Table Of ContentCCOOMMPPUUTTAATTIIOONNAALL MMOODDEELLSS OOFF DDIISSCCOOUURRSSEE
TThhee MMIITT RPrcesss; SSeerriieess iinn AArrttiiffiicciiaall IInntteclllliiggecnnccee
AArrrtiiJfiicciiaal l IInnlteelllliiggeennccee:: AAnn AAlllITT PPeerrsspperccttiviie~,e.VV oolluumrnee II:: EExxppeerr1t PPrroobblleemm SSoollvviinngg,
NNaatruurraall ILaanngguuaaggee UUnrrddeerrsstaranndidnigf~,gII,n nrteelllliiggeernltt CCoomffrppuutleerr CCooaacchheess,. RRecp[~reresesnetnaltaiolinoft
Ganndd LLeeaarrfnrrinngg ecddiittecdd bbyy PPaattrriicckk HHcennrryy WWiinnssttoonn aanndd RRiicchhaarrdd HHcennrryy BIIrroowwnn,, 11997799
AArrltri$fciciaial l/ln~/rclleiilgiigenecnec:r: AAfnr /MIITT PPeerrssppeccctilvivec. VVoolluummee 111/:: UUlrIrddeerrsstrGalrlrddiningg VViissiioonrz,
MMaanniiypuullaartiiuonn,, C(-oommppuutleerr DDressiiggnn,~,SS yj,mrnbbool/ bMlaarnriippuullaati~oinonce ddiittcedd bbyy IP'aattrricickk HHeennrryy
WWiinnssttoonn aanndd RRiicchhaarrdd HHcennrryy BBrroowwnn,, 11997799
NNEETTLL:: AA SSyysstreemrn ffoorr RReepprrees$eennti/ninggaa lflrdd UUssiinrrgg RRemall-- WWoorrlldd KKnnoowwlleeddggee bbyy SSccootttt
FFaahhllmmaann,, 11997799
TThhee IIrnrtleerrpprreetraat~ioinorootf fVi'isisuuaal lbM!oot/iioon~rbb yy SShhiimmoonn UUllllmmaann,, 11997799
AA TThheeoorryy oo ffSSyynr~tarcatcicticRR eeccooggnrzititiioonn ffoorr NNaattuurraall Il..aanngguuaaggee bbyy MMiittcchhcellll PP.. MMaarrccuuss.,
11998800
TTuurrtrllee GGeroommeetrrfyy:: TThhee CCoomr~pruptuerreraa ss aa MAfeeddiiuumm ffoorr EExxpplloorriinngg AAtfaorthheermnaortiiccss bbyy
HHaarroolldd AAbbcellssoonn aanndd AAnnddrreeaa ddiiSSecssssaa,, 11998811
FFrroomm IImmaaggeess ttoo SSuurrfjaaccees:: AA CCoomn~ppuutartoiorniaarl~oSSltt uuddyy oo ff!thhee HHuummaann EEaarrllyy VViissuuaall
SSyj'ssrteemm bbyy WWiilllliiaamm EErriicc LLceiiffuurr GGrriimmssoonn,, 11998811
CCoom~nppuutartaiotinoanlalMM ooddeellss oof fDDiissccoouurrssee EEddiitteedd bbyy MMiicchhaaecll BBrraaddyy aanndd RRoobbeerrtt CC..
UBecrrwwiicckk,, 11998833
RRoabboart MMoortiioornr:: PPllaannnniinngg aanndd CCoonntrrrooll bbyy MMiicchhaaecll BBrraaddyy,, JJoohhnn HHoollllcerrbbaacchh,, TToommaass
LLoozzaannoo--PPeerreezz,, MMaatttthhecww MMaassoonn,, aanndd TTiimmootthhyy JJoohhnnssoonn,, 11998833
CCOOMMPPUUTTAATTIIOONNAALL MMOODDEELLSS OOFF DDIISSCCOOUURRSSEE
EEddiitteedd bbyy MMiicchhaaeell BBrraaddyy aanndd RRoobbeerrtt CC.. BBeerrwwiicckk
CCoonnttrriibbuuttoorrss::
JJaammeess AAlllleenn
RRoobbeerrtt CC.. BBeerrwwiicckk
JJeerrrroolldd KKaappllaann
DDaavviidd MMccDDoonnaalldd
CCaannddaaccee LL.. SSiiddnneerr
BBoonnnniiee LLyynnnn WWeebbbbeerr
TThhee MMIITT PPrreessss
CCaammbbrriiddggee.,M Maassssaacchhuusseettttss
LIdonnddoonn., EEnnggllaanndd
PPUUBBLLIISSHHEERR''SS NNOOTTEE
'Tlhhiiss ffoorrtmT!aatt iiss iinntteennddeedd ttoo rrcedduuccce tthhee ccoosstt ooff ppuubblliisshhiinngg cceerrttaaiinn wwoorrkkss iinn bbooookk
ffoornmn aanndd ttoo sshhoorrtteenn tthhee ggaapp bbcettwwcecenn eeddiittoorriiaall pprreeppaarraattiioonn aanndd ffiinnaall ppuubblliiccaattiioonn..
TThhee ttiimmee aanndd cexxppcennssec [oIFf ddcettaaiillcedd eeddiittiinngg aanndd ccoommppoossiittiioonn iinn pprriinntt hhaavvee bbeeeenn
aavvooiiddeedd bbyy pphhoottooggrraapphhiinngg Lthhee tteexxtt ooff tthlliiss bbooookk ddiirrceccttllyy ffrroomm tthhee aauutthhoorr''ss
ccootmnppuuttcerr pprriinnttoouutt..
FFoouurrtthh pprriinnttiinngg,, 11998899
CCooppyyrriigghhtt O© 11998833 bbyy
'Tlhhee MMaassssaacchhuusseettttss IInnssttiittuuttee ooffTTcecchhnnoollooggyy
AAllll rriigghhttss rrcesscerrvvcedd.. NNoo ppaarrtt ooff tthhiiss bbooookk mmaayy bbce rrcepprroodduucccedd iinn aannyy ffoornmn,, oorr bbyy
aannyy mmceaannss,, eelleeccttrroonniicc oorr mmcecchhaanniiccaall.. iinncclluuddiinngg pphhoottooccooppyyiinngg,. rreeccoorrddiinngg,, oorr bbyy
aannyy iinnffoonrmnaattiioonn ssttoorraaggee aanndd rrcettrriicevvaall ssyysstteemm,, wwiitthhoouutt ppccnnnniissssiioonn iinn wwrriittiinngg ffrroomm
tthhee ppuubblliisshheerr.,
PPrriinntteedd iinn tthhee UUnniittcedd SSttaatteess ooff AAmmeerriiccaa.,
LLiibbrraarryy ooff CCoonnggrreessss CCaattaalloogpiinl~ggiinn PPuubblliiccaattiioonn DDaattaa
MMaaiinn eennttrryy uunnddeerr ttlittllee::
CCoommppuuttaattiioonnaall MMooddeellss ooff DDiissccoouurrssee
((TThhee MMIITT PPrreessss ssecrriieess iinn aarrttiiffiicciiaall iinntteelllliiggeennccee))
BBiibblliiooggrraapphhyy:: pp,.
IInncclluuddeess iinnddeexx..
I1.. AArrttiiffiicciiaall IInntteclllliiggeennccee.. 22.. LLiinngguuiissttiiccss----DDaattaa
pprroocceessssiinngg.. 33.. SSppeeeecchh pprrowccessssiinngg ssyysstteemmss.. II..BBrraaddyy,,
MMiiechhaaccll,, 11994455-- 1111.. BBecrrwwiicckk,, RRoobbeerrttCC.. IIllll.. AAlllleenn,.
JJaammeess.. I1VV.. SSeerriieess..
QQ333355..CC5S66 l1n9833 0M0111.5.533''55 ~822--2200440022
IISSBBNN 00--226622--0022118833-8-8
IISSBBNN: 00--226622--5522339911--44 ((pPaappeerrbbaacckk))
CONTENTS
CONTENTS
Forcword
ForewoRrdlichacl Brady xiii
MichaelBrady xiii
Preface
PreCacellavid Isracl xvii
DalidIsrael xlii
C:omputational aspccts of discourse
Computationalaspectsofdiscourse
Hobcrt C. I3crwick
HobertC.Bemick 27
Why computational models?
Whycomputationalmodels? 27
Thc syntax of discourse: Wcbbcr and Sidncr
Thesyntaxofdiscourse: WebberandSidner 37
Creating and linking discourse entities
Creatingand [inkingdiscourseentities 37
Creating discoursc cntitics: Wcbbor
Creatingdiscourseentities: Webbor 42
Computing the Webber LF
CompuLtiinngkitnhge dWisecbobuersrcL cFntities: Sidner 46
LinkingEdviisdcconucrcs efoern Stiitdiensc:r'Ss ifdonceurs theory 50
EvidenceforSidner'sfocustheory 59
The world as database: Kaplan
TheworldMasQdLat aabnads eth:cK ianptelarnaction of syntax and scmantics 63
MQLa'In'hdct hineteinrtaecrtaioctni oonf soyfnstyanxt aaxnda nsdcmseamntaincsti cs 66
Theinteractionofsyntaxandsemantics 68
Questions, empty scts, and intentions
Questions,emptysets, andintentions 70
Allcn: Meaning and plans
Allen: Meaningandplans 74
Allen's systcm: the details
Allen'ssystem: thedetails 77
McDonald: saying what you mean
McDonald':Ihsacy MingcDwohnaatlydo muomdeeal n 84
TheMcDonaldmodel 87
Recognizing intcntions from natural language uttcrances
RecognizingintentionsCromnaturallanguageutterances
James Allen
JamesAllen 107
Introduction
Introduction 107
An overvicw of the model
Anoverviewofliemodel 110
Actions, plans, and speech acts
Actions,plans,andspeechacts HO
Plan construction
Planconstruction HI
Plan inference
Plan inference 112
Obstacle detection
ObstaclRecdleatteecdt iwoonrk 113
Relatedwork 114
Plan infcrcncc and obstacle detection
Planinferenceandobstacledetection llS
Contents vi
Contents vi
Bclicf, knowledge, and wants
nelief,knowledge,andwants 116
Actions and plans
Actionsandplans 117
Ihc plan infcrcnce rules
Thcplaninferencerules 120
Rating hcuristics
Ratingheuristics 126
?11c control of plan inferencing
111econtrolofplaninferencing 129
Obstacle detection
Obstacledetection 132
Examplcs of hcfpful responses 134
Examplesofhclpfulresponses 134
'fie train domain 134
'Thetraindomain 134
Ihc spccch act definitions 135
111espEeexcahmapcltc d1e: fpinroitvioidnisng more information than requcstcd 135 137
ExampElexaI:mpprlocv 1id1: inag ycmso/nreo iqnufoersmtioanti oannstwhaenredre nqnue sted 137 142
Example11:ayes/noquestionansweredn" 142
Indircct spccch acts
Indirectspeechacts 144
Spccch acts and mutual belief
Speechactsandmutualbelief 148
Surface linguistic acts
Surfacelinguisticacts 151
13xtcndcd plan infcrcncing
Extendedplaninferencing 152
Examplcs of indircct acts
Examplesofindirectacts 155
Using gcncraI knowledge
Usinggeneralknowledge 159
l>iscussion
Discussion 160
Analyzing sentcncc fragments
Analyzingsentencefragments 161
An example of a scntcnce fragment
An exampleofasentence fragment 162
Conclusions 164
Conclusions 164
Coopcrstive responscs from a portlhle natural languagc databasc qucry system
Cooperativeresponsesfrom aportablenaturallanguagedatabasequerysystem
Jcrrold Kaplan 167
Jerrold Kaplan 167
Introduction 167
Introduction 167
Computational pragmatics
Computationalpragmatics 170
What is a loaded question?
Whatisaloadedquestion? 172
Corrective indircct responscs
Correctivcindirectresponses 174
Relevance to database queries
Relevancetodatabasequeries 175
Language-driven and domain-driven inference
Language-drivenanddomain-driveninference 176
CO-OP: a cooperative qucry system
CO-OP: acooperativequerysystem 177
IIle Mcta Query Language
111eMetaQueryLanguage 178
Computing corrcctivc indirect responses
Computingcorrectiveindirectresponses 180
Focus and suggcstivc indircct responses
Focusandsuggestiveindirectresponses 183
Vagucness and supportive indirect responscs
Vaguenessandsupportiveindirectresponses 187
CO-OP sample queries
CO-OPsamplequeries 189
Portability
Portability 199
Ibmain-specific structures
Domain-specificstructures 200
Effort required and cxtcnt of new domain
Effortrequiredandextentofnewdomain 201
vii
Rcsults and cxillnplcs
Resultsandexamples 201
Conclusion
Conclusion 205
Natural I;~ngsagcg cncr:ltion as a comput~lionapl roblcm: an introduction
Naturall;wguagegenerationasacomputationalproblem:anintroduction
Ihrid 1). hlcnonald
Da~id D.l\lcDonald 209
Introduction 209
Rcsults for tcst spcakcrs
Results fortestspeakers 210
'Thc diffcrcnt input rcprcscntations
Thedifferentinputrepresentations 212
?'he LOGIC domain
The LOGICdomain 214
Planncr-stylc assertions
PlanneNtyleassertions 219
A computational modcl
Acomputational model 222
Characterizing thc problem
Characltearnizgiunaggtch egcpnrcorbalteimon as decision-making 223
Languagegenerationasdecision-making 224
Rcstrictions on thc rnodcl
Restrictionsonthemodel 224
'The relationship bctwccn thc spcakcr and the linguistics component
Therelationshipbetweenthespeakerandthelinguisticscomponent 226
Messages
Messages 226
Run-time relationships
Run-timerelationships 229
lhc'intcrnal structure of the linguistics componcnt
The"internaAl sctarsuccatduere oof ftwthoe tlrianngsudiustcicesrsc omponent 231
A cascaRdecporfctswcnotitnragn lsidnugcueisrtsic context: the tree 231
Representinglinguisticcontext:thetree 234
The controller
Thecontroller 236
An example
An examplReecursive descent through thc formula 244
Recursivedescentthroughthe formula 247
Stcpping the controllcr through the tree
Steppingthecontrollerthroughthetrce 248
Thc realization process
ThcreaClizoanttiionnuipnrgoc tehsrsough the tree 249
Continuingthroughthetree 252
Delaying decisions
Delayingdecisions 254
Intcractions between decisions
Interactionsbetweendecisions 257
Realizing mcssagc elcnicnts in terms of their roles
Realizingmessageclementsintermsoftheirroles 258
Contributions and limitations
ContributioSnpsccainfdic lcimonittaritbiountisons of this research 259
Specificcontributionsofthisresearch 259
Relation to previous A1 work on natural language generation
Relation topreviousAI work onnatural languagegeneration 260
Whcn is this linguistics componcnt appropriate?
Whenisthislinguisticscomponentappropriate? 262
What this modcl cannot do
Whatthismodelcannotdo 264
Focusing in thc comprehension of dcfinitc anaphora
Focusingin thecomprehensionofdefiniteanaphora
Candace L. Sidner
CandaceL.Sidncr 267
Jntroducdon
IntroductioRncscarch on anaphora 267
Research onanaphora 270
Con tents
Contents viii
The focusing approach to anaphora
The focusingapproachtoanaphora 273
Thc definition of focus
Thedefinitionoffocus 278
A skctch of the proccss model of focusing
Asketch ofthe processmodeloffocusing 278
'Ihc rcprcscntation of focus
The representationoffocus 280
Finding the discourse focus
Findingthe discoursefocus 283
Kcjecring thc cxpcctcd focus
Rejectingtheexpectedfocus 287
In fcrring and focusing
Inferringandfocusing 289
An algorithm for focusing
An algorithmforfocusing 291
Focus rnovcment
Focusmovement 295
Rackwards focus movcment
Rackwardsfocusmovement 299
Using b ef ocusing algorithm for movcment
Using thefocusingalgorithm formovement 302
Focus fur pronoun interpretation
Focus forpronoun interpretation 304
Using focus for pronoun intcrprctation rules
Usingfocus forpronouninterpretationrules 305
Focus and knowlcdgc rcprcscntation
Focusandknowledge representation 310
Focus rcstrictions on co-specification
Focusrestrictionsonco-specification 314
Pronouns which have no co-specifiers
Pronounswhich havenoco-specifiers 316
'Ihc problcm of parallelism
The problemofparaJlclism 318
Thc intcrprctation of [his and that
Theinterpretationofthisandthat 320
Co-prcscnt foci in anaphor disambiguation
Co-presentfoci inanaphordisambiguation 320
lntcrpretation of co-prcscnt [hisand lhal
Interpretationofco-present thisandthai 321
This and [hat in focus movement
Thisandthatinfocus movement 323
Using the focus movcmcnt algorithm
Using thefocusmovementalgorithm 327
Conclusions 328
So what can we talk about now?
Sowhatcanwetalkaboutnow?
Bonnie L. Wcbber
Bonnie L.Webber 331
Introduction
Introduction 331
Fundamental assumptions
Fundamentalassumptions 334
Factors in forming discourse-dependent descriptions
Factorsinfanningdiscourse-dependentdescriptions 339
The dcfinitc/indcfinite distinction
The definite/indefinitedistinction 340
Quantifier scoping
Quantifierscoping 342
Membcr/set information
Member/setinformation 345
I'hrce uses of plurals
Threeusesofplurals 345
An appropriate formalism for computing descriptions
Anappropriatefonnalism forcomputingdescriptions 347
Noun phrases in general
Nounphrasesingeneral 347
Singular noun phrases
Singularnounphrases 349
Plural noun phrases
Plural nounphrases 350
Deriving discoursc entity IDS
DerivingdiscourseentityIDs 353
IDS for specific discourse entities
IDs forspecificdiscourseentities 353
ix
Ills for dcrivcd entities: generic sets
IDsforderivedentities:genericsets 361
One anaphora
Oneanaphora 364
Conclusion
Conclusion 370
Bihliograph y
Bihliography 373
Index 391
TTHHEE AAUUTTHHOORRSS
JJaammeess /A\llIleenn
AAssssiissttaanntt PPrrooffecssssoorr
D13ecppaarrtmtrnecnntto off CCoom~pnuptie~rtSScccri ieennccee
UUnniivveerrssiittyy oofTRRoocchhecsstteerr
RIloocchheesstleerr,. NNYY 1144662277
RIloobbeerntCC.. BBecrrwwiicckk
AAssssiissttaanntt PPrrooffeessssoorr
DIlceppaarrttmmecnntt ooff EEklcec.. EEnngg.. aanndd CCoomrnppuuttecrr SScciieennccee
MArttiinficciiaall llnntteclllliiggecnnccec ll.aabhoorraattoorryy
Mhlaassssaacthhuusscettrtss Ilnnssttiittuuttec ooffT Teeechhnnoollooggyy
CCaamrnbbrr.iiddggec MMA/\ 0022113399
JJ.. MMiicchhaaeell BBrraaddyy
SSeenniioorr RRecssecaarrcchh SScciieennttiisstt
MArttiinticciiaalll nlntteclllliiggecnnccec LLaabboorraattoorryy
MMaassssaacchhuussectttlss IInnssttiittuuttee ooffT Teeechhnnoollooggyy
CCaammbbrriiddggee,. MMAA 0022113399
DDaavviidd IIssrraaeell
RRecssecaarrcchh SScciieennttiisstt
BBoolltt,, BBecrraanneekk,, aanndd NNeewwmmaann IInncc..
5500 MMoouullttoonn SSttrreeeett
CCaammbbrriiddggee,, MMAA 0022113399
SS.. JJecrrrroolldd KKaappllaann
VViiccee PPrreessiiddeenntt,. BBuussiinneessss DDeevveellooppmmeenntt
TTeckknnoowwlleeddggee IInncc
552255 UUnniivveerrssiittyy AAvveennuuee
PPaalloo /A\Ilttoo,, CCAA 9944330011
