{"title":"通过识别频繁子句来检测nou CGED系统中的语法错误","authors":"Chuan-Jie Lin, Shao-Heng Chen","doi":"10.18653/v1/W18-3730","DOIUrl":null,"url":null,"abstract":"The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.","PeriodicalId":321264,"journal":{"name":"NLP-TEA@ACL","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences\",\"authors\":\"Chuan-Jie Lin, Shao-Heng Chen\",\"doi\":\"10.18653/v1/W18-3730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.\",\"PeriodicalId\":321264,\"journal\":{\"name\":\"NLP-TEA@ACL\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NLP-TEA@ACL\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/W18-3730\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NLP-TEA@ACL","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/W18-3730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detecting Grammatical Errors in the NTOU CGED System by Identifying Frequent Subsentences
The main goal of Chinese grammatical error diagnosis task is to detect word er-rors in the sentences written by Chinese-learning students. Our previous system would generate error-corrected sentences as candidates and their sentence likeli-hood were measured based on a large scale Chinese n-gram dataset. This year we further tried to identify long frequent-ly-seen subsentences and label them as correct in order to avoid propose too many error candidates. Two new methods for suggesting missing and selection er-rors were also tested.