{"title":"改进汉语情态“LE”识别规则的误差驱动方法","authors":"Yihui Zhou, Hongying Zan, Lingling Mu, Yingcheng Yuan","doi":"10.1109/NLPKE.2010.5587825","DOIUrl":null,"url":null,"abstract":"We have a “Trinity” way for the recognition of Chinese modality “LE”, in which dictionary, usage rule base and usage corpora combine as the knowledge base. Handcrafted rules can hardly cover all usages in the real texts. So this paper proposes an error driven method for the automatic rules improvement. Experimental results show that, after the automatic rules improvement, the recognition precision of the modality “LE” improves by over 1.85%.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"269 10-13","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An error driven method to improve rules for the recognition of Chinese modality “LE”\",\"authors\":\"Yihui Zhou, Hongying Zan, Lingling Mu, Yingcheng Yuan\",\"doi\":\"10.1109/NLPKE.2010.5587825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have a “Trinity” way for the recognition of Chinese modality “LE”, in which dictionary, usage rule base and usage corpora combine as the knowledge base. Handcrafted rules can hardly cover all usages in the real texts. So this paper proposes an error driven method for the automatic rules improvement. Experimental results show that, after the automatic rules improvement, the recognition precision of the modality “LE” improves by over 1.85%.\",\"PeriodicalId\":259975,\"journal\":{\"name\":\"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)\",\"volume\":\"269 10-13\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NLPKE.2010.5587825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NLPKE.2010.5587825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An error driven method to improve rules for the recognition of Chinese modality “LE”
We have a “Trinity” way for the recognition of Chinese modality “LE”, in which dictionary, usage rule base and usage corpora combine as the knowledge base. Handcrafted rules can hardly cover all usages in the real texts. So this paper proposes an error driven method for the automatic rules improvement. Experimental results show that, after the automatic rules improvement, the recognition precision of the modality “LE” improves by over 1.85%.