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Texts

AlexandraKlein

1

,BrigitteKrenn

1

,andHaraldTrost

2

1

AustrianResear hInstituteforArti ialIntelligen e(OFAI),

Freyung6/6,1010Vienna,Austria,

2

Se tionforArti ialIntelligen e,

CenterforMed.Statisti s,Informati s,andIntelligentSystems,

Medi alUniversityofVienna,

Freyung6/2,1010Vienna,Austria

Abstra t. Usually,humans have noproblem interpretingnegation in

text.For NLPsystems,thereare so far nostandardsolutions for

han-dlingnegations. ManyNLPsystemsdonotmodelnegationphenomena

anden ounterdi ulties wheneverfa tsare takenas given evenwhen

the statement is negated. Besides from negating obje tive fa ts,

nega-tionmayfulllotherfun tionsinnaturallanguage,su hasbeingpartof

arhetori al relation.Thus,anadequate interpretationof negations

re-quiresame hanismfordistinguishingthedierentfun tionsofnegation

asotherwise, the ontent ofa text annotbe analysedproperly.While

negationhasbeenextensivelystudiedinlinguisti s,itseemsthatthereis

no lassi ationofnegationfun tionswhi h anbeusedforNLP.Thus,

a orpus-basedstudywas arriedoutonGermannewspapertextsin

or-derto derivea taxonomy ofnegation fun tions fromthe pointof view

ofNLP.Fourmain ategorieshavebeenidentied:negationsrelatedto

statements,dis oursemarkers,speakerattitudesand idiomati

expres-sions.All ategoriesmayo urinthe ontextoftemporalmarkerswhi h

assignonly atransient validity to thenegated expression.The

atego-rizationservesasabaseforapattern-basednegation-pro essingmodule

whi hidentiesand lassiesnegations.

1 Introdu tion

Negationfullls variousfun tions intext. Inthefollowingpaper,wewillargue

that NLPsystems need to handle negation, e.g. by means of apre-pro essing

module:someinstan esofnegationmaybevitaltorepresentingtheunderlying

meaning of atext while negationin other ontexts maynot ontribute to the

propositional ontentofa orestatement.No lassi ationseemstobeavailable

whi h anbeusedtodeterminethe ontributionofnegatedexpressiontotextual

meaningfromthepointofviewofNLP.Thus,wehave arriedoutanempiri al

studyontheuseofnegationinGermannewspapertextsasabasefora

negation-pro essingmoduleforthedomain.Thestudyis motivated bybeneedsofNLP

(2)

automati pro essing.While thestudy has been arriedout onGerman

news-papertextsandwhiletherealizationofnegationislanguage-spe i ,weexpe t

thattheanalysisofnegationfun tionmayhavemanylanguage-independentand

domain-independentaspe ts.

Forillustrativepurposes,wewillgivesomeEnglishexamplesfromnewspaper

textsforwhatwe onsider themain fun tionsofnegation.Anobviousfun tion

is the reversal of thetruth value in astatement about an obje tivesituation.

Inthese ases,thestatementisexpli itlymarkedasfalse onsideringaspe i

situationand ontrarytotheassumedexpe tationsonthereader'spart[1,2℄.In

theexamplesenten e

Example 1. Ni klas Bendtner has nottravelledto Malaysiafor the rstpart of

Arsenal'spre-seasontourashe loses inonamove away from the lub. 3

thereistheunderlyingfa tofNi klasBendtner'stravelingtoMalaysiawith

Arsenal. The statement marks this as false, given the urrent situation, and

refutestheassumedpriorexpe tationonthereader'spartthattheso erplayer

willjointhepre-seasontour.Ifnegationisignoredinthissenten e,e.g.bya

bag-of-wordsapproa h,theextra tedfa ts onsistofNi klasBendtner'stravelingto

Malaysia,but they do not ontain the vitalinformation that a tually, Ni klas

Bendtner did not go on this journey with his teammates. Thus, Information

Extra tion appli ations need to in lude negations in a representation of the

ontentofatextifthenegationsarepartofstatements.

Negationdoesnotonlyo urin orestatementsregardingthepropositional

ontentofasenten e;itmayalsoindi ateaspeakerattitude.Inthesenten e

Example 2. MelaniePhillipsis,asyoumightexpe t,nothappy eitherattheidea

of thelikes of CooganandHughGrant taking amoral stan e. 4

the ore statement is the fa t that Coogan and Hugh Grant take amoral

stan e. But this is an embedded statement, and the negation is part of the

introdu tory segment of the senten e ontaining theinformation that Melanie

Phillipsisnothappy aboutthisidea.Sentiment/Subje tivityAnalysisorOpinion

Miningsystemswouldhavetotakeintoa ountthis informationasitrefersto

theopinionorattitude ofapersonwithrespe ttoasituation.

Negationmayalsosignaldierentrhetori alrelations.Inthesenten e

Example 3. Other in idents brea hed hispriva y butnotthe law. 5

3

guardian. o.uk, Ni klas Bendtner misses Arsenal's Asian tour as transfer

nears,Sunday10July2011,http://www.guardian. o.uk/footba ll/2 011/j ul/10 /

ni klas-bendtner-arsenal-tra nsfe r

4

guardian. o.uk,News of the World phone-ha king s andal part one,

Monday 11 July, http://www.guardian. o.uk/ne ws/bl og/2 011/j ul/11 /

news-world-ha king-s andal-live

5

guardian. o.uk, News International papers targeted Gordon Brown,

(3)

thementionedin identswerenotillegal.Inthis ase,anInformationExtra tion

systemhasto onsider andresolvethenegationasitis importanttonote that

the senten e essentially ontains twostatements: 1) thein identsbrea hed his

priva y,2) thein identsdidnotbrea hthelaw.

There is also a rhetori al relation whi h ontains negation as a dis ourse

markerwhi h ontributeslesstothepropositional ontentofthe orestatement:

Example 4. A ordingtothenewspaper,thefor esofMurdo hnotonly

attempt-ed to gain a ess to Brown's voi email but also obtained private banking and

medi al information. 6

Inthisexample, bothstatementsare positive: 1)the for esof Murdo h

at-tempted to gain a ess to Brown's voi email, 2) the for es of Murdo h also

obtainedprivatebankingandmedi alinformation.Thetwostatementsare

on-ne tedbymeansofnotonly...butalso.AnInformationExtra tionsystemshould

not onsiderthenegationifitdoesnotextra trhetori alrelations,butinstead

itshouldfo usonthetwopositivestatements.

Negationsmayalsobemodiedbytemporalmarkers:

Example 5. News International hasnot yetrespondedtothe laims. 7

Here, the negation refers to a situation at a ertain point in time, whi h

maybetransitory.Temporalmodi ationsmayinuen ealltypesofnegations.

Information Extra tionand OpinionMining systemsneedtotakeinto a ount

temporalmodierswhi hmayindi ate transientsituations.

As the examples have shown, it is important to analyse whi h parts of a

statement or its ontext are negated and what the intended ee ts are. For

theextra tion ofrelations, itisessentialto onsider negatedrelationsbetween

termsor on eptsasnegativeexpressionsareoftenmu h morethanmere

fun -tionwordsfromthepointofviewofsystemsrepresentingorannotatingtextual

ontent.

2 Handling Negation in NLP

Mostof resear h on erningNLPandnegationhasbeen arried outin the

do-mainofbiomedi altexts.Negationisimportantinthisdomainasitmayindi ate

theabsen e of ertain relevantsymptoms, pre- onditions,oradverserea tions.

This isindispensableinformationforele troni patient re ords,quality ontrol

andbillingpurposes.Inapproa hesforextra tinginformation frombiomedi al

text, negationis handled by dening or learningpatterns for ombinations of

negationmarkersandmedi al on epts, f.e.g.[3,4℄.Corporaofbiomedi altexts

6

Ameri anJournalismReview,The Es alatingMurdo hS andal,Monday11July

2011,http://www.ajr.org/Arti le.asp?i d=510 9

7

(4)

English [5℄.

In ontrast to NLP systems for biomedi al texts, resear h on Information

Extra tioninotherdomainshasjuststartedtoexaminethefun tionsandee ts

ofnegation.[6,7℄representre entapproa hestoin orporatingnegationinNLP

beyond the medi al domain. The appli ation is the dete tion of oni ts and

in onsisten iesamongpie esofinformationforautomati questionanswering.

Another eld of resear h where negation has to be onsidered is

Senti-ment/Subje tivityAnalysisandOpinionMining;foranoverview, f.[8℄.Inorder

to representnegative ontexts of opinion words,words orphrases are marked

as negative, and they are added to the features whi h are used to determine

thepositive,negativeorneutralpolarityofanexpression[9,10℄.[11℄distinguish

betweenprior and ontextualpolarityof expression whi h maybereversed by

negation. [12℄ des ribe a system for determining the s ope of negation using

ConditionalRandomField(CRFs)modelswhi haretrainedontheoutputofa

dependen yparer.

Toourknowledge,no lassi ationsofnegationfun tionsareavailablewhi h

anbeadoptedinNLPsystems.[1℄has arriedoutanempiri alstudyon orpora

ofwrittenandspokenEnglish,andshehasanalysedtheuseofnegation.Shehas

deriveda lassi ationwhereshedistinguishesbetweenthetwomain fun tions

REJECTIONandDENIAL.REJECTION on ernssuggestionswhileDENIAL

on erns propositions. This lassi ation omes from a orpus- or

dis ourse-linguisti sperspe tive;itla ks on ernfortherequirementsofNLPappli ations.

In parti ular, it does not dierentiate between negated propositional ontent,

negationinspeakerattitudes,rhetori alrelationsandidiomati expressionsand

the ontributionofnegationtotextualmeaningasanalyzedbyNLPsystems.

3 Empiri al study: Negation in a orpus of German news

texts

CorporaofGermannewspapertextsserveasbaseforouranalysis ofnegation.

Whiletherearemany onventionsregardingthestyleofnewspaperarti les,there

is a large variety of expressions ompared to other domains, and newspaper

arti les over a wide range of topi s, somedes ribing temporal developments.

Furthermore, large orpora are available  not only for English, but also for

otherlanguages.Wethereforethink thatnewspaperarti lesareasuitablebase

for a lassi ation of negation fun tion beyond morelimited domains su h as

biomedi altexts.

We onsider only instan es of expli it negation and only lexi ally realized

negation.Wedidnottakeintoa ountmorphologi alnegation,e.g.en odedin

theprexun-,asinapproa heswhi harebasedonbag-of-words,awordwitha

negativeprexbe omesafeature,while lexi al negationhasto be analysedin

(5)

lexemes,e.g.deny whi hoftensignalsnegationinthebiomedi aldomain:

Example 6. The patient deniesany hest pain.

As a lexeme, deny arries a positive and a negative meaning. The a t of

stating somethingis positive, while theassertionthat something isnot trueis

negative. deny ombines both aspe ts. The rationalefor the ex lusion of any

lexemes whi harenotonlynegation'fun tionwords'liesin thefa t that,from

the point of view of NLP, lexemes with positive/negativemeaning tend to be

domain-dependent, produ tive due to wordformation pro esses, and fuzzy or

non-binaryin polarityassignment(e.g.hardly).

TheNEGRA orpus[13℄Version2isasynta ti allyannotatedGerman

or-pus ofnewspapertexts. Inorder to derive anegation sub orpus, all senten es

ontaining one or more negation elements were extra ted from the rst 4000

senten esoftheNEGRA orpus.626(15.7%)ofthe4000senten es ontain705

negation elements, with weder...no h, the Germanequivalent to neither...nor,

being ountedasonenegationelement.Mostsenten es ontainonlyonenegation

element,butthereweresenten eswithuptofournegationelements.

ni ht ('not')is themostfrequentnegationelement, whi h isnotsurprising,

as itis the main negationlexeme for senten e negation in German, similar to

theEnglishnot.Figure1showsalistofallnegationelementswhi hwerefound

in thesub orpuswiththeirfrequen yofo urren e.

Negationelement Count %

ni ht ('not') 46866.7% kein ('no') 10314.7% ohne ('without') 53 7.5% ni hts ('nothing') 23 3.3% nie ('never') 21 3.0% weder...no h ('neither...nor') 10 1.4% niemand ('nobody') 8 1.1%

keinerlei ('no...atall/no...whatsoever') 3 0.4%

niemandem ('nobody'),dat) 3 0.4%

nirgendwo ('nowhere') 2 0.3%

keineswegs('bynomeans') 2 0.3%

niemanden ('nobody',a ) 2 0.3%

keins ('none') 1 0.1%

ni ht-('non-') 1 0.1%

nirgends ('nowhere') 1 0.1%

niemals ('never') 1 0.1%

Fig.1.Negationelements

(6)

our negation-pro essingmodule to berobust, whi h pre ludes relyingon deep

parsing. On the other hand, the whole negated statement whi h is important

forrelationextra tionandontologybuildingmay onsistofmorethantheverb

phrase. Therefore, we have fo ussed on negation ontext in terms of the ore

statementswhi h ontainnegationsaswellasthestatementswhi harepartof

arhetori alrelationmodiedbynegation.

4 Classifying the Fun tion of Negation

Forabottom-up lassi ationof negationfun tions, wehave startedfrom the

senten estru ture.Analyzingthenegationsub orpus,itbe omesapparentthat

negationappearsinfourtypesofsenten estru ture:Statement,Rhetori al

Re-lation,SpeakerAttitudeandNegativePolarityItem/Idiomati Expression.

Fig-ure2showshowthe 705lexi allyrealized negationelementsappearaspartof

astatement,arhetori alrelation,aspeakerattitude, and aNPI, basedonthe

manualannotation. Type Count % Statement 58082.3 Rhetori alrelation 9012.8 Speakerattitude 29 4.1 NPI/Idiomati expression 6 0.9

Fig.2.Contextsandfun tionsofnegation

Inthefollowing,wewillbrieydes ribethefourtypesoffun tionsand

illus-tratethem with examplesfrom the orpus.All negation fun tionsmayappear

inthe ontextoftemporalinformation.Temporalmodiersweremarkedinthe

orpus.

4.1 Statement

Forthe purpose of identifying the s ope and fun tion of negation, we lassify

a statement as propositional ontent whi h may be represented in terms of a

predi ate-argumentstru ture. Astatementmay be lexi alizedasa lauseora

nounphrase.Negationinsinglestatementsmaynegatethepredi ate(averbin

averbphrase,anominalizationin aNP)oroneormoreofitsattributes.

Thefollowingsenten efromthe orpus(senten enumber35intheNEGRA

orpus),whi histakenfromareviewofa on ert,givesanexampleofanegated

statement:

Example 7. Selbst die otteren Passagen werden nie ausgelassen und fröhli h.

(7)

Negationsmaybepartofrhetori alrelations.Withinrhetori alrelations,

nega-tionsmay ontributeto thepropositional ontentof astatement,orthey may

marktherelation withoutnegatingastatement.Relations betweenstatements

establish textual oheren e. Rhetori al Stru tureTheory (RST) [14℄ and

Seg-mentedDis ourse RepresentationTheory(SDRT) [15℄relyonvarying

invento-riesofdis ourserelationsintextanalysisandgeneration.Insome ases,asubset

ofrelationsissele tedwhi hismostrelevantinaspe i appli ation.Rhetori al

relations onne tsequen esofstatements;theymaybeimpli it,orsignaledby

dis oursemarkers.

For Information Extra tion, it is importantto distinguish the ontribution

(with respe t to propositional ontent)and fun tion of negation.All instan es

of expli itnegationin thenewspapersub orpuswere examinedin orderto

de-termineiftheyo uraspartofarhetori alrelation.Theinventoryofrhetori al

relations was taken from the SDRT relations dened in [15℄. [16℄ presents an

approa hfor using linguisti uesto lassify rhetori alrelations from asubset

of the SDRT relation inventory in [15℄.In the newspaper negationsub orpus,

threedierenttypesofrhetori alrelationswereasso iatedwithnegations:

 CONTRAST:

ni ht...sondern (not...but ), ni ht...aber (not...however) signal a

CON-TRASTrelation. The rst partof the sequen edes ribesastatement

(re-ferringtoanexpe tation)whi hismarkedasfalse.Inthese ond part,itis

repla edbyinformationwhi hdes ribesthea tualsituation.Bothsegments

usuallyshare some ommon featuresin form and ontent. InCONTRAST

ontexts,negationisimportantasitexpli itlyreje tsanexpe tation.

Examplefromthe orpus:

ni htdas Wort, sonderndie Tatistwi htig (2978)

(`notwords,buta tionsareimportant')

 CONTINUATION:

Patternsofthetypeni htnur...sondern(notonly...butalso),signala

CON-TINUATIONrelation.These ondpartofthesequen e,whi hmay ontain

moreunexpe tedinformationthantherstpart,isaddedbymeansof

negat-ingrestri tiveadverbssu hasnur orallein(`only',`simply').In

CONTINU-ATION ontexts,thenegationonlyhasarhetori alfun tion.Its ontribution

tothe propositional ontent anbe negle ted.Forthe purposesof analysis

in anNLPsystem, thenegation andrestri tion anbe removed, and both

parts anbetreatedasrelatedfa ts withequal ontributions.

Examplefromthe orpus:

Ni htnureinTanz,sondern einGefühl (3437)

(`notonlyadan e,butafeeling')

(8)

whi hmustbegivenforonestatementinorderforase ondstatementtobe

appli able.

Examplefromthe orpus:

Allerdings soll diesnur mögli h sein, wennsi h Kunst ni ht in den Dienst

politis her Fors hrittskonzeptestellt. (1810)

(`however this should only be possible if art does not adhere to politi al

on eptsofprogress')

If negation is part of a rhetori al relation, negation marks a sequen e of

statementsand establishesarelationbetweentheminform and ontent.

4.3 Speaker attitude

Newspaper ommentary is a genre whi h ontainsa omplex mixture of fa ts

andopinions[18,17℄.Inthesub orpus,speakerattitudeswereexpressedmostly

byverbsand adje tives.If anegationo urred,itreversed themeaning ofthe

verboradje tive,e.g.

Fürni ht empfehlenswerthält erFuÿball

[

...

]

(2224)

(`Hedoesnotre ommend(playing)so er')

[1℄notesinherempiri alstudythatnegationtendstoo uroftenwithmental

verbssu hasthink.

4.4 NPIs/Idiomati expressions

Whilethepreviouslydes ribed ategoriesfor ategorizingnegationsemploy

fun -tional riteria,lexi alizedexpressions ontainingnegationelementswereassigned

theirown ategorysin etheseexpressionshavetoberepresentedasawholein

orderto grasptextualmeaning.These asesare importantforInformation

Ex-tra tionsystemsasbag-of-wordsapproa hesmay omeupwithdistortedresults

ifidiomati expressionaretakenliterally.Lexi al itemsmaypreferorestablish

negative ontexts.Insome ases,theresultingexpressionsareidiomati

expres-sions,e.g. He didn'tbudge.Er zu kte ni ht mit derWimper.Other examples

notbeingidiomati expressionsin thestri t sense arelexemes whi h are likely

too urwithinnegative onstru tions,e.g.any inEnglish.

In the sub orpus, only six  dierent  instan es of idiomati expressions

ontainingnegationo urred, f.Figure3.

ForGerman,alistofNPIsisavailable whi hhasbeenextra tedfromlarge

orporausing o-o urren einformation[19,20℄.Thislistishelpfulfor

automat-i allydete tingnegationwhenitis partofanNPI.Sin e ollo ationsarerigid

(9)

ni htKindervonTraurigkeitsein `toknowhowtoenjoyoneself' (235)

keinGeringerer als `noneotherthan' (1084)

ni hthinterdemBerghalten `tobeunhesitating' (1678)

ni hts hle htstaunen `tobeastonished' (3528)

ni htverhehlen `notto on eal' (3616)

überGeldni htreden sonderneshaben`nottotalk aboutmoneybuttohaveit'(3744)

Fig.3. NPIs/Idiomati expressions

5 Automati pattern-based analysis of negations

The analysis of negation in the NEGRA orpus, whi h was des ribed in the

previousse tions, hasresultedin agoldstandardaswellaspatterns for

nega-tionre ognitionand lassi ation.Inordertoexaminewhetherthe lassi ation

whi hwasderivedfromtheNEGRA orpus anbeappliedtoothernewstexts,a

se ond orpuswasbuiltwhi h onsistsofarti lesfromtheAustriandaily

news-paperDer Standard.65 arti lespublished on thesamedayin various se tions

of the newspaperwere sele ted. The orpuswaspro essed by apart-of-spee h

tagger[21℄,whi halsoassignedsenten eboundaries.In ontrasttothesituation

intheNEGRA orpus,bothpart-of-spee htagsandsenten eboundariesinthe

Standard orpuswere not orre tedmanually.The senten esweredivided into

segmentsa ordingtorules.Theaimwasto reatesegments onsistingofaone

statementea h. Thepatternsfornegationidenti ation and lassi ationwere

formulatedasregularexpressions,andtheywereappliedtotheStandard orpus.

Theresultsofthenegationidenti ationand lassi ationwerethen ompared

toamanualannotation.

A ording to the assignment of senten e boundaries, the orpus ontains

1611 senten es; 169 senten es (i.e. 10.5 % of the 1611 senten es) ontain at

least one negation element. The 1611 senten es in the Standard orpus were

automati ally separated into segments, yielding 4952 segments. 171 segments

(i.e. 3.45% of the segments) ontain at least onenegation element. In the171

segments, 138 ases of negated statements, 15 ases of rhetori al relations (9

for the CONDITION relation, 4 for the CONTRAST relation and 1 for the

CONTINUATIONrelation),17 asesofspeakerattitudesandonly1 aseofan

NPIwereassigned.14temporalmarkerswereidentiedbythesystem.

Allnegationelementswereidentied orre tly,whi h omesasnosurpriseas

wehave on entratedon expli itlexi alnegation, witha losed lassof lexi al

items.Of the169senten es ontainingatleastone negationelement,112(66.3

%) weresegmented orre tly,i.e.in awaythat thenegatedstatementwas

seg-mented.Intheremaining37 ases,adeepersynta ti analysisisneeded.Sin ein

ontrasttotheNEGRA orpus,theStandard orpusisrawandwasnot leaned

(10)

disam-determinewheter oordination onne tsdierentstatementsorwhether it

on-ne tsdierentelementswithinonestatement,e.g.

Example 8. Man soll jani ht überkritis h oder vorauseilendbösesein

[

...

]

(`one shouldnotbeover riti alandanti ipartorilymean

[

...

]

')

wherethe negations opeextends to bothadje tives, but thesegmentation

separatesthematthe oordinationand versus

Example 9. Wenn ni hts passiert und die Regierung auf das Errei hen des

Nulldezits wartet

[

...

]

(`ifnothinghappensandthegovernmentawaitsrea hingzerode it

[

...

]

')

wherethe oordinationseparatestwostatements.

TheStandard negation orpus ontainsonlyoneNPI,anditwasnotfound

bythesystemasitis not ontainedin theNPIlistforGerman[20℄. This may

beduetothefa tthatitisanexpressionwhi his ommoninAustrianGerman,

but less ommon in Standard German (S hmied vs. S hmiedl 'expert vs. non

expert').

Ofthe17instan esofspeakerattitudeswereassigned,none anbe onsidered

ana tualspeakerattitude.Thepatternsonlyapplyto aseswherethespeaker

attitude on ernedanembeddedsenten ewiththea tualstatementdes ribing

anobje tivesituation.12 ofthe lassi ationsaredue to errorsofthe

part-of-spee htagger.Thus,itturned outthat theassignmentofspeakerattitudesdid

notyieldany orre tassignmentswithouttakingintoa ountthea tualopinion

words;theintegrationoflexi alindi atorsforspeakerattitudesseemsne essary.

Forrhetori alfun tions,however,allassignmentsin theStandard negation

orpusare orre t. Insum, all15 instan es ofrhetori alfun tions were found,

namely 9for theCONDITION relation, 4for the CONTRASTrelation and1

fortheCONTINUATIONrelation.

Of the14 temporal modiers identied in theStandard negation orpus,4

indi ate `notyet'and 10indi ate `notanymore'.2ofthese assignmentsturned

out to be false positives. There are no false negatives. The errors are due to

lexi alambiguities.

6 Con lusion

Unstru turedtextsarelayeredstru tureswhi h onveyinformationaboutfa ts,

(e.g. ausal ortemporal) relationshipsandattitudes to readers.Ea h negation

elemento urring in atext playsa role in presentingthis information by

em-phasizingthat a ertain assumed fa t isnot validin agivensituation.Human

readersorlistenersareusually abletointerpretthisinformationgiventhe

on-text. They develop a representation of the positive fa ts in a statement and

reversethepolarityofthenegatedaspe tsofthestatement.Apartfromsystems

(11)

straight-fa ts, without onsidering negated ontexts. Sin e the ontribution of negated

informationtothepropositional ontentdependsonthefun tionofnegationin

aspe i ontext,dierenttypesofnegationsneedtobedistinguished.Inorder

to ome up with a lassi ation of negation fun tion, an empiri al study was

arriedout;Germannewspapertextsweresele tedasasampledomain.

Anegation sub orpus wasderivedbysele ting senten es whi h ontain

ex-pli it lexi alnegationfrom asample oftheNEGRA orpus.A lassi ationof

thefun tionsoftheobservednegationsandtheir ontextswasderived,basedon

theperspe tiveofNLPappli ationssu hasInformationExtra tionandOpinion

Mining.Negationelements,s opesandfun tionswereannotatedinthe

sub or-pus.

Asanextstep,thenegationphenomenawhi hwereen ounteredinthe

NE-GRA sub orpuswere transformed into regularexpressions for apattern-based

negation-pro essing approa h. A small raw orpus of texts from the Austrian

newspaperDer Standard waspart-of-spee h tagged,and thepatternswere

ap-pliedtothetest orpus.Theresultsareen ouraging:itturnsoutthateventhis

simpleapproa hperformsreasonablywellidentifyingfa tualnegation,rhetori al

relations and temporal modiers. Forthe lassi ation ofnegation in the

on-text of speakerattitudes, morelexi al resour esare needed. Thesegmentation

ofnegatedstatementsstillneedstobeimproved.

Fromthepointofviewoflinguisti resour es,theempiri alstudyhasresulted

inanannotatednegationsub orpusofGermannewspapertextswhi hmayprove

usefulinvariousappli ations.Furthermore,a lassi ationofnegationfun tions

wasderivedwhi hdes ribesthenegationphenomenaintheGermannewspaper

orpus but whi h also an be applied to other languages and domains. From

there,patternsdes ribingfun tionsofnegationsinGermanwere reatedwhi h

will beextended and integratedinto anegation-lteringmodule whi h an be

usedbyNLPsystemsforGerman.

A knowledgment

The Austrian Resear h Institute for Arti ial Intelligen e is supported by the

AustrianFederalMinistryforTransport,Innovation, andTe hnology.

Referen es

1. Tottie,G.: (1991).NegationinEnglishSpee h andWriting:AStudy inVariation.

SanDiego:A ademi Press,1991.

2. Horn, L. R.:A NaturalHistory of Negation. TheDavidHume Series: Philosophy

andCognitiveS ien eReissues.CSLIPubli ations,2001.

3. Chapman, W. W., Bridewell, W., Hanbury, P., Cooper, G. F.,Bu hanan, B.G.:

A Simple Algorithm for Identifying Negated Findings and Diseases inDis harge

Summaries.JournalofBiomedi alInformati s,34:301310, 2001.

(12)

Annotationfor Negation,Un ertainty andtheir S opeinBiomedi al Yexts.BMC

Bioinformati s,9(Suppl11):S9,2008.

6. Harabagiu, S., Hi kl, A., La atusu, F.: Negation, Contrast and Contradi tion in

TextPro essing.Pro .of AAAI06,2006.

7. deMarnee,M.-C.,Raerty,A.,Manning,C.D.:FindingContradi tions inText.

Pro .ofACL/HTL,2008.

8. Wiegand, M.,Balahur,A.,Roth,B., Klakow,D., Montoyo,A.:.A Surveyonthe

Role of Negation inSentiment Analysis.Pro . of the Workshop on Negation and

Spe ulationinNaturalLanguagePro essing,Uppsala,Sweden,6068,2010.

9. Das,S.R.,Chon,M.Y.:Yahoo!forAmazon:SentimentExtra tionfromSmallTalk

ontheWeb.ManagementS ien e,53:13751388,2007.

10. Na, J.-Ch.,Sui, H.,Khoo,Ch., Chan, S.,Zhou, Y.:Ee tivenessof Simple

Lin-guisti Pro essing inAutomati Sentiment Classi ation of Produ t Reviews. In

Conferen e of the International So iety for Knowledge Organisation (ISKO), pp.

4954,2004.

11. Wilson,Th.,Wiebe,J.,Homann,P.:Re ognizingContextualPolarityin

Phrase-levelSentimentAnalysis.InPro eedings ofthe HumanLanguageTe hnology

Con-feren e andtheConferen e onEmpiri alMethodsinNatural LanguagePro essing

(HLT/EMNLP),pp.347354,2005.

12. Coun ill,I.,M Donald,R.,Velikovi h,L.:What'sgreatandwhat'snot:Learning

toClassifytheS opeofNegationforImprovedSentimentAnalysis.InPro eedings

of theWorkshoponNegationandSpe ulationinNaturalLanguagePro essing,pp.

5159,Uppsala,Sweden,July2010. UniversityofAntwerp.

13. Skut, W.,Krenn,B., Brants,T., Uszkoreit,H.: An AnnotationS hemefor Free

WordOrderLanguages.Pro .ofANLP-97,Washington,DC.,1997.

14. Mann, W. C., Thompson S.: Rhetori al Stru ture Theory: Toward a fun tional

theoryoftextorganisation. Text,8(3):243281,1988.

15. Asher,N.andLas arides,A.:Logi sofConversation,CambridgeUniversityPress,

2003.

16. Sporleder, C., Las arides, A.: Exploiting Linguisti Cues to Classify Rhetori al

Relations.InPro eedingsofRANLP-05, pages532539,Borovets,Bulgaria,2005.

17. Asher,N Benamara,F.,Mathieu,Y. Y.:DistillingOpinion inDis ourse:A

Pre-liminary Study.In Pro eedings of COLING, volume CompanionVolume:Posters,

pages710,Man hester,UK,2008.

18. Stede,M.: Surfa esand DepthsinTextUnderstanding:TheCase of Newspaper

Commentary.In Pro .of the HLT/NAACLWorkshop on Text Meaning,

Edmon-ton/AL,2003.

19. Li hte,T.andSoehn,J.-Ph.:TheRetrievalandClassi ationofNegativePolarity

Items using Statisti al Proles. In Roots: Linguisti s in Sear h of its Evidential

Base. MoutondeGruyter,2007.

20. Soehn,J.-Ph.,Liu,M.,Trawinski,B.,Iorda hioaia,G.:PositiveundNegative

Po-laritätselementealslexikalis heEinheitenmitDistributionsidiosynkrasien. In

Pro- eedingsoftheEurophras, 2008.

21. S hmid,H.: Probabilisti Part-of-Spee hTagging Using De ision Trees. In

Pro- eedings ofthe InternationalConferen e onNewMethods inLanguage Pro essing,

References

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