Translation by Abduction 
Jerry R. Hobbs 
ArtificiM Intelligence Center 
SRI International 
Menlo Park, California. 
Megulni I(ameya.ma 
Center for the Study of Language 
and Information 
Stanford University 
Stanford, California. 
Machine Translation and World Knowledge. 
Many existing approaches to machine translation take 
for granted that the information presented in the out- 
put is found somewhere in the input, and, moreover, 
that such information should be expressed at a single 
representational level, say, in terms of the parse trees 
or of "semantic" mssertions. Languages, however, not 
only express the equivalent information by drastically 
different linguistic means, but also often disagree in 
what distinctions should be expressed linguistically at 
all. For example, in translating from Japanese to En- 
glish, it is often necessary to supply determiners for 
noun phr;tses, and this ira general cannot be (lone with- 
out deep understanding of the source ~ text. Similarly, 
in translating fl'om English to Japanese, politeness 
considerations, which in English are implicit in tile 
social situation and explicit in very diffuse wws ira, 
for examl)le, tile heavy use of hypotheticals, must be 
realized grammatically in Japanese. Machine trans- 
lation therefore requires that the appropriate infer- 
(noes be drawn and that the text be interpreted to 
stone depth (see Oviatt, 1988). Recently, an elegant 
approach to inference in discourse interpretation has 
been developed at a number of sites (e.g., ltobbs et al., 
1988; Charniak and Goldman, 1988; Norvig, 1987), 
all based on tim notion of abduction, and we have 
begun to explore its potential application to machine 
translation. We argue that this approach provides the 
possibility of deep reasoning and of mapping between 
the languages at a variety of levels. (See also Kaplan 
et al., 1988, on the latter point.) 1 
Interpretation as Abduction. Abductive infer- 
enee is inference to the best explanation. The easi- 
est way to understand it is to compare it with two 
words it rhymes with---deduction and induction. De- 
duction is; when from a specific fa.ct p(A) and a gen- 
1The authors have profited from discussions about this work 
with Mark Stickel and with the l)arl.lcipants in the 'rransla- 
tion Group at CSLI. The research was funded by the I)eDnse 
Advanced Research Projects Agency under Ot/iee of Naval Fie- 
search contract N00014-85-Co0013, and by a gift fl'om the Sys- 
tems Development Fmmdatlon. 
eral rul  (V*)v(:) q(*) we co, ch, de q(A). In- 
duction is when from a number of instances of p(A) 
and q(A) and perhaps other factors, we conclude 
(Vx)p(x) D q(x). Abduction is the third possibil- 
ity. It. is when fl'om q(A) and (Vx)p(x) D q(a:), :re 
conch, de p(A). Think of q(A) as some observational 
evidence, of (Vx)p(x) D q(x) ~s a general law that 
could explain the occurrence of q(A), and of p(A) as 
the hidden, underlying specific cause of q(A). Much 
of tile way we interpret the world in general can be 
understood as a process of abduction. 
When the observational evidence, the thing to be 
interpreted, is a natural language text, we must pro- 
vide the best explanation of why the text would be 
true. In the TACITUS Project at SRI, we have de- 
veloped a scheme for abductive inference thatyields 
a significant simplification in the description of inter- 
pretation processes and a significant extension of the 
range of phenomena that can be captured. It has been 
implemented in the TACITUS System (Itobbs et al., 
1988, 1990; Stickel, 1989) and has been applied to 
several varieties of text. The framework suggests the 
integrated treatment of syntax, semantics, and prag- 
mattes described below. Our principal aim in this 
paper is to examine the utility of this frmnework as a 
model for translation. 
In the abductive framework, what the interpreta- 
tion of a sentence is can be described very concisely: 
'.Ib interpret a sentence: 
(1) Prove tile logical form of the sentence, 
together with the constraints that 
predicates iml)ose on their 
arguments, 
allowing for coercions, 
Merging redundancies where possible, 
Making assumptions where necessary. 
By the first line we mean "prove from the predicate 
calculus axioms in tile knowledge base, the logical 
1 155 
form that. has been produced by syntacl.ic analysis 
and selnantic translation of t.he sentence." 
In a discourse situation, the speaker and hearer 
hotll have their sets of private belieN, and there is 
a. large overlapping set of mutual beliefs. An utter- 
ance stands with one foot in nmtual belief and one 
foot in the speaker's private beliefs. It is a bid to ex- 
tend the area of mutual belief to include some private 
beliefs of the speaker's. It is anchored referentially 
in mutual belief, and when we prove the logical form 
and the constraints, we are recognizing this referen- 
tial anchor. This is the given in formation, the definite, 
the presupposed. Where it is necessary to make as- 
sumptions, the information comes from the speaker's 
private beliefs, and hence is the new information, the 
indefinite, the ~sserted. Merging redundancies is a 
way of getting a minimal, and hence a best, interpre- 
tat, ion. 
An Example. This characterization, elegant 
though i~ may be, would be of no interest if it did 
not lead to the solution of the discourse problenas we 
need to have solved. A brief example will illustrate 
t.hat it indeed does. 
(2) The Tokyo office called. 
This example illustrates three problems in "local 
pragmatics", the reference i~roblem (What does "the 
Tokyo oftlce" refer to'?), t, be compound nominal in- 
terpretation problem (What is the implicit relation 
between Tokyo and the office?), and the metonymy 
problem (ltow can we coerce from the office to the 
person at the office who did the calling?). 
Let us put these problems aside, and interpret the 
sentence according to characterization (1). The logi- 
cal form is something like 
(3) (3 e, z, o,b)calr(e, ~;) A pe,'son(z) 
Arel(x,o) A office(o) A nn(t,o) 
A Tokyo(t) 
That is, there is a calling event e by a person x related 
somehow (possibly by identity) to the explicit subject 
of the sentence o, which is an office and bears some 
unspecified relation nn to t which is Tokyo. 
Suppose our knowledge base consists of the follow- 
ing facts: We know that there is ~ person John who 
works for O which is an office in Tokyo T. 
(4) person(J), work-fo,'(J,O), office(O), 
in(O, T), Tokyo(T) 
Suppose we also know that work-for is a possible 
coercion relation, 
(5) (v x, y) y) 
a.nd that in is a possible implicit relation in compound 
nominals, 
(6) (v y, z),:,,(y, z) y) 
Then the proof of all but tim first, conjunct of (3) is 
straightforward. We tiros assutl\]e (~ e)call'(e, J), and 
this constitutes the new informalAon. 
Notice now that all of our local pragmatics prob- 
lems have been solved. "The Tokyo office" hms been 
resolved to O. The implicit relation between Tokyo 
and the office has been determined to be the in rela- 
tion. "The Tokyo office" has been coerced into "John, 
who works for the Tokyo office." 
This is of course a simple example. More com- 
plex examples and arguments are given in ltobbs 
at al., (1990). A more detailed description of the 
method of abductive inference, particularly the sys- 
tem of weights and costs for choosing among possible 
interpretations, is given in that paper and in Stickel, 
(1989). 
The Integrated Framework. The idea of in- 
terpretation as abduction can be combined with the 
older idea of parsing as deduction (Kowalski, 1980, 
pp. 52-53; Pereira and Warren, 1983). C, onsider a 
grammar written in Prolog style just big enough t,o 
handle sentence (2). 
(7) (Vi,j,k)np(i,j) A v(j,k) D s(i,k) 
(8) (Vi,j,k,l)det(i,j) A n(j,k) A n(k,I) 
D np(i, 1) 
That is, if we have a noun phrase from "inter-word 
point" i to point j and a verb from j to k, then we 
have a sentence from i to k, and similarly for rule (8). 
We can integrate this with our abductive framework 
by moving the various pieces of expression (3) into 
these rules for syntax, ms follows: 
(9) (Vi,j,k,e,x,y,p)np(i,j,y) A v(j,k,p) 
Ap'(e,x) A Req(p,x) A rel(x,y) 
s(i, k, e) 
That is, if we have a noun phrase from i to j refer- 
ring to y and a verb from j to k denoting predicate 
p, if there is an eventuality e which is the condition 
of p being trne of some entity x (this corresponds to 
calf(e, x) in (3)), if ~ satisfies the selectional require- 
ment p imposes on its argument (this corresponds to 
person(x)), and if x is somehow related to, or co- 
ercible from, y, then there is an interpretable sentence 
from i to k describing eventuality e. 
(10) (Vi,j,k,l,w~,w~,z,y)det(i,j,the) 
^  (j,k,wd ^ ,.(k,l, ^ ^  2(y) 
A nn(z, y) D np(i, I, y) 
1~56 2 
That is, if l.here is the determiner "the" from i to j, a 
noun from j to k denoting predicate wl, and another 
noun from k to 1 denoting predicate w~, if there is a 
z that wl is l,rue of and a y that w2 is true of, arm if 
there is a.n nn. relation between z and Y, then there is 
an interprelable noun phrase fl'om i to I denoting y. 
These rules incorporate the syntax in the liter- 
als like v(j,k,p), the pragmatics in the litera.ls like 
p'(e,a:), and the compositional semantics in the way 
the pragmatics expressions are constructed out of tilt 
in lbrmal.ion provided by the syntactic expressions. 
To 1)arse wilh a grammar in the Pmlog style, we 
plove s(0, N) where N is the number of words in I,he 
sentence. To parse and interpret in the integrated 
,,,e prove (3 N, 
An appeal of su<:h declarative frameworks is their 
u.~ability for generation as welt as interpretation 
(Shieber, 1988). Axioms (9) and (10) ca.n be used 
for generation as well. In generation, we are given an 
ewmtuality l'2, and we need t.o find a seutence with 
sorne number n of words that describes it. Thus, we 
n,:ed t.o prove (3,,)s(0, n, £'). Whereas in interpreta- 
tion il, is tile new informal.ion that is assumed, in gen- 
eral, ion it is I:.he terminal nodes, like v(j, k, p), that are 
a,';:;umed. As.suming them constitutes uttering l, heln. 
Translation is a matter of interpreting in the source 
language (say, English) and generating in the target 
language (sa.y, Japanese). Thus, it can be cha.rac- 
terized as proving for a sentence with N words the 
e:~ l)ression 
(\]:1) N,e) a 
where sf.: is I.he root node of the English grammar and 
so is the root. node of the Japanese. 
Actually, ~,his is not quite true. Missing in the logi- 
cal form in (3) and in the grammar of (9) and (10) is 
the "relative mutual identifiabillty" relations that are 
encoded in the syntactic structure of sentences. For 
example, the o\[lice in (2) should be mutually identifi- 
able once Tokyo is identified. In the absence of these 
conditions, the generation conjunct of (11) only says 
to express something true of e, not something that 
will enable the hearer to identify it. Nevertheless, the 
framework a.s it is developed so fa.r will allow us to 
address some nontrivial problems in translation. 
This l)oint exhibits a general problem in transla- 
tion, machine or human, namely, how literal a trans- 
lation should be produced. We may think of this as a 
scale. At one pole is what our current formalization 
yMds--a translation that merely says something true 
about the eventuality asserted in the source sentence. 
AI. the other pole is a translation that translates ex- 
plicitly every property that is explicit in the source 
sentence. Our translation below of example (2) lies 
somewhere in between these two poles, ldeMly, tile 
translation should be one that will lead the hearer to 
tile same underlyiug situation as an interpretation. I~ 
is not yet clear how this can be specified hmnally. 
The ExamI)le Translated. All idiomatic trans- 
lation of sentence (2) is 
(12) Tokyo no office kara denwa ga a.ri-nmshita. 
Tokyo's ofllce f,'om call Subj existed 
Let us say the logical form is ~ follows: 
(13) aru(e) A ga(d,e) A denwa(d) A kora(o,e) 
A office(o) A ,,o(1., o) A Tokyo(Q 
A toy grammar plus pragmatics for Japanese, cor- 
resl)onding to the grammar of (9)-(10) is ~s follows~: 
(14) (Vi,j,k,l,e,p)pp(i,j,e) A pp(j,k,e) 
A v(< t, ^ > ,(i, l, e) 
(15) (Vi, j,k,z,e,pari),,p(i,j,;,:) 
A pa,'t ide(j, k, l,a,'t ) A pa,'t(x,e) 
-o pp(i, k, e) 
(16) (Vi,j,k,l,.~,V),u,(i,j,~j) A pa,'iicle(j,k,,,o) 
a t, A ,,,o(v, 
.p(i, l, z) 
(17) (Vi,j,w,z)n(i,j,w) A w(.~) D np(i,j,z) 
pp(i,j, e) mean.~ that there is a particle phrase from i 
to j with the missing a.rgumenl, e. part is a particle 
and the predicate it encodes. 
If we are going to translate between the two lan- 
guages, we need axioms specifying the transfer relao 
tions. Let us suppose "denwa" is lexically ambigu- 
ous between the telephone instrument denwal and 
the calling event denwa2. This can be encoded in the 
two axioms 
(18) aenw ( ) 
Lexical disambiguation occurs &s a byproduct of in- 
terpretation in this framework, when the proof of the 
logical form uses one or the other of these axioms. 
"i)enwa ga aru" is an idiomatic way of expressing 
a calling event in Japanese. This can be expressed by 
the axiom 
(20) (Ve, x)ca.'(<x) D (3,0,1e,,.,,o.~(, 0 
A :~,,(a, e) A a,',,(e) 
The agent of a calling event is Mso its source: 
2For simplicity in t.his example, we are assuming the words 
of the senl.ences are given; in practice, this can be carried down 
to the level of characters. 
3 157 
(21) _9 
We will need an axiom i, hat coarsens the granularity 
of l.he source. If Jolm is in Tokyo when he calls, then 
Tokyo as well as aolln is the source. 
(22) (v y, ^ ;D 
D Source(y, e) 
If x works for y, then x is in y: 
(23) (V x, y)work-for(z, y) D in(z, y.) 
Finally, we will need axioms specifying the equiva- 
lence of the particle "karl" with the deep cruse Source 
(24) - 
and the equivalence between tile particle. <<no" and the 
implicit relation in English compound nolniuals 
(2r,) (v v) - .,D 
Note that these "transfer" axioms encode world 
knowledge (22 and 23), lexical ambiguities (18 and 
19), direct relations between tile two languages (20 
and 25), and relations between the lang,\[ages and deep 
"interlingnal" predicates (21 and 24). 
'the proof of expression (11), using the English 
grammar of (9)-(10), tile knowledge base of (4)-(6), 
tile Japanese grammar and lexicon of (14)-(19), and 
the transfer a.xioms of (20)-(25), is shbwn in Figure 
1. Boxes are drawn a.round the expressions that need 
to be assmned, namely, the new information in the 
interpretation and the occurrence of lexical it.eros in 
the generation. 
The axioms occnr at a variety of levels, from tile 
very superficial (axiom 25), to very langnage-pair spe- 
cific transfer rules (axiom 20), to deep relations at the 
interlingual level (axioms 21-24). This approach thus 
permits mixing in one framework both transfer and 
interlingual approaches to translation. One can state 
transfer rules between two languages at various levels 
of linguistic abstraction, and between different levels 
of the respective languages. Such freedom in transfer 
is exactly what is needed for translation, especially 
for such typologically dissimilar languages as English 
and Japanese. It is thus possible to build a single sys- 
tem for translating among more than two languages 
in this framework, incorporating the labor savings of 
interlingual approaches while allowing the convenient 
specifieities of transfer approaches. 
We should note that other translations for sentence 
(2) are possible in different contexts. Two other pos- 
sibilities are the following: 
(26) Tokyo no office ga denwa shirnashita. 
Tokyo's office Subj call did-Polite 
Ti, e 'tokyo omce made {aM, el call. 
(27) Tokyo no otlice kara no denwa ga arimashita. 
Tokyo's office from's call Subj existed-Polite 
There was the call fl'om the Tokyo omce (that 
we were expecting). 
The difference between (12) and (26) is the speaker's 
viewpoint. Tile speaker takes tile receiver's viewpoint 
in (12), while it is neutral between the caller and the 
receiver in (26). (27) is a more specific version of 
(12) where the call is mutually identifiable. All of 
(12), (26) and (27) are polite with the suffix "-masu". 
Non-polite variants are also possible translations. 
On the other hand, in the following sentence 
(28) Tokyo no office karl denwa shimashita. 
Tokyo's office from call did-Polite 
\[1 made {althe\] call fl'om the Tokyo omce. 
there is a sti!ollg hfference that the caller is the speaker 
or son\]eone else who is very salient hi the current coil- 
text. 
The use of "shimashita" ("did")in (26) and (28) 
indica.tes tim description from a neutral poiig of view 
of an event of some agent in tile Tokyo office CallSillg 
a telephone call to occnr at the recipienWs end. This 
neutral point of view is expressed in (26). In (28), tile 
subject is omitted and hence must be salient, and con- 
sequently, the sentence is told from tile caller's point 
of view. In (12) "ari-mashit£' ("existed") is used, 
and since the telephone call exists primarily, or only, 
at the recipient's end, it is a~ssumed the speaker, at 
least in point of view, is at the receiver's end. 
Although we have not done it here, it looks as 
though these kinds of considerations can be formal- 
ized in our framework as well. 
IIard Problems. If a new approach to machine 
translation is to be compelling, it must show promise 
of being able to handle some of the hard problems. 
We have identified four especially hard problems in 
translating between English and Japanese. 
1. The lexical differences (that occur between any 
two languages). 
2. Honorifics. 
3. Definiteness and number. 
4. The context-dependent "information structure". 
The last of these includes the use of "wa" versus "g£', 
tile order of noun phrases, and the omission of argu- 
ments. 
158 4 
(7 e,n) SW(0,4,e ) Sj (0,n,e) 
PP(0,4,E) & PP(4,6,E) &~ & aru(E) 
NP(0,3,O) NP(4,5,D) 
NP(0,I,T) ~'~ 
'.ii;!;iii, / & NP(2,3,0) _%o,..0, 
& Tokyo(T) / & office(O) / 
NP(0,3,O) ~ 
person(J) 
& V(3,4,call) &~ 
& rel(J,O) 
work-for(J,O) 
Det(0,l,the) & Noun(l,2,Tokyo) & Tokyo(T) 
un(2,3,office) & office(O) 
& nn(T,O) 
in(T,O) 
Figure i. Translation by Abduction 
5 159 
These are the areas where one language's roof 
phosyntax requires distinctions that are only implicit 
in the commousense knowle(Ige or context, in tile other 
language. Such problems cannot be handled by ex- 
isting senl.ence-by-senteuce translation syst.ems with- 
out unnecessarily complicating the representations for 
each language. 
In this short paper, we can only give the briefest 
indication of why we think our framework will be pro- 
ductive in investigating the Iirst three of these prob- 
\]el/iS. 
Lexical Differences. Lexical differences , where 
they can be specified precisely, can be encoded ax- 
iomatically: 
(V~)w.te,'(~) ^ ,~.,'.qhot,(~) - v,,(~) 
(v,),o.t~h(~) - tok~i(~) ^ ,,,o,,(~) ' 
(yx)clock(x) =__ tokei(x) A ~worn($) 
Information required for supplying Japanese numeral 
classifiers can be specified similarly. Thus the equiv- 
alence between the English "two trees" and the 
Japanese "ni hou no ki" can be captured by tim ax- 
ioms 
(Vx)t,'ee(x) D cyli,,.d,'ica.l(~:) ' 
(V x)eylind,'ieal(x) - hon(x) 
Honorilies. Politeness is expressed in very differ- 
ent ways in English and Japanese. In Japanese it 
is grammaticized and \[exiealized in s6metimes very 
elaborate ways in the form of houorifics. One might 
think that the problem of honorifics does not arise 
in most practical translation tasks, such as translat- 
ing computer manuals. English lacks honorifics and 
in Japanese technical literature they are convention- 
alized. But if we are translating business letters, this 
aspect of language becomes very important. It is re- 
alized in English, but in a very different way. When 
one is writing to one's superiors, there is, for example, 
much more embedding of requests in hypotheticals. 
Consider for example the following English sentence 
and its most idiomatic translation: 
Would it perhaps be possible for you to lend 
me your book? 
Go-hon o kashite-itadak-e-masu ka. 
llonorific-book Obj lending-receive-can- Po- 
lite ? 
In Japanese, the object requested is preceded by the 
honorific particle "go", "itadak" is a verb used for 
a receiving by a lower status person from a higher 
status person, and "rnasu" is a politeness ending for 
verbs. In English, by contrast, the speaker embeds 
160 
tile request in various modMs, "would", "perhaps ~', 
and "possible", and uses a more formal register than 
normal, ill his choice, for example, of "perhaps" rather 
than "maybe". 
The facts about the use of honorifics can be encoded 
axionmtically, with predicates such as HigherStatus, 
where this information is known. Since all knowledge 
in this framework is expressed uniformly in predicate 
calculus axioms, it is straightforward to combine in- 
formation from different "knowledge sources", stlch as 
syntax and the speech act situation, into single rules. 
It is therefore relatively easy to write axioms that, for 
example, restrict the use of certain verbs, depending 
on the relative status of tim agent and object, or the 
speaker and hearer. For example, "to give" is trans- 
lated into the Japanese verb "kudasaru" if tim giver 
is of higher status than the recipient, but into the 
verb "s~shiageru" if the giver is of lower status. Simi- 
larly, the grammatical fact about the use of tim suffix 
"-masu" and the fact about the speech act situation 
that speaker wishes to be polite may also be expressed 
in the same axiom. 
We can also express the facts concerning the use 
of the honorific particle "o" (or "go") before nouns. 
There seem to be three closes of nouns in this re- 
spect. Some nouns, such as "cha" ("tea"), always take 
the particle ("o-cha'). Some nouns, especially loan 
words like "kShi" ("coffee"), never take the particle. 
Other nouns, such ~ "bSshi" ("hat"), take the hon- 
orific prefix if the entity referred to belongs to some- 
one of higher status. For this class of nouns we can 
state the condition formally. 
(Y i, j, k, p, x, y)Honorific(i, j, o) 
^ No. (j, k, p) A p@) ^ pos   s(U, 
A HigherStatus(y, Speaker) 
D NP(i, k, x) 
That is, if the honorific particle "o" occurs from point 
i to point j, the noun denoting the predicate p occurs 
from point j to point k, and p is true of some entity x 
where someone y possesses x and y is of higher status 
than the speaker, then there is an interpretable noun 
phrase from point i to point k referring to x. 
Definiteness and Number. The definiteness and 
number problem is illustrated by the fact that the 
Japanese word "ki" can be translated into "the tree" 
or "a tree" or "the trees" or "trees". It in not so 
straightforward to deal with this problem axiomati- 
cally. Nevertheless, our framework, based ~ it is on 
deep interpretation and on the distinction between 
given and new information, provides us with what we 
need to begin to address the problem. A first approxi- 
mation of a method for translating Japanese NPs into 
English NPs is as follows: 
1. R.esolve deep, i.e., find the referrent of the 
Japanese NP. 
2. Does the Japanese NP refer t.o a set of two or 
more? If so, translate it as a plural, otherwise as 
a singular. 
3. Is the entity (or set) "mutually identifiable"? If 
so, then translate it ~s a definite, otherwise as an 
indefinite. 
"Mutually identifiable" means first of all that the de- 
scription provided by the Japanese NP is mutually 
known, and secondly that there is a siltgle most salient 
such entil,y. "Most salient" means that there are 
no other equally high-ranking interpretations of the 
Japanese sentence that resolve tim NP in some other 
way. (Generic definite noun phrases are }?eyond the 
scope of this paper.) 
Conclusion. We have sketched our solutions to 
the various problems in translation with a fairly broad 
brush in t, his short paper. We recognize that many 
details need to be worked out, and that in fact most of 
l, he work in machine translation is in working out the 
details. But we felt that in proposing a new formalism 
\[or translation research, it. was iml)orl, aut to sta.nd 
1)a.ek and get a. view of the forest befot'e moving in to 
examine the individual trees. 
Most machine translation systems today map the 
source language text into a logical form that is fairly 
close to the source language text, transfor,n it into a 
logical tbrrn that is fairly close to a target, language 
text, and generate the target language text.. What 
is needed is first of all the possibility of doing deep 
interpretation when that is what is called for, and 
secondly the possibility of translating from the source 
to the target langua.ge at a variety of levels, from the 
most superficial to levels requiring deep interpretation 
and access to knowledge about the world, the context, 
and the speech act situation. This is precisely what 
the framework we have presented here makes possible. 

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