce MaltParser, a data-driven parser generator for dependency parsing. Given a treebank in dependency format, MaltParser can be used to induce a parser for the language of the treebank. MaltParser supports several parsing algorithms and learning algorithms, and allows user-defined feature models, consisting of arbitrary combinations of lexical features, part-of-speech features and dependency features. MaltParser is freely available for research and educational purposes and has been evaluated empirically on Swedish, English, Czech, Danish and Bulgarian.
Keywords	parsing, dependency parsing, data-driven methods
Full paper	MaltParser: A Data-Driven Parser-Generator for Dependency Parsing

Title

MaltParser: A Data-Driven Parser-Generator for Dependency Parsing

Authors

J. Nivre, J. Hall, J. Nilsson

Abstract

We introduce MaltParser, a data-driven parser generator for dependency parsing. Given a treebank in dependency format, MaltParser can be used to induce a parser for the language of the treebank. MaltParser supports several parsing algorithms and learning algorithms, and allows user-defined feature models, consisting of arbitrary combinations of lexical features, part-of-speech features and dependency features. MaltParser is freely available for research and educational purposes and has been evaluated empirically on Swedish, English, Czech, Danish and Bulgarian.

Keywords

parsing, dependency parsing, data-driven methods

Full paper

MaltParser: A Data-Driven Parser-Generator for Dependency Parsing