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

Joakim Nivre, Johan Hall, Jens Nilsson · 2006

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.

Read the paper · More papers on PaperTik