LR Parsing for LCFRS

Kallmeyer, Laura; Maier, Wolfgang

doi:10.3390/a9030058

Cited by 4 publications

(1 citation statement)

References 31 publications

(35 reference statements)

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“…From an empirical point of view, a transition system that overgenerates is necessary for robustness, and is desirable for fast approximate linear-time inference. However, from a formal point of view, the relationship of the SR-GAP transition system with automata explicitly designed for LCFRS parsing (Villemonte de La Clergerie, 2002;Kallmeyer and Maier, 2015) requires further investigations.…”

Section: Completeness and Soundnessmentioning

confidence: 99%

Incremental Discontinuous Phrase Structure Parsing with the GAP Transition

Coavoux¹,

Crabbé²

2017

Proceedings of the 15th Conference of the European Chapter of The Association for Computational Linguistics: Volume 1

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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 German treebanks shows that SR-GAP outperforms the previous best transitionbased discontinuous parser (Maier, 2015) by a large margin (it is notably twice as accurate on the prediction of discontinuous constituents), and is competitive with the state of the art (Fernández-González and Martins, 2015). As a side contribution, we adapt span features (Hall et al., 2014) to discontinuous parsing.

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Section: Completeness and Soundnessmentioning

confidence: 99%