MaltParser is a system for data-driven dependency parsing, which can be used to induce a parsing model from treebank data and to parse new data using an induced model. MaltParser is developed by Johan Hall, Jens Nilsson and Joakim Nivre at Växjö University and Uppsala University, Sweden.

The latest version 1.7.2 of MaltParser is available from the MaltParser download page.

NB: Since version 1.7 the jar-file has been changed to maltparser-1.7.2.jar and is also available via the official Maven repository.


NB: Parsers developed using MaltParser have achieved state-of-the-art accuracy for a number of languages. However, please note that MaltParser is a complex system with many parameters that need to be optimized. Simply using the system "out of the box" with default settings is likely to result in sub-optimal performance and should not be used as a reference in comparative parser evaluations (unless it is explicitly stated that it is a non-optimized version of the system). Please read "A Quick Guide to MaltParser Optimization" to get hints and tips to how you can optimize MaltParser. For many languages and data sets, information about optimized settings can be found in the literature or on the web. Please make the effort to use this information in order to avoid misleading comparisons. You can also try MaltOptimizer, a new tool for automatic MaltParser optimization.