 be naive to associate the meanings

a rooky dance

or an unripe dance

so we are left with a coloured spherical object.

PROCEDURAL DEDUCTIVE SYTEMS

The system requies programming techniques capable of using procedural information but at the same time expressing this information in ways which do not depend on the idiosyncracies of particular languages. PLANNER is a goal-oriented procedural language designed to specify the bill. It handles simple assertions efficiently and it can handle complex information expressable in predicate calculus. Complex information is expressed in procedural form and this can include ideas of how to go about a proof. Being goal-oriented it is not concerned about interaction between procedures. The language is concerned with achieving goals not in how they are achieved and any valid accelerator can be introduced. New theorems can be easily added. PLANNER is a uniform notation for expressing procedural knowledge just as predicate calculus is a notation for describing a limited range of information.

COMPARISON WITH OTHER PARSERS

The early machine-translator dseigners were forced to develop their own linguistics as they worked and they produced rough versions. The parsers were packages of routines that evolved as the grammars emerged and grew to handle more complex sentances. When the machine-translation failed it seemed clear that it had been premature to tackle the natural language problem without sufficient linguistic development. Computer programs for natural language took separate paths:

the first was to ignore syntax completely and to use a general pattern matching process to derive information for example SIR STUDENT and ELIZA. They limited the user to a small set of inputs or their understanding to things that ignored syntax.

the second was to take a simplified subset of English which could be handled by a well understood form of grammar. Bobrow has produced a summary of this work.

AUGMENTED TRANSITION NETWORKS

ATN's have the power of Turing machines since they have changeable registers and can transfer control depending on the state of these registers. They can handle any type of gramar that can be parsed by any machine. ATN's appear to operate more closely with the way humans work thus they give a natural and understandable representation for grammars.

GRAMMAR

As we have seen it uses the concepts of CLAUSE GROOUP and WORD

the structure of a CLAUSE is quite complex and a simplified form has been shown.

be naive to associate the meanings 

 a rooky dance 

 or an unripe dancing 

 so we are leave with a coloured spherical aim. 

 PROCEDURAL DEDUCTIVE SYTEMS 

 The system requies program techniques capable of practice procedural information but at the like meter expressing this data in ways which do not depend on the idiosyncracies of particular languages. PLANNER is a finish - oriented procedural linguistic process designed to specify the circular. It handles simple assertions efficiently and it can wield complex information expressable in predicate calculus. Complex information is expressed in adjective form and this can admit ideas of how to go about a proof. Being goal - orient it is not concerned about interaction between procedures. The language is concerned with achieving goal not in how they are achieved and any valid accelerator can be introduced. New theorems can be easily added. PLANNER is a uniform notation for expressing adjective cognition just as predicate calculus is a notation for trace a limited range of information. 

 COMPARISON WITH early PARSERS 

 The early car - translator dseigners were forced to develop their own linguistics as they exploit and they produced rough versions. The parsers were packages of routines that evolved as the grammars emerged and grew to handle more complex sentances. When the car - translation fail it seem clear that it had been premature to tackle the lifelike language problem without sufficient linguistic development. Computer programs for natural language took separate path: 

 the first was to neglect syntax completely and to use a cosmopolitan pattern matching process to derive data for example SIR STUDENT and ELIZA. They limited the exploiter to a small set of input or their understanding to thing that ignored syntax. 

 the second was to take a simplified subset of English which could be handled by a well understood form of grammar. Bobrow has produced a summary of this work. 

 AUGMENTED TRANSITION NETWORKS 

 ATN's have the ability of Turing machines since they have mutable registers and can transfer control depending on the state of these registers. They can handle any character of gramar that can be parsed by any machine. ATN's appear to operate more closely with the way humans work therefore they give a natural and understandable representation for grammars. 

 GRAMMAR 

 As we have seen it uses the concepts of article GROOUP and WORD 

 the structure of a CLAUSE is quite complex and a simplified form has been shown.
 be naive to associate the oeanings

a rooky dance

oc an undipe danze

so we are left with a colonred spheeical object.

PROCEDURAL DEDUCTIVV SYTEMS

Tye sbstem requies programminn tecgkiquev capable of uslng procedusal informatiot cuc at the same time expressing this igformatooj in ways whicr do got svptnd on the idiosyncracies of partjcular nanguages. PLAMNER is a goal-oriented profedugal language desigjed to specufy eye bill. It hxndles simklz assertiona efficiently and it can handle compkex informqtuon gxpressable mn preqicate calculus. Compnex infprmation is exiressxd ib procedural form and this can include ydeas of voc to go about a proof. Bwing coal-mrievred it ix hot cojcecned about jnteraction between procedures. Trv language is concewnqd with achieving goals not in how they ars achieved and any valie accelerator can be lntroduceq. New theorems can be easily added. PLANNER is a utiforj nouablon wir expressing procedural knowledge just as predydaue balculus is a notction for descrinijg w limited ranee of nhfkrmation.

COMPARISON WITH OJHER PQRSERS

The earky machine-translator dseignwrs were forbed ro develop their ocn linguisties as jhey wprked and they produced roufh versions. The parssfs were packages of rmutines ufat evolved as thq grammarw emzrged ana grgw to hwndle more complex sentances. When hhe mcchina-translatiln failed it seemed clear that mv had been prgmadurv to tackje thc natural languwge problem wijhout sufyicieng linguistpc develo'ment. Computqr programs fmt natural lanjuage tooh separare pathr:

ghe first was yo ignore syntax conpletely and to usc a ggnsral pattern macehung process to cerkve ijfpridtion for exdmpld SKT STUAENT and ELLZA. Theu limited the user tm a amall set of inputx jr their understwnding to thimgs that ignored sjntax.

vhe serond wss jo take a simplified subset of Snglish wjicm could be hagdlee by a well bnderstood form of grammar. Bobrow has priduced a summary od this work.

AUGMENTEB URANSITION NEVWORKS

WTN's have the power of Turing machines since tmey have changeable refisterv and can transfer control depending on the state of these registers. They can yandle any type of grakar tvac ccn be pwrsev uy any machine. ATM's appear to operate more closeuy with dhz way humans work thus they govd a natural avd understandable repressntation for grammars.

GRAMMAR

As we have xeen it uses the conceptx of CLAYSE GDOOUP and XORD

the structure of a CLABSE is quite xomppex and a simoligicd form had betn skown.

be naive to associate the meanings a or unripe dance we are left PROCEDURAL SYTEMS The system programming techniques capable using procedural information but at the time expressing this information in ways which do not depend on the idiosyncracies particular languages. PLANNER is a goal-oriented procedural language designed to specify the bill. handles assertions and can handle complex information expressable in predicate calculus. Complex information is expressed in procedural form and can include ideas of how to go about proof. Being goal-oriented it not concerned about interaction between The is concerned achieving not how they are and any valid accelerator can be introduced. New theorems can be easily added. PLANNER is a uniform for expressing just as calculus a for describing a of information. COMPARISON WITH OTHER PARSERS dseigners were forced to develop their own linguistics they worked they produced rough versions. The parsers packages of routines that evolved as the grammars and grew to handle more complex sentances. When the machine-translation failed it seemed clear that been premature to tackle natural language problem sufficient development. programs natural language separate paths: the first was to ignore syntax completely and to a general pattern matching process to derive information for example and They limited the to a small set inputs their understanding to things syntax. second a subset English which could be by a well understood form grammar. Bobrow has produced AUGMENTED TRANSITION NETWORKS ATN's have the power of machines since they have changeable registers and transfer control depending on the state of these registers. They can handle type of can be parsed by any machine. ATN's appear operate more closely with way humans work thus they give a natural and representation grammars. GRAMMAR we have seen uses the concepts CLAUSE GROOUP and structure of CLAUSE quite simplified form has been shown.
 be naive to associate the meanIngs

a rooky Dance

Or aN unRiPe daNce

sO we are left with A ColoUred spherical object.

PROcEDURaL deDUCtiVe SYTEmS

The sySTeM REquIeS pRogRaMMiNg tecHniQues capAble of usinG prOcEdural informATiOn but at the SamE time expressIng This inFoRmaTIon in WayS whicH do not DEpend oN the idiosYnCRacies OF particULAr LangUages. PLANNER is a goAL-oRIented procedurAl langUaGE dESIgnEd tO specify thE bIll. It HAndles sIMpLE ASseRTions efficienTly and it can HAndLe compLeX inFOrmatiOn expReSSabLe in predicaTe caLculus. ComPlex inFOrmatioN Is expreSsed in ProCedUral FOrM aNd tHiS Can INcLudE IdeAs of how tO gO aBout a ProoF. bEINg goAl-oRienTed it Is not concerneD abOut iNTerActioN betwEen pRoCedurEs. The lAnguaGe Is concerned with AchiEving goalS noT iN hoW tHey arE AchievEd aNd aNy valid AccelerATor CaN BE InTroduced. New theoremS cAN Be Easily adDed. PLAnnEr iS A uniform NoTatIon fOR ExpreSsinG PrOcedural KnowleDGe JuSt as preDiCate caLcUluS is A notaTIon fOr descRibing a lImiteD Range of informaTIon.

COMPARISON wiTh otHer PARsERs

The early maChinE-TranSlatOR dSeiGNers wEre foRcED tO Develop their own lingUiStics aS they Worked and they Produced roUGH Versions. the pARsERs were packages Of rouTines that eVOlved as tHe graMmars emeRged and grEW To handle MorE coMplEx sENTaNces. When the maCHIne-tRaNslatioN faIled it sEemEd cLeaR thAt It had been PrematurE tO tAcKlE thE natuRAl languaGe ProBlEm wIthouT SufficIent lInguIsTiC DevElopmenT. coMPUter PrOgRams For NaTural LangUAge Took sepArate pathS:

thE FirsT wAs To ignorE syntax compleTeLy and to use A gEneRal patTERn matchiNg process to derive informATion for ExaMple SiR STuDENT and ElIZa. They lImiTEd the uSer to a Small SeT of INPuts oR THeIr uNdErstanding TO ThiNgs thAt IgnoRed syntAx.

the second was to taKE a sImplified subsEt oF EngLISh WhiCH cOUld Be HAndLED by a well understOod form of gRaMMaR. Bobrow has PRodUcEd a summAry of thIs worK.

aUGMENTeD TRANSITiON NETWORkS

aTN's HAVe tHe power of TUring macHines sincE They hAVe ChangEabLe regiStErs And caN transFEr cOntroL depenDiNg on thE statE oF these reGisters. They can handle any Type of GramaR thAt can be paRseD By aNy machine. aTN's Appear to opEraTe mOre clOseLY with The wAY hUmaNS work Thus THey give a nATuRal AND uNderstandabLE REprEsentAtiON for grAmmaRs.

GRAMMAR

As we have SEen it uses the coNcepTS Of ClAUse GROoUp and WORD

the strUctUrE OF a CLAUSE Is Quite compleX and a simPlIFied fOrm has Been shOwn.

 be naive to associate the  meanings
a ro oky  da nc e

o r an  unripe danceso w e are left with a colo uredsp h eric a lobjec t.

PRO C ED U R ALDE DU CTI VE SY TEMS
Th e syste m requiespro gr amming techn i qu es capable  of  using proce dur al inf or mat i on bu t a t the  samet ime ex pressingth i s info r mationi n  w ayswhich do not depe n do n the idiosync racies  o f  p a r tic ula r language s.  PLAN N ER is a go a l - ori e nted procedur al language des ignedto  sp e cify t he bi ll .  It  handles si mple  assertio ns eff i ciently and itcan ha ndl e c ompl e xin for ma t ion ex pre s sab le in pr ed ic ate c alcu l u s .  Com ple x in forma tion is expre sse d in pro cedur al fo rm a nd  this  can i nclud eideas of how to  goabout a p roo f.  Be in g goa l -orien ted  it  is not  concer n edab o u t  i nteraction between  p r o ce dures. T he lan g ua ge is conce rn edwith a chiev ingg oa ls not i n howt he yare ach ie ved an dany  va lid a c cele ratorcan be i ntrod u ced. New theor e ms can be eas i ly a dd e d. P LAN NER is a un ifor m  not atio n  f ore xpres singpr o ce d ural knowledge just  a s pred icate  calculus isa notation f o r descri bing al imited range o f inf ormation.COMPARIS ON WI TH OTHER  PARSERST he early  ma chi ne- tra n s la tor dseigners w erefo rced to  de velop t hei r o wnlin gu istics as  they wo rk ed  a nd  th ey pr o duced ro ug h v er sio ns. T h e pars ers w erepa ck a ges  of rou t in e s  tha tev olve d a sthe g ramm a rsemerged  and grew  to hand le  m ore com plex sentance s.  When thema chi ne-tra n s lation f ailed it seemed clear t h at it h adbeenprem ature totac kle th e n a turallangua ge pr ob lem w ithou t su ffi ci ent lingui s t icdevel op ment . Compu ter programs for n a tur al language t ook  sep a r at e p a th s :
th e  fi r s t was to ignore  syntax co mp l et ely and to use  a  genera l patte rn ma t ching p rocess to  derive i nf orma t i onfor exampl e SIR ST UDENT and ELIZA .  T hey l imi ted th euse r toa smal l  se t ofinputs  o r thei r und er standing  to things that ignored  synta x.

t hesecond wa s t o  ta ke a simp lifi ed subsetofEng lishwhi c h cou ld b e  h and l ed by  a w e ll unders t oo d f o r mof grammar. B o bro w has  pr o duceda su mmary of this wor k .

AUGMENTED T RANS I T ION  NE T WORK S
ATN's have th e p ow e r  of Turi ng  machines s ince the yh ave c hangea ble re gisters a nd can tr ansf ercontrol d epe nd i ng on t he  s t ate of  the se  regis ters.T heyc a n handle any typ e ofg r amart hat  canbe  parsed by a ny machine . ATN's app ear to  ope ratemore cl os ely wi thth e way huma n s work th us th ey give  a  nat ura l andunde r s tanda blere pre sentation f or gr am m ars .

G RAMMA R
Aswe have s e en it us est he conc ep tso f  CLAUS E  G R O OUP and WO RD
thes t ructure of a CL A US E  is q uite c omplex  and as imp li fied fo rmh a s been sh own.

 be_naive to_associate the meanings

a rooky_dance

or an_unripe_dance

so we_are_left with a_coloured spherical object.

PROCEDURAL_DEDUCTIVE SYTEMS

The system requies_programming techniques capable_of_using procedural information but at the same time expressing this information in ways which_do_not depend_on_the_idiosyncracies of particular languages. PLANNER_is a goal-oriented procedural language_designed to_specify the bill. It handles simple assertions efficiently_and_it can handle_complex information expressable in predicate calculus. Complex information is_expressed in procedural form and this_can include ideas_of_how_to go about a_proof. Being goal-oriented it is not_concerned about interaction between procedures. The_language is concerned with achieving goals not_in how they are achieved and_any valid accelerator can be_introduced. New_theorems can be easily added._PLANNER is a_uniform notation_for expressing procedural_knowledge just as predicate calculus is_a notation for_describing a limited range of information.

COMPARISON_WITH_OTHER PARSERS

The early_machine-translator_dseigners_were forced_to develop their_own_linguistics as_they_worked and they produced rough versions._The_parsers were packages of routines that evolved_as the grammars emerged_and_grew to handle more_complex sentances. When the machine-translation_failed it seemed clear that it_had been_premature to_tackle the natural language problem without sufficient linguistic development. Computer programs_for natural language took separate paths:

the_first was to ignore_syntax completely_and_to use a_general_pattern matching_process to derive information for example SIR_STUDENT and_ELIZA. They limited the user to_a small set of_inputs_or their understanding to things that_ignored syntax.

the second was to take_a simplified subset of English_which_could_be handled by a well_understood form of grammar. Bobrow has_produced a summary_of this work.

AUGMENTED TRANSITION NETWORKS

ATN's have the_power_of Turing machines since they have_changeable_registers and can transfer control depending_on_the_state of these registers. They_can handle any type of gramar_that can be parsed by any machine. ATN's appear_to operate more_closely with the way humans_work_thus_they give a natural and understandable representation for grammars.

GRAMMAR

As we_have seen_it uses the_concepts of CLAUSE GROOUP and WORD

the structure of a CLAUSE_is quite complex and a simplified form_has been shown.
