Huang, Ting-Hao K.Ting-Hao K.HuangYUN-NUNG CHENKong, LingpengLingpengKong2020-05-042020-05-042015https://scholars.lib.ntu.edu.tw/handle/123456789/490801While morphological information has been demonstrated to be useful for various Chinese NLP tasks, there is still a lack of complete theories, category schemes, and toolkits for Chinese morphology. This paper focuses on the morphological structures of Chinese bi-character words, where a corpus were collected based on a welldefined morphological type scheme covering both Chinese derived words and compound words. With the corpus, a morphological analyzer is developed to classify Chinese bi-character words into the defined categories, which outperforms strong baselines and achieves about 66% macro F-measure for compound words, and effectively covers derived words. © 2015 Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing, SIGHAN 2015 - co-located with 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing, ACL IJCNLP 2015. All rights reserved.enComputational linguistics; Complete theory; Compound words; F measure; Morphological analyzer; Morphological information; Morphological structures; Natural language processing systemsconference paper10.18653/v1/W15-31052-s2.0-85039147271https://doi.org/10.18653/v1/W15-3105