Potential Governing Relationship and a Korean Grammar Checker Using Partial Parsing

Kang, Mi-Young; Park, Su-ho; Yoon, Ae-Sun; Kwon, Hyuk‐Chul

doi:10.1007/3-540-48035-8_67

Cited by 2 publications

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“…For further discussion of the PPT on the potential governor, seeKang et al [2002]. 14 Note that in our system a word is defined as a spacing unit, not taking into account its linguistic function.This implies that a word cannot only be a unit that is morphologically analyzable, but must also be a syllable or syllables that have failed to be analyzed morphologically.…”

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Improving partial parsing based on error-pattern analysis for a Korean grammar-checker

Kang

Yoon

Kwon

2003

ACM Transactions on Asian Language Information Processing

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__________________________________________________________________________________________The main aim of this work is to make improvements to Mirine 2.2, a Korean grammar-checker that takes Korean language properties into account and to develop a system that satisfies user expectations. Particular attention is given to processing Korean texts that may contain users' grammatical and practical errors. In order to treat these errors efficiently, the system includes methods based on asymmetric relations from which partial parsing and the potential governing relationship are derived, implying the starting point for checking, the direction for parsing, and the limits of the scope for parsing.To organize partial parsing efficiently, the system requires an appropriate knowledge base. As its essential prerequisites, this study (a) considers the factors from which the various error types encountered while parsing various Korean texts arise; (b) extracts general patterns from the linguistic or extra-linguistic factors obtained in this manner; and (c) demonstrates how the system, based on a linguistic analysis, procures an adequate knowledge base for partial parsing to satisfy end-users.. Mirine 2.2 achieves an F-measure of about 0.80 in detecting unknown erroneous words; an F-measure of about 0.98 when not considering unknown words; and 98.94% precision in correcting erroneous words.

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confidence: 99%