Parsing the Penn Chinese Treebank with Semantic Knowledge

Abstract. We build a class-based selection preference sub-model to incorporate external semantic knowledge from two Chinese electronic semantic dictionaries. This sub-model is combined with modifier-head generation sub-model. After being optimized on the held out data by the EM algorithm, our improved parser achieves 79.4% (F1 measure), as well as a 4.4% relative decrease in error rate on the Penn Chinese Treebank (CTB). Further analysis of performance improvement indicates that semantic knowledge is helpful for nominal compounds, coordination, and N V tagging disambiguation, as well as alleviating the sparseness of information available in treebank.

• Type: Conference
• Year: 2005
• Where: IJCNLP
• Authors: Deyi Xiong, Shuanglong Li, Qun Liu, Shouxun Lin, Yueliang Qian
• Keywords: Electronic Semantic Dictionaries, External Semantic Knowledge, IJCNLP 2005, Natural Language Processing, Semantic Knowledge