2015
DOI: 10.5715/jnlp.22.251
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Left-corner Parsing for Dependency Grammar

Abstract: In this article, we present an incremental dependency parsing algorithm with an arc-eager variant of the left-corner parsing strategy. Our algorithm's stack depth captures the center-embeddedness of the recognized dependency structure. A higher stack depth occurs only when processing deeper center-embedded sentences in which people find difficulty in comprehension. We examine whether our algorithm can capture the syntactic regularity that universally exists in languages through two kinds of experiments across … Show more

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Cited by 5 publications
(4 citation statements)
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“…In Figure 4, we find DMO converges faster than EM and converges to a higher log-likelihood. In Figure 4, we find that the model accuracy of DMO is much higher than that of EM at (Noji and Miyao, 2015). DV,VV:…”
Section: Comparison Of Training Methodsmentioning
confidence: 90%
“…In Figure 4, we find DMO converges faster than EM and converges to a higher log-likelihood. In Figure 4, we find that the model accuracy of DMO is much higher than that of EM at (Noji and Miyao, 2015). DV,VV:…”
Section: Comparison Of Training Methodsmentioning
confidence: 90%
“…In the literature, we can find only a few experiments where some Hungarian corpus was also among the examined languages. Noji (2016) used pseudo-projective dependency parsing to process the non-projective language formulas [19]. For Hungarian they achieved 80,9% UAS with arc-eager and 79,1% with arc-standard algorithms.…”
Section: Proposed Parsing Modelmentioning
confidence: 99%
“…Moreover, statistical left-corner parsers have proven themselves empirically effective for several grammar formalisms (Roark andJohnson, 1999; Roark, 2001;Díaz et al, 2002;Noji and Miyao, 2014;Noji et al, 2016; Shain et al, 2016; Stanojević and Stabler, 2018;Kitaev and Klein, 2020).…”
mentioning
confidence: 99%