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1、AComparisonofSelectionalPreferenceModelsforAutomaticVerbClassificationWillRobertsandMarkusEggInstitutfürAnglistikundAmerikanistik,HumboldtUniversity10099Berlin,Germany{will.roberts,markus.egg}@anglistik.hu-berlin.deAbstractverbargumentpreferences.SPsarerepresentedbyfeaturesca
2、pturinglexicalinformationabouttheWepresentacomparisonofdifferentselec-headsofargumentstotheverbs;werestrictourtionalpreferencemodelsandevaluatethemfocusheretonouns.onanautomaticverbclassificationtaskinWeoperationaliseaselectionalpreferencemodelGerman.Wefindthatallthemodelsweas
3、afunctionwhichmapssuchanargumentheadcompareareeffectiveforverbclustering;toaconceptlabel.Wesubmitthattheprimarythebest-performingmodelusessyntacticcharacteristicofsuchamodelisitsgranularity.Ininformationtoinducenounsclassesfromourbaselinecondition,allnounsaremappedtotheunlab
4、elleddatainanunsupervisedman-samelabel;thiseffectivelycapturesnoinformationner.Averysimplemodelbasedonlexicalaboutaverb’sSPs(i.e.,weclusterverbsusingsub-preferencesisalsofoundtoperformwell.categorisationinformationonly).Ontheotherex-treme,eachnounisitsownconceptlabel;weterm1
5、Introductionthisconditionlexicalpreferences(LP).BetweenthebaselineandLPlieaspectrumofmodels,inSelectionalpreferences(KatzandFodor,1963;whichmultipleconceptsaredistinguished,andWilks,1975;Resnik,1993)arethetendencyforeachconceptlabelcanrepresentmultiplenouns.awordtosemantical
6、lyselectorconstrainwhichOurmainhypothesisisthatverbclusteringwillotherwordsmayappearinadirectsyntacticre-workbestusingamodelofsuchintermediategran-lationwithit.Selectionalpreferences(SPs)haveularity.ThisfollowstheintuitionthatverbswouldbeenaperennialknowledgesourceforNLPtask
7、sseemtoselectforclassesofnouns;forinstance,suchaswordsensedisambiguation(Resnik,1997;wesupposethatessen‘eat’wouldtendtopreferasStevensonandWilks,2001;McCarthyandCar-adirectobjectanounfromtheabstractconceptEs-roll,2003)andsemanticrolelabelling(Erk,2007);sen(‘food’).Weassumeth
8、attheseconceptscanbeandrecognisingselectionalviolationsisthoughtexpressedin