• Title/Summary/Keyword: Phrase analyzer

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A Study on Lexical Ambiguity Resolution of Korean Morphological Analyzer (형태소 분석기의 어휘적 중의성 해결에 관한 연구)

  • Park, Yong-Uk
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.4
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    • pp.783-787
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    • 2012
  • It is not easy to find out syntactic error in a spelling checker systems of Korean, because the spelling checker is generally to correct each phrase and it cannot check the errors of contextual ill-matched words. Spelling checker system tests errors based on a words. Disambiguation of lexical ambiguities is important in natural language processing. Its outputs is used in syntactic analysis. For accurate analysis of a sentence, syntactic analysis system must find out the ambiguity of morphemes in a word. In this paper, we suggest several rules to resolve the ambiguities of morphemes in a word. Using these methods, we can reduce many lexical ambiguities in Korean.

A Method for Clustering Noun Phrases into Coreferents for the Same Person in Novels Translated into Korean (한국어 번역 소설에서 인물명 명사구의 동일인물 공통참조 클러스터링 방법)

  • Park, Taekeun;Kim, Seung-Hoon
    • Journal of Korea Multimedia Society
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    • v.20 no.3
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    • pp.533-542
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    • 2017
  • Novels include various character names, depending on the genre and the spatio-temporal background of the novels and the nationality of characters. Besides, characters and their names in a novel are created by the author's pen and imagination. As a result, any proper noun dictionary cannot include all kinds of character names. In addition, the novels translated into Korean have character names consisting of two or more nouns (such as "Harry Potter"). In this paper, we propose a method to extract noun phrases for character names and to cluster the noun phrases into coreferents for the same character name. In the extraction of noun phrases, we utilize KKMA morpheme analyzer and CPFoAN character identification tool. In clustering the noun phrases into coreferents, we construct a directed graph with the character names extracted by CPFoAN and the extracted noun phrases, and then we create name sets for characters by traversing connected subgraphs in the directed graph. With four novels translated into Korean, we conduct a survey to evaluate the proposed method. The results show that the proposed method will be useful for speaker identification as well as for constructing the social network of characters.