• 제목/요약/키워드: Quantifying languages

검색결과 2건 처리시간 0.015초

양화사유동과 관련된 한국어의 분석과 전산처리 (Analysis and Computational Processing of Quantifier Floating in Korean)

  • 이진복;박종철
    • 한국언어정보학회지:언어와정보
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    • 제7권1호
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    • pp.1-22
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    • 2003
  • Quantifier floating is one of the much studied phenomena in natural languages where quantifying expressions may appear in places other than their original prenominal one. Its presence is especially prominent in languages such as Korean that allow more or less free word order. We find that, in addition to what is described in the literature, there are other remarkable regularities in the way the language allows quantifiers to “float” with respect to various constructions including coordination, relative clauses, and embedded clauses. These regularities are captured syntactically in a combinatory categorial grammar (CCG) framework for Korean. We also show how to derive semantic representations for Korean quantifier floating in the same CCG framework.

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한글에서의 정성적 확률 표현의 정량적 변환 (A Conversion of Qualitative Probabilistic Expressions into Numerical Probabilities in Korean)

  • 박경수;신수환;이재인
    • 대한인간공학회지
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    • 제25권4호
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    • pp.41-49
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    • 2006
  • In a decision making process, the ambiguity of qualitative probabilistic expressions may result in a wrong conclusion. For this reason there had been many studies of quantifying qualitative probabilistic expressions in English-speaking countries. In this research, quantification of Korean qualitative probabilistic expressions is conducted through 4-step questionnaires. The numerical data of 78 verbal phrases were collected in the first questionnaire and classified in two categories (i.e., uncertainty and frequency). In each category, qualitative probabilistic expressions were divided into eleven groups according to the similarity of the numerical values. In the second questionnaire, subjects selected a representative expression for each group, which totaled 11. In the third questionnaire each subject was asked to rank eleven expressions from 1 to 11 with 1 indicating the highest probability. At last, subjects conducted pairwise comparisons to obtain relative weights, which are used to convert into the numerical probability scale.