%0 Journal Article %A Lu, Xiaofei %T Hybrid models for sense guessing of Chinese unknown words %D 2008 %J International Journal of Corpus Linguistics %V 13 %N 1 %P 99-128 %@ 1384-6655 %R https://doi.org/10.1075/ijcl.13.1.06lu %K sense tagging %K lexical acquisition %K corpus-based models %K corpus annotation %K knowledge-based models %K Chinese unknown words %I John Benjamins %X This paper addresses the problem of classifying Chinese unknown words into fine-grained semantic categories defined in a Chinese thesaurus, Cilin (Mei et al. 1984). We present three novel knowledge-based models that capture the relationship between the semantic categories of an unknown word and those of its component characters in three different ways, and combine two of them with a corpus-based model that uses contextual information to classify unknown words. Experiments show that the combined knowledge-based model outperforms previous methods on the same task, but the use of contextual information does not further improve performance. %U https://www.jbe-platform.com/content/journals/10.1075/ijcl.13.1.06lu