A statistical parser for Czech
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
CoNLL-X shared task on multilingual dependency parsing
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
Combining czech dependency parsers
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Two-step translation with grammatical post-processing
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
DEPFIX: a system for automatic correction of Czech MT outputs
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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In this paper we present the results of our experiments with modifications of the feature set used in the Czech mutation of the Maximum Spanning Tree parser. First we show how new feature templates improve the parsing accuracy and second we decrease the dimensionality of the feature space to make the parsing process more effective without sacrificing accuracy.