Corpus-Based Coherence Relation Tagging in Chinese Discourse

• Main Authors: Shou-Yi Cheng, 鄭守益
• Other Authors: Tyne Liang
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/96375712768665040446

碩士 === 國立交通大學 === 資訊科學與工程研究所 === 94 === Discourse analysis plays an important role of document understanding and is crucial for clarifying the proposition and logical structure of the document. Therefore, this thesis is aimed to built a automated Chinese discourse tagging system by collecting and expanding the coherence feature of discourse base on corpus study and to design the corresponding rules. We used the written documents from Sinica Balance Corpus 3.0 as our mining corpus. It includes 7265 articles covering news, biographies, essays, letters, commentary and illustration manuals. We mine individually cue term, continuous POS tag and peculiar punctuation marks for nine types of rhetorical relations of Chinese discourse, that includes Coordinate, Continue, Option, Forward, Disjunctive, Cause and Effect, Conditions, Elaboration and Goal. In our experiment, we used 100 news editorial articles, each of which contains around 1500 words(1424~1558), as testing corpus. The precision, recall and filtration precision of intra sentence tagging achieve 91%, 95% and 98%. On the other hand, the precision, recall and filtration precision of inter sentence tagging achieve 86%, 93% and 95%.