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NATURAL LANGUAGE LEARN_N{_
BY COHRUTER
_AURENT iSIKLOSSY
SUBMITTED TO T4E CARNEGIE=.MELLON UNIvERSITy
IN PARTIAL F'U=FILLMEN? OF THE REQUIREMENTS
F.OR THE DEQREE OF Doc'roR _F PNILO_OPNY
PITTSBURGN, PENNSYLVANIA
1968
THZ$ WORK WAS SUPPORTED PARTIALLY BY TN_ DANFORTN FOUNDATION ANDPARTIALLY BY TH_ ADVANCED RESEARCH #RnJEC?$ AGENCY OF' TI4E OFFICEOF THE _ECRETARY iF DEFEN.3E {_D...146}AND _$ HON_TORED BY THE AIR
FORCE OF.FIC_ OF $CIENTIFI_ REBEARCN._R
ABSTRAOT
LEARNINQ A NATURAL LANGUAGE I_ TA_(EN AS AN IMPROVEMENT XN A
SYSTEM_ ABXLITY TO EXPRESS $1TUATION_ IN A NATURAL LANGUAGE°
TMX$ D|$S_RTATXON DESORIBE_ A COMPUTER PRO{_RAM_, CALLED ZBIE_
WRITTEN XN |BL--V_ WHIC_ AOOEBT_ THE DE_OR,IPTION OF SITUATXONS IN
k UNIFORM_ STRUCTURED -_UNOTIONkL LANGUAGE AND TRIE_ TO EXPRESS
THESE _|TUATION$ XN A NATURAL LANGUAGE o EXAMPLES ARE GIVEN _OR
GERMAN AND,, MOSTLY_ RUSSIAN°
AT RUN-TIME, ZBIE _UILD$ $1HBLE MEMORY STRUCTURE_o PATTERNS
AND SETS ARE @UILT ON TH_ RUNCTIONAL LAN_UAGEo THE TRANSLATION
RUL@$ OF THE PATTERNS AND AN IN_ONT_XT VOCABULARY PROVIDE THE
TRANSITION ?0 THE NATURAL LANGUAGE, ZBIE IS A CAUTXOUS LEARNER_
; AND AVOIDS ERRORS BY SEVERAL HEOHANISMSo ZBIE I$ OAPABLE OF SOME
_VOLUT_ONARY L_ARNINGo
III
ACKNOWLEDGMENT_
AMONG ?HE MANY STUDENTS WHO HAVE H_LPED ME, I WOULD LIKE TO
THANK ,PARTICULARLY G® BER_LA$$_ R_ F'IKB$, P, FREEMAN_ Ro GROVE
AND ?ME LOCAL IPL-V EXPERTS, R, @U_HYA{_ER AND T, CUNNINGHAMo
MY WIFE HA_ SPENT MA_Y HOURS PROOFREADING THE THESIS AND HAS
G XVEN ME MUOH MORAL SUPPORT,
ABOVE ALL I AM ZNDEBT_D TO PROFESSOR HERBERT A, SIMON FOR
HIS GUIDANCE AT ALL STAGIE_ OF T_l_ WORK°
IV
TABLE OF CONTENTS
PA_E
TITLE RAGE I
ABSTRACT Xl
ACRNOWLEDQMENT$ Ill
TABLE OF CONTENTB IV
CNAPT_R I, INTRODUCTION. C
OHAPTER lI,
A® THE FUNCTIONAL LANQUAGE_ FL,
@o THE PRO@RAM_$ XNTERN_L REPRESENTATION, 10
$ _ THE PATTERN, l_
2 = ELEHENTARY DESCRIPTION OF
THE MATCHING ROUTINE. C2
3 = TRE TRANBLATION RULE, 13
4 _ TH_ !NmCONTEXT V3CABULARY, 17
C_ THE PROGRAMt$ OR_ANI_ATION i_
RODE I, INITIALIZATI3No 18
MODE 2, SINGLE SENTENCE ANALYSIS. i9
CHART_R Ill, LEARNIN@ RUSSIAN, 34
CHARTER IV, A CRITICAL LOOK AT _g_E, 84
CHAPTER V, _NVOI 9C
APPENDIX A. CODE FOR CYRI_L_IC ALPHABET. 93
PAGE
APPENDIX 9_ _EVOLUTIONARY LEARNING to 94
@I@LIOGRAPMY, I0_
.=i..
CHA_TER I o
INTROOUCTTON,
WORKERS XN ARTIFICIAL INTELLIGENCE HAVE_ AS ONE OF THEIR
GOALS, THE WRITING OF $O=HI$TICATED COMPUTER PRO_RAM_ wMIC_ WILL
PERFORM _INTERE_TING _ AND _DIFFICULT _ TASKS. PROGRAMS CAN IMPROVE
THEIR SOPHISTICATION BY LEARNING_ ANO LEARNIN@_ I$_ INDEED, A
CENTRAL PROBLEM OF ARTIFIC:IAL INTELLIGENCE,
ONE OF TWE FIRST LEARNING TABK_ THAT HUMAN BEING9 PERFORM IS
ACQUIRING A NATURAL LANGUAGE {ABBREVIATED NL). THROUGHOUT HISTORY
MEN HAVE USED NL_S FOR COMHUNI_ATING AMONG THEMSELVES AND
INVESTIGATING AND INTERACTING WITH THE WORLD. FOR THE PAST
D_CADBj NATURAL' LAN_UAB_' COMMUNICATION OF MUMAN_ WITH COMPUTERS
HAS B_EN AN AOTIV_ AREA 0_ INTEREST IN ART|FICIAL_ XNT_LLIGENCEo
INTERESTS IN THE FIELDS OF LEARNING AND NATURAL LANGUAGE ARE
COMBINED MERE IN A PR3GRAM _CALL_D ZBIE THAT ATTEMPTS TO LEARN
NATURAL LANGUAGES AT AN ELEMENTARY LEVEL, THE TASK IS CONSIDERED
WORTHY OF INVESTIGATION IN _T$ OW_ RI_HT_ THE PROGRAM DOES NOT
TRY TO SIMULATE THE LEARNING BEHAVIOR OR HUMAN BEINGS.
NATURAL LANGUAGE L_ARNING PROQRANB HAVE BEEN FEW. TO THE
BEST OF THE AUTHOR'S _NOWLEDGE_ CORROBORATED BY A REVIEW OF
REC_NT WORR IN ARTIFIOI_L INTELLIGENCE _$OLOMONOFF _9_6)_ ONLY
ONE WORK CAN QUALIFY I UNR 1964, BY A pROCESS OF STR_NG MATCHING
AND STATISTICAL LEARNIN_ UH_ PROQRAH$ ATTEMPT TO TRANSLATE
STRINGS FROH ONE NL (NLC) INTO STRINGS OF ANOTHER NL (NL_}, THE
PROGRAMS ARE INSUFFICIENTLY DOCUMENTED TO EXPLAIN THEIR STRUCTURE
IN QETAIL_ BUT PROM THE 03TPUT$ EXH%BITED, SEVERAL LIMITS APPEAR_
THE IDIOSYNCRASIES OF NLC QIV_ DIfFICULTiES T_ THE PROGRAMS AND
THE LEARNING PROCESS SEEM_ TO CYCLEo
A BOSSIBLB CAUSE FOR THE_ LAOK _F =_NTEREST IN NL LEARNING
PROGRAMS IS THE REELING, AMONG MANY LINGUISTS, THAT TM_ LANGUAGE
LEARNING TASK I$ EXTREMELY ARDUOUS° TWO O_ THE FOREMOST
SCIENTISTS IN THE FIELD 0_ MODERN LINGUISTICS STATED (CHOMSKY AND
MILLER_ %963}_
TO IHAGXNE THAT AN ADEQUATE _RAHMAR _OULD BE SELECTED FROH THE
INFINITUDE OF CONCEIVABLE ALTERNATIVES BY $O_E PROOE_$ OF PUR_
,_ INDUCTION ON A FINITE CORPUS OF UTTERANCES IS TO MISJUDGE
_OMBLETELY THE MAGNITUDE OF THE _ROBLEH,
TWO RELATED AREA_ HAV_ qECE_VED MUCH MORE ATT_NTION_ THE
INDUCTION OR _RAMMAR$ OF ABSTRACT L_NGUAGE$ AND T_E EXTRAPOLATION
OF SB_UENCE$o _OLOMONO_F {/Q5_} OFFERED A SKETCH FOR THE
HECHANI_ATION _R LINGUISTIC L_ARN_NG_ wH_ICH DOES NOT APPEAR TO
HAVE BEEN BRO_RAMHED_ A_D_ LATER (E_4}_ HIS FORMAL T_EORY OF
INDUCTIVE _NFERENOE PRE_ENTS VARIOUS _ODEL$ FOR EXTRAPOLATING A
LONG _EQUENOE OF SYMBOLS CONTAINING ALL DATA TO BE USED IN THE
PREDICTION, A PROBABILISTI_ APPROACH IS U_ED. SIMON AND KOTOVSKY
(I@63} DESCRIBE PROGRAMS_ THAT i_DUCT RULES TO EXPLAIN THE
FORMATION OF GIVEN SERIAL ALPHABETIC PATTERNS. THE RULES CAN THEN
BE APPLIED TO CONTINUE TR_PATTERN_ PIVAR AND FINKELBTEIN (C9_4}
REPORTED ON A $1MILAR_ PERFORHAN_E-ORIBRTED PROGRAM WHICH ALSO
HANDLES INTEGER STRINGS. (FOR A REVIEW OF REC_NT RE_EARCH_ SEE
$OLOMONOFF_ 1966_. IN EITHER AREA_ THE STRING_ OON$IDERED ARE
_EMRTy_j THEY LAC_ THE CONTENT THAT NATURAL LANEUAGES POSSESS AS
WAYS OF EXPRESSING SITUATIONS OR OUR HUMAN ENVIBONMEN?o
B_FORE TRYING TO DE_INE THE LEARNING TASK, LET US CONSIDER
THE TEOHNIOUE FOR TEACHI_@ LANgUAGeS (?0 HUMANS) USED BY I. Ao
RIOHARDS AND HIS CO=WORKERS {RIOHARDS, _9_$}o IN TH_ LANGUAGE =
THROUGH = PICTURES SERIE$_ PICTURES ARE ASSOCIATED WITH SENTENCES
IN AN NL TO BE LEARNT. THE PICTURB$ ARE TO ACT AS A GENERAL
REPRESENTATION FOR ALL HUMAN BEINGS (tENGLISM THROUGH PICTURE$_
BOOK I _ I$ PREFACED IN 4C LAN_UAQE$}o THE STUDENT IS SUPPOSED TO
USE THE PIOTURE_ AS OLUE_ TO THE MEANIN_ OF THE SENTENCES AND, BY
BUOQE_IVE OOMPARISON$ OF THE SENTENCES, TO INFER_ THE VOCABULARY
AND GRAMMAR OF THE NL STUDIED.
THE STUDENT'S OWN MAIN OR _OTHER TONGUE IS @YPA$_ED_ THEREBY
AVOIDING PROBLEMS OF TRANSLATION FROM O_E TONGUE INTO ANOTHER_
INSTEAD THE _TUDENT LEAR_$ TO TRANSLATE _!TUATIO_S DIRECTLY FROM
_REALITY_ INTO A NEW _L.
{AS AN ASIDE, THE AUTHOR MAY ADD THAT HE TRIED TO LEARN
HEBREW_ ABSOLUTELY UNKN3WN BEFOREHAND, FROH _HEB_EW THROUGH
P_ICTUR@$ t, HE HAD THE ADVANTAGE OF HAV_IN@ HAD READ PREVIOUSLY
SEVERAL OTHER _LANGUA;E THROUGH PICTURES _ BOOKS IN KNOWN
LAN_UAGESJ NEVERTHELESS _E HAD GREAT DIFFICULTIES IN TRYING TO
DETERMINE THE MEANINGS OF THE PICTURES _R THE CLUES TO BE DERIVED
FROH THEM, AND HE FINALLY ABANDONED THE ENDEAVOUR. SEVERAL OTHER
PERSONS REPORTED IDENTIOA_ DIFFICULTIES.}
THE PHILOSOPHIES BEHIND ZBIE AND Io Ao RICHARD$_B BOOKLETS
ARE SIMILAR. _BIE USES A _UNCTIONAL LANGUAGE _ABBREVIATED FL} TO
REPRESENT SITUATION$_ FL _ HAS THE SAME FUNCTION IN ZBIE AS THE
PICTURES IN RIOHARDS. @Y SUCCESSIVE COMPARISONS O_ $1TUATION$, AS
REPRESENTED IN FL AND AS _XPR_$_ED IN A_ NL_ ZBXE TR_ES TO LEARN
HOW TO EXPRESS OTHER SITUATIONS REPREQENTED IN _L AND, FAILING
TNAT_ TO USE ITS PREVIOUS _NOWLEDGE TO TRY TO LEARN HOW TO
EXPRESS THE OTHER SITUATIONS. THE L_ARNIN_ SEQUENCE U_ED IS TAKEN
FROM _RU$$1AN THROUGH PICTURES _ WITH SLIGHT MODIFICATIONS°
CHAPTER IX IS DIVIDED XNTO THREE PARTS,
IN BART A_ WE DE$ORIBE FL BRIEFLY°
IN PART B, wE DESCRIBE TN_ _NTERNAL REPRESEnTATiONS USED BY
ZBIE8 FATTERNS_ SETS. TRANSLATION RULES AND IN=CONTEXT
VOOABULARY.
IN PART C_ WE DESCRIBE THE ORGANIZATION OF ZBIE AND THE _AIN
PROOES_OR ROUTINES.
SINCE CHAPTER II IS RATME_ DETA_LED_ TWE READER MAY WELL
WANT TO COME BACK TO XT A_TER READING TWE FOLLOWING CHAPTER=
CMAPTER Ill OOMMENTS ON _BXE_S LEA_NINQ OF RUSSIAN,
CHAPTER IV COMPARES IBIE WIT_ UHR_ PROGRAMS AND_D_$CUSSES
SOME OF _BIE_$ INADEQUAOI_$,
APPENDIX A SMOW$ TME CODE USED TO TRANSLATE THE RUSSIAN
CYRILLIC ALPHABET INTO LATIN ALPHANUMERICS,
APPENDIX B GIVES A SIMPLE E_AMPLE= IN _ERMAN, OF ZBIE_$
_EVQLUTIONARy LEARNING _ CAPABILITIE_o
ZBIE I$: OODED IN I_L-V (_EWELL, 1964} AND MA$ BEEN RUN ON
THE CARNEGIE=MELLON UNIVERSITY _OO G-_$ COMPUTER, S_INCE IPL=V
CODE IS TYPZCALLY UNREADABLE_ THE PROGRAM IS NOT ENCLOSED, BUT IT
I$ _E_CRIBED SEMI-FORMALLY IN CHAPTER If, PART C,
CHAPTER TIo
A_ THE FJNCTIONAL LANGUA_E_ FLo
THE PURPOSE OF FL IS TO R_PRESENT SITUATIONS IN A FASHION
SOMEWHAT SIHILAR TO THE PICTURES (AND PICTURE LANGUAGE} USED IN
THE LANGUAGE - THROUGH - _ICTUR_B SERIES. THE MAIN SPIRIT BEHIND
FL MAY BE SUMMARIZED THUS _ '_IMILAR SITUATIONS SHOULD HAVE
SIMILAR REPRESENTATION8 IN FL_ _HERB AN INTUITIVE REELING FOR
SIMILARITY IS USED_ FOR _XAHPLE THE SENTENCES I
THIS IS A HAT°
THIS IS HIS HAT. (R_F_RRING TO A BOY}
THIS I$ THE BOY'S HAT.
SHOULD HAVE SIMILAR REPRESENTATIONS IN RL. TO AVOID
IDIOSYNCRASIES OF NL_'S, RL IS NOT INFLEOTED AND OMITS ARTICLES.,
TO IMPROVE ITS DESCRIPTIVE POWER WE _AVE ADDED SOH_ SEMANTICS_.
FOR INSTANOE THE REFERENT OF P_ONOUNB I$ SPECIFICALLY MENTIONED_
HE={MAN) OR YOU=(SPOKEN BOY) _F THE PERSON SPOKEN TO IS A BOY
(REHEMBER THE BICTUREB)_
FL IS NOT UNLIKE THE LANGUAGE DESCRIBED BY REIOHENBAOH
($947) FOR HIS ANALY$1S OF ENGLISH. _NSTBAD OF THE USUAL
FUNCTIONAL NOTATION F{XI, X2,..,, XK!) W_ USE A LISP-LIKE NOTATION
(MCOARTHY 1963}, (F XI X2 ,o, X_} A_D ALSO USE DESCRIPTION LISTS_
ENCLOSED IN SQUARE BRACKETS [ A_D }o
VERBS AND FUNCTION WORDS ARE TREATED AS N-PLACB FUNCTIONS_
A FEW EXAMPLES SHOULD MAKE _O_E OF THE ELEMENTARY CONSTRUCTIONS
OLEAR,
RL ENGLISH EQUIVALENT
(BE ½AT) THX$ |$ A HAT
(BE! HAT[OF BOY|} THIS IS THE BOY'_ MAT
(BE HAT[OF (BOY}|} THIS IS HIS HAT
(Q BE BOOK HERE} IS THE BOOK HERE Q
{BEI (ON HAT TABLE}} THE MAT I$ ON TH_ TABLE
(BE_ (ON TABLE HAT}} THE TABLE IS ONTHE HAT
(B@_ (ON HAT[OF (BOY}| TABLE}} HI_ HAT IS ON TM_ TABLE
(B@ (IN {AND HAT BOOK} DRAWER})
THE HAT A_D THE BOOK ARE _N THE DRAWER
(BE {IN {{AND HAT BOOK)) (DRAWER}}} THeY ARE IN IT
INPUT TO ZBIE [B IN THE FORM OF IPLV LIST STRUCTURES
EQUXVALENT TO THEI ABOVE N3TAT!ON, THE MOST IMPORTANT FEATURES OF
FL SEEM TO BE ITS UNIF3RMITY AND STRUCTURE = FL SENTENCES ARE
USUALLY TREES_ NOT STRINGS,
TO MAKE EXPLIOIT THE BT_UOTURE OF THE TREES IN _L, IT IS
SUFFICIENT TO DEFINE A RECOGNIZER FOR THE TERMINAL NODES OF THE
TREES, THE FOLLOWIN@ ARE TERMINAL NODE_
-8-
- AN ATOMIC SYMBOL Of.E. AN I_L-V REGIONAE)
EXAMPLEZ BB, TABLE, BOY, 2.
- {<ATOMIC SYMBOL>}
BXAMPLE_ (BOY}°
= (S_EAKXNQ <ANY FL, CONSTRUCT>)
EXAMPLEI (SPEAKING BOY},
= (SPOKEN <ANY FL CONSTRUCT>}
EXAMPLE_ (SPOKEN BOY{NUMB _I}_ WHERE NUMB = _UMBERo
" {<ATOMIC SYMBOL>{NUMB <ATOMIC SYMBOL>)'}
EXAMPLE_ (MAN{NUMB _])o
- <ATOMIC SYMBOL>[NUMB _LUR|, WHERE PLUM = PLURAL.
EXAMPLES BOY{NUMB BL;JR|.
THE TERMINAL NODES IN FL ARE CALLED FL UNITS. ALL OTHER
CONSTRUCTS IN FL ARE _L OOMPLE_ STRUCTURES° THE PROGRAM
_UN_ER_TAND_' FL TO THE_ E_TENT THAT IT BECOGNIZEB THE FL UNITS OR
AN FL _TRUCTUREo
(IN THE IPL-V IMPLEMENTATION, THE SQUARE-BRACKETED
DE$ORIRTION LIST ACTUALLY OCCURS ABOVE THE £L UNIT THAT I_
DESCRIBED, SO THAT HAT{OF BOY_ LOOK_ LIKE ((0_ @0¥) HAT) WHEN
CON$1DERED PURELY AS A LIST STRUCTURE. FOR AN EXAMPLE, SEE THE
IPL-V D_BCRIPTION OF SENTENCe; 3 IN APPENDIX Bo THE ORDER
_D_$CRIBTION LIST - DESCRIBED FL UNIT_, IS MAINTAINED IN THE
PATTERN STRUCTURES, TO BE OE$CRIBEDo FOR AN EXAMPLE, SEE CHAPTER
ItI_ SENTENOE 12.}
-9=
AT THX$ STAGE FL IS A TOOL,, TO BE MOD'.I_F|EDIF NE_ESSARYo WE
HAKE NO CLAIM THAT XT IS _THE_ REPReSeNTATION,, OR THAT IT IS
UNIVERSAL, IT IS DOUBTFUL THAT THE RXCTUR_ EANGUA_E IS UNTVERSAL_
FOR INSTANCE, IN _GERMAN THROUG_ RICTUR_$_ P, 2_9, A GERMAN BOY
PLAYS BASEBALL,
=104
Bo THE PRO@RA_$ INTERNAL REPRESENTATION_
AT RUN-TIME_ ZBIE @UILDB A_D THEN USES CERTAIN MEMORY
STRUCTURES WHICH WILL NOW BE DE_CRI_EDo
- THE PATTERN.
THE MAIN WORKING STR3CTURE 15 THE PATTERN_ _HICR _$ USED TO
MATOH FL STRUCTURE$_ AND THEN, U_ING THE PATTERN,S TRANSLATION
RULEs TO TRANSLATE THE _L STRUCTURE_ INTO NL. THERE ARE TWO TYPES
OF PATTERNS_ DIFFERENTIATED BY A HARK_R ON THE DESCRIPTION LIST
(DoL,} OR THE PATTERN. A TOP PATTERN X$ USED TO MATCH FL
SENTENCESJ A BUBPATTERN TO MAT_H FL _OHP_EX SUBSTRUCTURES° A
PATTERN I$ AN ORDERED LIST OF RAIRSJ EACH PAIR OONgIST$ OF THE
NAH_ OF A SET AND AN EXTRACTOR, ON THE _.L. OF TH_ PATTERN IS THE
TRANSLATION RULE OF THE_ PATTERN, AND OTHER INFORMATION°
A MORE FORMAL DESCRIPTION OF A PATTERN CAN BE QIVEN IN
8oN,F.8
<PATTERN> Sz= <==LIST><DESCRIPTION LIST>
<P=LTST> _8= <_ET NA_E><EXTRACTOR> i
<BET NA_E><_XTRACTOR><P_LIST>
<_E$CRIPTION LIST>SS= <_TTRXBUTE><VALUE>I
<_TTRIBUTE><VALUE><DE$CRIPTZON LIST>
=11 _'
<SET NAME> 8_= AIJA2IA_ o,oETC,o,
<EXTRACTOR> |_= YIIY2tY3 ,o_ETCoo,
<ATTRIBUTE> s_= <IPL=V REGIONAL OR XNTERNAL SYMBOL>
<VALUE> _s= <IPL=V LIST STRUCTURE>
IN IPL-V, A PATTER_ IS k SIMPLE DE_CRXBABLE LI_T.
THE ELEMENTS OF A SET ARE FL ONITS OR (RECUR$IVELY)
PATTERN$_ WHICH ARE TRE4 REFERRED TO AS. SUBPATTERNS° A BET CAN
ALSO BE EMPTY_
THE TRANSLATION RULE OF A PATTERN IS A FUNCTION OF THE
EXTRACTORS OR_ THE PATTERN. E_AMPLEs
<P2> <9=1 = 2617B> <9-2 = 28570> <9-3 = 26200>
02 9-$ 04 0 04 0 04 0
O0 A4 O0 TO O0 Y1 O0 Y1
O0 Yt 02 9=2 O0 Y2 O0 Y2
O0 A3 O0 D12
O0 Y2 02 9_3
O0 013
04 26180
THE EXAMPLES ARE! TAKEN _ROM CHAPTER lit. P_ IS THE NAME OR THE
PATTERN_ ITS P-LXST I$ (A4 YI A3 Y2_J ITS DESCRIPTION L_$T X$ THE
LZST STRUCTURE 9-I, THE $_T$ ARE A4 AND A_I THE E_TRACTORS ARE Y!
AND Y_. THE TRANSLATION RULE OR THE BATTERN IS TO(P2}=9=2, TME
LIST ¢YI Y2}.
ALL OTHER ATTRIBUT_ _ VALUE PAXR$ ON THE D.Lo OR THE
PATTERNS MAY BE DISREGARDED AT THE PRESENT.
TO UNDERSTANO THE FUNCTION OF THE EXTRACTOR$_ LET US
DE$ORI@E THE PROCESS WHIC_ MATC_E_ AN FL _TRUCTURE TO A PATTERN°
- ELEMENTARY DEBORTPTION OR THB MATCHING ROUTINE°
LET US ASSUME THAT W_ WANT TO MATCH THE FL SENTENCE (BE BOY}
TO P2. WE _0 DOWN THE $_NTENC_ AND THE P-_IST 0_: THE PATTERN IN
PARALLEL. WE CHECK WHBTRER THE FIRST ELEMENT OF THE RL SENTENCE
(HERE, OBEY} |B A MEMBER OF THE RIRST _E? ON THE P-LIST OF THE
PATTERN (MERE, A4}. IN OUR CABE_ tBE_ I_ A MEM@ER OR A4, AND WE
SAY THAT _BE _ WAS (SUCCESSFULLY} MATCHED TO A4. _BE _ IS THEN
PLA_ED ON THE DESCRIPTXON LIST OF YI._ YI HAS _EXTR_CTED _ THE
ELEHENT OF THE RL SENTENC_ WHIC_ WA_ MATCHED TO A4. THE MATCHINQ
ROUTIN_ LOOPS BACK AND TESTS WHETHER TH_ _ECOND ELEMENTOR THE FL
_ENTENC_ (HERE', _BOY _} _S A MEMBER OF THE SECON_ SET ON THE
P-L_$T O_ THE PATTERN {HE_E_ A3}, ETC,oo
WHEN WE _ANT TO TRANSLATE THE MATCHED FL SENTENCE INTO NL,
WE U$_ THE T_ANSLATION RU;E OF THE PATT_RN. THE TRANSLATION RULE
OF _2 I_ TO{P2}= (Y1Y2}_ TH_ _EANIN_ OF THE TRANSLATION RULE IS
AS ROLLOW$_ TAKE THE ELEMENT EXTRACTED BY Y$_ _BE_ TRANSLATE IT
IN THE APPROPRIATE CONTEXT {HERE, THE CONTEXT CONB:IST_ OF THE SBT
A4_ OR WHICH _BE _ _A_ A MEMB_R_ AND OR THE PATTERN P2)_ THEN
FOLLOW THIS TRANSLATION {'E_TO _} BY THE TRANSLATION OR THE
ELEMENT EXTRACTED BY Y_, _BOY _, IN THE PROPER CONTEXT {H_RE_ TME
SET A3 AND THE PATTERN P2}, THE _ECOND TRANSLATION I_ _MAL$Y_K _,
$0 THAT THE TOTAL TRANSLATXON IS _E_TO MA_IYIK_ IF WE CANNOT
FINg A TRANSLATION FOR _BOY_, _E _NSERT A 'Z _ IN THE TOTAL
TRANSLATION, WHXCH WOULD BECOMES _E_TO _'°
IT MAY HAPPEN THAT, _OR EXAMPLE, THE SECOND ELEMENT OF FL 15
NOT AN FL UNIT, (SEE SENTENCE IP_ CHAPTER III}o THE MATCHIN_
ROUT|NE THEN TRIES_ RECUR_XVELY, TO FIND IN A_ A BUBPATTERN WHICH
CAN MATCH THE SECOND ELEHENT OF FL,
THE MATOHINQ ROUTINE USES ONLY SET INCEUSION TESTS, BUT USES
THEM RECUR$1VELY, IT IS SEEN THAT A NECESSARY CONDITION FOR MATCH
IS THAT THE LENQTH OF TH_ FL STRUCTURE AT ITS TOP LEVEL BE EQUAL
TO THE NUM@ER OF' PAIRS {$ET_ EXTRACTOR} IN THE PATTERN, THE
MATOHIN_ ROUTIN_ WILL BE CON$10_RED IN _ETAIL IN CHAPTER II_ HART
C_
3 - T_E TRANSLATION RULE,
THE TRANSLATION RULE TO{PATTERN} IS A FUNCTION _ROM THE
EXTRAOTOR$ OF THE PATTERN INTO NL AUgMeNTED BY Z'$_ WHERE A Z
INDICATES THAT BO_ETHIN_ WAS NOT TRAN_LATED_ A HEW EXAMPLES
FOLLOW|
A} 61NEAR ARRANGEMENT OR THE EXTRACTORS=
<P37> <9-1 = 2650_> <9-_ = _7334> <g-3 = 2_C_)
02 9-_ 04 0 04 0 O_ 0
O0 AI_ O0 TO O0 Y96 O0 Y96
O0 y97 02 9=_ O0 Y97 O0 Y97
O0 A2 O0 052 O0 Y9_ O0 Y9_
O0 Yg6 02 g=3
o0 A13 O0 D13
O0 Y95 84 27144
O0 Dg
O0 A14
O0 VO
O0 J4
THE TRANSLATION RUL_ OF P37 l_ TO{P_7_ = (Yg6 Yg7 YgS}_ AND
IS TO BE READ AS FOLLOW_| LOOK UP ZN THE VOCABULARY_ IN THE
PRO_ER CONTEXT {HERE, OF THE SET A2 AND THE PATTERN _37}_ THE
TRANSLATION OF THE PART OF THE;FLSTRUCTURE THAT_A_ MATOHED TO
A2J THEN FOLLeW THIS TRANSLATION 8Y THE TRANSLATION, IN THE
PROPE_ CONTEXT, OF THE PART OR THE FL STRUCTURE THAT WAS MATCHED
TO _$2, ETC.°,
6) LINEA_ ARRANGEMENTOF SOME OF TN_ EXTRACTOR$o
<PI> <9"1 = 2541B> <g-2 = _5752> <g-3 = 252_)
02 g-1 04 0 04 0 04 0
O0 AI O0 PO 00 PO O0 Y2
O0 Y$ 0219"2 O0 Y3
O0 A2 O0 YO
O0 Y2 O0 J3
O0 A3 O0 J4
O0 Y3 O0 J3
o0 TO
02 g-3
THE TRANSLATION RULE OF B$ IS TO{PI} = ¢Y2 Y3}= XT IS TO BE
READ AS IN OASE A} ABOVE. NOTICE_TMAT T_E_EXTRAOTOR Y_ |$ MIB$1NG
IN THE TRANSLATION RULE. SUCH k RULB CAN BE USED WHEN SOME FL
PART IS NOT EXPRESSED IN _L_,
C} _ROUP|NG O_ SOME EXTRACTORS.
<PO> <9-1 = 25458) <9=2 _ 25228> <g-3 = 2_5P4)
02 g-$ 04 0 04 0 04 0
O0 AI O0 TO 02 9-3 O0 Y1
O0 Y1 02 9=2 O0 Y_ O0 Y2
O0 A2
O0 Y2
O0 A3
O0 Y3
THE TRANSLATION RUL_ I$ TO'BE READ AS FOLLOWSS TAKE THE FL
STRUCTURE THAT WAS MATCHED_TO At, FOLLOW THIS STRUCTURE BY THE FL
$TRUCTURB THAT WAS: MATCHED TO A_I THEN LOOK UR TM|_S FL ¢OMPLE×
STRUCTURG IN TRE VOCABULARY IN THE PROPER CONTEXT (M_RE_ OF TME
PATTERN PO}o THE NL STRXN_ _ OBTAINED IS FOLLOWED BY THE
TRANSLATXON OR, THE ELEMENT EXTRACTED BY Y3, AS ABOVE_ TO _IVE THE
TRANSLATION OF_ THE STRUCTURE MATCHED TO PO_
BXAMPLE8 (OMAPTER_ IiI_ SENTENCE $.) IF WE MATCH {BE (MAN)
MERE} TO PO, WE SHALL_ _OOK U_ THE FL COMPLEX (BE {MAN}} IN THE
VOCABULARY, AND HOLLOW THE TRANSLATION OF {BE (MAN}} BY TME
TRANSLAT_ION OF _HERE _ {IN THE PROPER CONTBXT}.
THE ABOVE THREE_FUNOTION$ ARE NOW USED BY ZBIE, NOTE THAT
SXNOE THE FL STRUCTURE MATCHED TO A!, SAY, CAN, BE A COMPLEX FL
PART_ A RECURSXVE TRANSLATION LOOK=UP XS X_PLI_XT IN THE
TRANSLATXON RULES, FOR A DETAILED _XAMPLE_ SEE _HAPTER |||,
SENTENCE, SZ,
THE TRANSLATION _ULE FUNCTXONS CAN BE GENERALXZED
IMMEDIATELY. TWO EXAHPLES_OF DIFFERENT TRANSLATION RULES FOLLOW,
AND MANY MORE COULD BE DREA_ED UP_= {WE ASSUME A PATTERN WITH
EXTRACTORS Y20 AND Y21)I
D} XNTRODUCTION OF CONSTANTS.
19_ 0
Y2%
NLI
Y20, O
WHERE NL| X$!SOME STRING XN NL. SUCH A RULE COULD BEU_EO WHEN
SOME:EXPRESSION IN NL_ HAS IDIOMATIC FILLERS.
E) _ISJOINT PARTS:,
9_ O
FIRST(Y2$}
Y20
SEOOND{Y21} O
WHERE _ FIRST AND SEOOND ARE FUNCTIONS _WHi|CH MUST BE DEFINED) ON
THE TRANSLATION OF THE FL;STRUCTURE=WHIOR WAS EXTRA_TED BY Y2%_
SUCH A RULE OOULD BE USED TO HANDLE SEPARABLE GERMAN VERBS.
4, = T_E XN-OONTEXT VOOABULA_Y_
THE VOCABULARY OF;ZBIE HAS THE TWO FOLLOWING FORMS_I
A} FL UNIT=FL(X}_ SET=ACJ}_ PATTE_N_PCK_a NL STRXNG=NL(L},
TO 6E INTERPRETED= THE_ TRANSLATXON OF THE FL_ UNZT FL!(1) WHEN A
MEMBER OF THE_ SET A{J} A_D IN THE CONTEXT OF_THE PATTERN P{K} IS
THE STRING OF, NL_WORDB NL(L_}.
B} FL OOMPLEX=FL{I}, PATTERN=B{J.}_ NLJSTRING=NL{K}
TO @E INTERPRETED!! THE TRANSLATION OF TRE F_ COMPLEX RL_(I} IN THE
CONTEXT OF THE PATTERN B(J) IS THE 9TRINE N_{K} IN,NL.
NOTE THAT WE_OANNOT CONCLUDE THAT SONE FL UNIT FL(I} HAS: A
TRANSLAT|ON IN_ THE CONTEXT A{J}, P(R) FROM THE;KNOWLEDGE THAT
FL(X} IS A MEMBER OR A{J}. WE MAY HAVE A TRANSLATION !N THE
CONTEXT OR SOME_ OTHER_ PATTERN P{Kt}_ OR, FOR THAT MATTER_ NONE AT
ALLo
C, THE _ROGRAMt_ ORGANI_ATXON,
THE CONTROL STRUCTURE OF _BXE CONSISTS OF TWO MODSS° THERE
IS FIRST AN INITIALIZATION OF' THE INTER_AL STRUCTURe, WHEN A
FIRST PATTERN |5 CONSTRUCTED, THE CONTROL THEN pASSES TO A SECOND
MODE. WHEN SITUATIONS ARE _ROUGHT IN ONE BY ONE AND PROCESSEDo
MODE I. INITIALIZATION.
TWO S|TUATXONS ARE! P..qESENTEDTO ZB!E, REPRESENTEI) IN FL AND
EXPRES$_I) |N NL, THE $_ITLJAT!ONSMU_T BB SUFFICIENTLY $|MILAR_ $0
THAT BY COMBARING THEM _BIE CAN D_DUCE ITS FIRST PATTERN°
MORE PRECISELY, ZS'IE EXPECTS_| THAT THE TWO,FLI SENTENCES WILL
BE OF DEPTH O_ I,E, HAV_ NO FL'_COMPLE_ SUBSTRUCTUREj THAT THEY
WILL, HAVE, EXACTLYONE ELEMENT DIFFERENT AND IN THE, SAME POBITION_
AND THAT THE TWO _ORRESPO_DXNG NL SENTENCES_ WILL HAVE, EXACTLY ONE
ELEHENT DIFRERENTAND IN THESAME_POSITION, WHICHMU_TBE AT THE
BEGINNIN@ OR_ AT_THE_ND OR {EITHER} NL SENTENCE_. THE DISTINCT
ELEMENTS IN RL AN_I NL_ ARE THEN: ASSUMED TO OORRESPOND TO EACH
OTH@R_ THE_ COMMON PART_ IN FL_ AND NL AR_ AL_O ASSUMED TO
CORRESPOND T_ EACH OTWER AND A R'IRST PATTERN PO |$;_SET UP_ WITH
ITS _ET$_ AND TRANSLATION RULE_ THE %_-CONTEXT VOCABULARY I$
IN_TIAT_.
MODE 2, S_INGL_ SENTENCE ANA_YSXS.
AFTER XNITZALtZATION, 7B|E_ O_ERATES _N THE FOLLOWING HODEo
FIRST* THE PREVIOUSLY P_OCESSED FL AN_ NL SENTE_CES_ARE ERASED_
THEN, THE DESORIPTION_ |_; RL OR; A SITUATION IS READ _N_ TOGETHER
WITH_ _T$ EXPRESSZON IN NL_ WHICH IS STORED FOR!LATER USE_. THE FL
SENTENCE |$_ THEN PROCESSED FOLLOWING THE BASIC fLOW CHART BELOW
(WRITTEN IN AN_ALSOL-LIKE, LANGUAGE_ t<t. AND t>, DELIHITBLOCK$)S
SXNSLE!SENTENCE PROCESSOR;,
FOR ALL TOP PATTERNS (LAST'CREATED_ FXR_T CONSIDERED} DO
<HATCH FL TO' TOP PATT_R_J
COMHEN?| THE_NATCHING_ROUTXNE_XS _ESCRIBED XN PART _ BELO_
IF,TOTAL HATCH THEN
<TRANSLATE_
|R T_ANSLAT|ON HAS NO UNKNOWNSTHEN <_O_PARE TO _NPUT NL_
_F T_ANSLAT_ON = INPUT _L_ THEN (EXIT AND _EAD |N THE NEXT
SITUATION> ELSE GO TO,E_ROR RECOVERY>
ELSE IF, T_ANSLATION IS CONSISTENT _|TH_ INPUT NL THEN STORE
PATTERN LI_T IN_ _ATTERN LIST HOLDER TO PRO_E$S ELSE DO
NOTHINg>
CO_HENT_ THE_CON$1S_E_CY TEST I$ DE_CRi|BED IN PART _I
E6SE STORE_ PATTERN LIST |N PATTERN LI_T HOL_ER>,
PROOES_ ELEMENTS ON_THE;BATTERN_L_IST HOLDER
COH_ENT_ PROCESSING THEiPATTERN L_ISTS _=DESCRI_ED IN; _ART 3_
<IF _ _ROC_SSING _ $U_CESSRUL, THEN (E_IT AND _EAD_ IN THE NEXT
SXTUATXON>>:
COHHENT s EVERYTH_XNG FAILE9 SO HAR_
CREAT_ A NEW TOP PATTERN _O_ THE SITUATXON,
COMMENTt THE PATTERN OREAT|NQ, ROUTINE Ig DESCRIBED XN PART 4_
@ERORE DE$CRIBINQ _OW THE' PATTERN LZST$ARE'PROCESSED_ LET
US EXPLAIN SOME_ OF_ THE TERMS USED,
WE SAW IN CHAPTER XI_ PART'B HOW AN F6 SENTENCE_ WAS MATCHED
TO A PATTERN, ONE OR THE MAIN ROUTIN_$ OF ZBXE IS THE HATCHIN_
ROUTINE, WH|CH_OBTAZN$_ ALL POSSIBLE TOTAL_ AND PARTIAL MATCHES OR
PATTERNS ¢ANDI,$UBPATTERN$) TO_AN,_L SENTENOE, L_T US _ONSIDER THE
MATOHING HEOHANi|SM A@AIN,
PART i -_THE HATCHING ROUTXNE.
AN FL SENTENCE |$_A TREE STRUCTURE_ THE TERHINAL_NODE$ ARE
THE RL UNITS, THE_ SET$_ OF TH_ P=LI_T OF A TOP_ PATTERN CAN BE
VIEWEO AS THEI ZERO-TH'LEV_L!OR A TREE_ THEPATTERN TREE_. THE SETS
THEMSELVES _, CAN; OONTAIN {SUB)PATTERNSj WE CAN TH_INK OF EACH
SU@PATTERN AS INITIATIN_ A NEw BRANCH OR THE PATTERN TREE, AN
_N_TANCE OR _ A _ET WILL_ BE _ONB|DERED A_ A TE_M|NAL_NODE OF THE
PATTERN TREE' IF WE SELECT AN FL UNIT OF THE, SETo, XF_ WE SELECT A
SUBBATTERN OF THE: SET_ THE INBTANOE OF THE SET WILL, BE CONSIDERED
AB A NON-TERMINAL;NODE_ AND THE _UBPATTERN WILLi IN_T'IATE, A NEW
SUBTREE. _INCE A SUBPATTERN $P$ HAY HAVE ON IT$P-L_IST. THE NAME
OF A BET WHZ_H CONTA|4$ A CSUB}PATTERN P2 _UCH_ THAT P_ I$ AN
ANCESTOR OR BP_ A TOP _ATTERN OAN BE CONSIDERED AS THE HEAD OF
AN _NF|NXTY OR TREES OF A_BITRA_IEY LARGE DEPTH° HOWEVEr= $INOE_
ANY FL SENTENCE IS A F'IN_ZTE TREE_ NO PATTERN TREE_ OF A DEPTH
SUPER|OR TO THE DEPTH_OR THE FL; SENTENCE NEED BE CONStDERED,
THE PATTERN TREE$_ FORMED BY THE PATTERNS RESEHBLE A
DI$ORIHINATZON NET, A NET OR' DEPTH_N CANNOT DISTINGUISH BETWEEN
TWO TREES OF DEPTH LARGER THAN N WHICH ARE IDENTICAL_UP TO AND
INCLUDXNQ DEB?H No HOWEVER_ IN _OMECASE$, N DIFFERENT PATTERNS
COULD OISTINGUISH TWO SUCH;TREES THANKS TO THE RECUR_IVE FEATURE
OF THE PATTERNS_, THE PATTERN TREE$_ARE, THEREFORE_ MORE POWERFUL
THAN A SIMPLE DISCRIMINATION NET.
WE CAN VIEW THEI _ATCHINQ PROCESS AS A TEST OR_ WHETHER A
PATTERN TREE _ IS CLOSE TO BERING ISOMORPHIC TO THE;FL SENTENCE
TREE, AN FL BENTENCE_ TREE; i$ ISOMORPHIO TO A PATTERN TREE IF THE
TREES CAN BE_SUPERIMPOSEDI_ ANDr THE TE_MINAL_ NODES (RL UNITS} OF
THE FL SENTENCE ARE RESPECTIVELY IDENTICAL TO THE_TERM;INAL NODES
(FL UNITS OF TERMINAL: SETg} OF THE PATTERN TREE. USUALLY WE 9HALL.
HAVE_ NO ISOMORBHIBM_ WE THEN LO0_ FOR AS GOOD A FlIT OF, A PATTERN
TREE_ TO THE FL SENTENOEIAS_WE CAN FXND.
DISREGARDIN8 THE. BOOKK_EPI_G. CHORE_ INVOLVED IN _AOKTRACKING
AND RE_UR$1ON_ IT IS: ENOUGH TO CON_IDER MOW AN FL SUBTREE IS
MATOH_D TO AN ELEMENT O_ A _ET_ NODE OR THE PATTERN TREE, BY
CON$1DERIN@ THE TOP _ATTE_N_ AS ELEMENT_ OF, A BET, NO _ENERALITY
IS EO_T, WE TREAT THE_ SPECIAL CASE OF AN EMPTY SET BY POSTULATING
AN EMPTY ELEMENT FOR _UOH A SET,
PART I,I _ OUTL_NE_OR TH_ HATOH_NG ROUTINEo
MATCH FL {SUB}TREE TO _LSMENT OF SETJ
COMMENT8 QUICK EXITSJ
ELSET _= ELEHENT OF SETJ
FLTREE=z FL SUBTREEJ
(IF ELSET ISAN RL WHOLE OR IF ELS_T IS EMPTY} THEN _NO MATCHt_
GO TO EXIT>J
COMMENTS ELSET |S A ($U6}PATTE_N_
IF LENGTH (P=LIST OFf EL$ST} _= 2 _ LENGTH OF FLT_EE
THEN <_NO MATCH_tl GO TO EXIT>J
OOMMENTS INITIAL'IZE LOOPJ
MZSTAKE OOUNTER_8_ 0J
COMMENTs THE MXSTARE O0_NTER XS ASSOCXATED WITH THI_ PARTXCULAR
LEVEL, AS ARE THE OTHER IDENTIFIER$_
I 81 OJ
LOOP_
IF MISTAKE COUNTER > I TH_N <_NO _ATCH_ GO TO _XIT>_
IF I-TH SGN OF' FL_REE'D_E$: NOT _XIST TH_N @0 TO EXITI
I_LTRE_ |_ !-_H SON OF _LTREE_
IEL_ET _ |-TR SET OF P_LIIBT 0_: EL_ET_
_R _FLTREE _$:A_ FL_ WHOLE THEN
<IF IRLTREE |B A HEHBER OR IELBBT THEN
_0 TO LO0_
ELSE <MISTAKE COUNTBR |= MI-_TAKE COUNTER . C_ GO TO LOOP>>
ELSE <MATOH IFLTREE TO THE _L_MENT$ O_ IELSET_
COMHENTI THE MATCH IS T.qIED SUCCE_SIVELY ON ALL THE ELEMENTS OF'
IELSET. THANKS TO T_E HIDDEN BOOKKEEPING. WE ONLY HAVE TO
CONSIDER THE MATCH FOR ONE ELEM_NT_
IF R@TURN _NO MATCH_ THEN
<MISTAKE COUNTER s-_MISTAKE COUNTER., $_ GO TO LOOP).
ELSE GO TO LOOP>
IT IS SEEN THAT,. BASICALLY_. UR TO ONE 'MISTAKE, (AS DERINED
BY THE PROGRAM} IS ALLOWED AT A G_VEN LBVEL IN A SUBT_E_o
PART io2 = USE OF THE MATOHIN@ ROUTI_.!E.
THE MATCHING ROUTINE F!IND$ PATTERN L_STB, WHICH XT STORES IN
A PATTERN LIIST HOLDER IN DECREASING O_DER OF MATCH-DEPTHo A
PATTERN LIST IS A LIST 0_ PATTERNS, HEADED BY A TOP PATTERN AND
CONTAINING OTHER (OR PO$$|BLY _0} _UBPATTERNS WHICH wERE MATCHED
TO SU@STRUCTURE$ OF THE FL SE4TENOEo WITH THE: PATTERN LIST IS
ASSOCIATED A CORRESPONDING LIST OF FL COMPLEX STRUCTURES IN
ONE®TO-ONE OORREBPONDENOE WITH TH_ SUBPATTERN$ THEY HATCHED, THE
MATOHING ROUTINE ALSO, RECORD_ THE DEEPEST LEVEL; IN THE FL
SENTENCE TO WHICH THE MATCH WAS CARRIED. THE MATCH-DEPTH. AND
WHETHER THE HATCH WA$:TOTAL_ OR _ARTIALo A MATCH IS PARTIAL IF AT
ANY POI_T_ DURIN@_ THE MATCH_ OR A PATTERN TREE TO THE RL SENTENCE.
A MZSTAKE COUNTER WA$_ INC_EMENT_Do TH_ MATCH-_EBTH |$ A MEASURE
OF HOW GOOD THE MATCH OF THE FL_ _ENTEN_E TO THE PATTBRN LIST HAS
BE_ AND ZSI_ LOO_S AT_T_E BESTMATCHES _RST,
WHBN THE TRANSLATION OF A PATTERN L_IST IS ATTEH_TED_ IT HAY
HAPPEN THAT $OME_FL_ STRUOTURE CANNOT BE TRANSLATED, ROR EXAMPLB_
THE BTRUCTURB MAY BE_ AN FL UNIT WITH NO TRANSLATION IN THE
CONTEXT OONS'IDERED_ OR IT_ IB AN FL COMPLEX PART WHIOH_ FOR THE
PARTICULAR PATTERN LI_T OO_$1DERED, HAS NO, OORRESPONDING
SUBRATTERN TO;WHXOHIT WAS:HATCHEDo R_ THEN INSERT A Z OZO, ZI,
Z2_ ...) IN THE TRANSLATION. THE' ZIg CON$1DERED By ZBIE TO BE
THE RESULT OF; AN UNFULFILLED EXPECTATION_ AND ZBIE; CABITALIZBB ON
THESE EXPECTATIONS _ FOR LEARNING. 7BIE, OHBO_B WHETHER THE
TRANSLATION OBTAINED IS_00NSIST_NT_ITH_ THE; INPUT NL 9ENTENCEo
PART 2 _.THB _ON$1$TENCy TEST,
_E CAN IHAGINE; THAT TH_ TRANSLATe|ON AN_ THE INPUT NL
SENTENCE ARE PUT _IDE BY S_IDE, _E SHALL;HAVE CONSISTENCY IF _E
CAN REPLACE, THE:Z'S OR THe;TRANSLATION BY _ON_EMPTY STRXN_S IN NL
IN A UNIQUE NON-AMBIgUOUS WAY $0 THAT THE TRANSLATION BECOMES
IDENTICAL TO THE INPUT. _HETHER THIS CAN BE DONE OR NOT IS OFTEN
TRIVIAL IF NO, TWO Z_ ARE ADJACENT. WHEN TWO_ OR MORE Z_$ ARE
ADJAOENT_ ZBIE_ DOES' NOT_,IVE_ U_ BUT REBLACES THE_F;IRBT Z BY AN
APPROPRIATE _OOD _UEB$; (IR_AVAILABLE, BEE BELOW). THE VARIOUS
GUESSES THAT _ILL' BE TRIBD ARE BR|N_ED. IF PROGRESS IS _ADE
TOWARDS CON$:IBTEN_Y_ THE GUESS IB _DOPTED (_E _0, NOT HAVE
COMPLETE BACKTRACKINQ'HEREI)_ ANDI;_E CONTINUE. OTHERWISE, GUESSES
ARE TRIED FOR_ THE SECOND _, IF THIS LAST RE5ORT FAIL$_ THE
TRANSLATION AND_ THE INPUT NL _ENTENCE A_E,_OT CO_$1$TENTo
HERE WE_SEE AN EXAMPLE OF THE CAUTION ZBIE USES XN LEARNZNQo
XF WE WANT Z _$ TO CORRESPOND TO THE NL: STRING NLI NL2 NL3, WE
CAN MAKE TH6 CORRESPONDENCE IN TWO WAYS (THE ZtS MUST _E MATCHED
TO NON-EMPTY STRINGS IN_ NL!}|
Z_NLE_ Z$_NL2 NL3;
Z_NL$ NL2, ZI_NL3J
HOWEVER, XF IT IS A GOOD GUESS T_ ASSUHE THAT Z_NL$, THEN WE CAN
LET ZI_NL_ NL3o
AN EXAMPLE FROM CHAPTER |If {SENTENCE 4} WILL_ ILLUSTRATE THE
POINT, WE A_E TESTING TH_ CON$1$TENCY OF {Z Zl} AND {TI2 ZDES$}o
{Z ZE} XS TH_ TRANSLAT_O_ OF {BE (_POK_N BOY} HERE}. _Z_ COMES
FROM THE UNKNOWN TRANSLATION OF {SPOKEN BOY} AND t_1_ FROM THE_
UNKNOWN TRANSLATION OR _MERE t, WITH NO ADDITIONAL INRO_MATION,
ZBI@ _EFUSES_ TO MAKE A CORRESPONDENCE BETWEEN THE_ Z_ AND THE NL'
WORO$, AND WOULD FINO TR_ SENTENCE _TO0 HAROLD {STRIOTLY, WE _
SHOULD LET Z_TI2, Zl_ZOESI AS _S CORRESPOND TO NON-EMPTY
STR|N_$, BUT ZBI_ I$ _VE_ MORE CAUTIOUS.} HOWEVER, IT _$ A '_OOD
QUES$_, IN THIS CONTEXT, TO A_$UME THAT THE TRANSLATION OR _HERE'
IS _DE_$_, $0 THAT, AS A R_ULT_ Z_TI2,
IR $O_E PATTERN LI_T COMPLBTELY _ATCHE$ AN FL _ENTENCE AND
WE OBTAIN A TOTAL TRANSLATION {_ITROUT ANY Z_S} WHICH I$ NOT
IDENTICAL TO THE INPUT NL_ SEVERAL PO$SIB_LITIE_ ARISE_
I} THERE WA_ A RISTAKE IN THE' 14PUT {THAT HAS: HAPPENED).
_} THE TRANSLATION AND THE INPUT ARE TWO DIFFERENT WAYS OR
EXPRESSING THE SAME $1TUATION, HERE A TEACHER CAND PREFERABLY A
TIH_ SHARING: SITUATION} I$ NEEDED TO CONVEY THE INFORMATION TO
ZBI_o
3} ZBIE MADE SOME ERROR SOMEWHERE AND _HOU_D TRY TO RECOVER FROM
THIS BRROR, QOOD ERROR RECOVERY IS A VERY HARD PROBLEM WHICH WILL
BE MENT|ONED LATER, AT THIB! STAGE, ZBIE POBSESSEB NO ERROR
RECOVERY MEOHANISM, IT WAS FELT' THAT T_YI_G TO AVOID ERRORS IS A
MORE FRUITFUL APPROACH THAN TRYING TO RECOVER FROM THEM, THE
ERROR AVOIDINB MECHANISM I$ POWERFUL ENOUGH $0 THAT ZBIE ACTUALLY
MAKES NO ERRORB WHEN ?EBTED ON THE $!HPLE SENTENOES GIVEN AS
EXAMPLES,
PART 3 - PR3CE$SING THE PATTERN LISTS,
WE NOW RETURN TO THE BASIC FLOW-CHART. THE PROCES$1NG I$
$LXL_HTLY DIFFERENT FOR FL SENTENCES WITH FL O0,_PLEX PARTS THAN
FOR LINEAR RL SENTENOE$1 {C)FDEPTH 0}_ LET US DESCRIB_ PROCES$1NG
THE FORMER BENTBN{_ES,
PART 3e$ - PATTERN L_IST$ OR RL SENTENCES WITH COMPLEX PARTS,
COMMENT 8 PROOES$ PATTERN L_ISTSJ
ROR ALL PATTERN LZST$ OF_THE DEEPEST LEVEL {THEN DEEPEST LEVEL
1_ ETC,,,} 00
<TRANSLATE PATTERN LISTSJ
KEEp ONLY PATTERN LISTS WHICH_HAVE A TRANSLATION CONSISTENT
WITH THE INPUT NLI
PROCBSS _ PATTERN LIST$ WITH CON_ISTBNT TRANSLATION, BTARTIN@
WITH THE PATTERN Li|S?$_ THAT HAVE A TRANSLATION WITH THE
GREATEST NUMBER_ OF COMMON ELEMENTS WITH THE INPUT NL SENTENCE>
_N OTHER_ WORDS, Z@IE _OES A TRANSLATION _IN_PARALLEL _ OR ALL
PATTERN LISTS THAT MATOHED THE INPUT FL SENTENOE TO A GIVEN
DEPTHa STARTING WITH TH_ 4AXIMU4 DEPTH CBEST MATCHES} FXRSTo ZBXE
THEN DI$CARDB THEi PATTErN, LISTS W_ICH DID NOT GIVE k CONSISTENT
TRANSLATION AND STARTS PROCE$$XNG_ THE PATTERN LISTS WITH THE BEST
FIT TO THE INPUT, AS MEASURED _Y A SET INTERSECTTON WITH THE
INPUT NL SENTENOE,
3,1.1 - PROCESSING THE Zt$.
P_OCE$$1NG SUCH A TRANSLATION I_ EQUIVALENT TO PROCESSING
THE Z_, EACH Z TAKES THE PLACE OR SOME UNTRANSLATEO RL_ STRUCTURE
RLZ ANO, THROUGH THE CONSISTENCY TEST ¢PART 2 ABOVE}m THE Z 15 TO
BE REPLACED _Y A NON-EMPTYNL STRING NL_. FROM THE Z WE CAN ALSO
OBTAIN INRORMAT_ION SUCH: AS_| TO WHICH SET_ AZm DID WE TRY TO MATCH
FLZJ wHICH WA$_ THE PATTERN, P_, TO WHICH THE FATHE_ OF FLZ ¢IN
T_E FL SENTENCE TREE) WAS BEING MATCHED,
IF FL_ I_ A UNIT_ WE INSERT FLZ IN A_ AN_ SET UP THE
IN-OONTEXT VOCA@ULARY RLZ AZ P_ NLZo
IF RL_ IS A COMPLEX FLi_ WE TRY TO CREATE A LIST OR
SUBPATTERN$ TO MATCH FLZ TO NLZ ¢$EE BELOW_. IF SUCCEBBFUL_ WE
WOU6D LIKE TO INSERT THE TOP _UBPATTERN 0_ THE LI_T AT THE TOP OR
AZ,
=2B=
BEFORE INSERTING_ WE CHECK_ TO MAK_ BURE_ THAT THE SUBPATTERN
LIST WILL NOT CAUSE AMBIGUITIES, THIS CAN HAPPEN IR THERE IS
ALREADY IN AZ A SUSPATT_RN LIST $PI OR, WHICH THE NEW SUgPATTERN
LIST SR2 IS A HOHOMORPHIC IMAGE, I,Eo SETS OF SP_ ARE SUBSETS OF
THE CORRESPONDING SETS OR SPI AND THE TRANSLATIONS OR THE
SUBRATTERN$ IN SPC AND SB_ ARE APPROPRIATELY IDENT_ICAL_ IR SUCH A
CON_ITION IS SATISFIED (WITH SOHE MINOR ADDITIONS}_ NO INSERTION
TAKES PLACE, _NOT I_BERTEDt IS PRINTED, AND PROCES$ING OF THE
PATTERN LIST I$ ENDED,
IF AN FL COMPLE_ PART IS TO BE HATCHED TO A SETm THE
BACK=TRACKINQ_ HATCHING ROUTINE WILL _ SEA_CH F_R ALL THE
SUBPATTERNS (OF;THE BET) THAT WILL' MATCH THE FL COMPLEX PART, IF
TWO SUBBATTERNS CAN TRANSLATE THE FL OOMPEEX PART (IN DIFFERENT
WAYS}, THEN A POTENTIALi AMBIGUITY IS INTRODUCED IN THE $YSTEHo
EXAHPLEI IN CHAPTER Ill, SENTENCE 27, THE FL'OORPLE_ {HOD THIS]
IS TRANSLATED AS _E2TOT t BY SUBPATTE_N P33 AND AS; ,E2TA t By
SUBBATTERN P_2, THE TWO SUBPATTERN_ WILL CAUSE AMBIQUITY IF THEY
BELONG TO THE SAME SET,
HERE IS ANOTHER BXAHPLE _}FHO# ZEIIE TRIES TO AVOID GRRORSo
THE CONTEXT IN WHIOH THE SUBPATT_RN$ WERE ORIGINALLY GUILT WAS
TOO SHALL_ AND POSSIBLY = LATER, BY WIDENING THE CONTEXT,
SUB_ATTERNS CAN BE BUILT WITHOUT RISKING AMBI{_UITIE_ AT A LATER
TIME,,
NOTE THAT WE INSERT THE HEAD OF'_A _UBPATTERN LI$_' AT THE TOP
OF AZ SO THAT IF THE SAHE _L SENTENCE IB PRE_ENT_D ONOE MORE
IMMEDIATELY AFTERWARDS, IT WILL B_ MATCHED WITHOUT ANY
BACKTRACKING USING THE SU_PATTE_N{$:} JUST CREATED.
PART 3_2 =-PATTERN L_IST$ OF LINEAR FL SENTEN_ESo
WHEN PROCESSING LINEAR FL BENTENC_S, WE ARE ONLY CONCERNED
WITH TOP PATTERNS. PROCESSING ALL TOP PATTERNS WH;ICH GAVE A
PARTIAL HATCH WOULD BE WASTEFUL, _0 WE PROCESS THEM AS A STACK_
LAST CREATEO, FIRST CONSIDERED. HOWEVER IF A PATTERN I$ F|RST
CON$1D_RED, AND ITS TRANSLATION I_ JUg? Z {NOTHING IN NL}_ THEN
'WAIT, %S pRINTED AND TH_ PATTERN IS INSERTED AT ?HE. BOTTOM OF_
THE STACK _OR _ECONSIDERATION LATER, TF NECESSARY. WE DO TH_I$
BECAUSE _E HAY WELL FIND ANOTNER_PATTE_N WITH A TRANSLATION THAT
CONTAINS SOME NL'ELEHENT$ AND IS_CCNSXSTENT WITH THE INPUT.
PART 3.2.$ - HATCH-BACK.
THE MAJOR DIFFERENCE IN PROCESSINQ L_NEAR OR NON=LINEAR FL.
SENTENCES _ I$: THAT IF WE UPDATE THE VOOABUEARY By TRANSLATING AN
FL COHBLEX PART IN THE CONT_KT OF A PATTERN ONLY, I.E® TH_
TRANSLATION RULE OF_ THE PATTERN WAS OF TYPE C (SEE. ABOVE, CHAPTER
II-B}, THEN WB TRY ?C SPLIT THE TRANSLATION USING EXACTLY THE
$AHE ROUTINES THAT WER_ C USEDI_ FOR THE INITIALIZATION OF THE
SYSTEH. I_ _UCCE_SFUL_ WE ORBATE; A NEW PATTERN WHICH. WILL HAVE
THE $AHE SETS ANDI EXTRA_T3R_ AS THE PATTERN CONSIDERED, BUT _HICH
_IL6 HAVE A DIFFERENT (AN_ _I_PLER} TRAN$OATION RULE. WE CALL
-30=
THIS PROCESS1 MATOH=BAOK_ RO_ AN EHAHPLE_ SEE CHAPTER IIZ_
$_NTENCE 3J PATTERN Pi IS OBTAINED FROM PATTERN PO BY HATOH-BACKo
$|NOE WE TRY TO_ HATCH AN RL SENTENCE TO PATTERNS IN THE
REVERSE OROER IN WHZCH THEY W_R_ CREATED (LAST PATTERN cREATEO_
FIRST TRIED}, AN FL_!SENTENCECAN BE HATCHED AND TRANSLATED BY A
PATTERN {OBTAINED BY HATOH-BACR) RHICH IB NEWE_ THAN THE PATTERN
THAT WOULD OTHERWISE HAVE_HATOHED THE.FL _ENTENOE_. AS; A RESULT_
IT OAN HAPPEN THAT_ EFFE3TIVELY', _OME O_ THE OLOER PATTERNS ARE
NEVER REACHEO ANY HORE. THIS RESULT CAN BE BENEF;ICIAE AS $OHE OF
THE EARL_XER PATTERNS HAY HAVE |NCORPORATED M|$TAKES VHICH,
THEREFOREj WILL' NOT BE MADE ANY MORE, WE HAVE HERE A RATHER
ELEMENTARY EXAMPLE OF! WHAT_ MAY BE CALLE_ _EVOLUT|ONAR_ LEARNING_o
AN GXAMPLE IN GERMAN APPEARS IN APPENDIX B,
PART 3.2_._ " _TRY LEARN MORE_o
IF A L'INEA_FL SE_TE_OE HA_:_EEN T_ANSLATED BY A PATTERN PZ_
AN_ IF THE SENTENCE _AS COMPLETELY MATOHE_ BY _O_E_O_HER PATTERN
PJ WHICH HAD BEEN CREATED AFTER El, THEN _BIE TAKE$_THE FIRST
$UOH PATTERN PJ_ THAT WA_'CONSIDERED AND TR|ES T_ LEARN FROM PJ_
A_ IR THE _NTENCEIHAD NOT BEEN TRANQLATE_. _BIE PRINTB _TRY
LEARN HORE_ WHEN SUCH A CASE OOCURSo IT IS THE SIMPLE _TRY LEARN
MORE _ PROCE$S_ WH|CH_MAK_S__EVOLUTIONA_y LEARNIN_ POSSIBLE. WE
ONLY USE THIS'PROCESS:FOR LINEAR RL S_NTENCES. _0_ COMPLEX FL.
$ENTENCES_ _ONTE_T I$ BSSENTIAL_, AND _HE CONTEXT EX|STS MORE AT
THE LEVEL OF_ THE IN-CONTeXT TRANSLATION THAN AT THE LEVEL OF THE _
-31 =
SET INOLUSIQN TESTS,
PART 4 - TH_ PATTERN CREA?X_G ROUTINE.
FZNALLY, WE MUST O0_SIDER ANOTHER VERY IHPORTANT ROUTZNE IN
ZBIE8 THE PATTERN OREATZNG _OUTINEo DEPENDING ON AN INPUT
PARAMBTER, THIS ROUTINE CREATES A TOP PATTERN OR A SUBPATTERN,
WE SAW ABOVE HOW THE NEED _OR NEW SUBPATTERNS_ARIBES, ZBIE
ATTEMPTS TO CREATE A TOP;PATTERN WHEN AL_ PREVIOUSLY DESCRIBED
PROCESSIN@ HAS FAILED°
THE PATTERN OREATIN_ROUTINE IS ONE OF THE LONGEST AND MOST
COMPLICATED IN THE SYSTEM. ONLY ITS MAIN PARTS WILL BE DESCRIBED°
IT TRI_$ ?0 CREATE. A LIIST OF PATTERNS WHICH WILL_ HA?OH THE INPUT
RL _OMPLEX STRUCTURE FLII TOTALLY AND GIVE AS A TRANSLATION (AFTER_
SUCH A HA?OH) THE INPUT NL STRIN@ NLI, MAKING_USE OF ALREADY
RNOWN INFORMATION.
THE ROUTINE HAKES FROM ONE TO FOUR PASSES ONFLIo EACH PASS
IS FIRST PERFORMED ON ALLCAPPROPRIATE _LENENTS OF FLI BEFORE_THE;
NEXT PASS |S BEGUN. THE _AIN FEATURES OF_EACH PASS A_E=
PART 4.% = OUTLI_E_ OR PATTERN CREATING ROUTINE,.
I} FIND WHETHER AN RL UNIT {NOT_A VERB} IN FLI HAS A TRANSLATION
{IN SOME CONTEXT A_ P_}WH_!CH IS_FOUND E_AOTLY IN NLI_ IF THAT I$
THE CASE, AND F!ZNALLY THE PATTERNS ARE OREATED_ THEN THE SAME SET
A WILL BE USED, IN SAY SO_E {SUBc)PATTERN ,P_, AND ON THE SET A WE,
PUT THE INFORMAYION_ IF WE WANT_ ?H_ TRANSLATION OF,AN ELEMENT IN
=32-
A IN THE CONTEXT P_ IT XS_ A GO0_ GUESS TO ASSUME THAT THE
TRANSLAT|ON XS THE$AH_ A$_ XN THE CONTEXT As PJ AND VICE-VERSAo
THX$, tS A CASE_ OF THE _G30D GUESS _ HENTIONED WHEN_DISCUS$ING THE
CON$1STENCY OR A TRANSLAT'!ON WITH AN NL SENTENCE,
2} FIND WHETHER AN FL WHOLE_ (NOT' A VERB} I_ FLI HAS A TRANSLATION'
WHIOH 'LOOKS_ LIKE _ SQH_I STRXNG IN NL'|o A TEST ROR SUCH A
$1HILARITY IS MADE USI_S_THE FXRST FEW CHARACTERS OF THE PRINT
NAMES OF THE' TRANSLATION ANDI OR THE ELEMENTS IN NLI, FOR
INSTANCE, IN RUSSIAN, THE GENITIVE OF BOY LOOKS LIKE THE
NOMINATIVE OF_BOY_ {REMEmBeR THAT_ BECAUSE OF THE FL STATEMENT,
WE EXPECT SOMETHING, WHICH HAS_ TO DO W|TH _BOY_}. SUCH A TEST
WOU6D HAVE TO BE_ IHPROVEDI TO WORK FOR LAN@UAGES {SUCH AS HEBREW}
WHERE PRERXXE$_ ARE ADDED TO;WORDS.
3} TREAT VERBS_ AS IN I). {VERBS;VARY TO0 MUCH TO BE RELIABLE AT
RXRST}.
4} IF SOME RL WHOLE IN RLI HAD PREVIOUSLY BEEN FOUND NOT TO BE
TRANSLATED {WE; HAD A BARTIAL TRANSLATION RULE, OR _YBE B_ FOR
INSTANCE}_ THEN ASSUHE THAT AGAIN _T WILL NOT HAVE TO iBE'
TRANSLATED.
AFTER THE APPLIICATION OR A PASS TO AN ELEMENT OF_RLI_ A
CHECK IS MADE FOR CERTAI_ TERHXNATING CONDITIONB_ ALL_RL WHOLES_
IN FLI USED UP, ALL_ NL_ _LEMENTB IN NL_ USED UB_ OR'ONLY ONE FL
WHO_E L_RT UNACCOUNTEDROR. THE SVSTE_ ALSO CHECKS FOR BOSSIBLEI
AMB_GUIT_ES_, F_R EXAM_LE_ SUPPOSE T_O _IRRERENT RL__HOLES IN RLI
=33. ¸
HAVE__tAD |DENTICAL TRANSLAT'XON$,, TO BE FOUND |N NLX_ THERE XS NO
WAY TO HAKE A CORRESPONDENCe, AND THE PATTERN CREAT|NG ROUTZhtE
EXXT$ W|TH 'TOO HARDt,
THE NEXT STEP IS TO BUXLD TRAINSLATZQN RULES FOR THE
SU_PATTERNS CREATED, AT_TH_$ STAGE_ ONLY TRANSLATXON RULES OF.
TYPES A) AND B) ARE. ALLOW=.D, THE _ULE_ ARE BU|LT BY C(3N_|DEi_|NG
THE NL STRXNG! INPUT TO THE RC)UTXNE _,ND MAKXNi_ SURE THAT THE
TRANSLAT|GN OF' THE PATTERNS 9U:XLT WH_I_ HATCHED TO THE |NPUT FL
=34-
CHAPTER _XX°
L_ARNING RUSSIAN
WE ARE, PREBENT+ING _ERE THE OUTPUT OF A COMPUTER RUN DURING
WH|OH _BIE ATTEMPTS ?0 LEARN RUSB!AN+ THE O_TPUT IS REPRODUCED AS
OBTAINED FROM THE_ PRINTER+ INPUTS IN |PL-V FORM HAVE BEEN DELETED
EXCEPT IN ONe; ILLUSTRATIVe: CASE°
THE IMPORTANT ATTR_IBJTE$ AND VALUE9 OR A PATTERN PJ HAVE THE
FOLLOWING HEANING_
TO(PJ} = TRANSLATION RULE (A LIST STRUCTU_E_+
POCPJ} = A LX_T OR PATTBR_S WXTH_ A P-LIST IDENTICAL TO PJ,
VO¢PJ} = J4+ IF PQ_ I$ A SU_PATTE_N,
TH_ OTHER ATTRIBUTES ARE _ USED ROR @OBKKEEPIN@ AND HAY BE+
DISREGARDED
COMMENTS_ARE_GIVEN AT_TNE RII_HT OF INPBT$+ OR AT THB END OR
THE PROO_BSING ORIA SBNTENCE+
LOORIN@ AT SENTENCE COHMENTS
{BE (_AN)HBRE }
ON ZDm$1
{BE {MAN }THERE )
ON TAM THE_FIRST TWO SENTENCES
PROOES$ START' TO START THE INITIALITATXON®
PUT INTO VOCABULARY BE XS X_ SET ACJ(WOHANi} XN SET A2o
{BE (MAN })
ON
P CONTE_T VOCABUbARY ROR;FL_COMBLEX
PUT INTO VOOABULARY
HERE. IN=CONTBXT VOOABULARY FOR RL
ZDE$$ UNIT, T_E FL UNiT {IN THIS CASE,
A3 HERE_} IS INSERTED IN THE SET (IN
P THIS'_ASE_ A3_. P=PO,
PUT INTO VOOABULARY
THERE
TAN
A3
P
_NEW PATTERN
<PO> <9-I _ 25418> <9_2 = 25228> <9=3 = 255_4)
02 9_$ 04 0 04 0 04 0
O0 AS O0 TO 02 9=3 O0 Y$
O0 YI 02 9=2 00 Y3 O0 Y2
O0 A2
O0 Y2
O0 A3
O0 Y3
-36-
COMHENTI THE |NITI_LIZATXON PHAGE |$ OVER, ROR THE NEXT
$_NTENC_ WE SHOW THE IPL-V INPUT,
COHMENT= 'PUT INTO VOCABUL_Y_ HAS THREE, OR FOUR ARGUHENT$,_
EXAMPLES OF BOTH CASES AR_ XLLUST_ATED ABOVE¢
$} THREE ARGUHENTS, T_E F_RST ARGUH_NT_ _IS AN RE ;OMPLEX_ THE
$_COND ARGUMENT IS AN_NL _T_ING, THE THIRD ARGUMENT |$_ A PATTERN
GIVXNG THE OONTEXT_ T_E TRANSLATXON OR_ THE FL' COMPLE_ |N THE
CONTEXT OF THE_PATTERN I$_THE, NLi STRXNGo EXAMPLE_I (BE(MAN)}_ ON_
P(=PO}.
2} FOUR ARGUHENTS, THE FIRST A_GUMENT _S AN FL U_iITJ THE SECOND_
AN _L STR|NG_ THE TH_R_ A SET AND THE ROURTH_ A PATTerN, THE FL
UNiT I_ FIRST' I_ERTED _N THE SET {THE UNiT MAY ALREADY BE |_ THE
SET_ THE T_AN_LATION OR THE RLI UNIT _S A MEMBE_ OF THE $ET_ IN
THE CONTEXT OF THE_ PATTE_N_ IS!THE NL STR_NGo WE _ERER TO T_E
PA%R (_T_ PATTERN} AS THE CONTEXT IN WHICH THE TRANSLATION OR
THE FL UNIT IS TH_ NL; STRING, _XAMPLES_ HERE, 7DE$$, A3, P{=PO)_
THERE_ TAM, A3_ P(=PO},
ALL _ ADDIITIONS TOI THE V_CABULARY AREPRINTED _SD_SCR_BED
ABOVE,
|P _NPUT DATA 5 05
X4 9B 0
95 0
IP BE EO
IP ¢$PEAKIN_ HAN} 91
=37-
IP HERE E3 0
IP 9t O
XP SPEAKING E1
XP MAN E2 0
IP X_ 95 0
IP 95 0
XP AI R1
IP ZD_Sl R2 0
|P 5 JO
H2 = 2357 CELLS CO,COs06
LOOKXNG AT SENTENCE_3
(BE (SPEAKING MAN }HERE_ }
A1 ZDE$1 THE INPUTS ARE FXRST PRINTED
PROOES$ START THE_ _BIE STARTS PROCESSING,
TRY PATTERN
P
NOT MATCHED, (SPEAKXNG MAN} _$:NOT IN A2_
TRY LEARN FROH PATTERN
P
{Z ZDE_i } Z STANDS FOR TME UNTRANSLATED
PUT INTO VOCABULARY {BE{BBEAK!NG _AN}} RL COMPLEX°
(BE (SPEAKING MAN })
A1 THE RUSSIAN LETTER (=I}o
p_
PUT INTO VOCABULARY PATTERN P$ X$ BEING @UXLT.
(SP_A_ING MAN }
=38=
AI THE RUSSXAN LETTER (=|)_
A2 A SET NAME°
P1
NEW PATTERN
<P_> <9-1 = 25418> <9-_ = 25752> <9-3 = 252_)
02 9=! 04 0 04 0 04 0
O0 A1 O0 PO O0 P_ O0 Y2
O0 Y1 02 9-2 00 Y3
O0 A2 0O YO
O0 Y2 O0 J3
O0 A3 O0 J4
O0 Y3 O0 J3
O0 TO
02 9-3
OOMMENT_ PATTERN PI HAS A P-LZST TDEHTIOAL TO T_E P=LIST OF
PO, HOWEVER_ THE TRANSLATIO_ RULES ARE DIFFERENT_ ZB|E USED
¢_E{MAN}} _-ON_ AND (BE ¢SPEAKIN_ _AN)_ _ AI_ BOTH TRANSLATIONS
IN THE OONTBXT OR THE PATTERN PO, FOR MATCH BAC_, TM_ OOMPARISON
OF THE NON=OOMMON PARTS I_ FL, ARB NL_GAVE (SPEAKING MAN} _ A1 (IN
THE CONTEXT A2_ PI}o 91NCE THE _L STRINGS_USED FOR MATCH-BACK
HAVE NOTHING IN OOMMON, 'gE_ IS ASSUMED NOT TO BE TRANSLATED_ AND
THE EXTRACTOR Y$ OF TH8 SET AI (WHICH CONTAINS _BE,} IS NOT USED
IN TNB TRANSLATION RULE_ TO(P%}, IT IS WEL_ WORTH_ COMPARING THX$
PATTERN P$ TO THE PATTERN PI OR_ATED BY ZBIE WHEN LEARNING SOME
GERMAN (SEE APPENDIX B)o
ZBIE ALSO NOTES THAT IT IS A _OOD GUESSt TO ASSUME THAT THE
TRANSLATIONS OR A MEMBE_ OF A3 XN THE CONTEXTS {A3_BO} AND (A3,
PI} ARE THE SAME,
LOOHIN@ AT SENTENCE 4
(BE (SPOKEN BOY }HEREi )
T}2 ZD_Sl
PROOEgS START
TRY PATTERN
PI
NOT MATCHED_
TRY PATTERN
P
NOT MATCHED,
TRY LEARN F_OM PATTERN
P1
(Z Z$} (SPOKEN BOY} IS NOT IN SET A2,
GUESS 'HERE_ I$ NOT KNOWN IN THE OONTEXT
Zl (A3_Pi}_ BUT_ X$ @UESBED TO BE
ZDE$$ THE SAME AS IN THE CONTEXT (A3_PO)o
PUT INTO VOOABULkRY THE TRANSLATION XB CO_SISTENT_
{SPOKEN BOY }
Tt'2
A2
PI
"40'-
PUT XNTO VOCABULARY
H_RE
ZDESl
A3 NOW _HE_E_ ZS A_$O KNOWN _N
P! THE CONTEXT ¢A3,P$).
LOOK|N_ AT SENTENCE 5
(BE (MAN }#E_E }
ON ZD_$i THE FXR_T SENTENCE AQAINo
PROOES$ START
TRY PATTERN
PC
PATTERN MATCHED. REBULT_
{Z ZD_$i } (MA4} I_ NOT KROWN IN
TRY PATTBRN THE CONTEXT (A2, Pi}.
P
PATTERN MATCHED. REBULTs
(ON ZDE81 }
TRY L_ARN MORE PATTERN PC WAS MATCHED ENTIRELY,
TRY L_ARN FROM RATTERN
PC
CZ ZD_I )
PUT INTO VOCABULARY
(MAN }
ON
A2 THE 5ENTENC_ _L BE TRANBLATEO
=41=
P! BY THE PATTERN Pi FRO_ NOW ON,
LOOKIN_ AT SENTENCE 6
{BE {$RBAKINQ_ MAN }MAN }
AI HUGYINA
PRO_E$$ START
TRY PATTERN
P! _MA_ _ I_ NOT IN THE SET A_,
NOT MATCHED, $|NCE PO HA_ T_E SAME P=L|ST AS
TRY PATTERN P$_ T_E HATOH ON PO IS NOT
P ATTEMPTED,
NOT MATCHED,
TRY L_ARN FROM PATTERN
P1
{At Z }
PUT INTO VOCABULARY
MAN
MUGYINA
A3
PI
LOO_ING AT SENTENCE 7
{BE {MAN }MAN }
ON HUQYINA A N_W SENTENCE,
PRO_E$$ START
TRY PATTERN
PI
"42=
PATTERN MATOHEDo RESULTS
(ON HUGYINA } TRANSLATED CO_PEETELY,
LOOKINQ AT SENTENCE B
{BE {BBOKEN BOY }BOY }
TI2 HALSY%K
PROCESS START
TRY PATTERN
P1
NOT HATCHED,
TRY PATTERN
P
NOT HATCHED,
TRY LEARN FROM PATTERN
PI
(TI2 Z }
PUT INTO VOCABULARY
BOY BUILDIN_ UP T_E VOCABULARY,
HAL%YIK
A3
PI
LOOKING AT SENTENCE 9
{BE {SBOKEN GIRL_ }GIRL }
TI2 DEVOYKA
PROOESS START (SPOKEN GXRL} _$ NOT IN BET A;_
TRY BATTBRN _GIRL_ _S NOT IN BET A3o
-43_
PI
NOT MATCMED,
TRY PATTERN
P
NOT MATCHED,
TOO MARD
TWO HISTAKEH AT O_E LEVEL WERB OBTAINED DURXNG PATTERN
MATOHING, SO THAT NO PATTERN IS _CLOSE_ TO THE FL SENTENCE. THE
TWO FL UNITS (BBOKEN GIRL} AND 'GIRL _ CANNOT BE TRANSLATED IN ANY
CONTEXT {AT THIS STAQE}, AND NO NBW PATTERN CAN BE BUILT TO
TRANSLATE THE SENTENCE. NOTE THAT IF ZBIE HAD USED $OHE OF THE
SEMANTICS BUILT INTO £L T3 GUESS THAT (SPOKEN GIRL} HAY WELL HAVE
A TRANSLATION IDENTICAL TO {$DO_E_ BOY}, IN THE_ SAHE cONTEXTS,
THEN TH_ SENTENCE COULD HAVE B_E_ PROCESSED SUCCESSFULLY AT THIS
STA_E, THE GUESSED TRAN$.ATION WOULD HAV_ BEEN _TI2 7_, WHICH IS
OONSISTENT WITH THE INPUT_
WE SHALL H_REAFTER L_AVE O_T THE HC)NOTONOUS tTRY PATTERN .,_
PJ ,.. NOT HATOHED ,o_.
LOOK|N_ AT SENTENCE _0
{BE BOY } THIS SENTENCE MATCHES NO
E2Tg HALSYIK PREVIOU_ PATTERNB.
PUT INTO VOCABULARY CREATIN_ PATTERN P2o
BE
E2TO
=44'_
A4 A NEW SET.
P2
PUT INTO VOCABULARY
BOY
MALSYI_
A3 THE SAME TRANSLATION AS
P2 IN TH_ CONTEXT (A3,P$),
NEW PATTERN
<P2> <9=I = 26178> <g-_ = 26570> <9=3 = 26_>
02 9_$ 04 0 04 0 04 0
O0 A4 O0 TO O0 Y! O0 Y1
O0 YI 02 9=2 O0 Y_ O0 Y2
O0 A3 OO D12
O0 Y2 02 g=3
O0 D13
O4 261B_
COMMENT$_ THE SENTENCE _N FL HAS A LENGTH OR TWO, PREVIOUS
PATTErNs EXPECT AN FL SENTENCE OF LENGTH THREE° TO BUILD THE NEW
PATTERN, Z61E T_IED TO RI_D TRANSLA?ION_ FOR THE FL UNXT$ XN THE
RL SENTENOE_ WHICH WERE IDENTICAL OR CLOSE TO NL_ ST_ING_ IN THE
INPUT NL. _@E _ HAD N3 T_A_SLATIONj HOWEVER, _BOY _ HAD A
TRANSLATION _MALIYIK_ I_ THE CONTEXT CA_ PE} (SEE SENTENCE _}_
WHIOH I$ ROUND IN THE INBJT. THE FL UNIT ,BE_ WHICH HAD NOT BEEN
ACCOUNTED FOR IS MATCHED TO THE; RE_AIN_NG PARTS OF THE: NL INPUT,
NAMELY _E_TO_o ZBIE AL$3 MAKE_ A NOTE THAT IT IS A _GOOD GUESS _
=45_
TO ASSUME THAT THE TRANSLATXONS OF AN F_ UNIT IN THE CONTEXTS
CA3,P_} AND (A3_Pl} ARE XDENTICALo
LOOKIN_ AT _ENTE_CE i1
(BE FOOT }
E2TO NOSSA BUXLDIN_ UP THE VOCABULARY,
PROOESS START
TRY L_ARN FROM PATTERN
P2
{E2TO Z }
PUT INTO VOOABULARY
FOOT
NOG%A
A3
P2
LOO_ING AT SENTENCE 12
(BE FOOT fOR BOY }) NOT A LXNEAR FL SENTE_CEo
E2TO NOG$A MAL!YXKA
PROOES$ START
TRANSLATE
P2
RESULT8 Z STAND_ FO_ TME TRANBLATION OF
(E2TO Z } THE FL COMPLEX FOOT{O_ BO¥I_ AND,
TRY BY THE CONSISTENCY TEST, ? IS TO BE
P2 R_PLACED BY _NOGIA MALIYXKA o,
_'46=
PUT INTO VOCABULARY BUILDIN_ gUBPATTERNB P39 AND P_Bo
BOY
HALSYIKA
A6 A DIFFERENT TRANSLATION,
P3B UBI_ A DIFFERENT SET,
PUT INTO VOOABULARY
FOOT
NOG%A
A3 TNE SAME TRANSLATION AS IN
P39 THE OONTEXT (A3_P2)o
PUT INTO SET
P38 THE SUBRATTERN P38 IS INSERTED
A7 AT THE TOP 8F THE $_T A7o
NEW PATTERN
<P38> 49=i = 26474> <9=2 = 26766> <9=3 = 2_h6_>
02 9=I 04 0 04 0 04 0
O0 A5 O0 TO O0 YIO0 O0 ¥100
O0 YIO_ O2 g=2
O0 A6 o0 D12
O0 YIO0 02 9-3
O0 D13
04 26646
O0 09
O0 k7
o0 VO
O0 J4
<P39> <9=1 = 26454> <9-2 _ 26788> <9=3 = 2_92>
02 9-$ 04 0 04 0 04 0
O0 A7 O0 TO O0 YeS O0 Y98
00 Y99 02 9-2 80 Y99 OO Y99
O0 A3 O0 D12
O0 Y98 02 9-3
O0 D13
04 26678
O0 VO
O0 J4
PUT INTO SET
P39
A3
COHMENTS_ LET US CAREFULLY GO OVER OUR FIRST ENCOUNTER WITH
A NON-LINEAR _L SENTENCE. AT TNE TOP LEVEL_ THE FL SENTENCE
MATGNES PARTLY THE PATTER_ _28 _BE_ IS AN ELEHENT OF A4_ BUT THE
SET A3 HAS NO SUBPATTERN _ENBER_. CONSE_UENTLY_ THE FL CONPLEX
FOOT|OF 80Y| CANNOT BE HATCHED,
THE TRANSLATIONS IN #ARALL_L O_ PATTERN LIST5 HAVING HATCNED
THE FL SENTENCE TO TNE DE_PEBT ,_ATCH_DEPTN ARE TRIED. T_I_ ACTION
FOL_OW_ _TRANBLATE_ NER@, ONLY ONE PATTERN, P2, I$ FOUND° THEN,
THE P_TTERN LI_T$ WITR A OON$1ST_NT TRANSLATION ARE TRIED. THIS
ACTION ROLLOWS _TRY', HE_E WE ONLY _TRY _ THE PATTERN P_. BY TN_
CONSISTENCY TEST, THE FL COMPLEX FOOT[_F BOY] CORRESPONDS TO THE
NL STRING tNO81A MALIYIKA_8 AND THE PATTERN CREATING ROUTINE
=48="
MANAGES TO 9UILD $UBPATTE_NS TO MATCH THE FE COMPLEx, NOTE THAT
PREVIOUS KNOWLEDGE HAS BEEN USED TO AVOID BUILDINQ A WHOLE NEW
TOP PATTERN,
WHEN BUILDING THE _UBPATTERN_ THE TRANSLATION OR _ROOT' XN
THE OONTEXT OA3_P_} I_ USED, THB PREVIOUSLY ENCOUNTERED
TRANSLATION OR _BOY'_ 'HALIYXK'_ IS NOT ROUND IN THE NL STRING.,
HOWEVER_ _MALIYIK _ IS VERY CLOSE TO _MALIYIKA_ $0 THAT THE
TRANSLATION OR +BOY+a IN k NEW CONTBXT_ I$ ASSU_ED TO BE
'RAL,IYIKA_® SINCE ALL THE WORDS |N THE NL STRING _NOG_A MALIYIKA _
HAVE BEEN A_COUNTED FOR_ 'OR' I_ ASSUMED NOT TO BE TRANSLATEDo
THE P-LIBT OR THE SU_PATTE_N P_9 CONTAINS TWO SETS, THE BET
A3 CONTAINS ROOT {AND MA_Y OTHER FL UN_TB}J THE SET A7 CONTAINS
THE SUBPATTERN P38, B3B _ATCHEB THE RL COHPLEX STRUCTURE {OR
BOY|, $|NCE _OR _ IS k ME_6ER O_ TH_ SET A5 AND tBOY_ OR THE SET
A6,
LET US VISUALIZE THE SA_E $_NTENOE BEING _ATCHED AGAIN TO
THE PATTERN LIST {P2 =3g P_8}, A _ATCH OR TH_ FL COHRLEX
STRUCTURE FOOT{OF BOY] I$ ATTEMPTED AGAINST THE SUBPATTERN P39_
MEM_ER OF A_o A MATCH OR TM_ RL COMPLEX STRUCTURE {OR BOY) _$
ATTEMPTED A_AI_T THE SUB_ATTER_ P3_ M_HRER OR A_. ALL MATCHES
SUCOEE_o THE TRANSLATION RULE OR P_ CALL_ FOR THE TRANSLATION OR
THE STRUCTURE ROOT{OR BOY] _ATCRED AGAINST P39o THE TRANSLATION
RULE OR P39 CALLS FOR T_E TRANSLATION OR THE ELEMENT HATOHED TO
A3_ _FOOT_ IN THE O0_T_XT {A3_B_@), WHICH 15 _NOG_A _ ¢Y9_}_
=49_
ROL6OWED @Y THE TRANSLAT|3N OF TM_ FL C_MPLE× {OF BOY_ HATCHED TO
P38_ {Y99}. THE TRANSLATI3N RULE OF P38 CALES FOR THE TRANSLATION
OR THE ELEMENT MATCHED TO A6_ tBOY_, _N THE CONTE_T (A6_P38}_
NAMELY eMALSYIKA_ (Y/O0}o tHE TRANSLATION ROUTINE I$ SEEN TO
CALL ON ITSELF RECUR$1VELY.
NOTE THAT WHILE THE PATTERN P_Q I$ A MEMBER OF THE BET A3_
THE P-LIST OR P39 CONTAINB TM_ _AME SET A_ $0 THAT AN INFXNITELY
RECURgIVE PATTERN-TREE IS ALREADY POSSIBLE, WHEN U$IN8 MORE THAN
ONE TOKEN OF THE SAME PATTERN_ CARE MUST BE TAKEN TO UBE, AL$O_
TOKENS OF THE EXTRACTORBo
PATTERN P38_ WHICH _ATCMEB {OF BOY]_ IS A MEMBE_ OF THE SET
AT. A7 OCCURS ABOVE THE SET A3 (WHI'CH CONTAXN$ _BOY _} IN THE
P=LIST OR THE PATTERN P39_ THIB R_CULIAR'|TY XS DUE TO THE IPL_V
|MP6EMENTATION OF THE $OUARE=BRACKETED DESCRIPTION LI_T IN RL_ A$
DESCRIBED IN CHAPTER If, _ART Ao
LOOKIN_ AT SENTENOE %3
(BE HAND {OR BOY |}
E2TO RUKA MALIYIKA
PRO_ES$ START
TRANSLATE
P2 THE PATTERN LIST,
P39
P38
(E2TO Z HAL1YIKA } _HA_D_ X$ N_T XN SET A3,
TRY
P2
P39
P38
PUT XNTO VOCABULARY
HAN_
RUKA
A3
P39
LOO_!ING AT SENTENCE I4
{BE HAND
E2TO RUKA
PROOES$ START
TRY PATTERN
P2
PATTERN MATCHED. RESULT_
(E2TO _ } _HA_D_ X$ NST KNOWN IN THE
TRY LEARN FROM PATTERN CONTEXT (A3_P_}_
P2
GUESS BUT _AND t CAN BE GuESSED_ USING
Z THE BIM|LAR CONTEXTS ¢A3,P2}
RUKA AND (A3,_P39},
LOO_,ING AT SENTENCE 15
-51=
(BE BOOK
E2TO KNIESA
PROGES5 START
TRY LEARN FROM PATTERN
P2
CE2TO Z
PUT INTO VOCABULARY
BOOK
KNX_iA
A3
P2 MORE VOOABULARY_
LOOKING AT SENTENCE 16
(Q BE BOOK WHERE } Q MEANS OUE_T!ON_ XT |$ A
GCDE KNISSA MARKER, AND X_ NOT ?0 BE
PROOES$ START TRA_SLATEDo
PUT XNTO VOCABULARY BUILD!N_ PATTERN P3o
WHERE
GiDE
AiO
P3
PUT XNTO VOCABULARY
BOOK
KNI_IA
A3
P3
-52-
NEW PATTERN
<P3> <9-1 = 2.5550> <9=2 = 25286> <9-,3 = 284r}:._)
02 9=1 04 0 04 O 04 O
O0 A8 O0 TO O0 Y4 O0 Y4
O0 YI 02 9=2 O0 Y3 O0 Y3
O0 A9 O0 D12
O0 Y2 02 g=3
O0 A3 O0 D13
O0 Y3 O4 26952
O0 AIO
O0 Y4
OOMMENT| NOTfOE THE TRANSLATION RULE,
LOOKIN_ AT SENTENCE !7
(BE {IN {BOOK }HAND }}
ONA V RUKE
PROCESS START
TRANSLATE
P2
RESgL?s
(E2TO Z ) NOT CONBIST_NT,
TOO HARD
BOTH {BOOK} AND _IN _ A_E UNKNOWN_ AND A NEW TOP PATTERN
OOULD NOT BE CREATED, ZBIE W_LL NOW LEARN (BOOK)_ THEN RETURN TO
THE SAME SENTENOE, 'HAND_ COULD BE _UES_ED FROM _RUKA_ TO _RUKE_
LOOKING AT SENTENCE _8
{BE (BOOK }HERE
ONA ZDE$1
PROCESS START
TRY LEARN FROM BA?TERN
PC
{Z ZD_SI}
PUT INTO VOOABULARY
{BOOK }
ONA
A2 NOW (BOOK} ZS KNOWN A5 'ONA_
Pi IN THE OONT_XT (A2_P$},
LOOKING AT SENT_NOE 19
{BE {IN (BOOK)HAND }}
ONA V RUKE IDENTICAL TO _ENTENCE %7.
PROOEBS START
TRANSLATE
P2
REBULT_
{E2TO Z } NOT CONSISTENT,
PUT I_TO VOCABULARY BUILDING PATTERN P4°
HAN_
RUKE
A13 A NEW SET,
P37
PUT INTO VOCABULARY
IN
V
AI2
P37
PUT INTO VOCABULARY
(BOOK }
ONA
A2
P37
PUT INTO SET
P37
A14
N_W PATTERN
<P37> <9-I = 26506> <9-_ = P7334> <9=3 = 271_>
02 9-I 04 0 04 0 04 0
O0 k12 O0 TO O0 Y96 O0 Y96
O0 Y97 02 g-2 O0 Yg7 O0 Y97
O0 A£ ; O0 01£ O0 Yg5 O0 Y95
O0 Y96 02 9=3
O0 A13 O0 D13
O0 YgB 04 27144
O0 D9
o0 A14
O0 VO
-55,"
O0 J4
02 9-$ 04 0 04 0 04 0
O0 A!! O0 TO O0 Y_ O0 Y2
O0 YI O2 g=2
O0 k14 O0 012
O0 Y2 02 9-3
O0 D13
O4 2716_
COMMENT= PATTERNS :_2 AND P_ BOTH HAVE TwO SETS ON THEIR
P"=LXSTS_,BUT THESE SETS A_D THE TRANSLATION RULES OF THE pATTERNS
ARE QUITE D!FFERENT_ T_E TRANSLAT_O!_ RULE OF P37 IS WORTH NOTING_,
LOOKXNG AT SENTENOE 20
(BE (IN (BOOK )WAND {OF B3Y |})
ONA V RUKE MALIYXKA
PROCESS START
TRANSLATE
P4
P37
RESULT=
(ONA V Z ) k CONSISTENT TRANSLATXONo
TRY HAND[OF BOY] OORREBBOND$ TO
P4 RUKE MALIYIKA°
P37
=56_,
PUT INTO VOCABULARY BUILDIN_ SUBPATTERNS _36 AND P35o
HANg
RUK5
A!3 NOT A NEW SET(SEE SENTENCE 19}.
P36
PUT INTO VOCABULARY
BOY
MAL%YIKA
A6 NOT A NEW SET(SEE SENTENCE 12}.
P35
PUT INTO SET
P35
A16
NEW PATTERN
<P35> <9-L = 2753P> <9-2 = 27776> <9-3 = 27_>
02 9-1 04 0 04 0 04 O
O0 AI_ O0 TO O0 Yg3 O0 Y93
O0 Y94 02 9-2
O0 A6 O0 B12
O0 Y93 02 9=3
O0 D13
04 27674
O0 09
O0 A16
O0 VO
O0 J4
<P36> <9-I = 266B8> <9-2= 27786> <9=3 = 2777_>
02 9=I 04 0 04 0 04 0
O0 A16 O0 TO O0 Y91 O0 Y91
O0 Y92 02 9-2 O0 Yg2 O0 Y9_
O0 Ai3 OO Di2
O0 Y91 02 9=3
O0 013
04 27706
O0 VO
O0 J4
LOOKING AT SENTENCE 2!
(BE PENCIL }
E2TO KARANDAW
PROOE$$ START
TRY L_ARN FROM PATTERN
P4 WHEN THE TRANSLATION IS JUST Z_
(Z } W_ WAIT THE FIRST TIME AROUND,
WAIT
TRY L_ARN FROM PATTERN
P2
(B2TO Z } CON_IBTENT TRANSLATIOn,
PUT INTO VOCABULARY
PENCIL
KARANDAW
A3
=58,_
P2
IR WE HAD PROCESSED 34 FIRST, WE WOULD HAVE OBTA_NEDs
PUT XNTO VOCABULARY
PBN_XL
E2TO _ARANDAW
AC4
P4
LOOKXN_ AT SENTENCE 22
(Q @E PENCIL WHERE }
GIDE KARANDAW
PROCE$_ BTART
TRY PATTERN _PENC!L e IS NOT KNOWN XN THE
P3 CONTEXT (A3_P_}o
{G1QE Z }
TRY LEARN FROM PATTERN
P3 HOWEVER, THE TRANSLATION OR
(Q$_E Z } _PENC%L_ CAN BE @UE_$ED FROM THE
GUESS CONTEXT (A3,P_} TO THIS CONTEXT,
KARANDAW
PUT INTO VOCABULARY
PENCXL
KARANDAW
A3
P3
XF _GOOD GUESSES _ _AD BEEN U_ED, TH_|$ SENTENC_ wOULD HAVE
BEEN TRANSLATEDo
LOO_XNG AT SENTENCE 23
{BE (PENCIL )THERE }
ON TAM
P_O;ES$ START
TRY LEARN FROM PATTERN
PI
(Z Z$ } THE GUESS MAKES THE T_ANSLAT|ON
GUESS CONSISTENT WXTH THE I_PUT.
Zl
TAM
PUT XNTO VOCABULARY
{PENCIL )
ON
A2
PI MORE VOCABULARY°
PUT |NTO VOCABULARY
THERE
TA_
A3
PI
LOOK|NG AT SENTENCE 24
(BE (IN (PENCIL )DRAWER )}
ON V AIW21KE
PROOES$ START
TRANSLATE
P4
P37
RESULTI EVEN WITHOUT ?HE QUE$5_ THE
(Z V Z% } TRANSLATION I_ CONSISTENT WITH
@UE$$ THE NL XNPUT,
Z
ON
TRY
P4
P37
PUT INTO VOCABULARY
(PENCIL }
ON
A2
P37
PUT INTO VOCABULARY
DRAWER
AIW_I_E
Ai3
P37
LOOKING AT SENTENCE 25
(BE BOY {HOD THX$ |HERE )
E2TOT HALIYIK ZDES1
PROCESS START
TRANSLATE
PI
R_SULT_
(Z _D_Sl }
TRY
PI
PUT INTO VOCABULARY BUILDING SUBPATTERNS _34 AND P33o
E2TOT
A18
P33
PUT INTO VOCABULARY
BOY
MAL%YIK
A3
P34
PUT INTO BET
P33
A19
NEW PATTERN
<P33> <9=I = 27360> <9-2 = 27812> <9-3 = 2759p>
02 9-! 04 0 04 0 04 0
O0 A17 O0 TO O0 Y_9 O0 Y89
o0 Y90 02 9=2
=62=
O0 A18 O0 D12
O0 Y89 02 9-3
O0 D13
04 26168
O0 D9
O0 A$9
o0 VO
o0 J4
<P34> <9_I = 26422> <9-2 = 27840> <9m3 = 276_)
02 9-C 04 0 04 0 04 0
O0 klg O0 TO O0 Y88 O0 YS_
O0 Y88 02 9=2 O0 Y_7 O0 YS?
O0 A3 O0 D12
O0 Y87 02 9_3
O0 D!3
04 2772_
o0 VO
O0 J4
PUT INTO SE?
P34
A2
LOOKING AT SENTENCE, 26
(BE @IRL }
E2TO DEVOYKA
PROOE$$ START
"=_3-,
TRY LEARN FROH PATTERN
P4
(Z)
WAXT
TRY LEARN FROH PATTERN
P2
{E2TO Z }
PUT INTO VOCABULARY
GIR6
OEVOYKA
A3
P2 HOR_ VOCABULARYo
LOOKXNG AT SENTENCE 27
{BE _SROKEN GIRL }GIRL }
T|2 DEVOYKA THIS IS SENTENCE 9_ WHICH _AD
PROOE$$ START BEE_ FOUND _T08 HARD _ PREVXOU_LYo
TRY LEARN FROM PATTERN
P1 NOW, WE USE THE TRANSLATION OF
{Z Z$ _ 'GIRL _ IN THE OONTEXT {A3_P_}
GU@$S AS A _GUEBSt {SEE SENTENCE _6),
Z$
#EVOYKA
PUT INTO VOOABULARY
(SPOKEN GIRL }
T12
A2
P1
PUT INTO VOCABULARY
GIRL
DEVOYKA
A3
P!
LOOKXNG AT SENTENCE 28
{6E GIRL CMOD THX$ |MERE }
E2TA DEVOYKA ZDES1
PROOESS START
MATCHED PATTERN-LIST
PI PATTERN_LXST MATCHIN_ THE RL
P34 SENTENCE TO A MATCH-DEPTH OR 2_
P33
RESULT_
(E2TOT Z ZDE$$ } NOT CON$1$TBNT°
TRANSLATE
P1 PATTERN LIST HATCHING THE _L
P34 SENTENCE TO A MATCH-DEPTH OF 1,
RESULT_
(Z Z_ ZDESl )
@UE$$ W|TH THE GUB$S_ THE TRANSLATION
Z! IS CONSXSTENT WITH THE NL INPUT,
DEVQY_A
TRY
PI
P_4
PUT XNTO VOCABULARY
THIS
E2TA
A25
P32
NEW PATTERN
NOT XNSERTED SEE COM_ENT_ _ELOWo
TRANSLATE PATTERN LIST MATCHING THE FL
PI SENTENCE TO A MATCH=DEPTH OF 0,
RESULT_
{Z ZD_$1 } CONSISTENT WITH INPUT, Z TAKES
TRY THE PLACE OR _,IRL[HOD THI_]o
PI
PUT INTO VOCABULARY BUILDIN_ SUBPATTERNS m30 AND P3io
GIRL
DEVOYKA
A3
P31
PUT INTO VOCABULARY
THIS
E2TA
A2C
P30
PUT INTO SET
P30
A23
NEW PATTERN
<P30> <g =& = 28520> <g=2 _ 28752> <9w3 = 2_0>
02 g-& 04 0 04 0 04 0
O0 A22 O0 TO O0 Y83 O0 Y83
O0 Y84 02 9=2
O0 A25 O0 012
O0 Y83 O2 g-3
O0 D13
04 28636
O0 D9
O0 k23
O0 VO
O0 J4
<P31> <9_1 = 28:392> <g_2 _ 28762> <g_3 = 2_#>
02 9-$ 04 0 04 0 04 0
O0 A23 O0 TO Oo Y_2 O0 yS_
O0 Y82 02 g_2 Oo Y85 O0 YS&
O0 A3 O0 912
O0 Y85 O2 g-3
O0 D13
04 28668
O0 VO
O0 j4
"67-
PUT INTO SET
P3!
A2
HERE IS OUR FIRST ENCDUNTER W'_TM ZBIE_S LOOK=AHEAD
CAPABILITIES, T_E FL SENTENCE IF PIRST MATCHED TO A MATCH-DEPTH
OF 2 BY THE PATTERN-LIST {Pl P_4 P_3} BUT THE TRANSLATION IS NOT
CONSISTENT WITH THE NL INPUT, SINCE THE FXRST NL WORDS OF THE
TRANSLATION AND INPUT AR_ DIFFERENT° NEXT_ THE FL SENTENOE IS
MATCHED TO A MATCH=DEPTH OF i BY T_E PATTERN-LIST (P_ R34}, THE
FL STRUCTURE {NOD THIS| _A5 NO CORRESPONDING SUBPATT_RN TO WHICH
IT IS THEN MATCHED AND _ CONTRIBUTES T_E UNKNOWN Z{_ZO} TO THE
TRANSLATION OF THE RL SENTENCE, 'QXRL t IS NOT KNOWN _N THE
CONTEXT (A3,P34}_ AND 30NTRIBUTE_ THE UNKNOWN ZL_ $_NCE THE
TRANSLATION OF _GIRL' CA4 BE CORREOTLY @UE$SED, THE TRANSLATION
OF THE FL SENTEN_E_ I$ OONBISTENT W%TH THE INPUT, T_E UNKNOWN Z
TAKES THE BLAOE OF TM_ FL STRUCTURE [HOD THIS] AND_ BY THE
CON$1$_ENCY TEST_ I$ TO BE REPLACED BY THE FL SENTENCE IS FIRST
MATCHED TO A MATOH_DEPT_ OF 2 BY THE BATTERN_L|$T (m$ P34 P33},
BUT THE TRANSLATION I$ NOT CON$1$TENT W|TH THE NL INPUT SINCE THE
FIRST NL WORDS OF THE TRANSLATION AND INPUT ARE ISOMORPHIC TO
P32, (wE WOULD ONLY REQUIR_ THAT P32 B@ A HOMOMORPRIo IMAGE OR A
SUBPATTERN IN A19), P32 19 _NOT INSERTED _ IN A$9 AND TH_ NEXT
PATTERN LIST IS TRIED° 5ENT_NOE 3_ _ILL PROVIDE ANOTHER EXAMBLE
OF TH_ SAME TECHNIQUES,
'=68,=
LOOK|NG AT SENTENCE 29
(BE TREE
E2TO DEREVO
PROOES$ START
TRY LEARN FROM PATTERN
p4
(Z)
WA%T
TRY LEARN FROM PATTERN
P2
(E_TO Z }
PUT INTO VOCABULARY
TREE
D_REVO
A3 MORE VOCABULARY BEFORE
P2 THE NE×T SENTENCE.
LOOKING AT BENTENCE 30
{BE TREE {HOD THIS )HERE }
E2TO DEREVO ZDES$
PRO_ESS START
MAVCHED PATTERN=LIST
PUT INTO VOCABULARY
TREE
DEREVO
A3 MORE VOCABULARY BEFORE
=69-
P2 THE NEXT SENTENCE,
LOOKING AT SENTENCE 30
(BE TREE {MOO THIS ]HERE }
E2TO DEREVO ZDES1
PRO@E$$ START
MATCHED PATTERN=L,IST
P1 _TREE' X@ NOT KNOWN I_ TN_
P32 CONTEXT (A3,P3$},BUT CAN _E
P30 GUESSED FROM THE CONTEXT
RESULTI (A3_P_)o
(E_TA Z ZDEBI ) NOT CONSISTENT,
MATGHED PATTERN-L;IST
P1 _TREE _ IS NOT KNOWN I_ THE
P34 CONTE_T (A3_P34}_BUT CAN BE
P33 GUESSED FROM THE CONTEXT
RESULTS (A3_P_)o
(E2TOT Z$ ZDESI } NOT CONSISTENT,
TRANSLATE PATTERN_LXST wITH
PC MATCH=D_PTH O_ Io
P35
RE@ULT8
CZ Z$ ZDE$$ } CONSISTENT AFTER GU_S$o
@UEBB
ZI
DER@VO
-70-
TRANSLATE ALSO A PATTERN-LIST WITH
PI MATCH-DEPTH OF 1, TRANSLATED
P34 'XN PARALLEL' WITH TNE_ ABOV_
RESULT| PATTERN=LIST {PC P31),
(Z2 Z3 ZDESI } CONSISTENT AFTER GUESS,
GUESS
Z3
DER_VO
TRY NO _REFEREN_E BETWEEN THE
P$ PATTERN-LISTS, SO 'TRY' THE
P31 F|RWT ONE CONSXDERED FXRSTo
PUT INTO VOCABULARY BUILDINQ SUBPATTERN P2go
TRI$
E2TO
A25
P29
NEW PATTERN
<P29> <9-I = 29028> <9=2 _ 29554> <9=3 = 2_1_>
02 9-! 04 0 04 0 04 0
O0 A24 O0 TO O0 Y79 O0 Y79
O0 YSO 02 9=2
O0 A2B O0 D!2
O0 yTg 02 9-3
o0 D13
O4 29142
O0 VO
=71_
O0 J4
NOT INSERTED P_9 IS ISOMORBHIC TO P30o
TRY THE NE×TPATT_RN=LISTo
PI
P34
PUT I_TO VOOABULARY BUILDXNG SUBPATTERN P2B,
THI_
E2TO
A25
P28
NEW PATTERN
<P_8> <9=1 = 29_48> <9-2 _ 29258> <9-3 = 297_)
02 9-! 04 0 04 0 04
O0 A26 O0 TO O0 Y77 O0 Y77
O0 Y78 02 9_2'
O0 A2B O0 012
O0 Y77 02 9_3
O0 D13
04 29122
O0 VO
O0 J4
NOT INSERTED P_8 [_ _SOMORPHIC TO P33o
TRANSLATE PATTERN-LIST W!_TH
PI MATCH=DEPTH OF O,
RESULT_
CZ ZD_Sl )
=72-'
TRY
Pi
PUT INTO VOCABULARY 8UILDIN_ $UBPATTERNS _27 AND P26o
TREE
DEREVO
A3
P27
PUT INTO VOCABULARY
THIS
E2TO _E2TO_ _AS AL_O THE TRANSLATION
A2B OR _BE_ IN THE CONTEXT (A_,P2},
P26
PUT INTO SET
P26
A28
NEW PATTERN
<P26> <9=$ = 29085> <9-_ _ 29476> <9¢3 = 2_4_?>
02 9-$ 04 0 04 0 04 0
O0 A27 O0 TO O0 Y75 O0 Y75
O0 Y76 02 9=2
O0 A25 O0 D$2
O0 Y7_ 02 9-3,
O0 D53
04 29398
O0 09
O0 A28
=73,,
00 V8
80 J4
<P27> <9=L = 29L50> <9=2 = 29526> <9-3 = 294_4>
02 9=I 04 0 04 O 04 0
O0 A28 O0 TO O0 Y74 O0 yT_
O0 Y74 02 9-2 O0 Y?3 O0 Y73
O0 A3 O0 O/2
O0 Y73 02 9=3
O0 013
04 29430
O0 VO
O0 J4
PUT INTO SET
P27
A2
LOOKZNG AT SENTENCE 31
_SE BOY |HOD THAT ]THERE }
TOT MALIYIK TAM
PROOE$$ START
TRANSLATE PATTERN_LXSTS (Pl P_7 P26_,
Pi (PI P31 P30} AND {P_ _34 P33) ALL
P27 MATCH THE FL _ENTENOE TO A
P26 MAT_H-DEPTH O_ 2_ AND ARE
RESULTI TRANBLA?ED IN PARALLEL,
CZ Z$ TAM ) OONB_XST_NT AFTER GUESS,
-74_.
GUESS
ZI
MALSYI_
TRANSLATE
PI
P3!
P30
R_$ULT_
(Z2 Z3 TAM } CON$1ST_NT AFTER GU_$S._
GUESS
Z3
MAL_YIK
TRANSLATE
P34
P33
RE$_LTa
(Z4 HALIYIK TAM } COHSISTENT yITH INPUTo
TRY THE TRANSLATION OF THE PATTERN-
PC LIST (Pi P_4 R33} IS CLOSEST TO
P34 THE NL XNPUT_ AND (P$ P34 P_3}
P33 IS TRIED FIRST,
PUT INTO VOOABULARY
THAT
TOT
A18
"75-
P33
IF ZBIE HAD PROCESSED THE _ATTERN==LISTS_ STARTZNG WITH THOSE
OF DEEPEST MATCH._DE_TM_ XN THE ORDER |N _HIC_ THEY ARE
CON$1DERED_ THEN ZBIE WOULD HAVE ,_TARTED PRO_ESS_NG THE
PATTERN=LIST (P_£ P27 P26}o ZBIE WOULD HAVE CREATED THE FOLLOWING
VOCABULARY ENTR_ES
THAT TOT A25 P26
BOY MAL$YIK A3 P27
THE LAST ENTRY WOULD N3W ASSURE THE (INCORRECT} TRANSLATION OF
(BE BOY|MOO THI9| HERE} AS _E_TO MALiYIK _DEBI_ THE NEXT E×AMPLE
I$ A SLIGHT VARIATION OF THIS ONE.
LOOKING AT _ENTENCE 32
(BE GIRL {MOO THAT _TWERE }
TA DEVOYKA TAM
PROOE$$ START
MATOHED PATTERN L,IST
P$ 'GIRL _ X$ NOT KNOWN IN TM_
P34 CONTEXT (A3_P34_.
P33
RESULT8
(TOT Z TAM } NOT CONSISTENT.
TRANSLATE TRANSLATE PATTERN-L_ST5
P1 (Pl P_7 P_} AND {Rl P31 P30)
P27 IN _ARALLELo
-76-
P26
RESULT8
(Z Z$ TAM ) CONSII_TENT AFTER GUB$$_,
@UE$S
Zl
DEVOYKA
.TRANSLATE
Pi
P3!
P30
RESULTS
(Z2 OEVOYKA TAM } OONSIST_NTo
TRY PATTERN=LIST (P! P31 P30} G_VE$
Pi A TRANSLATION CLOSEST TO THE
P3i NL XNPUTo
PUT INTO VOCABULARY
THAT
TA
A2_
P30
LOO_IN_ AT SENTENCE 33
(BE HAND fOR (SPEAKING MA4 }I}
E2TO MOA$ RURA
PRO_ESS START
TRANSLATE
-77=
P2 HATCH-DEPTH OR 2,
P3@
P38
RESULTS
{E_TO RURA Z ) NOT C_NBISTBNT,
TRANSLATE
P2 HATCH-D_PTH OF io
P39
RE$_LT_
_2TO _UKA Z } NOT CON_IST_NT_
TRANSLATE TRA_BLATE IN PARALLEL
P4 P4 AND _? (MATCH_DEpTN 0}.
RESULT8
TRANSLATE
P2
RESUL?I
(E2TO ZI }
TRY THE TRANSLA?IO_ DUE TO B2 I$
P2 CLOSEBT TO ?HE NL INPUT°
PUT |NTO VOCABULARY BUILDIN_ SURPATTERNS _2_ AND P24o
{BP_A_ING HAN )
MOA$
A30
P24
PU? INTO VOCABULARY
=78-
MAN_
RUKA
A3
P25
PUT INTO SET
P24
A3!
N_W PATTERN
<P24> <9-1 = 2V396> <9-_ = 27938> <g,=.3= 2_.._:_>
02 9=I 04 0 04 0 04 g
O0 A29 O0 TO O0 Y71 O0 Y71
O0 Y72 02 g'_2
O0 k30 O0 0!2
O0 Y75 02 9-3
O0 D13
04 29418
O0 D9
O0 &31
O0 VO
O0 J4
(P25) (9-1 = 27180> <9"_ _ 29464> <9=3 = 2_'IA)
02 9-$ 04 0 04 0 04 0
O0 A3_L O0 TO OO YTO O0 YTO
O0 YTO 02 g=2 O0 Y69 O0 y6g
O0 A3 O0 D12
O0 Y69 02 g-3
"=79-
o0 D13
O4 28906
O0 VO
o0 J4
PUT INTO SET
P25
A3
LOO_ING AT SENTENOE 34
(BE HAND [OF (SPOKEN BOY )3)
E2TO TVOA$ RUKA
PROGE$$ START
TRANSLATE TRANSLATE IN PARALLEL
P2 PATTERN LXS?S (P2 P25 P24_ AN_
P25 (P2 P39 P3_} WNICH MATCHED
P24 THE FL SENT_NOE TO A gE_T_ OF 2,
RESULT8
{E2TO _ RUKA ) CONSISTENTo
TRANSLATE
P2
P39
P38
RESULT_
(E2TO RUKA ZI ) NOT CONSISTENT.
TRY
P2
P25
P24
PUT INTO VOCABULARY
{SPOKEN BOY )
TVOAI
A30
P24
LOOK!IN_ AT SENTENOE 35
(BE (ON (BOOK }_AND }}
ONk NA RUKE
PROCESS START
TRANSLATE
P4
P37
R_SULT_
¢ON_ Z RUKE )
TRY
P4
P37
PUT INTO VOOABULARY
ON
NA
P37
COMMENTZ TH_S SLXG_TLY UNNATURAL SENTENCE WAS ADDED TO
"81'=
AFFORd) A SMOOTH TRA_SXTXON TOWA_)S T_E NEXT SENTENCE WITHOUT
BUXLDINQ A NEW SUBPATT_RN, SEE THE COMMENTS AT THE E_D OF
SENTENCE 36,
LOOKXN_ AT SENTENCE _6
{BE {ON {BOOK }TABLE })
ONA NA STOLE
PROOES$ START
TRANSLATE
P4
P37
RESULT=
¢ONANA _ } _TABLE _ IS NOT KNOWN IN THE
TRY CONTE_T (Ai3_P37}=
P37
PUT INTO VOCABULARY
TABLE
STOLE
A13
P37
ASSUME THAT_ A) T_XS SENTENCE HAD BEEN _RESENTED BEFORE
SENTENCE 3_J B} _TABLE _ _A$ KNOW_ IN SOME CONTEXT_ _OR INSTANCE
AS _STOL _ {NOMINATZVE}_ AND O} _ON_ WA_ NOT KNOWN (WHICH WAS THE
CASE HER_}o TMEN ZBIE _OULD RAVE BUILT A NEW SUBPATT_RN By_ A}
GUESSING _TABLE t _ROH THE PREVIOUS PRINT-NAMEI B} PAIRING {BOOK}
=B2=
WITH ONE ACOEPTABLE TRANSLATION, 'ONA_, OF (BOOK)_ C) ASSIGNING
'ON _ TO THE STILL UNA;COUNTED FOR NL STRIN@ _NA_o THE NEW
SUBPATTERN WOULD HAVE BEE_ INSERTED IN THE SET A11_ ON THE P=LIST
OR P4,
AOTUALLY, IT XS NOT _ECESSARY TO BUILD A NEW SUBPATT_RNo THE
NEW F'L SENTENCE FITS I_TO THE PREVIOUS PATTERN STRUCTURE IF WE
ARE OAREFUL TO GIVE E_OU@H INTERMEDIARY SENTENCES,, SUC_ AS
SENTENCB 35,
ZBIE TENDS TO GENERATE TOO MANY SETS AND PATTERN_o IT WOULD
BE INTERESTIN@ TO GIVE _BIE T_E CAPABILITY TO RE,_ORGANI:EE ITS
STRUOTURES_ FOR EXAMPLE: BY MER@IN{_ _OME SETS OR SOME mATTERNSo
LOOK|NG AT SENTENOE 37
{FUTURE TAKE (BREAKING MA4 )BOOK }
At VOZ_,MU KNIGIU 'FUTURE_ IS A MARKER IN FL, AND
PROOE9_ START I_ _OT TO B_ TRANSLATED,
PUT INTO VOOABULARY BUILDING PATTERN PSo
BOOK
KNIQSU
A34
P5
PUT INTO VOOABULARY
TAKE
VOZ%MU
A33
P5
PUT INTO VOOABUL:ARY
(BP_AKXNG MAN )
AI THE RU$_XAN L_TT@Ro
A2 THE BET NAM_o
P5
NEW PATTGRN
<P5> <9-1 = 28B70> <9-2 = 28252> <9-3 = 292R_>
02 9=$ 04 0 04 O 04
O0 A32 O0 TO O0 Y3 O0 Y_
O0 YI 02 g'2 O0 Y_ O0 Y2
O0 A33 O0 D!2 O0 Y_ O0 y4
O0 Y2 02 g-3
O0 A2 O0 D13
O0 Y3 04 27858
O0 A34
O0 Y4
END O_ RUN
-84_
CHAPTER IV,
A CRITICAL LOOK AT ZBIE.
UHR_$ PROGRAMS (!964) MAY WELL GXV_ AN ILLUMINATING CONTRAST
TO SOME OF" THE MECHANISMS USED _Y Z_IEo UHR SHOWS OUTPUTS £OR TWO
PRO@RAMS AND DESCRIBES A _LANNED THIRD PROGRAM, ALL HIS PROGRAMS
LEARN TO TRANSLATE A NATURAL; LANGUAGE, NL$_ INTO ANOTHER NATURAL
LANQUAGEm NL2o
THE FIRST PROGRAM WAS APPLIED TO TRANSLATE GERMAN INTO
ENGL|$H, WORDS ARE SEPARATED BY BLANK$o THE PROGRAM DO_S NOT USE
CONTEXT AND RUNS INTO DIF;!ICULTIE_ ON THAT ACCOUNT, _OR _XAMPLEo
_DA$ t IN THE GERMAN 'gAS IST _ 3R _DA@ _LA$ _ BECOMES _ESPECTIVELY
_THX$_ OR _THE_o UHR_$ FIRST PROGRAM CANNOT HANDLE SUCH A
DIFFICULTY,
TME $_COND PROGRAH, WH|CH WA_ APPLIED TO T_ANSLATE ENGLISH
INTO FRENCH, I$ MORE P3WERFUL IN SEVERAL WAYS° WORDS ARE NOT
BEPARATED_ AND PART_ OF THE FUNCTION OF THE PROGRAM I$ TO SEPARATE
IMPORTANT ELEMENTB IN A C3NTINUOUB FLOW, FOR INSTANCE, TME _$_
MAR_ING A PLURALCAN BE S_PARATEDo IT I_ ALSO MORE DIFFTCULT TO
TRANSLATE A LANGUAGE WITH LITTLE INFLECTION_ SUCM AS ENGLISH_
INTO A MORE INFLECTED LAN_UAGE_ SUC_ AS FRENCH_ THAN TO TRANSLATE
...85,_
AN INFLECTED LANGUAGE_ GERMAN_ INTO ENQLI_H_ IN THE LATTER CASE_
AN INCREASED DICTIONARY O_'TEN SUFFICES, WM_E IN THE FORMER CASE,
CONTEXT IS ESSENTIAL,
1"0 OBTAIN CONTE×Tj, CLAS._E8 ARE BUI_T ON ELEMENTS OF NL2,
CLASS CLUSTERS ARE USED TO _qE$OLVE AMBIGUITIES AND GENERALIZE
PERMUTAT|ONg, IN THE GIVE_! OUTPUT, THOUGH, THE PRO@RAM DOES NOT
SEE_ TO LEARN THE 6ENERALIZED PERMUTATION= ADJECTIVE ._ NOUN _,
NOUN _, AI)JEOTIVE,
THE THIRD {PROJECTED} PROGRAM IS A ,.qTRENQTHENIN{_ OF PROQRAM
2.. IT CAN GENERATE CLASSES OF CLASSES, I oEo ENCOMPASS GROUPS OF
WOR_)$o
ALL THREE BROGRAM$ JSE STATISTICAL WEIGHTS FOR LEARNING AND
UNLEARNING, IT APPEARS THAT SOME U$_ IS MADE OF THE CORRESPONDING
ORDER OF THE LAN_UAGE_ 14 THE _IVEN EXAMPLE I_ FROM: ION BIN GIN
MANN _ I AM A MAN_ THE INFERENCES IOM _ I_ BIN _ AM_ EIN _ A_
MANN _ MAN _EEM TO BE DRARN_ I_ EXAMPL_ 3_ FROM_ IF THE BOY _ SI
LE @ARCON AND THE _ LE_ T_E INF_RENCE_ IF _ SI_ B_Y _ GARCON SEEM
TO BE DRAWN,
LET US APPLY SOME OF THE A_OVE CRITERia TO Z@_Eo INPUTS TO
ZB_E ARE WELL _EPARATED WORDS AND _B_E_S STRING MANIPULATIN_
CApABILITIE_ ARE LIMITED. TO CHECKIN_ WHETHER THE F_RST FEW
CHARACTERS OF TWO WORDS ARE IDENTICAL OR NOT, ZBIE TRIES TO
TRANSLATE FROM A STRONGLY NON-I_FLE_TE_ LANGUAGE {FL} IRTO
ANOTHER LAN_UA_E_ WHICH _ILL U_UALLY BB INFLECTED, THE CLASSES
UBE_ BY UHR_S PROGRAMS ARE BUILT ON NL_ THE CO_RESPOND!NG SETS
ARE BUILT ON FL_ E_UIVALENT TO NLI_ BY ZBIEo THE CLASSES OF
CLASSES DESCRIBED BY UNR _OR THE PROJECTED PROGRAM MAY CORRESPOND
TO THE RECURSIVE HIERARCHY {BUG}PATTERN _ SET _ SUBPATTERN® ZB!E
MAKES FEW ASSUMBTIONS ON _ORD ORDER, AND HENCE WAS ABLE TO LEARN
THE $ENTENOES EXHIBITED IN OHAPTER 3 WHEN THE RUSSIAN SENTENCES
HAD ALL BEEN PREVIOUSLY I_VERTEDo
ALL THE PROGRAMS CONSIDERED BUILD _TRUCTURE$ AT _UN=TIME AND
USE THESE STRUCTURES TO LEARN ;URTNER, _HICH HAY IHPLY BUILDIN_
NEW STRUOTUREB o
WE FEEL THAT U$1N_ A UNIFOR_ STRUCTURED REPRESENTATION_
SUCH AS FL_ WHICH IS I_ SOME SENSE _UNDERSTOOD_ _IVE_ ZBIE A
GREAT ADVANTAGE OVER A FLAT _TRING INPUT_ IT DESTROYS THE
SYMMETRY THAT UHR_$ PROGRAMS POSSESSo I? MAY BE THAT STRUCTURES
AS POWERFUL AS {OR EVEN M3RE POWERFUL THAN} THOSE BUILT IN FL CAN
BE CONSTRUCTED EVENTUALLY BY PROGRAMS STARTING FROM
(UNSTRUCTURED) STRINGSo
WE HAVE ALREADY E_COUNT_=RED VARIOUS DEFICIENCIES IN ZBIE_,
SOME OF THESE COULD B_ SOLVED BY MORE PROGRAMMING_ OTHERS
NECESSITATE A THOROUGH RETHINKING OF TH_ LEARNING TASK,
AMONG THE FIRST WE $_OULD _E_TION_"
-- THE INITIALIZATION R_ASE I$ INFLEXIBLE, SENTENCES COULD BE
STORED UNTIL TWO SENTENCES MEET THE CONDITIONS TO INITIALIZE THE
_87_
FIRST PATTERNo
= THE TRANSLATION RU_ES SHOULD BE MORE @ENERAL° WE GAVE IN
CHAPTER IX, PART B, T_O KI_D_ OF DESXRABLE TRANSLATION RULES
WHICH ARE PRESENTLY NOT USED BY Z_.I_o
= THE METHODS TO OBTAIN _GOOD GUESSES _ SHOULD BE IMPROVED..
THESE METHODS COULD US_ FOR IN_TANCE_ SOME; OF THE SEMANTICS
BUILT INTO F'L (SEE BELOW).
THE STRING MANIPULATING CAPABIL!ITIES SHOULD BE MORE
VERSATILE, IN PARTICULAR, PREFIXES AND SUFFIXES SHOULD BE
DIBOOVERED_ THEREBY ALLOW%N_ GENERALIZATIONS OF TRANSLATIONS° _OR
EXAMPLEs THE TRANSLATION OF AN ELEMENT FL_ IN THE CONTEXT AI, Pl
XS OBTAINED BY ADDING SOH_ STRING XN NL TO THE TRANSLATION OF THE
SAME ELEMENT FLI IN SOME OTHER CONT_×T AJ, PJ.
- A PATTERN SHOULD HAVE SEVERAL TRANSLATION RULES TO REFLECT
DIFFERENT WAYS IN WHICh. THE 9AME SITUATION CAN BE EXPRESSED IN
NL.
- A._ THE NUMBER OF ($Ug}PATT_RNS INCREASES, HEURISTICS (MAYBE
OF A SEMANTIC NATURE) MUST BE USED TO SPEED UP S_ARCH DURING
MATCHING,
- PRESENTLY_ THE CONTEXT OF THE (HAl:IN} VERB IS THE WHOLE
PATTERN, SO THAT_ AS THE SAME VERB (IN RL} CHAN_E_ (IN NL}_ A NE_
TOP PATTERN I$ CREATED. IN THI_ WAY_ THE NUMBER OF _ATTERNB
INCREA_E_ MUCH TO0 RAPIDLY,
=88=
BESIDES STRUCTUREs WE TRIED TO BUILD SOME SEMANTICS INTO FL°
WE CAN SPECIFY THE RE_ERENT OF A PRONOUN. WE CAN INDEX, IF
NEC6SSARY, SEVERAL PE_SON$ APREARING IN A $TTUATION TO
DIFFERENTIATE AMONG THEH, JUST AS THEY RAY BE_DIFFERENTIATED IN A
PICTURE. UNTIL NOW_ THOJGH, NO USE HAS BEEN MADE;OF THE CONTENT
OF THE SITUATIONS.
A FIRST BTEB, WHI3H WAB NEARLY |MPLEMENTED, I_ TO USE
FIN_IN@S SUCH ABI TRE SUBJECT PRONOUNS {MAN} AND {BOY} HAVE
IDENTICAL TRANSLATIONS IN RUSSIAN, WE COULD USE THIS FINDING TO
MAKE _OOD GUESSES _ ON HO_ _MAN_ AN_ _BSY_ WILL BEHAV_ IN SIMILAR
SITUATIONS, WE _OULD ALSO UsE_ TME FUNCTIONA_ LAN@UAGE DESCRIPTION
OFt (SPEAKING MAN{NUMBER 2])_ (SPEAKING {AND MAN WOHAN}), ETC°_o
TO OBTAIN THE NOTION OF (SPEAKING PLURAL},
A SECOND STEP WOULD BE T3 PROCESS 9EVERAL $1TUATIONS WHICH
A_E DYNAMICALLY RELATED. SEOUENCE_ SUCH AS_ THE BOOK I_ ON THE
TABLE_ I SHALL TAKE THE BOOK IN MY HAND, I AR TAKING THE BOOK,
THE BOOK I$ IN Ry HAND, IT WAS ON THE TABLE, ETC,.,, ARE USED BY
I. A, R ICRARDS TO TEACH TFN_EBo
A SIMPLE SCHEME O; SET INCLUSION TESTS ALDNE_. AS USED By
ZBIE_ IS NOT PDWERFUL EN,DUGH TO LEARN, FOR EXAMPLE, THE RUSSIAN
REFLEXIvB BOSBES$1VE SVOII. k HORE BOWEP,FUL SCHEME WHICH LOOKS AT
CORRELATIONS AMONG ELEMENTS IN THE _'UNCTIO_AL LANGUAG_ IS NEEDED_
IN THE FL SENTENCE
=89-"
{PUT (PERSONI} (IN HAT{OF {PERSON_}| DRAWER})
ARE PERSONS AND PERSON2 T_E SAME,
THE ABOVE DEFICIENCIES OAN BE OVERCOME BY MAKING BETTER USE
OF FL. WE MUST ALSO OUESTION THE U_E OF FLo
THE PURPOSE OF FL WAS DESCRIBED IN CHAPTER Xl, UNDOUBTEDLY,
THE _VI$10N OF' THE WORLD _ AS REPRESENTED BY FL IS VERY OLOSE TO
AN INDO...EUROpEAN_$ _VI$10_i OF TRE WORLD_. IT MAy BE POSSIBLE THAT
A SYSTEM COULD DISCARD THE FUNCTIONAL _ANGUA_E AND BOOTSTRAP
ITSELF TO LOOK AT THE WORLD XN THE LEARNED NATURAL LANGUAGE.
TM_ RUNNING SYST_Mo
PROGRAMMING ZBXE HAS BEEN A WORTHWM|LE E_PERIENCE® THE
PROGRAM GENERATED SOME BURPRISE_. T_E MECHANISMS _OR AVOIDING
ERRORS WERE NOT VERY CLEAR AT THE START. THE ADVANTAGE IN
TRANSLATIN@ IN PARALLEL PATTERN LIST_ OF A GIVEN DEPTH MAD NOT
BEEN FORESEEN_ IT _AS THOUGHT THAT A _!IMPLE HISTORIC MONITOR=
LAST PATTERN LIST OBTAINED_ FIRST TRIED_ WOULD BE ADEQUATE,
AT BRESENT_ THE PATTERN BUILDING ROUTINES CAN HANDLE ONLY FL
ELEMEN?_ WHICH HAVE 91NGLE NL wORD_ AS TRANSLATIONS= (THIS
LIMITATION CAN BE OVERCOM_ BY ADDITIONAL; B_OGRAMMING.}
CONSEQUENTLY_ ZBIE WOULD BRANCH TO AN EMPTY EXIT WMEN TRYING TO
PROOE$_, IN FRENCH, PENCIL! _ LE _RAYON {TWO NL WORDS}. DEALING
WITH ARTICLES_ MOSTLY U_NECESBARY BUT CUMBERSOME OBJECT_ POSES
SOME _ROBLEM$. I_ BENC%LI _ LE CRAYON_ _ND IF WE AL_O KNO_ THAT
BED _ LE LIT AND WALL _, LE HUR_ WE COULD CONCLUDE THAT _LE_ XS AN
UNNECESSARY OBJECTo TH_N IF WE MEET PENCXL _e UN CRAYON
{PO$SI_LY}_ WE CAN A$SJME THAT 'UN_ |S ALSO AN UNNECESSARY
OBJECT. THE SCHEME COLLAPSES NEXT_ THOU@H_ WHE_ WE MEET PENCIL
--_ SON CRAYON (HIS OR H_R PENCIL}° HERE A TEACHER MAY WELL BE
NEE_ED_
A _GOOD' TEACHING 9E_UENCE IS PROBABLY VERY IMPORTANT. EVEN
WITH A GOOD SEQUENCE,, THOUGH_ A TIME W|LL COME WHEN SOME BAD
GENERALI_ATION$_HAVE BEEN HADE_ AND THE_E MUST BE UNLBARNEDo ZBIE
IS CAREFUL ENOUGH TO AVOID MISTaKeS SO THAT, AT_ THE ELEMENTARY
LEVEL CON$1DERED_ ERROR RECOVERY IS NOT NEEDED. WE HAVE NO
EXCITING SCHEME TO PROPOSe, FOR ERROR RECOVERy_ IT APPEARS THAT
SUXTABL_ CHANGES IN SET MEMbErShIPS MAY BE SUFFICIENT IN $OHE
CABE$_ BUT ADDITIONAL WORK AT A MOR_ ADVANCED LEVEL OR LANGUAGE
PROFICIENCY IS IN ORDER,
=91®
CHAPTER V_
E_VOI
Z@IE IS A PROGRAM OF HEDIUH LENGTH {ABOUT 5000 LINES OF
IPL-V CODE} WHICH TRIE9 TO SOLVE SOME ASPECTS OF A TASK THAT HAY
OR HAY NOT BE VERY DIFFICULT8 NATURAL LANGUAGE LEARNINQ° ZBIE
|NT_RBRET$ TRE TASK AS LEARNXN_ TO EXPRESS XN A _ATURAL LANGUAGE
SITUATIONS AS DESCRIBED IN A UNIFORH_ STRUCTURED FUNCTIONAL
LANQUAGE, WHICH _ MAY BE 30NBIDERFD AS ;IVIN@ SOME CONTENT TO THE
$1TUATIONB_ ALTHOUGH ACTUALLY VERY LITTLE OF THE POWER OF THE
FUNCTIONAL LANGUAGE IS USED,
TO LEARN A LANGUA_E_ ZBIE BUILDB ELEMENTARY STRUCTURES AT
RUN-TIME8 SET$_ PATTERNS, $IMRLE TRANSLATION RULES_ AN IN-CONTEXT
VOCABULARY, IT I$ CAPABL_ OF SOMEWHAT _MPROVIN_ ITS _TRUCTURE TO
THE EFFECT THAT $O_E PREVIOUSLY LEARNED INSTANCE CAN BE LEARNED
IN A BETTER WAY, IT DOES NOT U_E STATISTICAL LEARNING $CMEMES_
IT HAS BOME ERROR-AVOIDING CAPABILXTY_ AND HAG POTENTIAL
ERROR-RECOVERY POSSIBILITIES WHIOH W_RE ACTUALLY NOT N_EDED AT
THE MODEST LEVEL_ OON$1DERED HER_, A_ OOULD BE EXPECTED, ZBIE USES
CONTEXT BOTH TO LEARN AND TO AVOID ERRORS°
QIVEN $1TUATIONB AR_ PARSED IN THE FUNCTIONAL LANGUAGE_ NOT
IN THE NATURAL LANGUAGEt THE PARSTNG GIVE_ A MEASURE OF HOW CLOSE
='92.,
A NEW SITUATION IS TO CERTAIN CLASSES OF PREVIOUSLY ENCOUNTERED
$_ITUATIONS. ZB|E TRIES TO MINIMI_E ITS LEARNIN_ AT EAC_ _TAGE BY
TRYING TO CAPITALIZE O'q THE MAXIMUM AMOUNT OF INFORHATION
AVAILABLE FROM PREVIOUS S!TUATION_, MEASURED, QUITE SIMPLY_ BY
THE DEPTH TO WHICH A NE_ SITUATION IS PARSED BY A COLLECTION OR
PATTERNS. IN FACT_ ZBIE A@A_DON_ THE LEARNING TASK WHEN FACED
WITH SITUATIONS THAT IT CONSIDERS TO_ D_XFFICULT TO HANDLE AT A
GIVEN STAGE. SINCE IT 3AN DIAGNOSE T_E PARTICULAR DIFFICULTIES
ENCOUNTERED, ZBIE COULD = ASK APPROPRIATE _UESTIONS IN A
TIME=SHARING ENVIRONME_To
IT WOULD APPEAR THAT THE VUNCTIONAL LANGUAGE SHOULD POSSESS
IN IT_ DESCRIPTION ALL THE _EMANTIC SUBTLETIES OF T_E NATURAL
LANGUAGE LEARNT_ AN UNAPPEALING FACT. A MUCH MORE POW_RPUL SYSTEM
MAY BE ABLE TO BOOTSTRA_I ITSELF AND U_E THE NATURAL LANGUAGE IT
HAS STARTED TO LEARN AS ITS MAIN REPRESENTATION, WITH POSSIBLE
REFERENCES FROM TIME TO TIME TO THE FUNCTIONAL LA_GUAGEo _EHANTIC
SUBTLETIES COULD THEN BE DESCRIBED IN THE _ATU_AL LANGUAGE
IT APPEARS TO BE ?RUITFUL TO LOOK A? NATURAL LANGUAGES AS
WAYS TO EXPRESS SITUATIONS WITH STRUCTURE AND CONTENT. HUCH
VALUABLE RESEARCH CAN BE DO_E IN AREAS TOUCHED UPON BY ZBIE,
AMON_ WM_C_ THE DESIGN 0_: _O_E ROWERFUL_ SEMANTICALLY ORIENTED_
FUNOTIONAL LANGUAGE$_ T_E: PROBLE_ O_ _RROR RECOVERY, AND THE
EVOLUTIONARY REORGANIZATION A_D _MPROVEMENT OF STRUCTURES MAY
WELL BE THE MOST INTEREBTIN_ AND CH_LLEN@INBo
APPENDIX Ao
CODE FOR CYR|LLIC ALPH#,BET®
A A. P R
5 B C
8 V T T
F GI Y U
E E X H
E _ ET L_ C
A G _4 ¥"
3 Z W W'
_1 | W, W2
l'r % 2
H _ Mt ti2
L b ?
M M 3 E2
N N' _.,; U?
n P
APPEnDiX B o
_EVO_UTIONARY LEARNING_o
WE ARE PRESENTING HERE A SHORT E×AHPLE, IN GERMAN_
EXHIBITING AN ASPECT OF ZBIE_B CARABILITXES. THE TRANSLATION RULE
OF _ATTERN Pl 19 INCORRECT, AS MORE E_AMPEEB ARE GIVEN_ TROUGH,
ZBIE BUILDS NEW PATTERNS P_ AND P3o THE SENTENCES WHICH WERE
PREVIOUSLY TRANSLATED WHE_ REAC_ING PATTERN P$ ARE NOW TRANSLATED
WHE_ REACHING BATTER_S P_ OR P_, _0 THAT PATTERN PC X$ NOT
REAONED ANY MORro PATTER_ Pl H_S EFFECTIVELY BEEN WASHED OUT.
THE OUTPUT IS REPRODUCED AS OBTAINED FROH THE PRINTER°
INPUTS IN IPL=,V FORM HAVE BEEN DELETED EXCEPT IN ONE _LLU_TRATIVE
CASE,
THE IMPORTANT ATTR!B3TE$ A_D VALUES OF A PATTERN PJ _IAVE THE
FOLL,OWING MEANIN_
TO{PJ} = TRANSLATION RULE (A LIST STRUCTURE_,
PO{BJ} =_ A LIST OF PATTER_IS WITR A F_=LI_T IDENTICAL TO PJo
TF_E OTHER ATTRIBUTES ARE USED FOR BOOK=KEEPING AND MAY BE
DISRE_IARDED,
COMMENTS ARE GIVEN AT THE RIGHT OF INPUT$_, OR AT THE END OF'
,,,gL=
THE PROCESS_N_ OF': A SEnTEnCE,
LOO_ING AT SENTENCE COMMENTS
(BE (WOMAN )MERE }
BIE XST MIE_
(BE (WOMAN _THE_E )
$IE IST DORT TME FIRST TWO SENTENCES
PRO;E$$ START TO _TART THE _NITXALIZATXON
PUT INTO VOCABULARY BE IS IN SET A$_(WOMAN} IN SET A2
(BE (WOMAN }}
{$1E IBT }
P CONTEXT VOCABULARY FOR FL COMPLEX
PUT INTO VOCABULARY
HER_ IN=CONTE×T VOCABULARY FOR FL
HIER UNIT, TME FL U_T (IN THI_ CASE_
A3 HER_) I_ |N_ERTED IN THE SET (XN
P THIS CASE_ A3_, P=Poo
PUT XNTO VOCABULARY
THERE
DOR?
A3
P
NEW PATTERN
02 9=$ 04 0 04 0 04 0
O0 kl O0 TO O? 9-3 O0 YI
,=96=
O0 Y1 02 9=2 O0 ¥3 O0 Y2
O0 A2
O0 Y2
o0 A3
O0 ¥3
COMMENTI THE |NITIALIZATIO_ PHA_E _$ OVER, FOR THE NEXT
SENTENCE_ WE SNOW THE IBL=V INPUT°
IP INBU? DA?A 5 05
X4 95 0
95 0
IP @E EO
|P {MAN{NUMB 2]} 91
|m ?NERE E4 0
xm 9-1 o
xp o
xp {NUMB 23 92
IB _AN E2 0
IP 92 0
IP NUMB EIO
IP _ E13 0
IP X3 95 0
IP 95 0
|m _XE RO
|P $IND R4
=97= •
IP _ORT R3 0
IP 5 JO
H2 ==_339 CELLS 00,=00=06
LOOKING AT SENTENOE
(BE (MAN {NUMB 2 I}THERE }
BXE $1ND DORT THE INPUTS ARE FIRST PRINTED
PROCESS START
TRY PATTERN
P
NOT MATCHED,
TRY LEARN FROM PATTERN
P (BE(MAN{NUHB _|} IB THE UNTRAN$ _
(Z _ORT} LATED PART, CORRESPONDING TO Z
PUT INTO VOOABULARY
(BE {MAN {NUMB 2 |})
{SI_ BIND }
P
PUT INTO VOCABULARY PATTERN P$ IS BEING BUILT
(MAN {NUMB 2 I}
BIN_
A2
PC
PUT INTO VOCABULARY
BE
SXE
AL
PL
NEW PATTERN
<P1> <9-I = 25256> <9=2 m _5774> <9-3 = 254_p>
02 9_I 04 0 04 0 _4 O
O0 kl O0 PO O0 PO O0 YI
O0 YL 02 9=2 O0 ¥2
O0 A2 O0 YO O0 Y3
O0 Y2 O0 J3
O0 A3 O0 J4
O0 Y3 O0 J3
O0 TO
02 9_3
COMMENTS PATTERN Pl NA$k P=LIST |OE_TICAL TO THE P-LIST OF
PO, HOWEVER, THE TRANSLATION RULES ARE DIFFERENT, ZBXE UsED
(BE{WOMAN}} _ $1E IST, AND (_EKMANKNUMB 2]}) _ SIE $1NOe BOTH
TRANSLATIONS IN THE CONTEXT Of TMB PATTERN PO, FOR MATCH BACK_
THE COMMON PARTS IN FL AND NL_ RG$_ECTIVELY _BE' AND _SIE_ WERE
PAIRED, THE COMPARISON OF THE N_N-COMMON PARTS GAVE (MAN{NUMB _J}
SXND {CONTEXT A2,PI}o T_E INFERENCE I_ GRAMMATICALLY INCORRECT°
NOTE THAT TNE TRANSLATION RULE I$ {Y$ Y2 Y3}s IN TM_ SAME ORDER
AS TNE SETSo IT I$ W_LL WO_T_ CO,PARING THX$ PATTERN P1 TO THE
PATTERN P$ CREATED BY ZBIE WHEN LEABNING RUSSIAN ¢$EE CHAPTER
=g9_,
IXI}.
LOOK|_G AT SENTENCE
{BE {WOMAN }HERE }
SXE |ST HIER THE FIRST SENTENCE AGAIN
PROCESS START
TRY PATTERN
PI
PATTERN MATCHED° RESULTg
¢6|@ Z Z$ } (WOHAN) IB NOT KNOWN IN THE
TRY PATTERN CONTEXT (A2,P%}_ HENCE TH_ Z
P ID, FOR HER_ {A3_PC} AND ZI
PATTERN MATCHED. RESULTz
(B|_ IST HX_R )
TRY LBARN MORE THE RATTERN P_, WAS THE FIRST TO
TRY L_RN R_OM PATTER_ BB TOTALLY _ATCHED_ BUT WAS NOT
Pl SUCOEgSFULLY TRANBLATED
(SIE Z Zl )
GUESS Z (Io_, (WOMAN_ XS NOT GUEBSED
ZI BUT ZC IB, _IVIN@ A CON$!BTENT
HIER TRANSLATION WITH_THE INPUT
PUT INTO VOCABULARY
(WOMAN }
IBT
A2
P1
PUT INTO VOOABULARY
HERE NOW _MERE_ IS AESO KNOWN
HI_R IN THE CONTEXT {A3_Pi}
A3
PI
COMMENT8 NOW (BE (WOMAN} HERE} WILL BE TRANSLATED BY PATTERN R:£o
LOOKIN@ AT SENTENCE
(BE {MAN }M_R_ }
MR lST HIER A NEW S_NTENCB
PROCESS START
TRY PATTERN
PI
NOT MATCHED, (MA_} I_ NOT IN A2
TRY PATTERN AS THE R=LI_TS OF PO AND Ri ARE
P IDE_T_CAL_ IT IS NOT _ECE_$ARY
NOT MATCHED, TO ACTUALLY MATCH PO
TRY LEARN FROM PATTERN
Pi
{SI@ Z HIER} NOT CONSISTENT WITH |_PUT
TRY LBARN FROM PATTERN
P
(Z MI_) Z STANDS FOR THE UNKNOWN
PUT INTO VOCABULARY TRANSLATION OR {BE(MA_}}
(BE (MAN }}
-iOi-
(ER |ST
P
PUT INTO VOCABULARY C_EATXNG PATTERN P2
( MAN
ER
A2
P2
PUT INTO VOOABULARY
BE
IST
AI
P2
NEW PATTERN
<P2> <9"=1 = 25_14> <9=2 =- 26054> <9"=3 = 2_i_>
02 9=__ 04 O 04 0 04 0
O0 kl O0 PO O0 PO O0 Y2
O0 Yl 02 9=2 O0 PI O0 YI
O0 A2 O0 YO O0 Y3
O0 Y2 O0 J3
O0 A3 O0 J4
o0 Y3 O0 J3
O0 TO
02 9-3
OOMMENT_ WE MATCHED 8AOK (BE(MAN}} _ ER IST AND (BE(WOMAN}}
SXE ]_$T_ TO OBTAIN A Nm.WPATTERN P_o THE T_ANSLATXON RULE OF
=i02_
P2, (Y2 Y1 Y3), Z$ DIFFERENT F_OM THE TRAnSLATiON RULE OF P1 AND
IS _RAMMATICALL¥ CORRECT, NOTE THAT TNE TRANSLATION RULE CONTAXN$
A TRANSRORMATXON,
LOOKING AT SENTENCE
(BE (WOMAN }HERE'}
$1E XST HIER AGAIN THE F_RST SENTENCE
PROCESS START
TRY PATTERN
P2
PATTERN MATCHED, RESULTs
(Z IST Z% )
T_Y PATTERN
P1
PATTERN MATCHED, RESULT=
($|E IST _|_} NOW T_ANSLATED BY Pi
TRY LEARN MORE
TRY LEARN FROM PATTERN
P2
(Z XST Zl }
GUESS
Zi
HXER
PUT XNTO VOOABULARY
HER_
MXE_
=I03-
A3
P2
PUT INTO VOOABULARY
(WOHAN)
PIE
A2 NOW THE $EN?ENCE WILL BE
P2 TRANSLATED 9Y P2
LOOMING AT SENTENCE
(BE (SPEAKING MAN {NUMB 2 |}HERE_ }
WIR SIND HIER A NE_ SENTENC_
PROOE$S START
TRY PATTERN
P3 (SPeAKInG MAN{NUMB 5|} I$
NOT HATCHED, NOT IN A2
TRY PATTERN
PI
NOT HATCHED,
TRY PATTERN
P
NOT HATCHED,
TRY LEARN FROM PATTERN
P2
(Z |ST HIER} NOT CONBIST_NT WITH XNPUT
TRY LEARN FROM PATTERN
PI
-104=
CSIE Z MIER }
TRY LEARN FROM PATTERN
P
(Z _IER )
PUT INTO VOCABULARY
(BE {_EAKING M&N [NUMB 2 |}}
(WIRSIND }
P
PUT ZNTO VOCABULARY CREATZN_ PATTERN P3
(SPEAKING MAN {NUMB 2 ]}
W!R
k2
P3
PUT INTO VOCABULARY
BE
SINO
At
P3
NEW PATTERN
<P3> <9-1 = 25584> <9=2 = 26328> <9-3 = 2_1_>
02 9=I 04 0 04 0 04 0
O0 kl O0 PO O0 PO O0 Y2
O0 YI 02 9-2 O0 P_ O0 YI
O0 A2 O0 YO O0 P! O0 Y3
O0 ¥2 O0 J3
O0 A3 O0 j4
=i05_
O0 Y3 O0 J3
O0 TO
O2 9-3
COMMENT_ THE TRANSLATION RULES O_ P3 AND P2 ARE IDENTICAL,
BUT _@E _ IS: TRANSLATED DIFFERENTLY IN THE CONTEXTS: {Ai,P2) AND
{Ai_P3}.
LOO_ING AT BENTENOE
(BE (MAN {NUMB 2 ]}THERE }
$1E $1ND DORT THE T_I_D SENTENCE AQA!N
PROOES9 START
TRY PATTERN
P3
PATTERN MATCHED. RESULT_
{Z SXND Z% }
TRY PATTERN
P2
PATTERN MATOHED. RESULTs
CZ IBT Z$ }
TRY PATTERN
PC
PATTERN MATOHED. RESULT_
{BIE SXND Z }
TRY PATTERN
P
PATTERN MATOHED. RESULT_
®i06-
(SXE BIND DORT }
TRY LEARN MORE
TRY LEARN FROM PATTERN
P3
(Z $1ND Z$ }
8UE88 THE TRANSLATION IS CONSISTENT WITH
Zi TNE INPUT EVEN WITHOUT THE GUESS
DORT OF _! (_TANDI_G FOR _THER_
PUT INTO VOCABULARY
THERE
_ORT
A3
P3
PUT INTO VOCABULARY
(MAN tNUMB 2 ))
$1E
A2 NOW THE SENTENCE WXLL BE
P3 TRANSLATED _Y P3
COMMENT_ WE SHALL NOW 81VE _ENTENCE$ ONE AND THREE AQAIN,
AN_) SHOW MOW THEY ARE TRA_BLATED BY P_ AND P3 RE$pECTIVELY, TFIE
PATTER_J P$ IS NOT REACHED ANY MORE,
LOOKING AT SENTENCE
(BE (WOMAN }HERE }
$1E IST HIER
PRO_E$$ START
=107=
TRY PATTERN
P3
PATTERN HATCHED. RESULTs
,,,(Z SX_D Z$
TRY PATTERN
P2
PATTERN MATCHED_ RESULT_
{SI_ XST HIER }
TRY LEARN MORE
TRY LEARN FROM PATTERN
P3
(Z $1ND Z$} NOT CON_ISTBN?
LOO_IN_ AT SENTENCE
{BE {MAN {NUMB 2 ]}THERE }
SXE $1ND DORT
PROOESS START
TRY PATTERN
P3
PATTERN MATOREDo RESULT_
(SIE BIND DORT }
END OF RUN
=lOS=
BXBLIOGRAPMYo
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XNDUOTIVE INFERENCE ON SEQUENCES, _ IN TME PROGRAMMING LANGUAGE
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%947.
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-R&Dindexin_ annotation must be on_ when the
:UR|TY C LASStFiCAT|ON
Carneg_.e-Mellon Unave.,..s_ocyDepartment of Computer So _aenee_ ab._R.UpPittsbur
REPORT TITLE
NATURAL LA_GUAGE LEARNING BY C0_'_PUTER
4. DESCRIPTIVE NOTES _Type Of _ep_ft end In©lusive _ee)
5. AU THOR(_) _me_ ))
Laurent Sik!_ssy
REPORT _ATE 7ao TOTAL NO, OF" PAGES 7be NO. OF REFS
May 1968 lIL_ 11Sa. CONTF_ACT OR GRANT NO, 9a° OF||GINATOR'S REPO_T NUMBF.R(S_
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97?8
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_3. ABSTRACT
Lear_._g a natural la_gu_ge is taken as an _mprovement in asystem's ability to express siouat _ons _.m a _L_atural language.
This d_ssertatiou describes a computer program_ calied Zbie_written im iPL-V_ which accepts the de_scr_ption of s_tuatioms ina _uiform_ structured functional !amguageamd tries to expmessthese situations _o_ a _,atural lamguageo Examples are given forGermam and_ most!y_ Russian.
,_ds simple memory structures. PatternsAt rt_u-time_ Z_,ie bui] -a_d sets are built on the fumctiona! language. The tramslatiou rulesof the patterns and an i_-context vocabulary prov:Lde the tramsiti_omto the natural language. Zbie is a cautious learmer_ and avoids errorby several mechanisms° Zble is ca_ab!e of some evo!utio_ary lear_i_go
Sect_rityClassification
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