A Korean Part-of-Speech Tagging System Using Resolution Rules for Individual Ambiguous Word

Authors:
Young-Min Ahn;Seung-Eun Shin;Hee-Geun Park;Hyungsuk Ji;Young-Hoon Seo
Affiliations:
School of Electrical & Computer Engineering, Chungbuk National University, Korea;BK21 Chungbuk Information Technology Center, Chungbuk National University, Korea;School of Electrical & Computer Engineering, Chungbuk National University, Korea;School of Information & Communication Engineering, Sungkyunkwan University, Korea;School of Electrical & Computer Engineering, Chungbuk National University, Korea
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Year:
2007

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Abstract

In this paper we present a Korean part-of-speech tagging system using resolution rules for individual ambiguous word. Our system resolves lexical ambiguities by common rules, rules for individual ambiguous word, and statistical approach. We built resolution rules for each word which has several distinct morphological analysis results with a view to enhancing tagging accuracy. Statistical approach based on Hidden Markov Model (HMM) is applied for ambiguous words that are not resolved by the rules. The experiment on the test set shows that the part-of-speech tagging system has high accuracy and broad coverage.