Abstract
Our approach to solve the problem of Korean named entity classification adopted a co-training method called DL-CoTrain. We use only a part-of-speech tagger and a simple noun phrase chunker instead of a full parser to extract the contextual features of a named entity. We will discuss the linguistic features in Korean which are valuable for named entity classification and experimentally show how large a labeled corpus and which unlabeled corpus is necessary for the better performance and portability of a named entity classifier. With only about a quarter of the labeled corpus, our method can compete with its supervised counterpart.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kwak, BK., Cha, JW. (2005). Named Entity Tagging for Korean Using DL-CoTrain Algorithm. In: Lee, G.G., Yamada, A., Meng, H., Myaeng, S.H. (eds) Information Retrieval Technology. AIRS 2005. Lecture Notes in Computer Science, vol 3689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562382_55
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DOI: https://doi.org/10.1007/11562382_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29186-2
Online ISBN: 978-3-540-32001-2
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