• Sijohaknonchong
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• v.21
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• pp.5-22
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• 2004

If Sijo poetry is referred to a text which is composed of sentences. its textuality can be explored in terms of 1) the figurative words used in each line. 2) the logical sequence between lines. 3) the syntactic composition of each line. With the ancient Sijo poem. 1) it is composed of logical sentences as a result of extremely restraining from using figurative words that could prevent the reader from grasping the logical sequence within the work; 2) there is a clear cohesion between lines that can make each work perfectly coherent; 3) each line has a balanced syntactic structure, so the entire structure of a Sijo poem is '6 phrases in lines'. With the modem Sijo peom. 1) it abounds in figurative words, which prevent the work from having a logical sequence, and sometimes even from having three lines; 2) there is a loose cohesion between lines which can't make each work coherent; 3) it sometimes destroys the syntactic structure, '6 phrases in 3 lines', unique to traditional Sijo poetry. I think that this trend of modern Sijo poetry can cause haphazard the existence of modern Sijo poetry.

• Journal of English Language & Literature
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• v.56 no.6
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• pp.1047-1065
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• 2010

English inversion constructions are not only hard for non-native speakers to learn but also difficult to teach mainly because of their intriguing grammatical and discourse properties. This paper addresses grammatical issues in learning or teaching the so-called 'predicate inversion (PI)' construction (e.g., Equally important in terms of forest depletion is the continuous logging of the forests). In particular, we chart the grammatical (distributional, syntactic, semantic, pragmatic) properties of the PI construction, and argue for adata-driven teaching for English grammar. To depart from the arm-chaired style of grammar teaching (relying on author-made simple sentences), our teaching method introduces a datadriven teaching. With total 25 university students in a grammar-related class, students together have analyzed the British Component of the International Corpus of English (ICE-GB), containing about one million words distributed across a variety of textual categories. We have identified total 290 PI sentences (206 from spoken and 87 from written texts). The preposed syntactic categories of the PI involve five main types: AdvP, PP, VP(ed/ing), NP, AP, and so, all of which function as the complement of the copula. In terms of discourse, we have observed, supporting Birner and Ward's (1998) observation that these preposed phrases represent more familiar information than the postposed subject. The corpus examples gave us the three possible types: The preposed element is discourse-old whereas the postposed one is discourse-new as in Putting wire mesh over a few bricks is a good idea. Both preposed and postposed elements can also be discourse new as in But a fly in the ointment is inflation. These two elements can also be discourse old as in Racing with him on the near-side is Rinus. The dominant occurrence of the PI in the spoken texts also supports the view that the balance (or scene-setting) in information structure is the main trigger for the use of the PI construction. After being exposed to the real data and in-depth syntactic as well as informationstructure analysis of the PI construction, it is proved that the class students have had a farmore clear understanding of the construction in question and have realized that grammar does not mean to live on by itself but tightly interacts with other important grammatical components such as information structure. The study directs us toward both a datadriven and interactive grammar teaching.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.291-298
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• 2022

In this paper, we present a method for dependency parsing with chunking in Korean. Dependency parsing is a task of determining a governor of every word in a sentence. In general, we used to determine the syntactic governor in Korean and should transform the syntactic structure into semantic structure for further processing like semantic analysis in natural language processing. There is a notorious problem to determine whether syntactic or semantic governor. For example, the syntactic governor of the word "먹고 (eat)" in the sentence "밥을 먹고 싶다 (would like to eat)" is "싶다 (would like to)", which is an auxiliary verb and therefore can not be a semantic governor. In order to mitigate this somewhat, we propose a Korean dependency parsing after chunking, which is a process of segmenting a sentence into constituents. A constituent is a word or a group of words that function as a single unit within a dependency structure and is called a chunk in this paper. Compared to traditional dependency parsing, there are some advantage of the proposed method: (1) The number of input units in parsing can be reduced and then the parsing speed could be faster. (2) The effectiveness of parsing can be improved by considering the relation between two head words in chunks. Through experiments for Sejong dependency corpus, we have shown that the USA and LAS of the proposed method are 86.48% and 84.56%, respectively and the number of input units is reduced by about 22%p.

• Journal of KIISE:Software and Applications
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• v.35 no.1
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• pp.50-58
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• 2008

Most of Korean sentences are complex sentences which consisted of main clause and embedded clause. These complex sentences have more than one predicate and this causes various syntactic ambiguities in syntactic analysis. These ambiguities are caused by phrase attachment problems which are occurred by the modifying scope of embedded clause. To resolve it, we decide the scope of embedded clause in the sentence and consider this clause as a unit of syntactic category. In this paper, we use sentence patterns information(SPI) and syntactic properties of Korean to decide a scope of embedded clause. First, we split the complex sentence into embedded clause and main clause by the method that embedded clause must have maximal arguments. This work is done by the SPI of the predicate in the embedded clause. And then, the role of this embedded clause is converted into a noun phrases or adverbial phrases in the main clause by the properties of Korean syntax. By this method, the structure of complex sentence is exchanged into a clause. And some phrases attachment problem, which is mainly caused by the modifying scope, is resolved easily. In this paper, we call this method clausal segmentation for embedded clause. By empirical results of parsing 1000 sentences, we found that our method decreases 88.32% of syntactic ambiguities compared to the method that doesn't use SPI and split the sentence with basic clauses.

• 재활복지
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• v.21 no.1
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• pp.193-212
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• 2017

The elderly often produce irrelevant speech and get off-topic more easily than the young; the former also has difficulty generating fewer syntactic structures and makes errors of grammatical morphemes. In particular, the elderly might have more difficulty writing since it requires more complex cognitive processes than storytelling. The participants in this study were 32 young people and 32 older people. They were asked to write a short story of Korean fairy tale('Heungbu Nolbu'). The data was analyzed in narrative composition and syntactic structures. The study revealed the following: First, in composition aspects, the elderly group showed significantly lower total number of story grammar and episodes. In addition, the elderly produced more off topic statements. Second, in syntactic aspects, although there was no significant difference in the number of producing complex sentences between two groups, the elderly group generated more inadequate cohesive devices and used fewer relative and adverbial clauses. These findings suggest that the elderly have a tendency to perform tasks by producing more off-topic statements and shows decreasing coherence by using lower number of relative and adverbial clauses. However, this study also uncovers that the elderly were able to write more complex and longer sentences using visual feedback.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1409-1425
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• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.

• KIISE Transactions on Computing Practices
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• v.20 no.9
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• pp.492-497
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• 2014

In this paper, we propose a method of retrieving opinioned tweets in Twitter, which is the one of the popular Social Network Services and shares diverse opinions among various users. In typical opinion retrieval systems, they may consider the presence of sentiment phrases (subjectivity) as the important factor even if the subjective phrases are not related to a given query or speaker. To alleviate these problems, we utilized the syntactic structure of a sentence to identify the relationships between 1) subjectivity-query and 2) subjectivity-speaker and 3) the syntactic role of subjectivity. Besides, our learning-to-rank approach is trained to retrieve opinioned tweets based on query-relevance, textual features, user information, and Twitter-specific features. Experimental results on real world data show that our proposed method can achieve better performance than several baseline methods in terms of precision and nDCG.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.73-85
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• 2011

Lots of valuable textual information is used to extract relations between named entities from literature. Composite kernel approach is proposed in this paper. The composite kernel approach calculates similarities based on the following information:(1) Phrase structure in convolution parse tree kernel that has shown encouraging results. (2) Predicate-argument structure patterns. In other words, the approach deals with syntactic structure as well as semantic structure using a reciprocal method. The proposed approach was evaluated using various types of test collections and it showed the better performance compared with those of previous approach using only information from syntactic structures. In addition, it showed the better performance than those of the state of the art approach.