A Situated Perspective on Natural-Language 
Processing 
Susan U. Stucky 
Stanford University 
Use the word 'situated' these days and all anyone can think of is situation 
semantics, t That's unfortunate from my point of view, because \[ would like to explore 
an idea that follows from ideas handily referred to as "a situated perspective." (Not 
surprisingly, both situation semantics and its companion logic situation theory are by 
and large consistent with this point of view, but they aren't the only way of working 
out a theory compatible with it.) Viewing computation, language, and inference 
through this perspective, \[ will maintain, suggests a conception of natural-language 
processing both more complicated and more realistic than that underlying much of 
current practice. No system yet exists under this conception, though there is one 
under design Isee note 4): therefore all \[ can reasonably hope to do is engage your 
interest and convince you that the overall conception merits consideration. 
This "situated perspective" \[ have in mind is best thought of as a cluster of 
mutually reinforcing assumptions. As implied, these assumptions don't constitute a 
theory in and of themselves; they're merely indicative of one. or several Furthermore. 
a curious fact is that many of the underlying assumptmns are unobjectionable. 
They're the sort of thing about which you find yourself ~.hinking well, who could 
argue with that. Take the claim that language is efficient--Barwise and Perry's way 
of referring to the fact that you can use the same expression over and ,)vet" again to talk 
about different things. That's as familiar a notion as the productivity of language 
(Barwise and Perry, 1983}. Thus, to claim that language is efficient is to claim that 
interpretation depends on context: to know what the interpretation of the word 'you' is 
(i.e., who is being referred to) on a particular occasion of use depends on who you are 
talking to. (\[ will be using the word 'interpretation' to mean the actual stuff referred 
to, the properties it is said to have etc.} Yet, if you pair the claim about the 
context-dependency of interpretation of language with the equally reasonable claim 
that computational processes similarly have context-dependent interpretations, you 
are all set for the more complicated perspective on natural-language processing \[ 
mentioned. 2 At least, this is what \[ am going to argue. 
Another central assumption of the "situated perspective" is the idea that 
meaning is relational. A kingpin of situation semantics, this assumption follows quite 
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reasonably from even a modest version of realism. Facts about the truth or falsity of 
an utterance are determined by the actual situation (used non-technically here), facts 
about the conversation and its participants as well as facts about the language. Thus, 
the meaning of the phrase 'near here' is a relation among the facts about the situation 
the phrase is used in, the phrase itself, and what it is being used to describe. 
Though I won't catalog the assumptions that make up this "situated 
perspective" entirely (others will emerge as we go along), I will briefly discuss one that 
isn't necessary to the "situated perspective", as far as I'm. concerned, though it figures 
centrally in situation semantics. \[ am not going to assume that meaning and 
interpretation can be defined in terms of observable behaviour (even broadly 
interpreted) without reference to internal architecture. Nor am \[ going to assume they 
can't. Similarly, I'm not going to assume you can or can't explain the structure of 
language in terms of external phenomena. A plausible assmption is that it may well 
take a pretty complicated story on both sides to provide an adequate theory of 
language use. What matters most to the situated perspective is the circumstantial 
dependence of interpretation, where circumstance is not restricted to phenomena 
external to the machine. 
Now, let's put these three assumptions together--that interpretation for both 
language and computational process is context-dependent, that meaning is relational, 
and that a plausible explanation of language and language use may well make appeal 
to a generous supply of facts about both internal and external phenomena. Here's a 
way of thinMng about natural-language processing in this situated perspective. We 
start with an agent to whom an expression u in some language has been put. The 
~gent then processes u and arrives at some internal slate m. where rn is a state of the 
machine, defined at a particular level of description of the machine. Which level is 
that? The one that has interpretation that can be outside the machine and in virtue or' 
which the machine understands u. Now there are a variety of relations that could hold 
between u and m, but one possible constraint is that u and m have the same 
interpretation; they describe the same state of the world. To put this more concretely, 
we obviously want the plane that the air controller refers to with his or her use of the 
phrase 'that plane' to be the same plane that the resulting m is about. (Of course, u 
might correspond to one or more re's, and vice-versa.) An important point is that u and 
rn can't have the same meaning: if we have adopted a relational account of meaning, 
then what u is related to (eg., states of the world and rn) and what rn is related to (eg., 
states of the world, other states of mind or machine, and u) are fairly likely not to be 
the same. This perspective rules out one familiar approach to natural language 
processing, namely, the one in which a representation of the syntax of u tRsu) is first 
computed (e.g., by parsing), whereupon a representation of the meaning of u (Rmu) is 
said to be computed from R~u. whereupon it is assumed that R,nu is the same as Rmm 
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(a representation of the meaning of m). Well, all right, you say, but suppose that what 
is really computed from Rsu is R,u, a representation of the interpretation of u. Then, 
you ask, can I assume Riu - Rim? Well, you can. But then the chickens come home to 
roost. After all, Rim isn't m itself. And given the circumstantial dependence of m's 
interpretation, getting from R,m to m may not be trivial. For instance, suppose that 
we've adopted a default such that the time at some point in the computation is taken to 
be whatever time it is when some particular bit of program is evaluated. Then Rim 
might be "15-OCT-86 16:30:17" where m is a kind of internal indexical having the 
force of'now'. Thus, what we want, ideally, is a system that can go directly from 'now' 
in u to an internal state having the equivalent interpretation, in a theoretically 
principled fashion, and without invoking an intermediate representation in which 
what time it is is explicitly represented. And this seems right: after all, we can deal 
with the word 'now' without knowing what time it is. 
As promised, this situated perspective does seem to have complicated things. 
You can't just take your favorite grammar formalism, code it up, implement a parser, 
derive a semantic representation and be done with it (as if that were an easy thing to 
do). You can't, on this view, design a language front-end for a system, unless you know 
the structure of the relevant level of description of the computation. And we've 
demonstrated that that level can't be analyzed as being equivalent to the 
representation of the meaning or intepretation of the expressions of the language 
being processed. 
On the other hand, there's a positive side to all this. It may well be possible to 
get from u to m in much more direct ways than we have so far imagined. And, having 
theories of the various kinds of contextual dependency and how thery interrelate 
should allow for more realistic (if you will pardon the pun) systems. As I said in the 
beginning, all this context-dependence isn't a surprise. Anyone who has taken 
natural-language processing seriously has had to come to grips with that property of 
language from the very beginning. It's just that many theories of language and 
computation haven't. 
Imagine, if you will, a system that understands a situated language, for which 
there is a well understood description of the level of computation relevant to 
interpretation of the sort we have been discussing and manifests what we might call 
situated inference. (Note that if interpretation of internal structures is context 
dependent, then inference is, de t:acto, situated.) Moreover, if inference is really going 
to be situated, then we won't be needing to flesh out (or even necessarily disambiguate) 
absolutely everything upon internalization, in principle anyway. For instance, we 
might expect a situated robot, upon discovering a note on .Jones' door saying "I'm at 
lunch" to infer directly that Jones was not there then and so not deliver the cup of tea 
it was carrying; and do this without using a sort of logical form that has the import of 
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"Jones is not in his office at 12:00 p.m. October 15, 1986". In other words, we would 
expectour situated inference engine to do situated inference. And, we expect this 
because of the overlap in the (temporal) circumstances of the situation of inference and 
the situation being reasoned about: it's being in the stuff it reasons about is precisely 
what makes it situated. Of course, if Jones later complains to me that my robot failed 
to deliver the tea he had ordered, I will also expect that the robot will have the 
capability of rendering explicit more information about the time of the failed delivery, 
but it need not do so initially. 3 One way of looking at this is to see that it will help 
keep our robot from drowning in information. 4 
I said at the beginning that the situated per.~pective was compatible with 
situation semantics and its companion logical theory Can we expect the latter to help 
in the design of such situated systems? The answer is yes, I think, but not in the way 
you (or Barwise and Perry) might have expected. Because situation semantics and 
situation theory are designed to account for the circumstantial relativity of 
interpretation, the language of situation theory is a good vehicle for a theorist to use in 
giving an account of the full interplay of language, inference, and computation on the 
view sketched here. Similarly, situation semantics isn't a bad way to go about giving 
an account of the external significance of language, as surely we must. On the other 
hand, coding up some situation semantics or replacing the semantic representation in 
a current system with a representation of situation semantics won't do justice, it 
seems, either to situation semantics or to the machine. 
Notes 
IThanks are due to the Situated Inference Engine project member~ at CSLI for 
clarification of many the ideas discussed in this paper. The research reported on was 
made possible by a gift from the System Development Foundation to CSLI: I would like 
to thank the foundation for helping to create an environment in which 
mufti-disciplinary research projects such as the SIE are both enc,)uraged and 
supported. 
2I say "equally reasonable" as if it were a) obvious that there are such 
dependencies and b) easy to say what these dependencies are It does seem obvious 
(though it is not often ackowledged) that a lisp expression can be on a particular 
occasion of use about a particular airplaine, say the one just now landing at San 
Fransisco International On the other hand, it seems far from obvious that it will be 
easy to say what these dependencies are. As in the natural language case, the 
information carried (by the execution of a program, for instance) is complex: 
dependencies arise from both the internal machine environment and the state of the 
external world. Delimiting the kinds of" context and finding appropriate ways to 
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characterize the complex of relations has only just begun. For work relevant to the 
situated perspective laid out here, see in particular (Smith, 1986a). 
3Of course it is a long way from expectation to reality. For a characterization of 
the internal structures that are causally responsible for an agent's or system's actions, 
those that have interpretations in the sense I have been using them here, see Smith 
(1986b). 
4Such a system is not entirely fantasy The Situated Inference (SIE) project at 
CSLI is a project to design and build a computational system that engages in situated 
inference. However, the point is not just that the language the SIE uses will be 
situated (that much is true of current natural language systems). Or even that 
internal structure depends likewise on circumstance for interpretation (that much is 
true of current systems). Rather the interest lies in the SIE's being designed with two 
additional purposes in mind: ¢i) all three, inference, internal structures, and language 
will be situated in compatible ways, and (ii) there is a commitment to develop a 
common theoretical framework in terms of which to understand the full interplay 
among language, content, and the internal structures etc. Progress reports on the SIE 
appear from time to time in the CSL\[ Monthly, a publication of The Center for the 
Study of Language and Information, Ventura Hall, Stanford University. Stanford CA. 
94305. 
References 
Barwise, K. J. and Perry J. 1983. Situations and Attitudes. Cambridge, 
Massachusetts: The MIT Press. 
Smith, B. C. 1986a. The Correspondence Continuum. In Proceedings of the Sixth 
Canandian AI Conference. 
Smith, B. C. 1986b. Varieties of Self-Reference. In J. Halpern {Ed.) Procedings of the 
1986 Conference on Theoretical Aspects of Reasoningabout Knowledge. Los 
Altos, Calif.: Morgan Kaufmann, 19-43. Revised version to appear in Artificial 
Intelligence. 
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