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학술지 Noun Sense Identification of Korean Nominal Compounds Based on Sentential Form Recovery
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양성일, 서영애, 김영길, 나동렬
ETRI Journal, v.32 no.5, pp.740-749
한국전자통신연구원 (ETRI)
In a machine translation system, word sense disambiguation has an essential role in the proper translation of words when the target word can be translated differently depending on the context. Previous research on sense identification has mostly focused on adjacent words as context information. Therefore, in the case of nominal compounds, sense tagging of unit nouns mainly depended on other nouns surrounding the target word. In this paper, we present a practical method for the sense tagging of Korean unit nouns in a nominal compound. To overcome the weakness of traditional methods regarding the data sparseness problem, the proposed method adopts complement-predicate relation knowledge that was constructed for machine translation systems. Our method is based on a sentential form recovery technique, which recognizes grammatical relationships between unit nouns. This technique makes use of the characteristics of Korean predicative nouns. To show that our method is effective on text in general domains, the experiments were performed on a test set randomly extracted from article titles in various newspaper sections. © 2010 ETRI.
KSP 제안 키워드
Context Information, Data sparseness, Machine Translation(MT), Practical method, Test Set, Traditional methods, Translation system, sense tagging, word sense disambiguation