• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.760-770
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• 2013

Detecting grammatical errors from a text is a long-history application. In this paper, we compare the performance of two grammatical error detection techniques, which are implemented as a sub-module of an automated English scoring system. One is to use a full syntactic parser, which has not only grammatical rules but also extra-grammatical rules in order to detect syntactic errors while paring. The other one is to use a finite state machine which can identify an error covering a small range of an input. In order to compare the two approaches, grammatical errors are divided into three parts; the first one is grammatical error that can be handled by both approaches, and the second one is errors that can be handled by only a full parser, and the last one is errors that can be done only in a finite state machine. By doing this, we can figure out the strength and the weakness of each approach. The evaluation results show that a full parsing approach can detect more errors than a finite state machine can, while the accuracy of the former is lower than that of the latter. We can conclude that a full parser is suitable for detecting grammatical errors with a long distance dependency, whereas a finite state machine works well on sentences with multiple grammatical errors.

• ETRI Journal
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• v.25 no.4
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• pp.219-230
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• 2003

This paper describes a rule-based approach for syntactic disambiguation used by the English sentence parser in E-TRAN 2001, an English-Korean machine translation system. We propose Parser's Ambiguity Type Information (PATI) to automatically identify the types of ambiguities observed in competing candidate trees produced by the parser and synthesize the types into a formal representation. PATI provides an efficient way of encoding knowledge into grammar rules and calculating rule preference scores from a relatively small training corpus. In the overall scoring scheme for sorting the candidate trees, the rule preference scores are combined with other preference functions that are based on statistical information. We compare the enhanced grammar with the initial one in terms of the amount of ambiguity. The experimental results show that the rule preference scores could significantly increase the accuracy of ambiguity resolution.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.21-28
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• 2016

The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1144-1147
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• 1987

This paper designs parser using GPSC for syntactic and semantic analysis of English input sentences. By use of a number of unification-based principles and Tomita's algorithm, syntactic analysis is described. Also in semantic analysis, Montague semantics is used.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.81-92
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• 2003

Generalized LR parsing is one of the enhanced LR parsing methods so that it overcome the limit of one-way linear stack of the traditional LR parser using graph-structured stack, and it has been playing an important role of a firm starting point to generate other variations for NL parsing equipped with various mechanisms. In this paper, we propose a conditional Action Model that can solve the problems of conventional probabilistic GLR methods. Previous probabilistic GLR parsers have used relatively limited contextual information for disambiguation due to the high complexity of internal GLR stack. Our proposed model uses Surface Phrasal Types representing the structural characteristics of the parse for its additional contextual information, so that more specified structural preferences can be reflected into the parser. Experimental results show that our GLR parser with the proposed Conditional Action Model outperforms the previous methods by about 6-7% without any lexical information, and our model can utilize the rich stack information for syntactic disambiguation of probabilistic LR parser.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1418-1429
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• 2004

This paper presents GrammE, a grammar development environment for feature-based APSG. At the stage of a grammar development, analysis are be done by interpreting the grammar under development, given in a text format, it is relatively easy to diagnose the grammar. Once developed, the grammar is compiled, by using the embedded grammar compiler, into a parser program written in $C^{++}$. The parser program can be used in various types of natural language processing systems requiring syntactic analysis. GrammE is language-independent, and so far has been used for the development of Korean and Chinese grammars.

• Korean Journal of Cognitive Science
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• v.13 no.4
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• pp.42-42
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• 2002

An adverb has been generally defined as what modifies verbs or adjectives in Korean, but we can find that some adverbs can modify nouns. These kinds of adverbs lead a structural analysis complicated; therefore, they should be exceptionally processed by a syntactic parser. In this paper, we categorize a noun-modifying adverb and characterize that from a syntactic analysis standpoint. And also, we propose a method to handle noun-modifying adverbs for improving the accuracy of syntactic analysis. By using this proposed method, we can show that the parser increases it′s accuracy from 81.9 to 83.6% on testing corpus.

• Korean Journal of Cognitive Science
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• v.13 no.4
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• pp.43-53
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• 2002

An adverb has been generally defined as what modifies verbs or adjectives in Korean, but we can find that some adverbs can modify nouns. These kinds of adverbs lead a structural analysis complicated; therefore, they should be exceptionally processed by a syntactic parser. In this paper, we categorize a noun-modifying adverb and characterize that from a syntactic analysis standpoint. And also, we propose a method to handle noun-modifying adverbs for improving the accuracy of syntactic analysis. By using this proposed method, we can show that the parser increases it's accuracy from 81.9 to 83.6％ on testing corpus.

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.267-276
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• 1991

This paper describes syntactic pattern recognition algorithm for pattern recognition and diagnostic parameter extraction of ECG signal. ECG signal which is represented linguistic string is evaluated by pattern grammar and its interpreter-LALR(1) parser for pattern recognition. The proposed pattern grammar performs syntactic analysis and semantic evaluation simultaneously. The performance of proposed algorithm has been evaluated using CSE database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1705-1712
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• 2009

Recently, most Korean syntactic analysis systems use Dependency Grammar, because it is quite good to analysis of Korean language structures. But Dependency Grammar makes many ambiguities during syntax analysis of Korean. We implement a system which decreases many ambiguities in syntax analysis. To decrease ambiguities we suggest several methods. First, we use about 200 dependency rules, second, we suggest a new segmentation method and third, one predicate can not have more than one subject or object. Using these methods, we can reduce many ambiguities in Korean syntactic analysis.