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        <title>Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence</title>
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        <namePart type="given">Caio</namePart>
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            <namePart type="given">Martha</namePart>
            <namePart type="family">Palmer</namePart>
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            <namePart type="given">Rebecca</namePart>
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    <abstract>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.</abstract>
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%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

Markdown (Informal)

[Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence](https://aclanthology.org/D17-1172) (Corro et al., EMNLP 2017)

• Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence (Corro et al., EMNLP 2017)

ACL

• Caio Corro, Joseph Le Roux, and Mathieu Lacroix. 2017. Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 1644–1654, Copenhagen, Denmark. Association for Computational Linguistics.