Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Inductive Dependency Parsing (Text, Speech and Language Technology)
Inductive Dependency Parsing (Text, Speech and Language Technology)
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
Ensemble models for dependency parsing: cheap and good?
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Very high accuracy and fast dependency parsing is not a contradiction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Getting the most out of transition-based dependency parsing
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
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The fastest parsers currently can parse an average sentence in up to 2.5ms, a considerable improvement, since most of the older accuracy-oriented parsers parse only few sentences per second. It is generally accepted that the complexity of a parsing algorithm is decisive for the performance of a parser. However, we show that the most time consuming part of processing is feature extraction and therefore an algorithm which allows efficient feature extraction can outperform a less complex algorithm which does not. Our system based on quadratic Covington's parsing strategy with efficient feature extraction is able to parse an average English sentence in only 0.8ms without any parallelisation.