Multilingual discriminative shift reduce phrase structure parsing for the SPMRL 2014 shared task
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[1] Michael Collins,et al. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms , 2002, EMNLP.
[2] Nizar Habash,et al. Overview of the SPMRL 2013 Shared Task: A Cross-Framework Evaluation of Parsing Morphologically Rich Languages , 2013, SPMRL@EMNLP.
[3] Percy Liang,et al. Semi-Supervised Learning for Natural Language , 2005 .
[4] Dan Klein,et al. Learning Accurate, Compact, and Interpretable Tree Annotation , 2006, ACL.
[5] Alon Lavie,et al. A Best-First Probabilistic Shift-Reduce Parser , 2006, ACL.
[6] Yannick Versley. Incorporating Semi-supervised Features into Discontinuous Easy-First Constituent Parsing , 2014, ArXiv.
[7] Marie Candito,et al. Expériences d’analyse syntaxique statistique du français , 2008, JEPTALNRECITAL.
[8] Michael Collins,et al. Head-Driven Statistical Models for Natural Language Parsing , 2003, CL.
[9] Yannick Versley,et al. Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither , 2010, SPMRL@NAACL-HLT.
[10] Eugene Charniak,et al. A Maximum-Entropy-Inspired Parser , 2000, ANLP.
[11] Benoît Crabbé,et al. An LR-inspired generalized lexicalized phrase structure parser , 2014, COLING.
[12] Marie Candito,et al. Parsing Word Clusters , 2010, SPMRL@NAACL-HLT.
[13] Yue Zhang,et al. Fast and Accurate Shift-Reduce Constituent Parsing , 2013, ACL.
[14] Wolfgang Seeker,et al. (Re)ranking Meets Morphosyntax: State-of-the-art Results from the SPMRL 2013 Shared Task , 2013, SPMRL@EMNLP.
[15] Marie Candito,et al. A word clustering approach to domain adaptation: Robust parsing of source and target domains , 2014, J. Log. Comput..
[16] Marie Candito,et al. Improving generative statistical parsing with semi-supervised word clustering , 2009, IWPT.
[17] Reut Tsarfaty,et al. Parsing Morphologically Rich Languages: Introduction to the Special Issue , 2013, Computational Linguistics.
[18] Richárd Farkas,et al. Special Techniques for Constituent Parsing of Morphologically Rich Languages , 2014, EACL.
[19] Robert L. Mercer,et al. Class-Based n-gram Models of Natural Language , 1992, CL.
[20] Miguel Ballesteros,et al. Effective Morphological Feature Selection with MaltOptimizer at the SPMRL 2013 Shared Task , 2013, SPMRL@EMNLP.
[21] Josef van Genabith,et al. Morphological Features for Parsing Morphologically-rich Languages: A Case of Arabic , 2011, SPMRL@IWPT.
[22] Veronika Vincze,et al. An Empirical Evaluation of Automatic Conversion from Constituency to Dependency in Hungarian , 2014, COLING.
[23] Mary P. Harper,et al. Feature-Rich Log-Linear Lexical Model for Latent Variable PCFG Grammars , 2011, IJCNLP.
[24] Dan Klein,et al. Less Grammar, More Features , 2014, ACL.