A FOUNDATION FOR SEMANTIC INTERPRETATION 
Graeme Hirst 
Department of Computer Science 
Brown University 
Providence, RI 02912 
Abstract 
Traditionally, translation from the parse tree repre- 
senting a sentence to a semantic representation (such 
as frames or procedural semantics) has a/ways been 
the most ad hoc part of natural language understand- 
 ng (NLU) systems. However, recent advances in lin- 
guistics, most notably the system of formal semantics 
known as Montague semantics, suggest ways of putting 
NLU semantics onto a cleaner and firmer foundation. 
We are using a Montague-inspired approach to seman- 
tics in an integrated NL U and pro blem-solving system 
that we are building. Like Montague's, our semantics 
are compositional by design and strongly typed, with 
semantic rules in one-to-one correspondence with the 
meaning-affecting rules of a Marcus-style parser. We 
have replaced Montague's semantic objects, functors 
and truth conditions, with the elements of the frame 
language Frail, and added a word sense and case slot 
disambiguation system. The result is a foundation for 
semantic interpretation that we believe to be superior 
~o previous approaches. 
I. Introduction 
By semantic interpretation we mean the process of 
mapping from a syntactically analyzed sentence of 
natural language to a representation of its meaning. 
We exclude from semantic interpretation any con- 
sideration of discourse pragmatics; rather, discourse 
pragmatics operate upon the output of the semantic 
interpreter. We also exclude syntactic analysis; the 
integration of syntactic and semantic analysis becomes 
very messy when complex syntactic constructions are 
considered, and, moreover, it is our observation that 
those who argue for the integration of the two are 
usually arguing for subordinating the role of syntax, a 
position we reject. This is not to say that parsing can 
get by without semantic help; indirect object finding, 
This work was supported by the Oflfice of Naval Research under 
contract number N00014-79-C-0592. 
and prepositional phrase and relative clause attach- 
ment, for example, often require semantic knowledge. 
Below we will show that syntax and semantics may 
work well together while remaining distinct modules. 
Research on semantic interpretation in artificial 
intelligence goes back to Woods's dissertation (1967, 
1968), which introduced procedural semantics in a 
natural-language front-end for an airline reservation 
system. Woods's system had rules with patterns that, 
when they matched part of the parsed input sentence, 
contributed a string to the semantic representation 
of the sentence. This string was usually constructed 
from the terminals of the matched parse tree frag- 
ment. The strings were combined to form a procedure 
call that, when evaluated, entered or retrieved the ap- 
propriate database information. This approach is still 
the predominant one today, and even though it has 
been refined over the years, semantic interpretation 
remains perhaps the least understood and most ad hoc 
area of natural language understanding (NLU).I 
However, recent advances in linguistics, most not- 
ably Montague semantics (Montague 1973; Dowry, 
Wall and Peters 1981), suggest ways of putting NLU 
semantic interpretation on a cleaner and firmer foun- 
dation than it now is. In this paper, we describe such 
a foundation. 2 
2. Montague semantics 
In his well-known "PTQ" paper (Montague 1973), 
Richard Montague presented the complete syntax and 
semantics for a small fragment of English. Although 
it was limited in vocabulary and syntactic com- 
plexity, Montague's fragment dealt with such impor- 
lit is also philosophically controversial. For discussion, see 
Fodor 1978, Johnson-Laird 1978, Fodor 1979, and Wilks 1982. 
2Ours is not the only current work with this Ko~tl; in Section 7 
we discuse other similarly motivated work, 
64 
tant semantic problems as opaque contexts, different 
types of predication with the word be, and the "the 
temperature is 90" problem; 3 for details of these, see 
Dowty, Wall and Peters (1981). 
Montague's semantic rules correspond to what we 
have been calling semantic interpretation. That is, in 
conjunction with a syntactic process, they produce a 
semantic representation, or translation, of a sentence. 
There are four important properties of Montague 
semantics that we will examine here. Below, we 
will carry three of these properties over into our own 
semantics. 
The first property, the one that we will later drop, 
is that for Montague, semantic objects, the results 
of the semantic translation, were such things as in- 
dividual concepts (which are functions to individuals 
from the cartesian product of points in time and pos- 
sible worlds), properties of individual concepts, and 
functions of functions of functions of functions. At the 
top level, the meaning, of a sentence was a truth con- 
dition relative to a possible world and point in time. 
These semantic objects were represented by expres- 
sions of intensional logic; that is, instead of translat- 
ing English directly into these objects, a sentence was 
first translated to an expression of intensional logic, 
for which, in turn, there existed an interpretation in 
terms of these semantic objects. 
Second, Montague had a strong theory of types for 
his semantic objects: a set of types that corresponded 
to types of syntactic constituents. Thus, given a par- 
ticular syntactic category, such as proper noun or ad- 
verb, Montague was able to say that the meaning of 
a constituent of that category was a semantic object 
of such and such a type. 4 Montague's system of types 
was recursively defined, with entities, truth values and 
intensions as primitives, and other types defined as 
functions from one type to another in such a manner 
that if syntactic category X was formed by adding 
category Y to category Z, then the type correspond- 
ing to g would be functions from senses of the type of 
3That is, to ensure that "The temperature is ~0 and the tem- 
perature is rising* cannot lead to the inference that "90 is ris- 
ing". 
4To be precise: the semantic type of a proper noun is set of 
properties of individual concepts; that of an adverb is function 
between set~ v\[ individual concepts (Dowry ¢~ al Ig81: 183, 187). 
Y to the type of X. 5 
Third, in Montague's system the syntactic rules 
and semantic rules are in one-to-one correspondence. 
Each time a particular syntactic rule applies, so 
does the corresponding semantic rule; while the one 
operates on some syntactic elements to create a new 
element, the other operates on the corresponding 
semantic objects to create a new object that will cor- 
respond to the new syntactic element. Thus the two 
sets of rules operate in tandem. 
Fourth, Montague's semantics is compositional, 
which is to say that the meaning of the whole is a 
systematic function of the meaning of the parts. At 
first glance this sounds trivial; if the noun phrase my 
pet penguin denotes by itself some particular entity, 
namely the one sitting on my lap as I write this paper, 
then we do not expect it to refer to a different entity 
when it is embedded in the sentence \[ love my pet 
penguin, and a semantic system that did not reflect 
this would be a loser indeed. Yet there are alternatives 
to compositional semantics. 
The first alternative is that the meaning of the 
whole is a function of not just the parts but also the 
situation in which the sentence is uttered. For ex- 
ample, the possessive in English is highly dependent 
upon pragmatics; the phrase Nadia's penguin could 
refer, in different circumstances, to the penguin that 
Nadia owns, to the one that she is carrying but doesn't 
actually own, or to the one that she just bet on at the 
penguin races. Our definition above of semantic inter- 
pretation excluded this sort of consideration, but this 
should not be regarded as uncontroversial. 
The second alternative to compositional semantics 
is that the meaning of the whole is not a systematic 
function of the parts in any reasonable sense of the 
word. This is exemplified by the interpretation of the 
word depart in Woods's original system, which varied 
greatly depending on the preposition it dominated 
(Woods 1967:A-43-A-46). For example, the interpreta- 
tion of the sentence: 
AA-57 departs from Boston. 
is, not unreasonably: 
5For example, the semantic type of prepositions is functions 
mapping senses of the type of noun phrases to the semantic type 
of prepositional phrases. 
65 
depar~ (as-57, boston). 
That is, the semantic object into which depart is 
translated is the procedure depart. (AA-57 is an air- 
line Right.) However, the addition of a prepositional 
phrase changes this; Table 1 shows the interpreta- 
tion of the same sentence after wrious prepositional 
phrases have been appended. For example, the addi- 
tion of ~o Chicago changes the translation of depart; 
to connect, though the intended sense of the word is 
clearly unchanged, s 
This is necessitated by the particular set of 
database primitives that Woods used, selected for 
their being %tom/c" (1967:7-4-7-11) rather than for 
promoting compositions/Sty. Rules in the system axe 
able to generate non-compositional representations be- 
cause they have the power to set an arbitrarily complex 
parse tree as their trigger, and to return an axbitrary 
representation that could modify or completely ignore 
the components of the parse trees they are supposed to 
be interpreting/ For example, a rule can say (1967:A- 
44): 
If you have a sentence whose subject is a flight, 
whose verb is leave or depart, and which has 
two (or more) prepositional phrases modifying 
the verb, one with /from and a place name, the 
other with a~ and a time, then the interpretation 
is equal (dtime (a, b), c), where a is the 
flight, b is the place, and c is the time. 
Thus while Woods's semantics could probably be made 
• reasonably compositional simply by appropriate ad- 
justment of the procedure calls into which sentences 
are translated, it would still not be compositional by 
design the way Montague semantics is. 
8~Ve have simplified a Little here in order to make our point. In 
fact, sentences like those in Table I with prepositional phrases 
will ~ctually cause the execution of two semantic rules: one for 
the complete sentence, and one for the sentence it happens to 
contain, A.A-57 depcrts from 8os~o~. The resulting interpreta- 
tion will be the conjunction of the output from each rule (Woods 
1967~9-5): 
AA-57 depLrts from Boston to Chicago. 
depar~ (aa-ST, boston) and connec~ (aa-57. boston, c~icago) 
Woods leaves it open (1967:9-7) a,s to how the semantic redun- 
dancy in such expressions should be handled, thou~,h one of hie 
suggestions is a filter that would remove conjuncts implied by 
others, giving, in this case, the interpretation shown in Table 1. 
7Nor is there &nything that prevents the construction of rules 
that would result in conjunctions with conflicting, rather than 
merely redund~tnt, terms. 
TABLE 1. 
NONCOMPOSITIONALITY IN WOODS'S SYSTEM 
AA-57 departs from Boston. 
depart (aa-57, bos~on) 
A.A-57 departs from Boston to Chicago. 
conltecT, (aa-5T, besT, on. chicago) 
AA-57 departs from Boston on Monday. 
dday (aa-57, boston, monday) 
AA-57 departs from Boston at 8:00am. 
equal (dtlme (aa-5T. boston), 8:00am) 
AA-57 departs from Boston after 8:00am. 
greater (dtime (aa-5T, boston), 8:00am) 
A.A-57 departs from Boston before 8:00am. 
greater (8:00am, dtlme (aa-5T. boston)) 
Although Montague semantics has much to recom- 
mend it, it is not possible, ho~vever, to implement it 
directly in a practical NLU system, for two reasons. 
The first is that Montague semantics as currently for- 
mulated is computationally impractical. It throws 
around huge sets, infinite objects, functions of func- 
tions, and piles of possible worlds with great abandon. 
Friedman, Moran and Warren (1978a) point out that 
in the smallest possible Montague system, one with. 
two entities and two points of reference, there are, for 
example, 22"s= elements in the class of possible denota- 
tions of prepositions, each element being a set contain- 
ing 2512 ordered pairs, s 
The second reason we can't use Montague seman- 
tics directly is that truth-conditional semantics are not 
useful in AI; A/uses know/edge semant.ics (Tarnawksy 
1982) in which semantic objects tend to be symbols or 
expressions in a declarative or procedural knowledge 
representation system. Moreover, truth-conditional 
semantics really only deals with declarative sentences 
(Dowry eC al 1981:13) (though there has been work 
attempting to extend Montague's work to questions; 
e.g. Hamblin 1973); a practical NLU system needs to 
be able to deal with commands and questions as well 
as declarative sentences. 
8Despite this problem, Friedman et ¢I (1978b, 1978c) have imple- 
mented Mont~gue semantics computationally by using tech- 
n/ques for maintaining partially specified models. However, their 
system is intended ~s ~ tool for understanding Montague seman- 
tics better, r~ther than &s ~ usable NLU system (1978b:26). 
66 
There have, however, been attempts to take the 
intensional logic that Montague uses as an inter- 
mediate step in his translations, and give it a new in- 
terpretation in terms of AI-type semantic objects, thus 
preserving all other aspects of Montague's approach; 
see, for example, Hobbs and Rosenschein 1977, and 
Smith's (1979) objections to their approach. There has 
also been interest in using the intensional logic itself 
(or something similar) as an AI representation ~ (e.g. 
Moore 1981). But while it may be possible to make 
limited use of intensional logic expressions, I° there are 
many problems that need to be solved before inten- 
sional logic or other flavors of logical forms could sup- 
port the type of inference and problem solving that 
AI requires of its semantic representations; see Moore 
1981 for a useful discussion. Moreover, Gallin (1975) 
has shown Montague's intensional logic to be incom- 
plete. (See also the discussion in Section 7 of work 
using logical forms.) 
Nevertheless, it is possible to use many aspects of 
Montague's approach in semantics in AI. The seman- 
tic interpreter that we describe below maintains three 
of the four properties of Montague semantics that 
we described above, and we therefore refer to it as 
"Montague-inspired". 
TABLE 2. 
TYPES IN THE AHSITY SEMANTIC INTERPRETER 
BASIC TYPES 
Frame a 
(penguin ?x), Clove ?x) 
Slot 
color, agent 
Frame determiner b 
(t~e ?x), Ca ?x) 
OTHER TYPES 
Slot-filler pair = slot ~ frame statement 
(color=red), (agent=(the ?x (f±sh ?x))) 
Frame descriptor = frame ~ slot-filler pair* 
(pen~uln ?x (owner=Nadla)), 
(love ?x (agent=Ross) (patient=Nadla)), 
(dog ?x) 
Frame statement \[or instance c\] 
= frame determiner -~ frame descriptor 
(the ?x (penguin ?x (owner=Nadla))), 
(a ?x (love ?x (agent=Ross) 
(pail ent=Nadl a) ) ), 
(the ?x (dog ?x)). 
pen~ln87 \[an instancel 
3. Our semantic interpreter 
Our semantic interpreter is a component of a system 
that uses a frame-like representation for both story 
comprehension and problem-solving. The system in- 
cludes a frame language, named Frail, a problem sol- 
ver, and a discourse pragmatics component; further 
details may be found in Charniak 1981, Wong 1981a, 
and Wong 1981b. The natural language front-end in- 
cludes Paragram, a deterministic parser based on that 
of Marcus (1980). Unlike Marcus's parser, Paragram 
has two types of rule: base phrase structure rules and 
transformational rules. It is also able to parse un- 
grammatical sentences; it always uses the rule that 
matches best, even if none match exactly. Paragram 
is described in Charniak 1983. 
91tonically, Montague regarded intensional logic merely as a con- 
venience in specifyin K his translation, and one that was com- 
pletely irrelevant to the substance of his semantic theories. 
lOGodden (1981) in f~ct uses them for simple translation bet- 
ween Thai and English. 
aThe queJtion-m~rk prefix indicates & variable. Whenever a free 
v~iable in a frame is bound to a v~iable in a frame determiner, a 
unique new name is generated for that variable and its bindings. 
In this paper, we shall assume for simplicity that vaxiable names 
~re maKically ~correct" from the start. 
bDo not be misled by the fact that frames and frame determiners 
look similar. They He actually very different: the first is a gtatic 
data structure; the second is a frame retrieva~l procedure. 
CAn instance is the result of evaluating a frame statement in Frail. 
It is a symbol that denotes the object referenced by the frame 
statement. To Absity, there is no distinction between the two; ~n 
instan.ce can be used wherever ~ frame Itatement c~n. 
The semantic interpreter is named Absity (for 
reasons too obscure to burden the reader with). As 
we mentioned above, it retains three of the four 
properties of Montague semantics that we discussed. 
The property that we have dropped is, of course, truth 
conditionality and Montague's associated treasury of 
semantic objects. We have replaced them with AI- 
style semantics, and our own repertory of objects, 
67 
TABLE 3. 
TYPE CORRESPONDENCES IN ABSITY 
SYNTACTIC TYPE SEMANTIC TYPE 
Major sentence 
Sentence 
Noun 
Adjective 
Determiner 
Noun phrase 
Preposition 
Prepositional Phrase 
Verb 
Adverb 
Auxiliary 
Verb phrase 
Clause end 
Frame statement, instance 
Frame descriptor 
Frame 
Slot-filler pair 
Frame determiner 
Frame statement, instance 
Slot name 
Slot-filler pair 
(Action) frame 
Slot-filler pair 
Slot-filler pair 
Frame descriptor 
Frame determiner. 
which are components of the frame language Frail. 11 
We do, however, retain a strong typing upon our 
semantic objects, that is, each syntactic category has 
an associated semantic type. Table 2 shows the types 
of components of Frail, how they may be combined, 
and examples of each; the nature of the components 
listed will become clearer with the examples in the 
next section. Table 3 gives the component of Frail that 
corresponds to each syntactic type. As a consequence 
of the kind of semantic objects we are dealing with, 
the system of types is not recursively defined in the 
Montague style, but we retain the idea that the type 
of a semantic object should be a function of the types 
of the components of that object. 
We have also carried over from Montague seman- 
tics the operation of syntactic and semantic rules in 
tandem upon corresponding objects. However, it is not 
possible to maintain the one-to-one correspondence of 
rules when we replace Montague's simple syntax with 
the much larger English grammar of the Paragram 
parser. This is because in Montague's system each syn- 
tactic rule either creates a new node from old ones-- 
for example, forming an intransitive verb phrase from 
a transitive verb and a noun phrase--or places a new 
llAlthou~h the object that represents a Sentence is • procedure 
call in Frail upon a knowledge basej this is not procedur~l sem~n- 
tics in the strict Woods sense, as the mes~aing inheres not in the 
procedures but in the objects they manipulate. 
node under an existing one--such as adding an adverb 
to an existing intransitive verb phrase. These are" ac- 
tions that clearly have semantic counterparts. When 
we start to add movement rules such as passivizatioa 
and dative movement to the grammar, we find our- 
selves with rules that have no clear semantic counter- 
part; indeed with rules that, it is often claimed (e.g. 
Chomsky 1965:132), leave the meaning of a sentence 
quite unchanged. 
We therefore distinguish between parser rules that 
should have corresponding semantic rules and those 
that should not. As the above discussion suggests, 
rules that attach nodes are the ones that have seman- 
tic counterparts. In Paragram, these are the base 
structure rules. For this subset of the syntactic rules, 
semantic rules run in tandem, just as in Montague's 
semantics, m 
It is a consequence of the above properties of 
our semantic interpreter that we have also retained 
the property of compositionaiity by design. This fol- 
lows from the uniform typing; the correspondence bet- 
ween syntactic and semantic rules that maintains this 
uniformity; and there being a unique semantic object 
corresponding to each word of English i~ (see Dowty e~ 
al 1981:180-181). Unlike those of Woods's (1967) air- 
line reservation system front-end discussed in Section 
2, our semantic rules are very weak: they cannot 
change or ignore the components upon which they 
operate, nor can more than one rule volunteer an inter- 
pretation for any node of the parse tree. The power of 
the system comes from the nature of the semantic ob- 
jects and the syntax-directed application of semantic 
rules, rather than from the semantic rules themselves. 
4. Examples 
Some examples will make our semantic interpreter 
clearer. First, let's consider a simple noun phrase, 
the book. From Table 3, the semantic type for the 
determiner She is a frame determiner function, in this 
case (the ?x), and the type for the noun book is a 
kind of frame, here (book ?x). These are combined 
12In her synthesis of transformationa.l syntax with Monta6,ue 
acrostics, Partee (1973, 1975) observes that the semantic rule 
corresponding to many transformations will simply be the iden- 
tity mapping. 
13We show in Section 6 how this may be reconciled with lexical 
ambiguity. 
68 
in the canonical way--the frame name is added as an 
argument to the frame determiner function--and the 
result, (the ?x (book ?x)), is a Frail frame state- 
ment (which evaluates to an instance) that represents 
the unique book referred to. 14 
A descriptive adjective corresponds to a slot-filler 
pair; for example, red is represented by (color=red), 
where color is the name of a slot and red is a frame 
instance, the name of a frame. A slot-filler pair 
can be added as an argument to a frame, so the red 
book would have the semantic interpretation (the ?x 
(book ?x (color=red))). 
Now let's consider a complete sentence: 
Nadia bought the book from a store in the mall. 
Table 4 shows the representation for each component 
of the sentence; note that the basic noun phrases 
have already been formed in the manner described 
above. Note also that we have inserted the pseudo- 
prepositional subject and object markers susJ and 
osJ, which are then treated as if they were real 
prepositions; see Hirer and Charniak 1982 or Hirst 
1983 for details of this. For simplicity, we assume that 
each word is unambiguous (we discuss our disambigua- 
tion procedures in Section 6); we also ignore the tense 
cn the verb. Table 5 shows the next four stages in the 
interpretation. First, noun phrases and their preposi- 
tions are combined, forming slot-filler pairs. Then the 
prepositional phrase in the mall can be attached to a 
store (since a noun phrase, being a frame, can have 
a slot-filler pair added to it), and the prepositional 
phrase from a store in the marl is formed. The third 
stage shown in the Table is the attachment of the slot- 
filler pairs for the three top-level prepositional phrases 
to the frame representing the verb. Finally, the period, 
which is translated as a frame determiner function, 
causes instantiation of the buy frame, and the trans- 
lation is complete. 
5. Semantic help for the parser 
As we mentioned earlier, any parser will occasionally 
need semantic help. In Marcus-type parsers, this need 
occurs in rules that have the form "If semantics prefers 
14Note ~hat it is the responsibility" of the frame system to deter- 
mine with the help of the pragmatics module which one of the 
books that it m~ty know about is the correct one in context. 
TABLE 4. 
ABSITY EXAMPL E 
WORD OR PHRASE SEMANTIC OBJECT 
SUBJ agent 
Nadia (the ?x (thing ?x 
(propername="Nadla"))) 
bought (buy ?x) 
oBJ pa~len~ 
the book (the ?y (book ?y)) 
from source 
a store (a ?z (el;ore ?z)) 
in loca~lon 
the mall (the ?w (mall ?w)) 
• \[period I (a ?u) 
X over Y then do X'; otherwise do Y". To answer 
such questions, we have a Semantic Enquiry Desk r, hat 
operates upon the same semantic objects as the seman- 
tic interpreter. Because these objects are components 
of the Frail frame language, the Enquiry Desk can 
use the full retrieval and inference power of Frail in 
answering the enquiry. 
6. Word sense disambiguation 
One problem that Montague semantics does not ad- 
dress is that of word disambiguation. Rather, there is 
assumed to exist a function that maps each word to a 
unique sense, and the semantic formalism operates on 
the values of this function.Is Clearly, however, a prac- 
tical NLU system must take account of word sense am- 
biguity, and so we must add a disambiguation facility 
to our interpreter. Fortunately, the word translation 
function allows us to ~dd this facility transparently. 
Instead of simply mapping a word to an invariant 
unique sense, the function can map it to whatever 
sense is correct for a particular instance. 
Our disambiguation facility is called Polaroid 
Words. Is Each word in the system is represented by 
15This is not quite true. Specified unique translations axe given 
for proper names and for a few important function words, such as 
the and be; see Monta~e 197312\]:261 , or Dowry ~ ~l 1981:192ff. 
16polaroid is a trademark of the Polaroid Corporation. 
69 
TABLE 5. 
ABSITY EXAMPLE (CONTINUED) 
SUBJ Nadia 
(agent,= (the ?x 
(thlng ?x (propername="Nadla")))) 
OSJ the book 
(patlenl;=(the ?y (book ?y))) 
in the mall 
(loca~lon:C1;he ?~ (mall ?w))) 
a store in the mall 
(a ?z (s~core ?z 
(loca~ion=C~he ?w (mall ?w))))) 
from a store in the mall 
(source=Ca ?z (s~ore ?z 
(locatlon=(the ?w (mall ?W)))))) 
NaSa bought the book from a storein the mall 
(buy ?u 
(agent=(the ?x (thlng ?x 
(propername="Sadia")))) 
(patient=(the ?y (book ?y))) 
(source=(a ?z (store ?z 
(location=(the ?w (m~ll ?w))))))) 
Nadia bought the book from a store in the mail. 
(a ?u 
(buy ?u 
(agenr,=(the ?x (thing ?x 
(propername=" N adla" ) ) ) ) 
(patient= (the ?y (book ?y))) 
(source=(a ?z (store ?z 
(locatlon=(1;he ?w (marl ?w))))))) 
a separate process that, by talking to other processes 
and by looking at paths made by spreading activation 
in the knowledge base, figures out the word's mean- 
ing. Each word is like a self-developing photograph 
that can be manipulated by the semantic interpreter 
even while the picture is forming; and if some other 
process needs to look at the picture (e.g. if the 
Semantic Enquiry Desk has an "if semantics prefers ~ 
question from the parser), then a half-developed pic- 
ture may provide enough information. Exactly the 
same process, without the spreading-activation phase, 
is used to disambiguate case roles as well. Polaroid 
Words are described more fully in Hirst and Charniak 
1982 and Hirst 1983. 
7. Comparison with other work 
Our approach to semantic interpretation may usefully 
be compared with other recent work with similar goals 
to ours. 
One such project is that of Jones and Warren 
(1982), who attempt a conciliation between Montague 
semantics and a conceptual dependency representation 
(Schank 1975). Their approach is to modify Montague's 
translation from English to intensional logic so that 
the resulting expressions have a canonical interpreta- 
tion in conceptual dependency. They do not ad- 
dress such issues as extending Montague's syntax, nor 
whether their approach can be extended to deal with 
more modern Schankian representations (e.g. Schank 
1982). Nevertheless, their work, which they describe 
as a hesitant first step, is similar in spirit to ours, and 
it will be interesting to see how it develops. 
Important recent work that extends the syntac- 
tic complexity of Montague's work is that on general- 
ized phrase structure grammar (GPSG) (Gazdar 1982). 
Such grammars combine a complex transformation- 
free syntax with Montague's semantics, the rules again 
operating in tandem. Gawron et al (1982) have imple- 
mented a database interface based on GFSG. In their 
system, the intensional logic of the semantic com- 
ponent is replaced by a simplified extensional logic, 
which, in turn, is translated into a query for database 
access. Schubert and Peiletier (1982) have also sought 
to simplify the semantic output of a GPSG to a more 
~conventional" logical form; and Rosenschein and 
Shieber (1982) describe a similar translation process 
into extensional logical forms, using a context-free 
grammar intended to be similar to a GPSG. Iv 
The GPSG approaches differ from ours in that 
their output is a logical form rather than an im- 
mediate representation of a semantic object; that 
is, the output is not tied to any representation of 
knowledge. In Gawron et al's system, the database 
17 Rosenschein and Shieber's semaxltic translation fonow~ pars- 
ing rather than running in parallel with it, but it iv strongly 
syntax-dLrected, and is, it seems, isomorphic to ~n in-t~ndem 
translation that provides no feedback to the p~rser. 
70 
provides an interpretation of the logical form, but 
only in a weak sense, as the form must first pass 
through another (apparently somewhat ad hoc) trans- 
lation and disambiguati0n process. Nor do these ap- 
proaches provide any semantic feedback to the par- 
set. is These differences, however, are independent of 
the choice of GPSG; it should be easy, at least in prin- 
ciple, to modify these approaches to give Frail output, 
or, conversely, to replace Paragram in our system with 
a GPSG parser. 19 
The PSX-KLON~- system of Bobrow and Webber 
(1980a, 1980b) also has a close coupling between syn- 
tax and semantics. Rather than operating in tandem, 
though, the two are described as "cascaded', with an 
ATN parser handing constituents to a semantic in- 
terpreter, which is allowed to return them (causing 
the ATN to back up) if the purser's choice is found 
to be semantically untenable. Otherwise, a process 
of incremental description refinement is used to in- 
terpret the constituent; this relies on the fact that 
the syntactic constituents are represented in the same 
formalism, KL-OSZ (Brachman 1978), as the system's 
knowledge base. The semantic interpreter uses projec- 
tion rules to form an interpretation in a language 
called JAaGON, which is then translated into KL-ONZ. 
Bobrow and Webber are particularly concerned with 
using this framework to determine the combinatoric 
relationship between quantifiers in a sentence. 
Bobrow and Webber's approach addresses several 
of the issues that we do, in particular the relationship 
between syntax and semantics. The information feed- 
back to the parser is similar to our Semantic Enquiry 
Desk, though in our system, because the parser is 
deterministic, semantic feedback cannot be con fluted 
with syntactic success or failure. Both approaches rely 
on the fact that the objects manipulated are objects of 
a knowledge representation that permits appropriate 
judgments to be made, though in rather a different 
manner. 
Hendler and Phillips (1981; Phillips and Hendler 
1982) have implemented a control structure for NLU 
18Gawron et al produce all poslible trees and their tranilations 
for the input sentence, s.nd then throw away any that don't make 
sense to the database. 
If'Our choice of Paragram was largely pragmatic~it w&s avL/l- 
• ble--and does not represent &ny particular commitment to 
transformational g~ammar s. 
based on message passing, with the goal of running 
syntax and semantics in parallel and providing seman- 
tic feedback to the parser. A ~moderator" trans- 
lates between syntactic constructs and semantic repre- 
sentations. However, their approach to interpretation 
is essentially ad hoc (James Hendler, persoaoi cum- 
munication), and they do not attempt to put syntactic 
and semantic rules in strict correspondence, nor type 
their semantic objects. 
None of the work mentioned above addresses 
issues of lexical ambiguity as ours does, though 
Bobrow and Webber's incremental description refine- 
ment could possibly be extended to cover it. Also, 
Gawron et al have a process to disambiguate case roles 
in the logical form after it is complete, which operates 
in a manner not dissimilar to the case-slot part of 
Polaroid Words. 
8. Conclusion 
We have described a new approach to semantic inter- 
pretation, one suggested by the semantic formalism 
of Richard Montague. We believe this work to be a 
clean and elegant foundation for semantic interpreta- 
tion, in contrast to previous ad hoc approaches. At 
the moment, though, the work is only a foundation; 
the test of a foundation is what can be constructed 
on top of it. We do not expect the construction to be 
unproblematic; here are some of the problems we will 
have to solve. 
First, the approach is not just compositional but 
almost too compositional. At present, noun phrases 
are taken to be invariably and unalterably specific 
and extensional, that is to imply the existence of the 
unique entity or set of entities that they specify. In 
English, this is not always correct. A sentence such 
as: 
Nadia owns a unicorn. 
implies that a unicorn exists, but this is not true of: 
Nadia talked abou~ a unicorn. 
which also has a non-specific reading. Montague's 
solution to this problem does not seem easily adaptable 
71 
to Absity. 2° Similarly, a sentence such as: 
The lion is not a beast to be trifled w/th. 
can be a generic statement intended to be true of all 
lions; Montague did not treat generics. 
Second, the approach is heavily dependent upon 
the expressive power of the underlying frame language. 
For example, our language, Frail, is yet deficient in 
its handling of time, and this is clearly reflected in 
Absity. Further, the approach makes certain claims 
about the nature of frame representations~that a 
descriptive adjective in some sense is a slot-filler pair, 
for example that might be shown to be untenable. 
We will also have to deal with problems in 
quantification, anaphoric reference, and many other 
areas. Nevertheless, we believe that this approach to 
semantic interpretation shows considerable promise. 
Acknowledgemems 
I am grateful to Eugene Charniak, C~role Chaski, Jim 
Hendler, Polly Jacobson, and Nadia Talent for their 
comments upon earlier versions of this paper. 
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