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1、BlastingOpenaChoiceSpace:LearningInflectionalMorphologyforNLP(FINAL)MarjorieMcShaneandSergeiNirenburg410-252-8969/443-858-5245DepartmentofComputerScienceandElectricalEngineeringUniversityofMaryland,BaltimoreCountyThepaper-mailcorrespondenceaddressis:CSEEDepartment,Universi
2、tyofMarylandBaltimoreCounty,1000HilltopCircle,Baltimore,MD21250,USA.Thee-mailaddressofM.McShane,whowilltakecareofcorrespondence,ismarge@umbc.edu1Abstract:Thisarticlediscussesthevariousaspectsofdesigningasystemforelicitingknowledgeaboutlanguagefrominformants.Foreachdesignas
3、pect,variousoptionsforimplementationarepresented,alongwiththeirpros,consandrepercussionsforotherpartsoftheknowledgeelicitationsystem.ArunningexamplethroughoutthetextistakenfromtheparadigmaticmorphologyelicitationmoduleofasystemcalledBoas,whichelicitsknowledgetosupportamach
4、inetranslationsystem.ThemainpointofthepaperisanargumentaboutthenecessitytoanalyzethedesignchoicespaceforcomplexNLPsystemsearly,comprehensivelyandovertly.keywords:knowledgeelicitation,systemarchitectures,morphology,naturallanguageprocessing,machinetranslation2Buildingnovelc
5、omplexapplicationsincomputationallinguisticsiscommonlyinfluencedbycountlessdecisionsthatderivefromanintangiblecombinationofknowledge,assumptionsandbeliefsthatthesystemdesignersholdaboutthecontentofthenascentsystemaswellasitsdesiredfinalfunctionalities.Someofthesedecisionsa
6、remadeconsciouslywhilesomeothersshouldbequalifiedastacitassumptions.Thisisunderstandable,atleastinpart,becauseexperimentalresearchdiffersinprinciplefrom“standard”softwareengineeringintherelativeunpredictabilityofitsoutcomes.Inexperimentalscienceitisdifficulttoanticipateall
7、therequirementsandeventualitiesthatwillinfluencetheultimatecontentandlookandfeelofthesystem.Inexperimentalresearchitis,thus,moreimportantthaninindustrialimplementationstoteaseoutasmanystrategicchoicesmade–deliberatelyorsubconsciously–duringsystemdesignbecause,ifonereachesa
8、bottleneckindevelopment,arecordofsuchchoicesprovidespossiblythebestblueprintforquickredes
