{"title":"带有信号的时间关系:以意大利语时间介词为例","authors":"Tommaso Caselli, F. Dell’Orletta, I. Prodanof","doi":"10.1109/TIME.2009.23","DOIUrl":null,"url":null,"abstract":"This paper presents a Maximum Entropy tagger for the identification of intra-sentential temporal relations between temporal expressions and eventualities mediated by temporal signals in constructions of the kind \"eventuality + signal + temporal relation\". The tagger reports an accuracy rate of 90.8%, outperforming the baseline (81.8%). One of the main results of this work is represented by the identification of a set of robust features which may be automatically obtained with a relative computational effort.","PeriodicalId":163298,"journal":{"name":"2009 16th International Symposium on Temporal Representation and Reasoning","volume":"157 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Temporal Relations with Signals: The Case of Italian Temporal Prepositions\",\"authors\":\"Tommaso Caselli, F. Dell’Orletta, I. Prodanof\",\"doi\":\"10.1109/TIME.2009.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a Maximum Entropy tagger for the identification of intra-sentential temporal relations between temporal expressions and eventualities mediated by temporal signals in constructions of the kind \\\"eventuality + signal + temporal relation\\\". The tagger reports an accuracy rate of 90.8%, outperforming the baseline (81.8%). One of the main results of this work is represented by the identification of a set of robust features which may be automatically obtained with a relative computational effort.\",\"PeriodicalId\":163298,\"journal\":{\"name\":\"2009 16th International Symposium on Temporal Representation and Reasoning\",\"volume\":\"157 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 16th International Symposium on Temporal Representation and Reasoning\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TIME.2009.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 16th International Symposium on Temporal Representation and Reasoning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIME.2009.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Temporal Relations with Signals: The Case of Italian Temporal Prepositions
This paper presents a Maximum Entropy tagger for the identification of intra-sentential temporal relations between temporal expressions and eventualities mediated by temporal signals in constructions of the kind "eventuality + signal + temporal relation". The tagger reports an accuracy rate of 90.8%, outperforming the baseline (81.8%). One of the main results of this work is represented by the identification of a set of robust features which may be automatically obtained with a relative computational effort.