Part-of-speech tagging considering surface form for an agglutinative language

Authors:
Do-Gil Lee;Hae-Chang Rim
Affiliations:
Korea University, Seoul, Korea;Korea University, Seoul, Korea
Venue:
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Year:
2004

Citing 1
Cited 1

Hidden Markov model-based Korean part-of-speech tagging considering high agglutinativity, word-spacing, and lexical correlativity

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics

Bridging morpho-syntactic gap between source and target sentences for English-Korean statistical machine translation

ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers

Quantified Score

Hi-index	0.00

Visualization

Abstract

The previous probabilistic part-of-speech tagging models for agglutinative languages have considered only lexical forms of morphemes, not surface forms of words. This causes an inaccurate calculation of the probability. The proposed model is based on the observation that when there exist words (surface forms) that share the same lexical forms, the probabilities to appear are different from each other. Also, it is designed to consider lexical form of word. By experiments, we show that the proposed model outperforms the bigram Hidden Markov model (HMM)-based tagging model.