Efficient Discontinuous Phrase-Structure Parsing via the Generalized Maximum Spanning Arborescence

2017-09-01 · EMNLP 2017 9 · Caio Corro, Joseph Le Roux, Mathieu Lacroix

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.

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Dependency Parsing

Hybrid Grammars for Parsing of Discontinuous Phrase Structures and Non-Projective Dependency Structures

2017-09-01 · CL 2017 9 · Kilian Gebhardt, Mark-Jan Nederhof, Heiko Vogler

We explore the concept of hybrid grammars, which formalize and generalize a range of existing frameworks for dealing with discontinuous syntactic structures. Covered are both discontinuous phrase structures and non-proje…

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This article introduces a novel transition system for discontinuous lexicalized constituent parsing called SR-GAP. It is an extension of the shift-reduce algorithm with an additional gap transition. Evaluation on two Ger…

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Dependency Parsing Machine Translation Translation

Unsupervised Discontinuous Constituency Parsing with Mildly Context-Sensitive Grammars

2022-12-18 · Songlin Yang, Roger P. Levy, Yoon Kim

We study grammar induction with mildly context-sensitive grammars for unsupervised discontinuous parsing. Using the probabilistic linear context-free rewriting system (LCFRS) formalism, our approach fixes the rule struct…

Constituency Parsing parameter estimation Tensor Decomposition

Parsing as Reduction

2015-02-27 · IJCNLP 2015 7 · Daniel Fernández-González, André F. T. Martins

We reduce phrase-representation parsing to dependency parsing. Our reduction is grounded on a new intermediate representation, "head-ordered dependency trees", shown to be isomorphic to constituent trees. By encoding ord…