Chinese Parsing Exploiting Characters

Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 125–134, Sofia, Bulgaria, August 4-9 2013. c⃝2013 Association for Computational Linguistics Chinese Parsing Exploiting Characters Meishan Zhang†, Yue Zhang‡∗, Wanxiang Che†, Ting Liu† †Research Center for Social Computing and Information Retrieval Harbin Institute of Technology, China {mszhang, car, tliu}@ir.hit.edu.cn ‡Singapore University of Technology and Design yue zhang@sutd.edu.sg Abstract Characters play an important role in the Chinese language, yet computational pro- cessing of Chinese has been dominated by word-based approaches, with leaves in syntax trees being words. We investigate Chinese parsing from the character-level, extending the notion of phrase-structure trees by annotating internal structures of words. We demonstrate the importance of character-level information to Chinese processing by building a joint segmen- tation, part-of-speech (POS) tagging and phrase-structure parsing system that inte- grates character-structure features. Our joint system significantly outperforms a state-of-the-art word-based baseline on the standard CTB5 test, and gives the best published results for Chinese parsing. 1 Introduction Characters play an important role in the Chinese language. They act as basic phonetic, morpho- syntactic and semantic units in a Chinese sentence. Frequently-occurring character sequences that ex- press certain meanings can be treated as words, while most Chinese words have syntactic struc- tures. For example, Figure 1(b) shows the struc- ture of the word “建筑业 (construction and build- ing industry)”, where the characters “建 (construc- tion)” and “筑 (building)” form a coordination, and modify the character “业 (industry)”. However, computational processing of Chinese is typically based on words. Words are treated as the atomic units in syntactic parsing, machine translation, question answering and other NLP tasks. Manually annotated corpora, such as the Chinese Treebank (CTB) (Xue et al., 2005), usu- ally have words as the basic syntactic elements ∗Email correspondence. 中国 建筑业 呈现 新 格局 NR NN VV JJ NN NP NP NP ADJP NP VP NP IP NP NP NP ADJP NP VP NP IP NN 局 NR-e 格 NR-b JJ 新 JJ-s VV 现 VV-e 呈 VV-b NN 业 NN-e 筑 NN-m 建 NN-b NR 国 NR-e NR-b 中 NP NP NP ADJP NP VP NP IP NN-c 局 NR-i 格 NR-b JJ-t 新 JJ-b VV-c 现 VV-i 呈 VV-b NR-r 国 NR-i NR-b 中 NR-t NN-r 业 NN-i 筑 NN-i 建 NN-b NN-c NN-t VV-t NN-t (a) CTB-style word-based syntax tree for “中国 (China) 建 筑业 (architecture industry) 呈现 (show) 新 (new) 格局 (pattern)”. 中国 建筑业 呈现 新 格局 NR NN VV JJ NN NP NP NP ADJP NP VP NP IP NP NP NP ADJP NP VP NP IP NN 局 NR-e 格 NR-b JJ 新 JJ-s VV 现 VV-e 呈 VV-b NN 业 NN-e 筑 NN-m 建 NN-b NR 国 NR-e NR-b 中 NP NP NP ADJP NP VP NP IP NN-c 局 NN-i 格 NN-b JJ-t 新 JJ-b VV-c 现 VV-i 呈 VV-b NR-r 国 NR-i NR-b 中 NR-t NN-r 业 NN-i 筑 NN-i 建 NN-b NN-c NN-t VV-t NN-t (b) character-level syntax tree with hierarchal word structures for “中 (middle) 国 …

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