{"title":"汉语逗号基本语篇单元识别","authors":"Shengqin Xu, Peifeng Li","doi":"10.1109/IALP.2013.8","DOIUrl":null,"url":null,"abstract":"Element discourse unit (EDU) recognition is the primary task of discourse analysis. Chinese punctuation is viewed as a delimiter of elementary discourse units in Chinese. In this paper, we consider Chinese comma to be the boundary of the discourse units and also to anchor discourse relations between units separated by comma. We divide it into seven major types based on syntactic patterns and propose three different machine learning methods to automatically disambiguate the type of Chinese comma. The experimental results on Chinese Tree bank 6.0 show that our method outperforms the baseline.","PeriodicalId":413833,"journal":{"name":"2013 International Conference on Asian Language Processing","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Recognizing Chinese Elementary Discourse Unit on Comma\",\"authors\":\"Shengqin Xu, Peifeng Li\",\"doi\":\"10.1109/IALP.2013.8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Element discourse unit (EDU) recognition is the primary task of discourse analysis. Chinese punctuation is viewed as a delimiter of elementary discourse units in Chinese. In this paper, we consider Chinese comma to be the boundary of the discourse units and also to anchor discourse relations between units separated by comma. We divide it into seven major types based on syntactic patterns and propose three different machine learning methods to automatically disambiguate the type of Chinese comma. The experimental results on Chinese Tree bank 6.0 show that our method outperforms the baseline.\",\"PeriodicalId\":413833,\"journal\":{\"name\":\"2013 International Conference on Asian Language Processing\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Asian Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IALP.2013.8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Asian Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IALP.2013.8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
摘要
要素语篇单元识别是语篇分析的首要任务。汉语标点符号是汉语基本语篇单位的分隔符。在本文中,我们认为汉语逗号是语篇单位的边界,并锚定以逗号分隔的语篇单位之间的语篇关系。我们根据句法模式将其分为七种主要类型,并提出了三种不同的机器学习方法来自动消除汉语逗号类型的歧义。在Chinese Tree bank 6.0上的实验结果表明,我们的方法优于基线。
Recognizing Chinese Elementary Discourse Unit on Comma
Element discourse unit (EDU) recognition is the primary task of discourse analysis. Chinese punctuation is viewed as a delimiter of elementary discourse units in Chinese. In this paper, we consider Chinese comma to be the boundary of the discourse units and also to anchor discourse relations between units separated by comma. We divide it into seven major types based on syntactic patterns and propose three different machine learning methods to automatically disambiguate the type of Chinese comma. The experimental results on Chinese Tree bank 6.0 show that our method outperforms the baseline.