• Title/Summary/Keyword: Sejong Electronic Dictionary

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Word Sense Disambiguation of Predicate using Sejong Electronic Dictionary and KorLex (세종 전자사전과 한국어 어휘의미망을 이용한 용언의 어의 중의성 해소)

  • Kang, Sangwook;Kim, Minho;Kwon, Hyuk-chul;Jeon, SungKyu;Oh, Juhyun
    • KIISE Transactions on Computing Practices
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    • v.21 no.7
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    • pp.500-505
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    • 2015
  • The Sejong Electronic(machine readable) Dictionary, which was developed by the 21 century Sejong Plan, contains a systematic of immanence information of Korean words. It helps in solving the problem of electronical presentation of a general text dictionary commonly used. Word sense disambiguation problems can also be solved using the specific information available in the Sejong Electronic Dictionary. However, the Sejong Electronic Dictionary has a limitation of suggesting structure of sentences and selection-restricted nouns. In this paper, we discuss limitations of word sense disambiguation by using subcategorization information as suggested by the Sejong Electronic Dictionary and generalize selection-restricted noun of argument using Korean Lexico-semantic network.

A Study of Methodology for Automatic Construction of OWL Ontologies from Sejong Electronic Dictionary (대용량 OWL 온톨로지 자동구축을 위한 세종전자사전 활용 방법론 연구)

  • Song Do Gyu
    • Language and Information
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    • v.9 no.1
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    • pp.19-34
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    • 2005
  • Ontology is an indispensable component in intelligent and semantic processing of knowledge and information, such as in semantic web. However, ontology construction requires vast amount of data collection and arduous efforts in processing these un-structured data. This study proposed a methodology to automatically construct and generate ontologies from Sejong Electronic Dictionary. As Sejong Electronic Dictionary is structured in XML format, it can be processed automatically by computer programmed tools into an OWL(Web Ontology Language)-based ontologies as specified in W3C . This paper presents the process and concrete application of this methodology.

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Word Sense Disambiguation of Predicate using Semi-supervised Learning and Sejong Electronic Dictionary (세종 전자사전과 준지도식 학습 방법을 이용한 용언의 어의 중의성 해소)

  • Kang, Sangwook;Kim, Minho;Kwon, Hyuk-chul;Oh, Jyhyun
    • KIISE Transactions on Computing Practices
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    • v.22 no.2
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    • pp.107-112
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    • 2016
  • The Sejong Electronic(machine-readable) Dictionary, developed by the 21st century Sejong Plan, contains systematically organized information on Korean words. It helps to solve problems encountered in the electronic formatting of the still-commonly-used hard-copy dictionary. The Sejong Electronic Dictionary, however has a limitation relate to sentence structure and selection-restricted nouns. This paper discuses the limitations of word-sense disambiguation(WSD) that uses subcategorization information suggested by the Sejong Electronic Dictionary and generalized selection-restricted nouns from the Korean Lexico-semantic network. An alternative method that utilized semi-supervised learning, the chi-square test and some other means to make WSD decisions is presented herein.

Assignment Semantic Category of a Word using Word Embedding and Synonyms (워드 임베딩과 유의어를 활용한 단어 의미 범주 할당)

  • Park, Da-Sol;Cha, Jeong-Won
    • Journal of KIISE
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    • v.44 no.9
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    • pp.946-953
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    • 2017
  • Semantic Role Decision defines the semantic relationship between the predicate and the arguments in natural language processing (NLP) tasks. The semantic role information and semantic category information should be used to make Semantic Role Decisions. The Sejong Electronic Dictionary contains frame information that is used to determine the semantic roles. In this paper, we propose a method to extend the Sejong electronic dictionary using word embedding and synonyms. The same experiment is performed using existing word-embedding and retrofitting vectors. The system performance of the semantic category assignment is 32.19%, and the system performance of the extended semantic category assignment is 51.14% for words that do not appear in the Sejong electronic dictionary of the word using the word embedding. The system performance of the semantic category assignment is 33.33%, and the system performance of the extended semantic category assignment is 53.88% for words that do not appear in the Sejong electronic dictionary of the vector using retrofitting. We also prove it is helpful to extend the semantic category word of the Sejong electronic dictionary by assigning the semantic categories to new words that do not have assigned semantic categories.

Automatic Mapping Between Large-Scale Heterogeneous Language Resources for NLP Applications: A Case of Sejong Semantic Classes and KorLexNoun for Korean

  • Park, Heum;Yoon, Ae-Sun
    • Language and Information
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    • v.15 no.2
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    • pp.23-45
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    • 2011
  • This paper proposes a statistical-based linguistic methodology for automatic mapping between large-scale heterogeneous languages resources for NLP applications in general. As a particular case, it treats automatic mapping between two large-scale heterogeneous Korean language resources: Sejong Semantic Classes (SJSC) in the Sejong Electronic Dictionary (SJD) and nouns in KorLex. KorLex is a large-scale Korean WordNet, but it lacks syntactic information. SJD contains refined semantic-syntactic information, with semantic labels depending on SJSC, but the list of its entry words is much smaller than that of KorLex. The goal of our study is to build a rich language resource by integrating useful information within SJD into KorLex. In this paper, we use both linguistic and statistical methods for constructing an automatic mapping methodology. The linguistic aspect of the methodology focuses on the following three linguistic clues: monosemy/polysemy of word forms, instances (example words), and semantically related words. The statistical aspect of the methodology uses the three statistical formulae ${\chi}^2$, Mutual Information and Information Gain to obtain candidate synsets. Compared with the performance of manual mapping, the automatic mapping based on our proposed statistical linguistic methods shows good performance rates in terms of correctness, specifically giving recall 0.838, precision 0.718, and F1 0.774.

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Korean Nominal Bank, Using Language Resources of Sejong Project (세종계획 언어자원 기반 한국어 명사은행)

  • Kim, Dong-Sung
    • Language and Information
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    • v.17 no.2
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    • pp.67-91
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    • 2013
  • This paper describes Korean Nominal Bank, a project that provides argument structure for instances of the predicative nouns in the Sejong parsed Corpus. We use the language resources of the Sejong project, so that the same set of data is annotated with more and more levels of annotation, since a new type of a language resource building project could bring new information of separate and isolated processing. We have based on the annotation scheme based on the Sejong electronic dictionary, semantically tagged corpus, and syntactically analyzed corpus. Our work also involves the deep linguistic knowledge of syntaxsemantic interface in general. We consider the semantic theories including the Frame Semantics of Fillmore (1976), argument structure of Grimshaw (1990) and argument alternation of Levin (1993), and Levin and Rappaport Hovav (2005). Various syntactic theories should be needed in explaining various sentence types, including empty categories, raising, left (or right dislocation). We also need an explanation on the idiosyncratic lexical feature, such as collocation and etc.

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Extension Sejong Electronic Dictionary Using Word Embedding (워드 임베딩을 이용한 세종 전자사전 확장)

  • Park, Da-Sol;Cha, Jeong-Won
    • 한국어정보학회:학술대회논문집
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    • 2016.10a
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    • pp.75-78
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    • 2016
  • 본 논문에서는 워드 임베딩과 유의어를 이용하여 세종 전자사전을 확장하는 방법을 제시한다. 세종 전자사전에 나타나지 않은 단어에 대해 의미 범주 할당의 시스템 성능은 32.19%이고, 확장한 의미 범주 할당의 시스템 성능은 51.14%의 성능을 보였다. 의미 범주가 할당되지 않은 새로운 단어에 대해서도 논문에서 제안한 방법으로 의미 범주를 할당하여 세종 전자사전의 의미 범주 단어 확장에 대해 도움이 됨을 증명하였다.

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Extension Sejong Electronic Dictionary Using Word Embedding (워드 임베딩을 이용한 세종 전자사전 확장)

  • Park, Da-Sol;Cha, Jeong-Won
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.75-78
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    • 2016
  • 본 논문에서는 워드 임베딩과 유의어를 이용하여 세종 전자사전을 확장하는 방법을 제시한다. 세종 전자사전에 나타나지 않은 단어에 대해 의미 범주 할당의 시스템 성능은 32.19%이고, 확장한 의미 범주 할당의 시스템 성능은 51.14%의 성능을 보였다. 의미 범주가 할당되지 않은 새로운 단어에 대해서도 논문에서 제안한 방법으로 의미 범주를 할당하여 세종 전자사전의 의미 범주 단어 확장에 대해 도움이 됨을 증명하였다.

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The Description of Korean particles and endings in the Sejong Electronic Dictionary (세종전자사전에서의 조사.어미 기술)

  • Kim, Chang-Seop;Kim, Jin-Hyeong
    • Annual Conference on Human and Language Technology
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    • 2001.10d
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    • pp.326-333
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    • 2001
  • 조사어미사전은 한국어 연구 및 교육, 정보처리 분야에 두루 이용될 수 있는 범용적 전자사전을 지향하는 세종전자사전의 한 위성사전으로서, 한국어 조사와 어미에 대한 각종 언어 정보를 체계적이고 일관된 형식으로 표상하는 것을 목적으로 하고 있다. 그러한 목적을 달성하기 위해 본 연구 작업에서는 조사와 어미의 형태적 변이 양상과 조건을 상세히 밝히는 한편, 의미 통사적 특성과 제약에 관한 다양한 정보들을 가능한 한 풍부하게 제시하고 있다. 조사와 어미에 대하여 사전에 풍부하고 다양한 언어 정보를 표상하는 작업은 기존의 한국어 인쇄사전은 물론 전자사전에서도 본격적으로 시도되지 않았던 것으로, 본 사전에서 현재까지 기술하고 있는 다양한 정보들은 앞으로 한국어에 대한 순수 언어학적 연구만이 아니라 한국어 정보 처리 분야의 발전에 있어서도 기여하는 바가 적지 않을 것으로 기대한다.

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Semantic Role Assignment for Korean Adverbial Case Using Sejong Electronic Dictionary (세종전자사전을 이용한 한국어 부사격의 의미역 결정)

  • Shin, Myung-Chul;Lee, Yong-Hun;Kim, Mi-Young;Chung, You-Jin;Lee, Jong-Hyeok
    • Annual Conference on Human and Language Technology
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    • 2005.10a
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    • pp.120-126
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    • 2005
  • 세종전자사전의 용언사전과 체언사전에 기재된 용언의 격틀과 명사의 의미부류는 문장의 의미분석을 위한 핵심적인 언어자원이다. 본 논문에서는 용언사전을 전산처리가 용이한 격틀사전으로 변형한 다음 이를 이용한 의미역 결정 시스템을 구축하였고 기계학습 방법에 기반한 의미역 결정 시스템과 혼합하여 한국어에 있어 '에, 로'를 격표지로 하는 부사격에 대한 의미역 결정 방법에 대해 다루고 있다.

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