A method for distinguishing English mass and count nouns

Nagata, Ryo; Masui, Fumito; Kawai, Atsuo; Isu, Naoki

doi:10.5715/jnlp.12.4_227

Cited by 1 publication

(4 citation statements)

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“…In this method, the original predictions were used when the estimated majority countability was unknown. Also, Nagata et al (2005a)'s method that was based on the DL learning algorithm was implemented for comparison.…”

Section: Methodsmentioning

confidence: 99%

“…In the experiments, we chose Nagata et al (2005a)'s method as the one to be reinforced by the proposed method.…”

Section: Experimental Conditionsmentioning

confidence: 99%

“…As the target noun, we selected 23 nouns that were also used in Nagata et al (2005a)'s experiments. They are exemplified as nouns that are used as both countable and uncountable by Huddleston and Pullum (2002).…”

Section: Experimental Conditionsmentioning

confidence: 99%

“…To overcome these limitations, Nagata et al (2005a) have proposed a method for predicting countability that relies solely on words (except articles and other determiners) surrounding the target noun. Nagata et al (2005b) have shown that the method is effective to detecting errors in article usage and singular/plural usage in the writing of Japanese learners of English.…”

Section: Introductionmentioning

confidence: 99%

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Reinforcing English countability prediction with one countability per discourse property

Nagata

Kawai

Morihiro

et al. 2006

Proceedings of the COLING/ACL on Main Conference Poster Sessions -

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Countability of English nouns is important in various natural language processing tasks. It especially plays an important role in machine translation since it determines the range of possible determiners. This paper proposes a method for reinforcing countability prediction by introducing a novel concept called one countability per discourse. It claims that when a noun appears more than once in a discourse, they will all share the same countability in the discourse. The basic idea of the proposed method is that mispredictions can be correctly overridden using efficiently the one countability per discourse property. Experiments show that the proposed method successfully reinforces countability prediction and outperforms other methods used for comparison.

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Section: Methodsmentioning

confidence: 99%

“…In the experiments, we chose Nagata et al (2005a)'s method as the one to be reinforced by the proposed method.…”

Section: Experimental Conditionsmentioning

confidence: 99%