Approximation-Aware Dependency Parsing by Belief Propagation
نویسندگان
چکیده
منابع مشابه
Approximation-Aware Dependency Parsing by Belief Propagation
We show how to train the fast dependency parser of Smith and Eisner (2008) for improved accuracy. This parser can consider higher-order interactions among edges while retaining O(n) runtime. It outputs the parse with maximum expected recall—but for speed, this expectation is taken under a posterior distribution that is constructed only approximately, using loopy belief propagation through struc...
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We formulate dependency parsing as a graphical model with the novel ingredient of global constraints. We show how to apply loopy belief propagation (BP), a simple and effective tool for approximate learning and inference. As a parsing algorithm, BP is both asymptotically and empirically efficient. Even with second-order features or latent variables, which would make exact parsing considerably s...
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Coordinate structures pose difficulties in dependency parsers. In this paper, we propose a set of parsing rules specifically designed to handle coordination, which are intended to be used in combination with Eisner and Satta’s dependency rules. The new rules are compatible with existing similarity-based approaches to coordination structure analysis, and thus the syntactic and semantic similarit...
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ژورنال
عنوان ژورنال: Transactions of the Association for Computational Linguistics
سال: 2015
ISSN: 2307-387X
DOI: 10.1162/tacl_a_00153