@inproceedings{nivre-etal-2006-maltparser,
title = "{M}alt{P}arser: A Data-Driven Parser-Generator for Dependency Parsing",
author = "Nivre, Joakim and
Hall, Johan and
Nilsson, Jens",
booktitle = "Proceedings of the Fifth International Conference on Language Resources and Evaluation ({LREC}{'}06)",
month = may,
year = "2006",
address = "Genoa, Italy",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2006/pdf/162_pdf.pdf",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T MaltParser: A Data-Driven Parser-Generator for Dependency Parsing
%A Nivre, Joakim
%A Hall, Johan
%A Nilsson, Jens
%S Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC’06)
%D 2006
%8 may
%I European Language Resources Association (ELRA)
%C Genoa, Italy
%F nivre-etal-2006-maltparser
%X 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.
%U http://www.lrec-conf.org/proceedings/lrec2006/pdf/162_pdf.pdf
Markdown (Informal)
[MaltParser: A Data-Driven Parser-Generator for Dependency Parsing](http://www.lrec-conf.org/proceedings/lrec2006/pdf/162_pdf.pdf) (Nivre et al., LREC 2006)
ACL