From: AAAI Technical Report SS-95-01. Compilation copyright © 1995, AAAI (www.aaai.org). All rights reserved.
An Integrative,
Layered Approach to
Lexical Semantics
and its Application to Machine
Translation
Inderjeet
¯ : ,).
This paper addresses these two problems by
describing a representation for meaningwhich
combines
the advantagesof both the logicoriented and the conceptualstructure oriented
frameworks. The approach is layered, allowing
different aspects or distinctions of meaningto
appearatdifferent levels. Aswill be illustrated
here, .in accommodating
different granularities of
meanmg,it offers a basis for the developmentof
a commonlexicon.
Manf
The MITRECorporation,
Z401
7525 Colshire Drive
McLean, VA 22102-3481
Phone: (703) 883-6149
mani @starbase.mitre.org
2. The Approach: Integration
1. Introduction
2.1 Representational
Oneof the practical problemswhichstands in the
way of the goal of developing a common
lexicon
for a languageis the variation in granularities of
meaningrepresentation. These varying
granularities have developedout of ecological
needs. For example,in the field of machine
translation (MT), researchers workingon
problems
oftranslation
divergences
at the
semantic level [Dorr 93a] [Dorr 93b], [Dorr and
Voss93] have tended to favor fairly abstract
representations of meaning,such as
Jackendoffian Conceptual Structures (CS)
[Jackendoff 83], [Jackendoff 90]. Others
(whether workingin an "interlinguar’ paradigm,
e.g., [Carbonell and Tomita87], [Carlson and
Nirenburg90], [Meyeret al. 90], [Barnett et al.
94], or semantictransfer paradigm,e.g., [’Nagao
87]) have dependedon more concrete
specifications of meaning,for example,based on
microtheoriesof different domains,e.g., [Levin
and Nirenburg94]. The question then arises as
to (1) whetherthese different granularities
meaningrepresentation can be related to each
other. In addition, there is (2) the problem
frameworkcompatibility; in particular, between
meaningrepresentations moreor less based on
logic, with its emphasison the semanticsof
reference and quantification, and the more
conceptual structure-oriented approachesOike
Jackendoff-inspired approaches) which focus
mainly on a rich ontologyof primitives and
structures. In general, the logic-based
representations appearto be especially useful in
application to "functional" (or closed-class)
categories associated with modality, mood,
tense, aspect, conjunctions, determiners, etc.,
while the Jackendoffian approachesare
particularly useful in connectionwith "lexicar’
(or open-class) categories.
Wewill be~nwith a semantic representation
that
is logic-based.
Wewill assumea standard
Davidsonian
[Davidson
67]representation
for
reference
toevents.
To simplify
the
presentation, wewill use for the mostpart a
uniformsemantic treatment of modification
within the Davidsonianapproach, as sketched by
[Parsons 90]. Our overall frameworkwill be
thatof Discourse
Representation
Theory
[Kamp
84],butthisismerely
a matter
ofconvenience,
related in part to its theoretical interest andin part
to experience with using this frameworkin
various NLPareas, including MT([Barnett et al.
90], [Barnett et al. 94]).
86
Assumptions
Toillustrate
theapproach,
considerthesentence:
(1) A boy swamacross a fiver.
In theDiscourse
Representation
Structure
(ORS)
forthissentence,
shown
inFigure
1,certain
letter
variables
stand
forcertain
basic
sorts:
el..en:
events,
xl..xn:
things.
Thesorts
indicate
theontological
class
oftheobject
denoted
bythe
variable.
Thetermscontributed
by themorpheme
"swim"are in boldface.
el
.xl
x2.
swlmmlng(el, xl, x2), past(el),
boy(x l), river(x2), water(x2), across(el,
[
Figure 1: DRS for "A boy swam across a
river."
2.2 Decomposition
Now,assume we wish to represent the lexical
semantics of"swim"at a slightly finer level of
granularity, in terms of "movement.across
water, by meansof limbs, caused by an animate
ggg.~. The newterms contributed by this new
view of the morpheme"swim" arc shown in
boldface in Figure 2.
el e2 xl x2 x3
cause(e2, xl, el),
+
rot(el),
Note that the DRSin Figure 3 is also equivalent
to the followingexpression in standard first-
orderlogic:
move(el, xl, x2),
boy(xl), animate(x1),
water(x2), river(x2), across(el,
limbs/x3 ), with(el+ x3)
3jl 3el 3xl 3x2 3x3 3kl 3wl [cause(el, xl,
jl) & gotjl, xl, kl, wl) ~ past(j1) & boy(x1)
& river(x2) & via(kl, x2) & limbs(x3)
with(wl, x3)]
Figure 2: DRS for "A boy swam across a
river.", where "swim" is decomposed in
terms of "move".
Figure 5: First-order logic
representation for "A boy swam across a
river.", from DRSof Figure 3.
It is importantto note that these DRS’scan
encodea decompositionalrepresentation such as
Jackendoffs CS. This follows from the
formaliT~tion of CSdescribed by [Zwarts and
Verkuyl 94], where the authors show howCS
can be interpreted as a (many-sorted)first-order
logic. Viewedas representational languages, the
maindifference betweenCSand typical logical
representations for meaningis that CShas many
different sorts of entities, with the variables and
existential quantifiers whichare explicit in logic
In general, for any sentence, a meaning
representation in any one of these three
formalisms (CS, DRT,and first-order logic) can
be transformedinto an equivalent representation
in any. of the others in whichthe sentence’s
meaningcan be expressed. It is worth pointing
out that whileexistential quantificationis
expressed in a straightforward mannerin CS, the
extent to whichuniversal quantification can be
expressedin CSis the subject of further
research. Thusthe DRSrepresentation allows us
to capture the quantifier scopingin sentenceslike
(2), while the CSrepresentation (at present)
not.
made invisible
in CS. To see the intuition
behind
this encoding, assume we view movingas a
kind of going. Let sort variables j stand for
spatial events, sort variables k stand for spatial
paths, and sort variables w stand for instrumental
positions. (Here weare using an extendedset of
Lexical ConceptualStructure (LCS)primitives
inventoried in [Doff 93a, p. 170].) Wethen have
the DRSin Figure 3:
l el xl x2 x3 kl wl
cause(el, xl, jl), go(jl, xl, kl, wl), past(.jl),
boy(xl),
water(x2), river(x2), via(kl,
limbs(x3), with(wl,
IJ
Figure 3: DRSfor CS-level
decomposition for "A boy swam across
river."
a
Asimple syntactic transformation on the DRSin
Figure 3 yields the equivalent CSshownin
Figure 4:
[Event CAUSE([Thing-Animate X 1 ],
[Event GOspatial([Thing-Animate X 1],
bmVIA([war=
X2])])
[Position WlTHInstr ([Limbs X3])]])]
Figure 4: CS for "A boy swam across a
river.", from DRSof Figure 3.
87
(2) Every boy whoknewwhere the river was
swamacross it.
2.3 Using different
ontoiogies
By using a many-sorted DRSin the manner
illustrated, we have demonstratedhowto encode
the semanticsof sentenceslike (1) at a variety
different levels of granularity. TheCSapproach
turns out to be simplya particular level of
granularity, with variables in the representation
associated with a specific ontology, with sorts
like spatial events(j variables), spatial paths
variables), and instrumental positions (w
variables). For a particular application, wecould
consider substituting a different ontology, for
example, the PENMAN
Upper Model [’Bateman
et al. 1990], an ontology for NLPused widely in
generation and MT.For a samplerepresentation
in the PENMAN
ontology, let the e variables be
of the sort relational process, j variables of the
sort motionprocess, x variables of the sort
object, k variables of the sort spatial extent, and
wvariables of the sort instrumental, whereall
these sorts are appropriate conceptsin the
Penmanontology. Wethen have the same DRS
as in the "CS"view in Figure 3, but nowin
terms of the Penmanupper model. Of course, in
thi.~ case the mappingfrom the CSontologyto a
different ontology was apparently not
problematic; in practice wewouldexpect
I.
conflicts
2.4 Application
In the examples in Section 2.2, we showedhow
a given meaningcould be decomposedinto and
expressedin rather different representations,
without loss of meaning.In Section 2.3, we
showed
how a common
representation
of
meaning
could
betiedtodifferent
ontologies.
These
suggest
practical
applications,
inallowing
MTsystems
to exploit
theadvantages
of both
logic-based
representations,
e.g.,
[Barnett
etal.
94],andconceptual
structure
oriented
representations,
e.g.,
[Dorr
93a][Dorr
93b],
[Dorr
andVoss93].Forexample,
we can
represent
precisely
thesemantics
of(3a)and(3b)
in DRT(butnotin CS).
(3a) Every boy swamacross the Potomac.
(3b) Every boy crossed the Potomac
swimming.
Note that the DRSfor (I) in Figure 2 could also
serve as the semanticsfor sentenceslike (4)2:
(4) A boycrossed
a riverby swimming.
Similarly,
by decomposing
"swim"
to a CS-level
go in theDRSfor(3a),
we willendupwiththe
decomposed
DRSforsentences
like(3b),which
happens
tobe a formofthenatural
French
translation
of(3a).
Thedifference
between
this
pairofsentences
(aswellas(I)and(4)),
translation
divergences
[Don"
93a],
[Dorr
93b],
[’Barnettet al. 94], reflects the fact that English
typically allows incorporation(conflation)
manner(which has been decomposedout in our
representations) into the verb, whereasFrench
doesn’t [Talmy85]3. Byintegrating these
lit is worth noting that the PENMAN
ontology has since
been merged (by hand) with the ONTOS
[Carlson and
Nirenburg
90]ontology,
as reported
by[Knight
andLuk
94].
2Webriefly
discuss
pmblerns
withclaiming
equivalence
viadecomposition
in Section
4.
3Notethatsuchlanguage
dependencies
in meaning
alternations,
e.g.,
[Talmy
85],[Levin
93],etc.,
seemto
support
theideaofdistinguishing
language-dependent
aspects
oflexical
meaning
fromworldknowledge.
See
88
different lexical approachesin a common
formalism,whichcan, further, be tied to
different ontologies (e.g., C_~, PENMAN),
the
MTsystem gains considerable power.
3 The Approach: Layering
Thusfar, our discussion has dealt in general with
sentential semantics. Wenowturn to the problem
of lexical representation,in relation to different
granularities of meaning.Wewill first introduce
the idea of views in relation to decomposition,
as a device for informationhiding. Wewill then
discuss the applications of this idea.
3.1 Decomposition
and Views
The different levels of decomposition
are
analogous
to different views ofa concept in
terms of its position in a subsumptionhierarchy.
Figure 6a showsthe "minimal"view for the
morpheme"swim" (i.e., the view corresponding
totheterms
for"swim"in Figure
1).Forclarity
ofpresentation,
we useda morestructured
variant of a DRSencodedin a feature-structure
formalisminstead of a term-based
formalism.
This representationis in fact the languagelnl.
[Calder et al. 89], where"(i) every expression
has a privilegedvariable (its index) and (fi) every
variable is sorted, so indicating the ontological
category of the object denotedby the variable"
[Calderet al. 89, p. 234].
As shown in Figure 6a, the meaning of"swim"
is expressed in the DRSof Figure I by meansof
a minimalview of the concept of swimmingwith only certain structures being considered
salient. Thesestructures include required
arguments.For sorts, only the most general sorts
(event and thing) and importantselectional
restrictions are consideredsalient at this level.
[pied: swimming
index:e levents
argl: [index: xlthing]
arg2: [index: X2wate~r]]
Figure 6a: View of "swim" (minimal
representation)
Figure 6b showsan initial decompositionview
of the same morpheme,where "swim" is
decomposedto movement(as before). Here,
[Hobbs
87],[Kegl87],[Pustejovsky
90] forvarious
points
ofviewonthis.
augment the ~ view with other structures.
In addition to the emergentcause structure, the
"agent" argument (commonto both events)
becomesan animate being, a swimmingevent
becomesa "move"event, and the optional
"instrument" argumentand direction feature are
included.
[pred: cause
index: e2causin~-events
argl: [index: xlanimate-being]
arg2: [pred: move
index: elevents
argl: [index: xlanimate-being]
arg2: [index: X2water
direction: across]
arg3: [index: x31imbs
means: with]]]
of a hierarchy of lexical templates). Third, the
different layers could be associated with different
lexical modules:for example, in MT
applications, a ~ representation of
meaningof"swim"used in a semantic-transfer
oriented
lexicon
(with
certain
associated
sortal
restrictions
on arguments)
maybe decomposed
further into moreelaborated representations of
meaningused in more"interlinguar’ lexicons
(with sortal restrictions associated with more
elaboratedontologies). Fourth,it is likely that
different levels of decompositionmaybe
associated with different linguistic processes.
For example,processeslike ellipsis, as in (5),
might look only at the minimalrepresentation.
Onthe other hand, an item in "implicit focus",
like the limbs in (6), maybe associated with
more decomposedrepresentation.
Figure 6b: View of "swim" decomposed
to ’~ove"
(5) John swamacross the river and Bill did
too.
In Hgure 6c, we showthe LCSrepresentation.
Here the "move"event becomesa "go" spatial
event, whosesecond and third argumentsare
"via" spatial paths and instrumental positions,
respectively.
(6) John swamacross the river, even though his
limbs were aching.
Fmally, one might speculate that such a layered
representation of morphememeaning maybe
necessaryforefficiency in natural
language
communication.
[pred: cause
index:.¢ .c~slng-events
argl: [index: xlanimate-being]
arg2: [pred: go
index:j 1 ~o-spatial-events
arg 1: [inc~x:x 1 animate-being]
arg2: [index: klspatial-path
pred:via
arg I: [index:
X2w~r]]
arg3: [index:
wlinstr-pos
pred: with
argI:[index:
x31imbs]]]]
4 Decomposition and Problems of
Generation and Translation
In practice,
someof theterms
ina more
decomposed
DRS may correspond
to new
morphemeswhich were not present in the
minimal DRS. The DRSin Figure 2 could serve
as the semantics (for the generation o0 sentences
like
(7)and(8),
inaddition
to (I)(repeated
here):
(1) A boy swamacross a fiver.
Figure 6c: View of "swim" decomposed
to LCS
(7)A boy crossed
a fiverby swimming.
Thus,at each level, different aspects of structure,
including sortal changes, emergeand become
salient.
3.2 Application
Thelayered representation of lexical meaninghas
several applications. First, the minimal
representation helps to distinguish verbs which
mayhave the same CSdecomposition. Second,
layering obviously provides for a more
perspicuous representation (analogous to the use
89
(8) A boy caused his limbs to movethrough
waterin a fiver.
If the decompositionis meaningpreserving (as it
should
beinprinciple), then the sentences
corresponding to the original and decomposed
DRSshould
be equivalent in meaning. As with
manyinstances of decomposition(cf. the
discussion of kill = cause-to-die [Lakoff71],
[Fodor 73], ffackendoff
84], [Dowty
90],
[Parsons90]), it is unclear if these sentencesare
t, ~ "
I amgrateful to Paul Portner for manyinsightful
commentsand suggestions on draft versions of
this paper.
in fact equivalent. However,this can, in
principle, be tested by checkingentailments.
Whetheror not certain decompositionspreserve
meaning, a layered view of meaningsuggests
that different aspects of meaningbecomesalient
at different levels of decomposition.Indeed,
sentences whichare related by decomposition
maydiffer in pragmaticproperties, such as
focus. For example,consider the alternations
involved in a cansativefmchoative
decomposition. A given DRScould generate,
dependingon the level of decomposition:
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