Analyzing Chinese Synthetic Words with Tree-based Information and a Survey on Chinese Morphologically Derived Words
Lu Jia, Masayuki Asahara, Yūji Matsumoto · International Joint Conference on Natural Language Processing · 2008
The lack of internal information of Chinese synthetic words has become a crucial problem for Chinese morphological analysis systems which will face various needs of segmentation standards for upper NLP applications in the future. In this paper, we first categorize Chinese synthetic words into several types according to their inside semantic and syntactic structure, and then propose a method to represent these inside information of word by applying a tree-based structure. Then we try to automatically identify the inner morphological structure of 3-character synthetic words by using a large corpus and try to add syntactic tags to their internal structure. We believe that this tree-based word internal information could be useful in specifying a Chinese synthetic word segmentation standard.