A. W. , On the Evolution of Complexity. Working papers, 1993.

B. Y. , Practical recommendations for gradient-based training of deep architectures, 2012.

B. Ayache, C. Bechet, F. , D. A. Kuhn-a, F. Lefèvre et al., Results of the french evalda-media evaluation campaign for literal understanding, LREC, pp.2054-2059, 2006.
URL : https://hal.archives-ouvertes.fr/hal-01160167

C. J. Nichols-e, Named entity recognition with bidirectional lstm-cnns, 2015.

C. K. Van-merrienboer-b, Ç. Gülçehre, F. Bougares, H. &. Schwenk, and . Bengio-y, , 2014.

, Learning phrase representations using RNN encoder-decoder for statistical machine translation

C. M. , Three generative, lexicalised models for statistical parsing, Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics, ACL '98, pp.16-23, 1997.

C. R. , W. J. Bottou, L. , and K. M. Kavukcuoglu-k.-&-kuksa-p, , 2011.

, Natural language processing (almost) from scratch, J. Mach. Learn. Res, vol.12, pp.2493-2537

. A. Dahl-d, M. Bates, M. Brown, . Fisher-w, . Hunicke-smith-k et al., Expanding the scope of the atis task : The atis-3 corpus, Proceedings of the Workshop on Human Language Technology, HLT '94, pp.43-48, 1994.

D. E. Mori, R. Bechet, F. Hakkani-tur-d, M. Mctear, and . Riccardi-g.-&-tur-g, Spoken language understanding : A survey, IEEE Signal Processing Magazine, vol.25, pp.50-58, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01314884

D. , Models cascade for tree-structured named entity detection, Proceedings of International Joint Conference of Natural Language Processing (IJCNLP), 2011.

D. , Tree representations in probabilistic models for extended named entity detection, European Chapter of the Association for Computational Linguistics (EACL), pp.174-184, 2012.

D. M. Vukotic-v.-&-raymond-c, Label-dependency coding in Simple Recurrent Networks for Spoken Language Understanding, Interspeech, 2017.

D. Y. Dinarelli-m.-&-tellier-i, Label-dependencies aware recurrent neural networks, Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing, 2017.

G. C. Rosset, S. Zweigenbaum, P. Fort-k, and . Galibert-o.-&-quintard-l, Proposal for an extension or traditional named entities : From guidelines to evaluation, an overview, Proceedings of the Linguistic Annotation Workshop, 2011.

H. S. Schmidhuber and J. , Long short-term memory, Neural Comput, vol.9, issue.8, pp.1735-1780, 1997.

H. Z. Xu-w.-&-yu-k, Bidirectional lstm-crf models for sequence tagging, 2015.

L. J. Mccallum-a and . Pereira-f, Conditional random fields : Probabilistic models for segmenting and labeling sequence data, Proceedings of the Eighteenth International Conference on Machine Learning (ICML), pp.282-289, 2001.

L. G. Ballesteros, M. Subramanian-s, . &. Kawakami-k, and . Dyer-c, Neural architectures for named entity recognition, 2016.

L. T. and C. O. Yvon-f, Practical very large scale CRFs, Proceedings the, p.48, 2010.

, Annual Meeting of the Association for Computational Linguistics (ACL), pp.504-513

M. X. Hovy-e, End-to-end sequence labeling via bi-directional lstm-cnns-crf, Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016.

N. , Improving Machine Learning Approcahes to Corefrence Resolution, Proceedings of ACL'02, pp.104-111, 2002.

P. A. Gross-s, C. S. Chanan, G. , Y. E. Devito-z, L. Z. Desmaison et al., Automatic differentiation in pytorch, NIPS-W, 2017.

S. W. Ng and H. T. Lim-d, A Machine Learning Approach to Coreference Resolution of Noun Phrases, Computational Linguistics, vol.27, issue.4, pp.521-544, 2001.

S. I. Vinyals-o and . V. Le-q, Sequence to sequence learning with neural networks, Proceedings of the 27th International Conference on Neural Information Processing Systems, vol.2, pp.3104-3112, 2014.

V. V. and R. C. Gravier-g, Is it time to switch to word embedding and recurrent neural networks for spoken language understanding? In InterSpeech, 2015.

V. V. and R. C. Gravier-g, A step beyond local observations with a dialog aware bidirectional GRU network for Spoken Language Understanding, Interspeech, 2016.

W. C. , Network of recurrent neural networks, 2017.

W. P. , Backpropagation through time : what does it do and how to do it, Proceedings of IEEE, vol.78, pp.1550-1560, 1990.