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Methodological questions about artificial intelligence: Approaches to understanding natural language

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humal ofPr+utic~ 1(197’1)69-84 @NorthHoUnd hblirbing Com,xq KETHODOLCGICAL QUESTIONS ABOUT ARTIFICIAL INTELWGENCE APF’RQACRk?S TO UNDERSTANDRUG NATUML LANGUAGE ‘fORx!P WILKS 1. lntroductiml This paper discusses a very general qwtion, as to whether there IS or II not a “scienx of language”. It then tur% la a nore :pectfic one about the nature of %rwntx primItrves*’ and their rol: I 1 language underslandmg systems, and argues that the SSU~ c.f semantx primibvcs 1s one aspect of the initial, more general, quer tion. In spite of IlS hfk, the paper 5swly dare to the cc!““Pr”r of many tingwts, especially since the two disciplines &ve drawn together recently, and begun to recoinl~e the V&E of each other’: Insights. I shall not attempt *o cxplam m any deM wb.tt artificif inteIligence (AI) is, or what is the substance of the re:earch work to which I refer. As much as IEneeded wdl be explamed JS we go along. M that IS required initially w to naha that AI b not, as some lmguists seem to ba?. bebeve*ed, a method of applying rules, demr:d by otners, wrth the aid uf a dlgitat compntx m order to test them. It is, in fact, a quite mdependont source of msigbt into the worhnga of natural language, w,n ring on tha notmn of the use of leg> structured cot&es for the representation of Ianpegc (em&tics~otcntially more highly rtmclured than IIngustir, derlvatlmu, that 13). awes that represent our lmowkdge of the real cxtemal world. Sw9 worken is AI have also advocated, as do the gn*r&ve lmgmrtr, the use of l~.ucd dzccmposltIon by means of semantic primitixer, ?ad it is with fhclr position (and I sub3cribc to It myself) that the last sectton of tho paper wdl be concerned. 69
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Page 1: Methodological questions about artificial intelligence: Approaches to understanding natural language

humal ofPr+utic~ 1(197’1)69-84 @NorthHoUnd hblirbing Com,xq

KETHODOLCGICAL QUESTIONS A BOUT ARTIFICIAL INTELWGENCE APF’RQACRk?S TO UNDERSTANDRUG NATUML LANGUAGE

‘fORx!P WILKS

1. lntroductiml

This paper discusses a very general qwtion, as to whether there IS or II not a “scienx of language”. It then tur% la a nore :pectfic one about the nature of %rwntx primItrves*’ and their rol: I 1 language underslandmg systems, and argues that the SSU~ c.f semantx primibvcs 1s one aspect of the initial, more general, quer tion.

In spite of IlS hfk, the paper 5s wly dare to the cc!““Pr”r of many tingwts, especially since the two disciplines &ve drawn together recently, and begun to

recoinl~e the V&E of each other’: Insights. I shall not attempt *o cxplam m any deM wb.tt artificif inteIligence (AI) is, or what is the substance of the re:earch work to which I refer. As much as IE needed wdl be explamed JS we go along. M that IS required initially w to naha that AI b not, as some lmguists seem to ba?. bebeve*ed, a method of applying rules, demr:d by otners, wrth the aid uf a dlgitat compntx m order to test them. It is, in fact, a quite mdependont source of msigbt into the worhnga of natural language, w,n ring on tha notmn of the use of leg> structured cot&es for the representation of Ianpegc (em&tics ~otcntially more highly rtmclured than IIngustir, derlvatlmu, that 13). awes that represent our lmowkdge of the real cxtemal world. Sw9 worken is AI have also advocated, as do the gn*r&ve lmgmrtr, the use of l~.ucd dzccmposltIon by means of semantic primitixer, ?ad it is with fhclr position (and I sub3cribc to It myself) that the last sectton of tho paper wdl be concerned.

69

Page 2: Methodological questions about artificial intelligence: Approaches to understanding natural language

70 Y WI s/Artrficla! mrertrkwl.e md naturd taneu~:e

? A science of language?

Arc rorkers I” Al dnd na:urd bnguage a happy band of brothers marching wth theu VB~OUE syste~ns together trwards the Promised Land tsystemr wluch I” the Y er of “,a”y well &rposed ovts, icrs are only notational vanants at bottom) 01, on the contrary. are there sen~us r.::hodologcal differences inherent 1” our iznolrs pwtlonsv I think there 8s tn fact o”c central difference, and that It 1s a meth- o ‘olag& reflection of a metaphysval dlffep:“ce about whether there LS, or IS not. a swrx~ OJ longwge There IS. of course, an enormous investment of scholarship behmd thai phrase that : .hall not attempt to tap here.Vfhat 1 am oncerned wth at tbls pomt IE a difference I” attrtudes to the task of detinmgand ,xogrammmga svstrm of ales that could cause x nutomato? (computer) to be sad to undentnnd language, m some generally acceptable se”:e OF that last phrase.

The ‘~“PUE difference of att.tude I hav? I” nund has to be separated o”t Inmally from the sorts of non.seno”s mcthodologxal IWIS that ause I” connection wth tbe ilxdys~s of language by mschmo I have m mind here such agxed pomts es that (,) .: would be ““xx to bwe an understanding systen workmg wtb a vocabulary of Nk herds rather than Mh, where h > M, and moreover, the system wocld gem,” .c~entlfic pla”sibdGy If the vocabrd.mes contained WOI”E of maxunally different types so that ~ohouse”,“iish , ” “commntee* and “‘testmwmal” would be a vocabu- lary wpenor to ‘Aouse”, ‘%ottagr.“, “palace” and “apartment block” And that, (“) I would be mcer to have a urlderstandlng system that cwreetly understood IV% of Input sentences than one wtxil undetstoodM% When I say non-serious here I do not mean unimportant. but only that nothing tbeoretval IS 1” quesno”, so that. for example, It could be only a” arbitrary (and not ” theorehca!) chokce whether or not a system that uoderstood correctly 95% of setdences fro”1 a 3JOO word vocabulary vas or wab not better than one which understood 98% fro,” a ICOO word vocsbulaly

Indeed, the very srzes of the vocabulanes and swcess rates I” the example show that such L choice, however arbmary, !s not one we dre bkely to be called upon to make I” the “ear future, so let “5 press on to wh.it I shall “eem a serious Issue.

Conadcr the followmg three points whwh 1 wll name for ease of subseqwt reference

(I) Theory and pracnce. ‘Trymp hard to make a” understan&“g system work 1s all very well, but 11’s too success-xlented what we need at the moment is more theoretical work”

(2) AI and snence ‘Whnt we should be after is the right set of rules, and expres. sions of real world knowledge, for uaderstandag x&x4 language 110 approxi- mate, 95%. solutions wll do.]xt as they wdl not do I” physss”.

(_O Where to start “‘Smce difficult examples clearly reqwc reasoning to be undsr- stwd, we cannot eve” be@” wthout such a themy because, without It, we could not know of even a” ap~awzrly rmple emn~le that ,t dld NOT require reaso”,“g t” order to be understood”

Page 3: Methodological questions about artificial intelligence: Approaches to understanding natural language

Y. tt’rl?d‘mficli7r Pdfa&w-r mmn “mirol lmgai;% 71

T!lc tlncc ~“sttm~~s above are fiat unended t” be a parody. and certnmy ,I”! B parody OS ,~ny particular person’s new I have not in fact heard ‘all three from LIE same indwdual. even though,?” my new. they ccnsttt~te a ccixent pcs~hon tden tc:ether. “ne wluch I believe to be not ,>nly wrong, and I wll ““me tn that, but also .wntid But tint I nwst set the sc8ne wth a elude h%tn~ tc.d generahsau”n.

It 1s clear that ‘hatursl !anguage undentondmg” has r”r,: t” occupy a :esr -,enpJw.i ~)lzce m AI,and much of the credit for Uas mwxt go to Wmogrdd (19-2, The posltmn expreswd by (i), (2) and (3) above, 1s ,n ~“mc ways a reactiw to that, bncl tu my new a, ~XECEE,V~ “tic. Behind the posnwn SC, cut above Ii.&5 tw susplclon d1a1 ibe S”CCSss of Wmograd’s system *as ,* part due tn Ita avtn~nlpl.tl- cati”ns and that we must now be wary, i”r a wlule at least, of apolrat~rns, w~~~,s- ful or athelwrc- that we must, m short, emphastse how dtftlcvlt ‘t dl 1~ bnd. Indeed, Wmograd has tumself emphawed (1976) that techmques are requlr<d rhat BIP far strongzr than those m hx early work

Now there IS undoubtedly scmethmg m Uus, but It seems w me that the reac- tlcn may hi.ic the paradoxlcai effect of wusmg the stuab of natwal fmguag in

Al t” be gwen up altcgcther In the last year or two a number of those <rho wmed t” be ccnamed wrth lhe proble;;.. of natural language no longer seem t” be 3”. There hds beer. P subtle change. frcm the actual analyms of stcnes, or whatever, to the settmg x# of schemata and sysfems of plans for mdlwdunl stones. usually ““es about slmp.e pnyucal awnties. It might then seem natural to mov: Mhsr from the produc:mn of stone? about tymg one’s shoe-laces, shoppmg I” s~~prmarketr, and s” on, t” plans, for robots of ccwse, that rvdl actually shop in supe. narkets. tie :hea own rho:-lacer. play diplomacy “I whatever. And then of ccutse ware back where we stut~d m AI back to AI’s old central mrerests, robots, problem-solnng and the or@zstton cl plans

Au rhlr w.“uid be a p,ty. not only because iomecne has, ds always, t” be lett hcldmg thr: baby of natural Ianguage awlyas, bu’ becwsa AI has not yet had tha benetic,al ,vffecl ,t 1s rapable of havmg, and ought t” hw, on rhe study of ndturll language. There are at Least fcer of these bwzfits, Ict me Just remmd you of them

(I) emphais on complex stored structures m a natural ldnguuage undcntandmg sye ten, trames. tf ysu like (Minsky 1975)

(b) emphasis on the unpcrtance of real w”rld, mductwe knowledge, expressed m the ntruct ,res of (I).

(lb) emphasis on the commumcative functmn of sentences m context. I e. the find dmg of the correct-m-context reading for a sentence, as opposed to one, :+cII inflwxt~al, lIng”l?atlc vtew, which 1s that the task 1s t!!e finding of a rarrge of possible readings, independent of context.

(w)empmsn on the expression of r&s, struetwes, and Infcrmntlcn vnthm an operational/p! cadural/-cmputational ewronment

Let me now leturn t” the pcmtion of (I). (2) and (3) Cove, and set cut scme

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72 Y rr’tik:,,&“fit.z~ Meuigmce lmdnomd*~e

sauntemdmg considerahonr. It should be mnde clear th;lt I” what follows 1 am

“xtktng only methodolo@al p&is about the assessment of @ems m SenwaI. No attack on the context of any~“?‘~ system IS Intended.

First, to the iheoy mz3 practice pmt. lt seems tame worth a”phasslsi”g agam thdt there can be no rther u:t”n& tat of a system fxu”ders+endi”gnatu.z! Ian- gu;ge than rt’, success I” dom& some speafic task, znd that to pretend othnwise 1s t(r ,ntroduce enormous confusion Conndcrattons of lo@c or psycholo@ pldw.

btity may i lderd be suggestwe m the ronstructlon of Al language systems, but that ts qune another matter Trca rhelr IultailEte accountabday, *wmLh cd” only be whether or not they worl. Suppose soi”e system had ail dewable logical propertrer, and had mn~eover beer. dccldred ‘by every respected psychologjs: to be co”~,ste”: wth all Laown erpenments on tuman reaction times and io on Even so. “one of this would mattec P got 1.1 its !ustlficatron as a computatimal system for “dtural languop.

In 3 sdar vex, tt seems to me iughly m&adi”g, 10 $22 the least, to descnbe the recenf tiowenng of A! uork on natural language mference. or whatever, as titeorcncoi work I would argue that 1s on the contrxy. as some psychoiqsts *“wt MI rx”mdmg us, the ~xpresplo” m some mo-e or less agreeable semi-forma- bsm of mluitwe, conxn~t~ense knoaledge. revealed by atrospect~o”. I hew set out in conslder.lble detd (WIIKS 1971) why such a” activny can hardly be called

‘theoreucal”, I” ~“y strong sense, however warthwhde it may be. That ,t is worth-

4u!e 1s not being 4’ .twned here. Nor could tt be questxoned here, siace I am engaged m the fame act niy myself (Widks 197Sb) I am maldng B methodologxal pomt that ths act,nf> croes not become more valuable by ce,“g dssc,lbed 1” value- added tenm The worthwh&xers, cf course, 1s shown later by teltmg. not by the ~“twtwe or aesthetic appeal of the knowledge represented o- :hc form&m adopted.

Let me turn to pnsn.o” (3 &amiscience. It Eeemrclear to me thal ow actin- t+, IS a” engn~enng. not a scte”tifiL. me and that attempts to draw dna!o@o between swe”w and AI work on langwige me not only overd~gn~fyu.gg, as ebcve, but are wtellectually mrsleading Conduct with me, If you &I, the iollow”S Gedanken-

ex~enmenr suppose that tomorrow someone produces what appears to be the complete Al undentaa&ng system, tncludmg of course all ihe ri,&t inference rules

ta msolve ail the pronoun ,&rences 1” Engbsh. We know I” advance thet many ~“gen~ous and mdusrrlous people would lmmedlately sit down and tmnk up exam-

ples “f perfectly ecc.:ptabte texts ::.a: woe not covered by those rules We !aow they would be able t3 do thlr jl ;t as surely as we k”now that tilt were posrtble for someone to show us a boundary to th:: physical ““went and say “you cannot step over this ‘, .ve would promptly do so.

Do not “usunderstand my point here It IS not th:t I would consnsld:r the one who offered the rule sy&m as refuted by swh a counter example, paruculnrly If

the latter took tmle and mgenu~ty to constnxt On the contrary, lt is the counter- example mcthodolo~ tnat IS te:uted,gwen that the proffered rules expnwd large

Page 5: Methodological questions about artificial intelligence: Approaches to understanding natural language

Y ikzlwtrtrfi%7? :nlallig~ee orld n‘mm7l lw guwc IJ

znd interes ~“g geneldaatlons and covered a wide raqgs of ex&npl?s For the wn- pie m&hoc ology of refut&on is the method of rdedlsed, though urzly of actual, SCIORCL, whxe a” durhward prrt ck cd” ov&&row I theory And within hngmstrcs Itself the “methodology of “comperence theory” has frequently present.?: stalred anomalous example sentences as d they poswsed both the mdubrtablhty rnd tnc re~ectmg pvzer of sdr%tdic expenments I” rhe study of bnguage ~“CJ B method- alow LS no more applopnate than ;. ri to consrder the deRru”on of fish as some- ti”g that swum and has fi”s as bclng “overthrovm” by the discovery ot a wtule Of course It ,s not, nor dxs the defimtlon lore “n power, we su”$y hdre special rules for whales.

The fact of the mLtter IS surely that we c,,:,“ot have d seno”s theory of .>nturnl Language whch req”w> that there be some, boundary to the languge. outslle which “ttecances are t 10 odd for considerdhon. Give” suf6x”t context and -via- “a”~” any seperficr=“y t’cuha, sente”<c can be acconmodated -d w+rstood It 1s fhu: bax hum !n language capacity that rtr,mtwal (uxludmg generativr) b”g..ar- ,cs has ~,stematl.tiy Ignored, and rvhtch a” Al vlcw of language should x able to deal wm. WC know ;” pnnclple fsee W Ila 19/t) what a would be hke to dn so, eve” tf -,o one has any concrete leeas about II ar :he toollent It would be d systenl that could dxover that some eartier mAren e It hod made was lnconslstent ’ wth what it found later m a text, and could relurr to try dqn to understand. 4nu here, to bc mterestmg, thz backtrachng would have tu be more than sunply the follow- ,“g of some br.mch of a panmg t,,dt had bc:” Ignored earher It would have to be somethmg equwalent to post&t ng a new se”%? ot B word, a “e.v reference of a pronoun, or we” a =ew I& of Inference It&f It Is 5ureiy the% sltuarions that the “AI paradigm OI- language understandzng” axd perhapa II alone, wdl be capable, I” pnnnple, ilf tackhng, I” the futux. and It !s thc.c fcatmes oi lulguage, that requw .“ch ma”oe”veri, that show most clearly why the “iOO%Sc~~ntrfic Rule” = Ptcture dws not tit language at all, and wt y t”ne spent trymg to make It tit may be a dwer- s~o” of attentio” from really key xeas bke the heunstlcs of mlsundcrstandme and contrddic hon.

Perhaps a rmmient’s further & atlo” on the role of countevexz’IIpI.3 is worth- whde here. Co.,r der two cou”tei.exa”ples one produced aga,“sr the “expecta- tm” as basic mcchanlsm of paw”:” hypothesis of kesbeck (hesbcck 1973), aad one agatnst my ox” “preference ts b?Slc mechants” etc.” (Walks 197%) hjpothe- his. fiesbeck consldcrs sentences 3uch 3s ‘John went hbntmg and shot a buck”,

’ wino~ad’s chear. of co”rIc, had a Jystem for CtEC-km~ inkrenees and llew inf0rmPd.m agsmn an that ti h,cw alnad, , though it ,j not cleat that such a direct me*od K~Outd cvtc”lt to B m&r wodd of “exfs. L, U’rlka (1968) there was P very cv-de program for fii&np: out “iat 111 arripr.ment of sa”x. earlier m a text, had gone won& but It ws almect cruatnty OT mex- terL&fe metboa. ’ The resder sirod,t be ctcx lhai “100 $5” hr re has no ret2tkx iIrx.ic to :tle FWO” ofirpproxrmo. *rOH. Mat I am llMYtn~ h that letcpwble ulterances foorm a set for expltwtton in *c way that the lentencel era logcallan~g,c., *In? data ofan eYpe”ment do.

Page 6: Methodological questions about artificial intelligence: Approaches to understanding natural language

ill ,. n~dk~,,%ntjicic%, trm,l~~“cr &Ed n,7t”nd lrmguoge

where, putting .t sunply, the ment%m ofhur~tmg causes the system to expecr more about huntmg, such as shoo+iig and game anm~&, and so rt re,olver, “buck’ co1 rectly as the anrmal and not tbe cesh. One ~mmcdiately tbmks cf “JoSo went hunt. mg and lost fifty bucys”, where the same method pmduces the wrong :eesuit

Convenoly, in my own system I make much of the preference uf concepts for otbei concepts to play certain roles, so that ior example L” “John tasted me port”, “port” w& be resolved <IS the dnnk and not the ha&our hecsus: of tie preference of tasbng for nn edi%Ie or potable ohJect I&e the bquid port Someo~\e. then, plzusrhly er?ough, m&t come up a.rk ‘He hcked the gun ti ovec znd the stock tasted good”, wt,eere the prefetew or, a sm.dI sale would get the wrong “soup” sense of “stock”. ad not the -gun part”.

It shordd bc clear that thex counler-examples zre to what appear to be, super- fi~laliy. OFpoSed theones of pUSl”g My po:nt IS that I” nat/lel case Jo the exam- ples succeed m shouwg B theory ~seb~ss, I : nerther “Preference ~‘i no good” nor “Expectst~on LS no good” ioUow from the productmn of the countwwmples S’hat is needed of course, and wlut II fact bottz partws are trymg for, I” some sutdhle ooxtore of the nproa hes but. and herr 1s the key pomt, them wti net be any msgtc ngbt mlxtore ~‘?et Theic L, ? .~nly be a combmaxi that wti Sself go wrong w;:h srrftictentiy inymoua ~1;-,nplcs OnI> a ~ecosery meci!onism wtl we us, Jimt as II saves people, w% mwwientand dl the trme. There wii never be, a RICW combmatron, m t!w WV th?t F = km&r”gives a nght theor, of grantahon when, and only when,n = 2

One futiber a>pect of *be msapprrbcnmor~ that the construction of B ‘language understander” LS a sc~entiiic task shows t?elf -II the b&f tbot such an understander would be prcdrchue I” the .vvny that sc~ntLic llrones are normally ruFposed to bc SUppOItWS ol tfils belief uould argue that, d such an understander “rrodels” human behdnou m an) intercstmg sense ihen, given il story contammg a prono~m, the understander should padtct hou n human understander w!ll refer the ,,mnoun when he reads &e slxv, uld hence predict wvbich ,tem m the story he WI] refer the proi*oun to.

But, I 1 tius expla~~~n. “predu~on ’ has, I” my view, taken on B very pecobar sense Aim all, if the text 1s clearly wt. .a we do not predict how peop’e adt refer tts pronouns, becaw we already know If we ir fact undentsnd the text, then predrctmg how people wdl refer tts pronouns LS as se.ubte a task dsmy predicting how men supertic~ally differ from women In essence nve airesdy how, ondpredrc- bon Over such an area 1s to cause the word to lose Its meamng of ptcdicting what we don’t know. The only evcrptmns would be where :~ther (a) we were de&g wtb mentauy IncapacItated people who could not understand language properly and who might get standard exampLs of pronoun reference wrong, or (b) If we were dealmg wth texts wluch wxe badly wntten and wluch referred ?ronouns unclearly, so that normal human understanders m&t properly &ifer about what was meant by such stones. 6ut neither of these uses would support any general b&f that ? language undezamdcr $8, m any norma’ sense of the word, prelctwe

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Page 8: Methodological questions about artificial intelligence: Approaches to understanding natural language

3. Prunitnes and words

I cant now PI tot,. from the general to the specific to what are, IIL my new.

niproper JUStitiG&OnS of the USC of SEma,,tlC pn”zrfi”es I” k4nguage undcrstandmg

systems The reader v&l reahse by now that by “mrproper” I mean those JUStdlCn-

hens that suggest that semantx pmmrwes are 1~ some sense r/~eorracaI oo,eers.

rather m the way that a neotnnon a theoret ob]ec: m quantum physxs.

WbVhat I man by semant,c pr wt,~es are those ,tem~ wntten var!ousl) zs ?&NN,

HU?UV, PIIYSOBJ that are used to fom express,ons of meamng m AI and appear

suprrticlally sundar to semantic mxkers in the sew of Katz and Fodor (1963)

n,tJ o/a> tbcx ttems sah 3s CAUSE, BECOME, STRILE, GIVE, PTRANS that

nppcor both 5” AI meuung repiesentatwrls (e g. &hank 197:al and also 8s ’ under-

:y,rg verbs” I” the worh or MLCawi?r (I w3) And Palal (1971) There are also

pwut,vcs m “se whxh do no, fir easl!y mtn etther of thesz typei, as w1 shall 6x

I am concerned here wth general questws about such items how rhex “SC IS

to be Jurtlfied. utd !n parttcular whether they are dlfferrnt m type fro.n the En&h

words they seem to resemble But ;e, bafoie,we mur: first dlstmgmsb these gcnerl,

0, extcmal, ques,Kms from 5, terra- quelilons

What I mean by “lntemzd qxahonr” about pnnutrves are detaded cowdcratmns

nt out what semantic prumtws to choose. or how to !mert them unto ILWE stnx- 1l’les m particular I.asSS so as to represent sornc CoLplex cr,neept or conce&‘uLl

relation, etc These zre questions that ~a., only onse uher *be gcnrral notml: of

s~mdntx pnmltlvc has already been accepted It IS not possible to dncw sah

wtimal questxons ahde one IS at the same tnx answenrn, external quest&ons, such

3: the jb>diC~tlOn OfSt%l~tl~ pnKtiU,tl*eS f~&%'EFd.

There are fxrly strstgbtforward mtemal critena for the selccuon and mnnte-

n mce of a prlmttwe vocabularr tile vocabulary should not be obviously ledundant,

aith two pnm,ttvcs covenng the xane, or nearly the same, range of meaomg If one

culd show ot aryone’s xggeited set of Pnmrtwes that tbts was IO, It would iollow

tilzt he cud not have a good set Sewndly, a prmut,ve vocab’dary shorid not he

o ,nously onwtzd towads 2 psrtlclllar SUbJeCt area, if ,t 1s at t5e same tono

c xmed to be a ~erwr~f set So, for example, tf, ,n a proffered set of prrmrtlvc

a:t,o”s, u e saw a mqonty of pnri,,twcs ccocerned mth human boddj actions such

a, movmg. expelbng. mpstmg, CL we m&t we!! wonder how such a system would

cope. wth the euprcr\ton of gcncral a‘tunn such as “d~~~de”.“separale”, ‘specify”,

‘undertdke”. “delay”, etc

AC Issue br.dges the gap txtwen irrtemnl and external qoestmns m an mteeres‘.

~ng wy, and wdt rerve me here as a new pomt of dcpdrtwe. A porn:: of cbffcrcncc :dween Schank’r ‘.XHE an2 my own has al.vavs been over the appearaocc ,n

Page 9: Methodological questions about artificial intelligence: Approaches to understanding natural language

g for 3BIECT. p,: for DIREC’WN. and t for a CAUSAI RE~LLT For Scnank there w only eleven ~nmltwes (of which PROPEL IS one) and the status of ,tens hke “i:un” IS not tiscusrsd, though &hank &urns to have no relrcr of the surface srruct~xe m ccnceptuali?atmns hke the dagrarn above

Whsrees ,n the repw;entx.tlons of Wrlks (1968, 1975~) there am c-!) stwxur. m@ of the pnr,utwcr B set mcreared from 54 ,n 1968 to 80 ,n 15175, and “gun” IS not or!e of them

The strwwe nee~l nor detam 4s except to note that the r&most prunitwe

Cl&SE LP the head, EL primlpdl pnmr:ive, of the action, and the nghtmost THING thd IS caused-to.mcx IF of cowse, the bullet, wMe the lettmost THING, thdt 1%

t!s. WSFrument. IS tlv. gun. I have arped &‘iks 1976n) that Shank’s dtagramsare therefore of rntied rype

a+ between prrmihve~ and word?. However, I now believe this cntsxn of rurtc to hate been badly put. znd to rest upon the assunxptlon that there ts some clear d~stmction between primrtlves and nonpnmiuves (i.e surface voabulary) H&on- tally, what happened m 3chmk’s system IS dear. he wanted z surfawfrer semdna representation mthout words in it, and ha< gradua!ly aclwved tis, most recently by t’.e cllminstion of many noun-wo.ds in favour of rodor ad Katz type pnmihve

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lists. 3s devel”ped by \t’eber (t972). I am pr”p”smg now in my “vn sy,tem t”

reverse the process, as it war!, and startag hOtI, at fnventary of only pmmtlves f” begut to m>?rt non.prmutwes, i e whit appear t? bz words, Into the font& strw- cures thst detine won! senses, but wth “ns tmportant provisc that I shall now explan. Thus WC m;ght actually ,nsert tne words “‘gun” and %dlat’ mt” rhe for.

mula. in place of the less specific THING, to produce a formula (I” hst form) as F”ll”m

Now, doea ttns method of recursw fnrmular, - wcuiswe m the scnsz of men- r,onmg fomlulas rnrxIs each other (as dUL for ‘ ore at * ““\i “lErtl”“S ‘hdt for “gx~” and for “bullet”) .- force me to wtbdne the “mtx&typs” crttic~sm I mzdt m da pc,s: of Schznk’s descrlptionsq Wsli, ye: and no Nu, m that F&hank’s use of,

cay. the vr”rd “gun- III the C”rcL$t”S & izx21Ly rzpre.~!“tatio” for “sh”“P was

rut ~e-c>i~ux~i m the ase I have detined rt. Ti;x was, d I underst-wtd hxn, no formula e:xwhcre for “gw ’ in his example the~c was tb2 En&h lzveme and no mw~ Hence. IF .I progir” pznwg tius system searched 1” Y text for “gun” xs the mstrument of ‘Shoor” and found “bow and anow”. it Hould be helpics?. bccaose it &d not find L <act]) vJul It WBS laoldng for - it would have no descrtptivc for- I-“& fx the sense of “‘gun” to help ,t to know that 11 had fcand r~.g!Q the bane

PO~I of thmg. Just as I” “Jch” shot her wh a soIt”,u w’uld have no I”~OI”FSIO” w.th vduch to separate the horse snd gun senses of ‘%olt” ,i would nther imd the

sou&t t:.&h kxeme or, ds m these ca.wb,“ot. &I! then agx”. OR the other had, &he cn”cwn fs changed becauce my &I.”

that there should not In pnizc~pie be mixed tq~c (ward and priirtive) semartx descnptions ts implicitly withdrawn by the .lbo\e propmal far re-entmnr forrr.u:as. Now there need be ‘LO venous “‘thccretfccl” cccslderattonn iwolved t” such a

pCOp&. It can be seen as Slrnpl) a nO’.atlOnzd c InVenielCe: in that “‘gun” ma fw mula for .:hoot” IS now j”st a shorthand ivrm foi the Mmtls for “‘~~~n”oWi”g elsewhere in tw sysicm. That makes the FoLmulas eawr to read for a human “seer

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F. iWks:Arficfal malf~cfm 1316 .uruml h,wogs 79

by avoidmg the insert,“” of too much repet,t,ve matad ,n enns of ~nm,t,ves mt” the body of the formula ,tnelf

Yet, there u a more tundamental potnt boned ,n all th,s,very nuch zr extrmat quest,““. and one whsh led me to m,s.rtate my cnt,c,sm of raued-type dcwp- aone m the past. Let me now go ,“I” tbu a bttlp though the dwuss~on will not reach conclunons lhat pve any comfort, &he, to those who xx mlxcd type descnpt!ons I” the past or to those who w,sb to avoid prxmt,ve ieanphom dto- gether.

My baste error -as to deiend the use of primrtwcs by unpbc~tly awummg t&t they were in some way essentfn& dzfi~rennr from ratural language words, and therefore that stntctores of ~r,mit,vrs were I” some way dlffert nt from stwc.t”res of natwal language word;. Wh,ch is to say, a~surmng that a sen,~,,,,r descnpuon m terms of pnmrtwes was wmethmg other than a reduced m,crdangoage. with ill the normal weakness and vaguenesses of a natural language. I ,,“w see “lore clear- ly that that IS “o, and COJWIO~ be so.

Let me take tira the psr;f~mcm aspect of th,s Mcrl nf tbos~: who bnve used pnt,,,t,ves for some tune have made use of the ,n,,ocen, n”tat,“nil cowent,“” of watmg pnmmver ,” opper case letters thus MAN, CAUSE. ?ROIS, etc And I would Pot wih to change tks, II is useful for mdicatmg wheiher we are, at soy even moment, desrribing a stIuct”xe m the pnmitwe “I the surfa..e !anguage The trouble ,s that such a “sage does mevltably carry the suggestlcn th. t the upper case entmes are somethng ,,ther tbao (over and above. or “deeper” tl a,,, but anyway ,i,Fferent from) tne xdmxy word. &ey look hke. Aod this, oicouix, !s exnr, pure and senple. There t eve certainly been clams from some quarten t) at these ~~“f,t,:s pre qu@e other t!dt CAL&E, say. represents, or rcfeis to some other 1.md of

ennly ,n cti.* brain or mmd directly.

At 1% crudest. ttos zs just the old cefirenhallst fallacy moved up a level, a* ,I were The low-lwe, fallwy, still alwe and well. IS that the meemngs of word> ue phyw.1 objects ‘ChChn,r”, tbc ivory goes, s,g,,,2es by referring to tlung! bke the one 1 am sntmg on, and co t5eref”re do “mmd”, “action”. “fnendshtp” and “cunning”, though perhaps II: a sbgbtly mope roundabout wey. 1 do not want to dnxsr tb,s v,e\v here, but ““Iv to po nt ““t that the new of pmmtwes ur,der d,s~uss,on holds that primihVeS, l?ke wo.dr, have t!ux meaoin&.igniticsncc m the some sort oi way, but I” their ease: hy reternng to certain rll-defined qtentat ent,t,c s. I ha e argued m d-ted elsewhere (Viilk, 1974) that thzs could not concmvnbly b,: b”, 01 be known eve” if rt were 1”.

But tlus eomwt~ip philoro?hy is not the heen of the matter what tbts new of pnmltrves doee, ,n real teims, ,s to lead to research that attempt: topstlf! partIc”- lar sets of prim,t,vc: direcrly a home way, md these days that welly means psy- choIo$cally.3 But I an argurllg that ,f formul*s, templates, conwptual degemtency

e I cannot see *et ,I:e aottan UT the ‘pw~ot”pic* ~urtihca”on DC ~x~mttivcs” mata wwa. thoqt 1 root” ba hepw I” be sbovm. I dr, nm of c~urez recRr here to worl i&c &hnrow

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Y wdRrlftmf3m~ mter1,_cmce mmd r*o;rr,‘?l bl@‘F~~ SI

,pe foormahrms, whe:e tt seems not unnetural to represent “l&n 1s at the statlon” es (AT JOHN STATlOp’;.

I hsre been tzmptod to cntaise such repmsentatlom LL) myself st Inst. on tbr grounds that they were sunply ‘3~ Engbsh words of the sentence (or somethirg very I&: ihem) teznanged m soo~e [~Ia~.~smlc v,q , 3113 ?hat therefore nathmg had been showa m srructured But, if one takes to heat the ~mnt that prnvrwe vocab- ulanes ax not awzt~& differect from tbosc eompnsag more obvlo~rl> surface xo~ds. then that critwsm cannot be mamtaned. for sky shouhl oat “Jobn”.“ar” and ‘stauon” be scmeane’s pnmi:.ve vceabulary?

Now the smlcrrrml cnticxm of tius melhod of codmg up seutence> IS unaffected That IS to say, bttle IS reveded b> such a method of c .ixess,on, urdess done m a \:ly systein>t,c manner, ‘and tt normally reba overmuch on ow int”tt,ve qvcc,a- tlon of the ~tillcture of rb ongmal sentcme, ,n such a vay as o be not really the stwcnrrmg of do example but a mere reprojestion oi the exam@_ t‘self To see thq one on’y has to thmk of wbdt ,t would b: hke to expws the fnst sentence of dus oaraga~h by such a method, the one be~nnmg ‘Now t e structural criticism etc S’

Howtver, the pomt ?t ,swe here is not rhls structural ooe but that of the stafos of :he ~‘ans m the descnptxon a~ I raised the q”won,bbt did n”t dlnwe~ It, why should , hose En&% words not be declared to be part of the prnmtwe vocabulary? For, IF as 1 have lust arEad no serious dainctioii of tvpe am be mamtamed berweer words and o&r prmxtwes, what could be nrotag wth thzt”

Well, ,i 1s essy to see what IT wrong, given that one accepts one other pnnciple namely, timt cm’s system, whatever it IS, shculd be extzns~bl: m :L non-trvial manner What we are now dlrcussmg is theforacy 01 the re,q, to adept a pb~losopl~- lcal cbald Wr have LI system clalmmg to represent the irmctcre o! natural language bolt uhl:h in izct represents It m the way e map would I+ as scale w:s one-mlle-to- onemib There would be somethmg wroog vntb such B map, that much IS clear. nnd s!miMy there IS somethmg wrong with s qrrenx whtch I. ody cxtcnslbte on ihe sarnz IC&: as what It represent* it adds to its pr;nitivcs(or~dmary words LO tlos ,ase) at rhe s.rme mte as !t adds fc the sentences covxed I am not trytng to smug. :le ball: any of the dlrtmctron bctwccn pnmirrves and non-prlmltn* moms that I have abwed, but dm only pointmg out that, lf 01.2 chooses surface wcrds as ~ne’s nnmitnes, tlwe 1s nothing theomicd1.v wrong, but there remam the pact& (and m xny new losuperable) dlf?culttes of (I) mabdlty to state s~gn~ficanr wmnnt,c generaLsatton% and (2) tke inibdity to extend one’s coverage of he Larqagc tn aayttrlng other than a mite.to~nde manner. It 1% for this reason that it stall xems possibk to m: to give up beliwag in any dlfferene: m pnnaple between pnma~ues aad otkr v/o,ds and yet advocate strongly tttr use of a Ee”slb&? selection of words ds a reduced. 01 pmm.we, sublanguage for semantic expression.

One final ipoint, nbich is not qument but merely the drawmg of a bead on a

’ The aoly att<mpt I know to do ths sort of th,n~ wtemat,ca”y 1s ~S~ndcu4l 1912,

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82 Y W,fks,fAlArrifi&l wtcff~encc end mrud Iawu~e

moic detast taxget It 19 the cz~e *itat the “se of a PLANNER, or Predicate Cdx-

lur type of represent?&” ,I! “‘qu~rt.Engltsh” thd 1 have post dixdssed IS intimately

assn Bstatcd wttl: the wew that the stsdy of reason.ilg is dtssoriable, or decouplable.

fro] 1 the study of me semantx ~txu.ture of natural language, and can be pursued t” no!etton I have w.4 d wmker of doubts about that YI~W tyxl1c4 197ha), but

here I wax, to add another whtch follows dtrectly from tht argument of this paper.

If tt IS true, as I nave argued here. that them IS tto escape from a natural langusge mto some other r&m, and iha\ a Language of representation t^rjust ,mother natud

languur~c whether ti.i primttt,cs 01 of “quasi-English”, L+en it follows that there is

no spectal extra-teirennal spheie Ix the ~‘~ammatto” of reasonmg. but only

translatzons tnto another natural language. Hence there IS no rensonlng about “atu-

nl language repardte from natural Lanyage,’ and ali we cd” do ,S to choose the language tn which we prefer to “IO&I the raasonzng and ov= whtch we prefer to

~o”,puto Tnus, to co”,p:cso thmgi somewhat. we have the chotx brtwee” comput-

ing about reasoomg in a prtr”,t,v?!ike languaea or one reduc~~lc to I, by tile

%-entrant” “tethod I derx.nbed, ot ,,I one ltke PcPNNER quaat-En&sh to whtch httle 1:. make erpbcn, and which would reqmre unotlrer system to make 1,s mt.mal

rclationshlps exphc~; for any but the most trtvlal example?

It may turn 011, that rt IS more rrnstble to sdy that lanyz~e undentandtng

depends on reasomng, rathu than ~~ce-wrw The great and the good m A I. seem to

behew thr fanner wnbotit ques(ron.and L have done “a more here tba” mtsc a few

rm:dl doucts that tt might. after aU,tur” out to be the other way around

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