M. Ballesteros, B. Bohnet, S. Mille, and L. Wanner, Deep-syntactic parsing, Proc. of COLING, 2014.

T. Berg-kirkpatrick, D. Burkett, and D. Klein, An Empirical Investigation of Statistical Significance in NLP, Proc. of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, pp.995-1005, 2012.

M. Daniel and . Bikel, Design of a multi-lingual, parallel-processing statistical parsing engine, Proc. of the second international conference on Human Language Technology Research, pp.178-182, 2002.

A. Björkelund, O. Cetinoglu, R. Farkas, T. Mueller, and W. Seeker, (re)ranking meets morphosyntax: State-of-the-art results from the SPMRL 2013 shared task, Proc. of the Fourth Workshop on Statistical Parsing of Morphologically-Rich Languages, pp.135-145, 2013.

B. Bohnet, Very high accuracy and fast dependency parsing is not a contradiction, Proc. of the 23rd International Conference on Computational Linguistics, pp.89-97, 2010.

A. Cahill, M. Burke, R. O. Donovan, J. Van-genabith, and A. Way, Long-distance dependency resolution in automatically acquired wide-coverage PCFG-based LFG approximations, Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics , ACL '04, 2004.
DOI : 10.3115/1218955.1218996

X. Carreras and L. Màrquez, Introduction to the CoNLL-2005 shared task, Proceedings of the Ninth Conference on Computational Natural Language Learning, CONLL '05, pp.152-164, 2005.
DOI : 10.3115/1706543.1706571

E. Charniak, A maximum-entropy-inspired parser, Proc. of the 1st Annual Meeting of the North American Chapter of the ACL (NAACL), 2000.

J. Chen and O. Rambow, Use of deep linguistic features for the recognition and labeling of semantic arguments Association for Computational Linguis- tics, Proc. of the 2003 conference on Empirical methods in natural language processing, pp.41-48, 2003.

M. Collins, Discriminative training methods for hidden Markov models, Proceedings of the ACL-02 conference on Empirical methods in natural language processing , EMNLP '02, pp.1-8, 2002.
DOI : 10.3115/1118693.1118694

A. Copestake, D. Flickinger, R. Malouf, S. Riehemann, and I. Sag, Translation using minimal recursion semantics, Proc. of the Sixth International Conference on Theoretical and Methodological Issues in Machine Translation, pp.15-32, 1995.

A. Copestake, D. Flickinger, C. Pollard, A. Ivan, and . Sag, Minimal Recursion Semantics: An Introduction, Research on Language and Computation, vol.19, issue.1, pp.281-332, 2005.
DOI : 10.1007/s11168-006-6327-9

D. Das, D. Chen, F. André, N. Martins, . Schneider et al., Frame-Semantic Parsing, Computational Linguistics, vol.19, issue.2, pp.9-56, 2014.
DOI : 10.1145/1390156.1390303

Y. Du, F. Zhang, W. Sun, and X. Wan, Peking: Profiling Syntactic Tree Parsing Techniques for Semantic Graph Parsing, Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pp.459-464, 2014.
DOI : 10.3115/v1/S14-2080

J. Flanigan, S. Thomson, J. Carbonell, C. Dyer, and N. A. Smith, A Discriminative Graph-Based Parser for the Abstract Meaning Representation, Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2014.
DOI : 10.3115/v1/P14-1134

D. Flickinger, Y. Zhang, and V. Kordoni, DeepBank: a dynamically annotated treebank of the wall street journal, Proc. of the Eleventh International Workshop on Treebanks and Linguistic Theories, pp.85-96, 2012.

Y. Freund and R. E. Schapire, Large margin classification using the perceptron algorithm, Proceedings of the eleventh annual conference on Computational learning theory , COLT' 98, pp.277-296, 1999.
DOI : 10.1145/279943.279985

Y. Goldberg, K. Zhao, and L. Huang, Efficient implementation of beam-search incremental parsers, Proc. of the 51st Annual Meeting of the Association for Computational Linguistics (ACL), 2013.

J. Haji?, M. Ciaramita, R. Johansson, D. Kawahara, M. A. Martí et al., The CoNLL-2009 shared task, Proceedings of the Thirteenth Conference on Computational Natural Language Learning Shared Task, CoNLL '09, pp.1-18, 2009.
DOI : 10.3115/1596409.1596411

J. Henderson, P. Merlo, G. Musillo, and I. Titov, A latent variable model of synchronous parsing for syntactic and semantic dependencies, Proceedings of the Twelfth Conference on Computational Natural Language Learning, CoNLL '08, pp.178-182, 2008.
DOI : 10.3115/1596324.1596354

J. Hockenmaier, Data and models for statistical parsing with Combinatory Categorial Grammar, 2003.

L. Huang, S. Fayong, and Y. Guo, Structured perceptron with inexact search, Proc. of HLT-NAACL 2012, pp.142-151, 2012.

A. Ivanova, S. Oepen, L. Øvrelid, and D. Flickinger, Who did what to whom?: A contrastive study of syntacto-semantic dependencies, 2012.

S. Kübler, R. Mcdonald, and J. Nivre, Dependency Parsing, Synthesis Lectures on Human Language Technologies, vol.2, issue.1, 2009.
DOI : 10.2200/S00169ED1V01Y200901HLT002

M. Marcus, B. Santorini, and M. A. Marcinkiewicz, Building a large annotated corpus of English: The Penn Treebank, Computational Linguistics, vol.19, issue.2, pp.313-330, 1993.

F. André, C. Martins, . S. Mariana, and . Almeida, Priberam: A turbo semantic parser with second order features, Proc. of the 8th International Workshop on Semantic Evaluation, pp.471-476, 2014.

R. Mcdonald and J. Nivre, Characterizing the errors of data-driven dependency parsing models, Proc. of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning, 2007.

A. Meyers, R. Reeves, C. Macleod, R. Szekely, V. Zielinska et al., Annotating noun argument structure for nombank, LREC, pp.803-806, 2004.

Y. Miyao and J. Tsujii, Deep linguistic analysis for the accurate identification of predicate-argument relations, Proceedings of the 20th international conference on Computational Linguistics , COLING '04, pp.1392-1397, 2004.
DOI : 10.3115/1220355.1220559

Y. Miyao and J. Tsujii, Probabilistic disambiguation models for wide-coverage HPSG parsing, Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics , ACL '05, pp.83-90, 2005.
DOI : 10.3115/1219840.1219851

URL : http://acl.ldc.upenn.edu/p/p05/p05-1011.pdf

A. Moschitti, D. Pighin, and R. Basili, Tree Kernels for Semantic Role Labeling, Computational Linguistics, vol.19, issue.2, pp.193-224, 2008.
DOI : 10.1162/153244303322533205

J. Nivre and J. Nilsson, Pseudo-projective dependency parsing, Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics , ACL '05, pp.99-106, 2005.
DOI : 10.3115/1219840.1219853

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.67.2372

J. Nivre, An efficient algorithm for projective dependency parsing, Proc. of the 8th International Workshop on Parsing Technologies (IWPT. Cite- seer, 2003.

S. Oepen, M. Kuhlmann, Y. Miyao, D. Zeman, D. Flickinger-hajic et al., SemEval 2014 Task 8: Broad-Coverage Semantic Dependency Parsing, Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pp.63-72, 2014.
DOI : 10.3115/v1/S14-2008

M. Palmer, D. Gildea, and P. Kingsbury, The Proposition Bank: An Annotated Corpus of Semantic Roles, Computational Linguistics, vol.19, issue.2, pp.71-106, 2005.
DOI : 10.1162/089120101317066122

S. Petrov, L. Barrett, R. Thibaux, and D. Klein, Learning accurate, compact, and interpretable tree annotation, Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL , ACL '06, 2006.
DOI : 10.3115/1220175.1220230

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.87.6643

K. Sagae and J. Tsujii, Shift-reduce dependency DAG parsing, Proceedings of the 22nd International Conference on Computational Linguistics, COLING '08, pp.753-760, 2008.
DOI : 10.3115/1599081.1599176

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.156.3938

K. Sagae, Analysis of discourse structure with syntactic dependencies and data-driven shift-reduce parsing, Proceedings of the 11th International Conference on Parsing Technologies, IWPT '09, pp.81-84, 2009.
DOI : 10.3115/1697236.1697253

D. Seddah, Exploring the spinal-stig model for parsing french, Proc. of the Seventh conference on International Language Resources and Evaluation (LREC'10), 2010.
URL : https://hal.archives-ouvertes.fr/inria-00525753

M. Surdeanu, R. Johansson, A. Meyers, L. Màrquez, and J. Nivre, The CoNLL-2008 shared task on joint parsing of syntactic and semantic dependencies, Proceedings of the Twelfth Conference on Computational Natural Language Learning, CoNLL '08, pp.159-177, 2008.
DOI : 10.3115/1596324.1596352

S. Thomson, B. O. Connor, J. Flanigan, D. Bamman, J. Dodge et al., CMU: Arc-Factored, Discriminative Semantic Dependency Parsing, Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), pp.176-180, 2014.
DOI : 10.3115/v1/S14-2027

K. Toutanova, A. Haghighi, D. Christopher, and . Manning, Joint learning improves semantic role labeling, Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics , ACL '05, pp.589-596, 2005.
DOI : 10.3115/1219840.1219913

Y. Tsuruoka, Y. Miyao, and J. Tsujii, Towards efficient probabilistic hpsg parsing: integrating semantic and syntactic preference to guide the parsing, Proc. of the IJCNLP-04 Workshop on Beyond Shallow Analyses. Citeseer, 2004.

É. Villemonte-de-la-clergerie, Exploring beambased shift-reduce dependency parsing with DyALog: Results from the SPMRL 2013 shared task, 4th Workshop on Statistical Parsing of Morphologically Rich Languages (SPMRL'2013), 2013.
URL : https://hal.archives-ouvertes.fr/hal-00879129

E. Szu-ting-yi, M. Loper, and . Palmer, Can semantic roles generalize across genres, HLT- NAACL, pp.548-555, 2007.