%0 Conference Proceedings %T Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence %A Corro, Caio %A Le Roux, Joseph %A Lacroix, Mathieu %Y Palmer, Martha %Y Hwa, Rebecca %Y Riedel, Sebastian %S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing %D 2017 %8 September %I Association for Computational Linguistics %C Copenhagen, Denmark %F corro-etal-2017-efficient %X We present a new method for the joint task of tagging and non-projective dependency parsing. We demonstrate its usefulness with an application to discontinuous phrase-structure parsing where decoding lexicalized spines and syntactic derivations is performed jointly. The main contributions of this paper are (1) a reduction from joint tagging and non-projective dependency parsing to the Generalized Maximum Spanning Arborescence problem, and (2) a novel decoding algorithm for this problem through Lagrangian relaxation. We evaluate this model and obtain state-of-the-art results despite strong independence assumptions. %R 10.18653/v1/D17-1172 %U https://aclanthology.org/D17-1172 %U https://doi.org/10.18653/v1/D17-1172 %P 1644-1654