Pseudo-projective dependency parsing
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Computational Linguistics
Algorithms for deterministic incremental dependency parsing
Computational Linguistics
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Predictive text entry using syntax and semantics
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Optimistic backtracking: a backtracking overlay for deterministic incremental parsing
HLT-SS '11 Proceedings of the ACL 2011 Student Session
Parse correction with specialized models for difficult attachment types
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
The best of both worlds: a graph-based completion model for transition-based parsers
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Divisible transition systems and multiplanar dependency parsing
Computational Linguistics
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In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre's parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM. Features take into account the static context as well as relations dynamically built during parsing. We experimented two main additions to our implementation of Nivre's parser: N-best search and bidirectional parsing. We trained the parser in both left-right and right-left directions and we combined the results. To construct a single-head, rooted, and cycle-free tree, we applied the Chu-Liu/Edmonds optimization algorithm. We ran the same algorithm with the same parameters on all the languages.