The nature of statistical learning theory
The nature of statistical learning theory
Statistical decision-tree models for parsing
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Dependency treebank for Russian: concept, tools, types of information
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Probabilistic parsing for German using sister-head dependencies
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Deep syntactic processing by combining shallow methods
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Towards history-based grammars: using richer models for probabilistic parsing
HLT '91 Proceedings of the workshop on Speech and Natural Language
Japanese dependency analysis using cascaded chunking
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Learning accurate, compact, and interpretable tree annotation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Morphology and reranking for the statistical parsing of Spanish
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Integrated morphological and syntactic disambiguation for Modern Hebrew
COLING ACL '06 Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Three-dimensional parametrization for parsing morphologically rich languages
IWPT '07 Proceedings of the 10th International Conference on Parsing Technologies
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Converting Russian treebank SynTagRus into Praguian PDT style
MRTECEEL '09 Proceedings of the Workshop on Multilingual Resources, Technologies and Evaluation for Central and Eastern European Languages
Improving Arabic dependency parsing with lexical and inflectional morphological features
SPMRL '10 Proceedings of the NAACL HLT 2010 First Workshop on Statistical Parsing of Morphologically-Rich Languages
Improving Arabic dependency parsing with form-based and functional morphological features
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
TSD'11 Proceedings of the 14th international conference on Text, speech and dialogue
Preliminary experiments in polish dependency parsing
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Getting more from morphology in multilingual dependency parsing
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Dependency parsing of modern standard arabic with lexical and inflectional features
Computational Linguistics
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We present the first results on parsing the SynTagRus treebank of Russian with a data-driven dependency parser, achieving a labeled attachment score of over 82% and an unlabeled attachment score of 89%. A feature analysis shows that high parsing accuracy is crucially dependent on the use of both lexical and morphological features. We conjecture that the latter result can be generalized to richly inflected languages in general, provided that sufficient amounts of training data are available.