MaltParser: A language-independent system for data-driven dependency parsing - NIVRE, JOAKIM; HALL, JOHAN; NILSSON, JENS; CHANEV, ATANAS; ERYİGİT, GÜLŞEN; KÜBLER, SANDRA; MARINOV, SVETOSLAV; MARSI, ERWIN (Natural language engineering, 2007)
Parsing unrestricted text is useful for many language technology applications but requires parsing methods that are both robust and efficient. MaltParser is a language-independent system for data-driven dependency parsing that can be used to induce a parser for a new language from a treebank sample in a simple yet flexible manner. Experimental evaluation confirms that MaltParser can achieve robust, efficient and accurate parsing for a wide range of languages without language-specific enhancements and with rather limited amounts of training data.