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1、中文名词性谓词语义角色标注研究*SupportedbytheNationalNaturalScienceFoundationofChinaunderGrantNos.60673041,60873150(国家自然科学基金);theNationalHigh-TechResearchandDevelopmentPlanofChinaunderGrantNo.2006AA01Z147(国家高技术研究发展计划(863));theNationalResearchFoundationfortheDoctoralProgramofHigherEducationofChinaunde
2、rGrantNos.20060285008,200802850006(国家教育部博士点基金);theNaturalScienceFoundationofJiangsuProvinceofChinaunderGrantNo.BK2008160(江苏省自然科学基金)李军辉+,周国栋,朱巧明,钱培德(苏州大学计算机科学与技术学院,江苏苏州215006)SemanticRoleLabelinginChineseLanguageforNominalPredicatesLIJun-Hui+,ZHOUGuo-Dong,ZHUQiao-Ming,QIANPei-De(Schoolo
3、fComputerScience&Technology,SoochowUniversity,Suzhou215006,China)+Correspondingauthor:E-mail:lijunhui@suda.edu.cnAbstract:Thispaperexploressemanticrolelabeling(SRL)inChineselanguagefornominalpredicates.InadditiontowidelyadaptedfeaturesfromverbalSRL,variousnominalpredicate-specificfeatu
4、resarealsoexplored.Moreover,weimprovethenominalSRLperformancebyproperlyintegratingfeaturesderivedfromastate-of-the-artverbalSRLsystem.Finally,wedetailnominalpredicaterecognition,whichisessentialinafullyautomaticnominalSRLsystem.EvaluationonChineseNomBankshowsthatproperintegrationofaver
5、balSRLsystemsignificantlyimprovestheperformanceofnominalSRL.ItalsoshowsthatournominalSRLsystemachievestheperformanceof72.67inF1-measureongoldenparsetreesandgoldenpredicates,andmuchoutperformsthestate-of-the-artnominalSRLinChineselanguage.However,theperformancedropsto55.14inF1-measureon
6、automaticparsetreesandautomaticpredicates.ThissuggeststhegreatchallengeinChinesenominalSRLaswellasthedisappointmentofChinesesyntacticparsing.Keywords:semanticrolelabeling;nominalpredicate-specificfeatures;verbalSRLfeatures;nominalpredicaterecognition摘要:本文研究了中文名词性谓词的语义角色标注(SRL).在使用传统动词性
7、谓词SRL相关特征的基础上,进一步提出了名词性谓词SRL相关的特征集.此外,本文探索了中文动词性谓词SRL对中文名词性谓词SRL的影响,并且联合谓词自动识别实现了全自动的中文名词性谓词SRL.在中文NomBank的实验表明,中文动词性谓词SRL的合理使用能够大大提高中文名词性谓词SRL性能;基于正确句法树和正确谓词识别,中文名词性谓词的SRL性能F1值达到了72.67,优于目前国内外的同类系统;基于自动句法树和自动谓词识别,性能F1值为55.14,说明中文名词性谓词SRL任务艰巨,同时中文句法分析还不够完善.关键词:语义角色标注;名词性谓词相关特征;动词性语义角
