DISAMBIGUATING AND INTERPRETING VERB DEFINITIONS 
Yael Ravin 
IBM T.J. Watson Research Center 
Yorktown Heights, New York 10598 
e-mail:Yael@ibm.com 
ABSTRACT 
To achieve our goal of building a compre- 
hensive lexical database out of various on-line 
resources, it is necessary to interpret and 
disambiguate the information found in these 
resources. In this paper we describe a 
Disambiguation Module which analyzes the 
content of dictionary dcf'mitions, in particular, 
definitions of the form to VERB with NP". 
We discuss the semantic relations holding be- 
tween the head and the prepositional phrase in 
such structures, as wellas our heuristics for 
identifying these relations and for 
disambiguating the senses of the words in- 
volved. We present some results obtained by 
the Disambiguation Module and evaluate its 
rate of success as compared with results ob- 
tained from human judgements. 
INTRODUCTION 
The goal of the Lexical Systems Group at 
IBM's Watson Research Center is to create 
COMPLEX, "a lexical knowledge base in 
which word senses are identified, endowed 
with appropriate lexical haforrn, ation and 
properly related to one another" (Byrd 1989). 
Information for COMPLEX is derived from 
multiple lexical sources so senses in one source 
need to be related to appropriate senses in the 
other sources. Similarly, the senses of def'ming 
words need to be disambiguated relative to the 
senses supplied for them by the various 
sources. (See Klavans et al, 1990.) 
Sense-disambiguation of the words found 
in dictionary entries can be viewed as a sub- 
problem of sense-disambiguation of text 
corpora in general, since dictionaries are large 
corpora of phrases and sentences exhibiting a 
variety of ambiguities, such as unresolved ?ro- 
nominal references, attachment ambigutties, 
and ellipsis. The resolution of these ambiguity 
problems in the context of dictionary defi- 
nitions would directly benefit their resolution 
in other types of text. In order to solve the 
~roblem of lexical ambiguity in dictionary de- 
fruitions, we are investigating how to auto- 
maticaUy analyze the semantics of these 
definitions and identify the relations holding 
between genus and differentia. This paper 
concentrates on one aspect of the task - the 
semantics of one class of verb definitions. 
I. DISAMBIGUATING DEFINITIONS 
We have chosen to concentrate initially on 
definitions of the tbrm 'to VERB with NW in 
Webster's 7th New Collegiate Dictionary 
(Merriam 1963; henceforth W7). 
Disambiguating these definitions consists of 
identifying the appropriate sense of 'with 
(that is, the type of semantic relation linking 
the VERB to the NP) and choosing, if possi- 
ble, the appropriate senses of the VERB and 
the NP-head from among "all their W7 senses. 
For example, the dis ambiguation of the defi- 
nition of angle(3,vi, l), to fish with a hook", 
determines that the relation between fish and 
hook is use of instrument. 1 It also determines 
that the intended sense of fish is (vi, l)-"to at- 
tempt to catch fish and the intended sense of 
cha°~c~fi~ InAo)idag, urved prll~;t im~re-/m~inttf° ~ 
senses ~or intransitive fish and "4 for the noun 
hook. To ether with the five senses of with 
(described m the next section), these yield 80 
~ook°SSible. sense combinations for to fish with a 
In addition to contributing to the creation 
of COMPLEX, disambiguating strings of the 
form "to VERB with NP" also contributes to 
the task of disambiguating prepositional 
phrases in free text, an tmportant problem in 
NL processing. As is well known, parsing 
prepositional phrases (PPs) in free text is 
problematic because of the syntactic ambiguity 
of their attachment. It is usually impossible to 
determine on purely syntactic grounds which 
head a given PP attaches to from among all 
those that.precede it in the sentence. Thus, 
sentences like the player hit the ball with the 
bat are usually parsed as syntactically ambig- 
uous between with the bat as modifying the 
verb and its modifying the noun. 
One way to resolve the syntactic ambiguity 
is to fisrt resolve the semantic ambiguity that 
underlies it. To resolve it, we follow the ap- 
proach proposed by Jensen & Binot (1987) 
and consult the dictionary defmitions of the 
words involved. This approach differs from 
others that have been proposed for the 
Thus we differ From other attempts at disambiguating definitions, (such as Alshawi 1987), which leave these "with" 
cases unresolved. 
260 
disambiguation of polysemous words in con- 
text in that it accesses large published diction- 
aries rather than hand-built knowledge bases 
(as in Dalhgren & McDowell 1989). More- 
over, it parses the information retrieved from 
the dictionary. Other approaches apply simple 
string matches (Lesk 1987) or statisUcal meas- 
ures (Amsler & Walker 1985). Consulting the 
dict!onary for the player hit the ball with the 
bat ", we identLf~¢ ~with the bat" as meaning, 
among other things, the use of an implement 
and qait' as a verb that can take a use modifier. 
These potential meanings favor an attachment 
of the PP to the verb. Furthermore, since no 
semantic connection can be established be- 
tween "ball" and "with the bat" based on the 
dictionary, the likelihood of the verb attach- 
ment increases. 
Within this approach, we can view the 
disambiguation of the text of dictionary defi- 
nitions as a subgoal of the general 
PP-attachment problem in free text. The 
structure of sentences like "he hit the ball with 
the bat" is "to VERB NP with NP", where 
syntactic ambiguity arises between attachment 
to the verb and attachment to the syntactic 
object. These sentences differ from definition 
strings, which have the form of "to VERB with 
NP , lacking a syntactic object. Even deft- 
nitions of transitive verbs, which are headed 
by transitive verbs, typicall), lack an object, as 
in bat, (vt, l)-"to strike or hit with or as if with 
a bat . In the absence of an object, there is 
no attachment amb!guity, since there is only 
one head available ( strike or hit"). However, 
semantic ambiguity still remains: "hit" means 
both to strike and to score; "bat" refers both 
to a club and to an animal. We can view such 
strings as cases where attachment has already 
been resolved, and view their disambiguation 
as an attempt to supply the semantic basis for 
that attachment. Thus, obtaining the correct 
semantic representation for cases where at- 
tachment is known directly benefits cases 
where attachment is ambiguous. 
Our Disambiguation Module (henceforth 
DM) selects the most appropriate sense 
combination(s) in two parts: first, it tries to 
identify the semantic categories or types de- 
noted by each sense of the VERB and the 
NP-head. It checks if the VERB denotes 
change, affliction, an act of coveting, marking 
or providing. It tests whether the NP-head 
refers to an implement, a part of some other 
entity, a human being or group, an animal, a 
body part, a feeling, state, movement, sound, 
etc. ~ rIqaen it tries to identify the semantic re- 
lation holding between the VERB and 
NP-head. In the constructions we are inter- 
ested in, the semantic relation between the two 
terms depends not only on their semantic cat- 
egories but also on the semantics of with, 
which we discuss in the following section? 
2. THE MEANING OF WITH 
To investigate the semantics of with, we 
turn to the linguistic literature on one hand 
and to lexico~aphical sources on the other. 
In the theoretical literature about prepositions 
and PPs, a syntactic distinction is made be- 
tween PPs as complements of predicates and 
PPs as adjuncts. In traditional terms, a 
complement-PP is more closely related to the 
I-predicate-I, which determines its choice, than 
to the prepositional complement' (Quirk et al. 
1972). In current terms, complement-PPs are 
determined by the predicate and listed in its 
lexical (or thematic) entry, from which syntac- 
tic structures are projected. To assure correct 
projection, the occurrence of complements in 
syntactic structures is subject to various con- 
ditions of uniqueness and completeness 
(Chomsky 1981; Bresnan 1982). Adjuncts, by 
contrast, do not depend on the predicate. 
They freely attach to syntactic structures as 
modifiers and are not subject to these condi- 
tions. 
Although the syntactic distinction between 
complements and adjuncts is assumed by 
many theories, few provide criteria for deciding 
whether a given PP is a complement or ad- 
junct. (Exceptions are Larson (1988) and 
Jackendoff (in preparation).) The theoretical 
status of with is particularly interesting in this 
context: It is generally agreed that some 
with-PPs (such as those expressing manner) 
are adjun~s and that others (like those occur- 
ring with spray/load" predicates) are comple- 
merits; but there is dtsagreement about the 
status of other classes, such as with-PPs ex- 
pressing instruments. See Ravin (in press) for 
a discussion of this issue. 
The distinction between complements and 
adjuncts bears directly on our disambiguation 
problem, as we try to match it to our dis- 
tinctton between NP-based heuristics and 
VERB-based ones (see Section 3). In turn, the 
results provided by our DM put the various 
theoretical hypotheses to test, by applying 
them to a large amount of real data. 
Dictionaries and other lexicographical 
works typically explain the meaning of prep- 
ositions in a collection of senses, some involv- 
ing semantic descriptions and others expressing 
usage comments. W.7, for example, defines with(l) 
semantically: in opposition to; against 
2 We have defined 16 semantic categories for nouns, so far. A most relevant question is how many such categories need 
to be stipulated. For the purpose of the work reported here, these 16 categories surf'tee. Others, however, will be 
needed for the disambiguation of other prepositions and other forms or" ambiguity. 
3 We concentrate here on with; however, preliminary work indicates that the treatment of other prepositions is quite 
similar. 
261 
('had a fight with his brother")"; it defines 
sense 2 by a usage comment: "used as a func- 
tion word to indicate one to whom a usu. re- 
ciprocal communication is made ("talking with 
a friend")". W7 lists a total of 12 senses for 
with and various sub-senses. The Longman 
Dictionary of Contemporary English 
(Longman 1978; henceforth LDOCE) fists 20. 
Quirk et al. (1972) attempt to group the variety 
of meanings under a few general categories, 
such as means/instrument, accompantment, 
and having. Others (Boguraev & Sparck Jones 
1987, Collins 1987) offer somewhat different 
divisions into main categories. 
After reviewin 8 the different characteriza- 
tions of the mearun~s of with against a small 
corpus of verb definitions containing with, we 
have arrived at a set of five senses for it, cor- 
responding to five semantic relations that can 
hold between the VERB and the NP-head in 
"to VERB with NP". Since we are concerned 
with verbs only, senses mentioned by our 
sources for "NOUN with NP" were not in- 
cluded (e.g., the "having" sense of Quirk et al., 
as in a man with a red nose" or "a woman 
with a large family"). Moreover, we have ob- 
served that certain common meanings of 
"VERB with NP" fail to occur in dictionary 
detinitions. The accompaniment sense, for 
examp!e, as in "walk with Peter" or "drink with 
friends , was not found in our corpus of 300 
defmltions. 4 
The five senses which we have identified 
are USE, MANNER, ALTERATION, 
CO-AGENCY/PARTICIPATION, and 
PROVISION, each including several smaller 
sub-classes. Each sense is characterized by a 
description of the states of affairs it refers to 
and by some criteria which test it. As can be 
expected, however, the criteria are not always 
conclusive. There exist both unclear and 
overlapping cases. 
USE - examples are ",'to fish with a hook"; "to 
obscure with a cloud ; and "to surround with 
an army". With in this sense can usually be 
paraphrased as "by means off or "using". The 
states of affairs in this category involve three 
participants: an agent (usually the missing 
subject of the definition), a patient (the missing 
object) and the thing used (the referent of 
"wtth NP"). The agent usually manipulates, 
controls or uses the NP-referent and the 
NP-referent remains distinct and apart from 
the patient at the end of the action. The sub- 
classes of USE are USE 
-OF-INSTRUMENT, -OF-SUBSTANCE, 
-OF-BODYPART, 
-OF-ANIMATE_BEING, -OF-OBJECT. 
MANNER - some examples are "to examine 
with intent to verify"; "to anticipate with anx- 
iety"; or "to attack with blows or words". 
"With NP" in this sense can be paraphrased 
with an adverb (e.g., anxiously ~, violently, 
verbally') and it describes the way in which 
the agent acts. The MANNER sub-classes are 
INTENTION-, SOUND-, MOTION-, 
FEELING- or ATTITUDE-AS-MANNER. 
The distinction between USE and MANNER 
is usually quite straightforward but one class 
of overlapping cases we have identified has,to 
do with verbal entities, such as retort in to 
check or stop with a cutting retort". Since 
verbal entities are abstract, they can be viewed 
as both being used by the agent as a type of 
instrument and describing how the action is 
performed. 
ALTERATION - examples are "to mark with 
bars; 'to impregnate with alcohol"; "to ftll 
with air ; and to strike with fear". In some 
cases, this sense can be paraphrased with 
~make" and an adjective (e.g., "make full", 
make afraid'); in others, with "put into/onto" 
(e.g., "put air into"; "put marks onto"). The 
states of affairs are ones in which change oc- 
curs in the patient and the NP-referent remains 
close to the patient or even becomes part of it. 
The sub-classes are ALTERATION 
-BY-MARKING, -BY-COVERING, 
-BY-AFFLICTION, and CAUSAL ALTER- 
ATION. Cases of overlap between ALTER- 
ATION and USE are abundant. 'To spatter 
with some discoloring substance" is an exam- 
ple of creating a change in the patient while 
using a substance. The definition of spatter 
itself indicates this overlap: "to splash wtth or 
as if with a liquid; also to spoil in this way. 
CO-AGENCY or PARTICIPATION - as in 
"to combine with other parts". Such strings 
can be paraphrased with and" ("one part and 
other parts combine ). The state of affairs is 
one in which there are two agents or partic- 
ipants sharing relatively equally in the event. 
PROVISION - as in "to fit with clothes"; and 
"to furnish with an alphabet". This sense can 
be p~aphrased with give (and sometimes 
with ~to" - "to furnish an alphabet to '), and it 
applies to states of affairs where the 
NP-referent is given to somebody by the agent. 
In addition to the five semantic meanings 
discussed above, there is also one purely syn- 
tactic function, PHRASAL, which with fulfdls 
in verb-prepositioncombinations, such as "in- 
vest with authority. It can be argued that with 
in such cases simply serves to link the NP to 
the VERB. 
The DM disambiguates a given string by 
classifying it as an instance of one of these six 
categories, and thus selecting the appropriate 
sense combination of the words in the string. 
A major contribution to the establishment of the senses of with has been comments and judgements of human subjects, 
who were asked to categorize samples of verb-definition strings into the various with senses we stipulated. 
262 
The process of disambiguation is a function of 
interdependencies among the senses of the 
VERB, the NP-head and with, as we show in 
the next section. 
3. THE DISAMBIGUATION PROCESS 
The DM is an extended and modified ver- 
sion of an earlier prototype developed by 
Jensen and Binot for the resolution of 
prepositional-phrase attachment ambiguities 
(Jensen & Bmot 1987). It uses a syntactic 
parser, PEG (Jensen 1986), and a body of se- 
mantic heuristics which operate on the parsed 
dictionary definitions of the terms to be 
disambiguated. The first step in the 
disambiguation process is parsing the ambig- 
uous string (e.g., "to fish with a hook') by 
PEG and tdentifyingthe two relevant terms, 
the VERB and NP-head (fish and hook). 
Next, each of these terms is looked up in WT, 
its definitions are retrieved and also parsed by 
PEG. Heuristics then apply to the parsed de- 
fruitions of the terms to determine their se- 
mantic categories. The heuristics contain a set 
of lexical and syntactic conditions to identify 
each semantic category. For example, the IN- 
STRUMENT heuristic for nouns checks if the 
head of the parsed definition is "instrument", 
"implement') "device" ,"tool" or "weapon"; if 
the head is part '~, post-modified by an of-pp, 
whose, object is "instrument", "imolement", 
et_c_~..tt.tlae head is post-modified by the 
partmpla~ usea as a weapon'; etc.. If any of 
these conditions apply, that sense of the noun 
is marked + INSTRUMENT. s 
Next, each of the possible with-relations is 
tried. Let us take USE as a first example. To 
determine whether a USE relation holds in a 
particular string, the DM considers the se- 
mantic category of the NP-head. The most 
typical case is when the NP-head is + IN- 
STRUMENT, as in to fish with a hook . In 
this case, the relationship of USE is further 
supported by a link established between the 
NP-head definition and the VERB definition 
through catch: a hook is an ~'... implement for 
catching, holding, or pulling and to fish is to 
attempt to catch fish. (See Jensen & Binot 
1987 for similar examples and discussion.) 
Such a link, however, is rarely found. In many 
other USE instances, it is the meaning of the 
NP-head alone that determines the relation. 
Thus, DM determines that USE applies to "to 
attack with bombs" based on bomb(n,l)-"an 
explosive device fused to detonate under .speci- 
fied conditions", although no link is established 
between attack and detonate. 
USE is also applied regardless of the VERB 
when the NP-head is +BODYPART and 
certain syntactic conditions (a definite article 
or a 3rd-person possessive pronoun) hold of 
the string, as ~ "to strike or push with or as if 
with the head" and to write with one's own 
hand". USE is similarly assigned if the 
NP-head is + SUBSTANCE: "to rub with oil 
or an oily substance" or "to kill especially with 
poison'. MANNER, like USE, is also deter- 
mined largely on the basis of the NP-head. It 
is assigned if the semantic category of the 
NP-head is a state ("to progress ,with much 
tacking or difficulty'); a feeling (to dispute 
with zeal, anger or heat")i a movement ("to 
move with a swaying or swindling motion"); an 
intention ("to examine with intent to verify"); 
etc. 
Since USE and MANNER are largely de- 
termined on the basis of the semantic category 
of the NP, they correspond to adjuncts, in the 
theoretical distinction made between adjuncts 
and complements. By contrast, ALTER- 
ATION, CO-AGENCY and PROVISION are 
determined mostly on the basis of the VERB 
and could be said to correspond to comple- 
ments. (There are, however, many compli- 
cations with this simple division, which we are 
currently studying.) To assign an ALTER- 
ATION relation to a string, the DM checks 
whether the VERB subcategorizes for an (op- 
tional) with-complement, based on informa- 
tion found in the online version of LDOCE 
and whether the VERB denotes change. The 
ftrst LDOCE sense of fill, ~to make or become 
full", for example, fulfills both conditions. 
Therefore, ALTERATION is assigned !n "to 
become filled with or as if with air, to fdl 
with detrital material" and "to become idled 
with painful yearning". ALTERATION also 
applies to other verb classes that are not 
marked for with-subcategorization in 
LDOCE, such as verbs denot~g affliction ("to 
overcome with fear or dread') or actions of 
marking ("to mark with an asterisk"). Finally, 
PHRASAL is assigned if a separate LDOCE 
entry exists for "VERB with, as in "to charge 
with a crime" and "to ply with drink". 
PHRASAL indicates that the semantic relation 
between the VERB and the NP is not re- 
stricted by the meaning of with but is more like 
the relation between a verb and its direct ob- 
ject. 
Since the heuristics for each semantic re- 
lation are independent of each other, conflict- 
ing interpretations may arise. There are cases 
of unresolved ambigu!ty, when different senses 
of one of the terms gtve rise to different inter- 
pretations. For example,. "to write with one's 
own hand" receives a ~ USE 
(-OF-BODYPART) interpretation but also a 
USE (-OF-ANIMATE BEING), which is in- 
correct but due to several W7 senses of hand 
which are marked +HUMAN ("one who 
performs or executes a particular work"; "one 
employed at manual labor or general tasks"; 
s The heuristics apply to each definition in isolation, retrieving information that is static and unchanging. In the future, 
we intend to apply the heuristics to the whole dictionary and store the information in COMPLEX. 
263 
"worker, employee", etc.). A general heuristic 
can be added to prefer a + BODYPART in- 
terpretation over a + HUMAN one, since this 
ambiguity occurs with other body parts too. 
Other instances of ambiguity, however, are 
more idiosyncratic. "I'o utter with accent", for 
example, receives a MANNER interpretation 
(correct), based on aecent(n,l)-"a distinctive 
manner of usually oral expression ; but it also 
receives USE(-OF-SUBSTANCE) (incorrect), 
based on aeeent(n,7,c)-"a substance or object 
used for emphasis . General heuristics cannot 
eliminate all cases of ambiguities of this kind. 
Another t~,pe of conflict arises when one 
semantic relation is assigned on the basis of the 
VERB while another is assigned on the basis 
of the NP-head. This is the case with to 
overcome with fear or dread", for which the 
DM returns two interpretations: ALTER- 
ATION (correct) because the verb denotes af- 
fliction and MANNER (incorrect) because the 
NP denotes a mental attitude. For "to com- 
bine or impregnate with ammonia or an 
ammonium compound" DM similarly returns 
ALTERATION (correct) because the verb is 
a causative verb of change and 
USE(-OF-SUBSTANCE) (incorrect) because 
the NP refers to a chemical substance. To 
handle this type of conflict:, we have imple- 
mented a "Tmal preference heuristic which 
chooses the VERB-based interpretation over 
the NP-based one. Note, however, that this 
heuristic has implications for cases of overlap, 
such as "spatter with a discoloring substance", 
discussed above. When DM generates both 
the VP-based ALTERATION link and the 
NP-based link of USE for this string, the for- 
mer would be preferred over the latter. Thus 
the fact that both links truly apply in this case 
will be lost. 
A third possible conflict arises between a 
PHRASAL interpretation and a semantic one. 
The DM returns PHRASAL-VERB (correct) 
and ALTERATION (incorrect) for to charge 
with a crime, based on eharge with-(espe- 
ciaUy of an official or an official group) to 
bring a charge against ,(someone) for (some- 
thing wrong); accuse of ; and eharge(with)-"to 
(cause to) take in the correct amount of elec- 
tricity". Since the existence of a PHRASAL 
interpretation is an idiosyncratic property of 
verbs, there is no general heuristic for solving 
conflicts of this kind. 
4. RESULTS 
We have developed our DM heuristics 
based on a training corpus of 170 strings - 148 
transitive and 22 intransitive verb definitions 
extracted randomly from the letters a and b of 
W7 using a pattern extracting program devel- 
oped by M. Chodorow (Chodorow & Klavans 
in preparation). The syntactic forms of the 
strings vary as can be seen from the following 
examples: "!o suffer from or become affected 
with blight'; to contend with full strength, 
vigor, craft, or resources'; to prevent from in- 
terfering with each other (as by a baffle). 
However, since we submit the strings to the 
PEG parser and retrieve the VERB and 
NP-head from the parsed structures, we are 
able to abstract over most of the variations. 
Currently, the DM ignores multiple conjuncts 
in coordinate structures and considers only one 
VERB and one NP-head. In the future, all 
possible pairings should be considered (e.g. 
"contend with strength", 'contend with vigor", 
"contend with craft , and so on, for the exam- ~ 
le mentioned above) and the results should 
e combined. As mentioned in Section 1, de- 
fruition strings lack a syntactic object. The few 
strings that contain an object include it in pa- 
rentheses (to treat (flour) with nitrogent 
trichloride 3. This, again, is tolerated by the 
PEG parser, and allows us to assume that in 
all the strings the with-phrase attaches to the 
VERB rather than to the object. 
The DM results can be summarized as fol- 
lows: The correct 6 semantic relation, based on 
the appropriate semantic category (of the 
NP-head or VERB), is assigned to 113 out of 
the 170 strings. Here are a few examples: 
sever with an ax 
USE(-OF-INSTRUMENT) 
wet with blood 
USE(-OF-SUBSTANCE) 
inter with full ceremonies 
(ACTION-AS-) MANNER 
dispute with zeal 
(ATTITUDE-AS-) MANNER 
ornament with ribbon 
ALTERATION (BY-COVERING) 
clothe with rich garments 
ALTERATION (BY-COVERING) 
equip with weapons 
PROVISION 
We consider these 113 results to be completely 
satisfactory. 
In a second group of cases, the correct se- 
mantic relation, based on the appropriate se- 
mantic category, is one of 2 (andrarely of 3) 
semantic relations assigned to the string. There 
are 15 such cases. Here are two examples: 
harass with dogs 
USE(-OF-ANIMATE_BEING) correct 
USE(-OF-INSTRUMENT) incorrect 
The second interpretation ts due to 
dog(n,3,a)-"any of various usually simple me- 
chanical devices for holding, gripping, or fas- 
tening consisting of a spike, rod, or bar". 
Lacking information about the frequency of 
different senses of words, we have at present 
no principled way to distinguish a primary 
6 See discussion of correctness at the end of this section. 
264 
sense (like the animal sense of dog) from more 
obscure senses (like the device sense). 
Make dirty with grime 
USE(-OF-SUBSTANCE) correct 
(STATE-AS) MANNER incorrect 
The incorrect interpretation of grime as man- 
ner is due to the definition of its hypernym 
dirtiness as "the quality or state of being dirty . 
We consider this second group of cases, which 
are assigned two interpretations, to be partial 
successes, since they represent an improvement 
over the initial number of possible sense com- 
binations even if they do not fully 
disambiguated them. 
In 37 cases, DM is unable to assign any 
interpretation. One reason is failure to identify 
the semantic category of the VERB or 
NP-head. For example, 'to pronounce with a 
burr should be assigned MANNER 
(SOUND), but the relevant definitions of burr 
read: "a trilled uvular r as used by some 
speakers of English especially ~n northern En- 
gland and in Scotland and a tongue-ooint 
trill that is the usual Scottish r", making tt im- 
possible for DM to identify it as a sound. (See 
discussion below.) There are other reasons for 
failure: occasionally the NP-head isnot listed 
as an entry in W7, as barking in to pursue 
with barking" or drunkenness in to muddle 
with drunkenness or infatuation". Even if we 
introduced morphological rules, identified the 
base of the derivational word and looked up 
the meaning of the base, the derived meaning 
in these cases would still not be obvious. 
Finally, a negligible number of failures is due 
to incorrect parsing by PEG, which in turn 
provides incorrect input for the heuristics. 
Failure to assign any interpretation does 
not, of course, count as success; but it does not 
produce much harm either. Far more danger- 
ous than iao assignment is the assignment of 
one incorrect interpretation, since incorrect in- 
terpretations cannot be differentiated from 
correct ones in any general or automatic way. 
Out of the set of 170 strings, only 5 are as- 
signed a single incorrect interpretation. These 
are: 
press with requests 
(STATE-AS-) MANNER 
based on the fourth definition of request: "the 
state of being sought after; demand". 
Seize with teeth 
ALTERATION (BY-AFFLICTION) 
based on seize(vt,5,a)-"to attack or overwhelm 
physically; afflict". 
Speak with a burr 
USE(-OF-INSTRUMENT) 
based on burr(n,2,b,1)-"a small rotary cutting 
tool". 
Suffuse with light USE 265 
where the semantic relation may seem correct, 
but the sense of light on which it is based ("a 
flame for lighting something") is inappropriate. 
Possess with a devil 
USE(-OF-ANIMATE BEING) 
where the intended semafftic relation is unclear 
(ALTERATION?) as is the semantic category 
of devil. However, the USE interpretation is 
clearly based on the several inappropriate 
+ HUMAN senses of devil ( an extremely and 
malignantly wicked person : fiend"; "aperson 
of notable energy, recklessness, and dashing 
spirit"; and others). 
As incorrect interpretations cannot be au- 
tomatically identified as such, it is most im- 
portant to design the heuristics so that they 
generate as few incorrect interpretations as 
possible. One way of restricting the heuristics 
ts by not considering the meaning of 
hypemyms, except in special cases. To return 
to "pronounce wtth a burr". We prefer to miss 
the fact that a burr, which is a trill, is a sound 
by ignoring the meaning of the hypemym trill 
than to have to take into account the meaning 
of all the hypemyms of burr. Considering the 
meaning of all the hypernyms will yield too 
many incorrect semantic interpretations for 
"pronounce with a burr". One hypemym of 
burr, weed, has a + HUMAN sense and a 
+ ANIMAL sense; ridge, another hypemym, 
has a + BODYPART sense. 
Since results obtained with the training corpus were promising, we ran DM on a test- 
ing corpus: 132 definitions of the form "to 
VERB with NP" not processed by the pro- 
gram before. The results obtained with the 
testing corpus are compared below with those 
of the training corpus. The first column lists 
the total number of strings; the second, the 
number of strings assigned a single, correct in- 
terl?retation; the third, the number of strings 
asstgned two interpretations, one of which ts 
correct; the fourth column shows the number 
of strings for which no interpretation was 
found, and the last column lists the number 
of strings assigned one or more incorrect in- 
terpretations (but no correct ones). 
TOT COR 1/2 0 INC 
TRAINING 170 113 15 37 5 
TESTING 132 75 13 22 22 
To measure the coverage of DM, we calculate 
the ratio of strings interpreted (correctly and 
incorrectly) to the total number of strings: 
TRAINING 
TESTING 
COVERAGE RATIO 
133/170 (or 78.2%) 
110/132 (or 83.3%) 
To measure the reliability of DM, we calculate 
the ratio of correct interpretations to incorrect 
ones: 
TRAINING 
TESTING 
COR-TO-INC RATIO 
113/133 (or 85%) 
75/110 (or 68%) 
If we include in the correct category those 
strings for which two interpretations were 
found (only one of which is correct), the reli- 
ability measure increases: 
TRAINING 
TESTING 
COR + I/2-TO-INC RATIO 
128/133 (or 96.2%) 
88/110 (or 80%) 
As expected, reliability for the testing material 
is lower than for the training set. This is due 
to the several iterations of free-tuning to which 
the training corpus has been subjected. The 
examination of the testing results suggests 
some further f'me-tuning, which is currently 
being implemented, and which will reduce the 
number of incorrect interpretations. 
Finally, we developed a criterion by which 
to measure the accuracy of our judgements of 
correctness. To ensure that our personal 
judgements of the correctness of the DM in- 
terpretations as reported above were neither 
idiosyncratic nor favorably biased, we com- 
pared them with the judgements of other hu- 
man subjects, both linguists and non-linguists. 
We randomly selected 58 definition strings 
whose interpretation we judged to be correct 
and assigned each of them to 3-4 different 
participants for their judgements. Participants 
were asked to perform the same task as the 
module's, namely, for each definition string, 
select the relevant with-link from among the 
six we have stipulated and choose the relevant 
senses of the VERB and the NP-head from 
among all their W7 senses. We provided short 
explanations of the different with-links (based 
on the descriptions found here in Section 2) 
with a few examples. We allowed participants 
to choose more than one link if necessary, so 
that we can detect cases of overlap; we also 
allowed the choice of OTHER, if no link 
seemed suitable; or a question mark, if the 
string seemed confusing. 
In 3 cases there was no consensus among 
the human judgements. Either 4 different 
choices of with-links or two question marks 
were given, as shown below: 
Affect with a blighting influence 
USE, PHRASAL, 
ALTERATION/PHRASAL, ? 
Fill with bewildered wonder 
PROVISION, PHRASAL, 
ALTERATION, MANNER 
fit to or with a stock 
PROVISION, USE, ?, ? 
Even though the DM choice for these strings 
(deemed correct by us) coincided with one of 
266 
the human choices, the variation is too large 
to validate the correctness of this choice. 
These 3 cases were therefore ignored. 
In 44 cases out of the remaining 55, there 
was (almost) unanimous agreement (3 or 4) 
among the human judgements on a single 
with-link. The DM choice was identical to 41 
of those 44. That is, in 41 out of 44 cases, our 
own judgement of correctness coincides with 
that of others. The cases where we differ are: 
flavor, blend, or preserve with brandy 
4 subjects out of 4: ALTERATION 
DM: USE 
face or endure with courage 
2 subjects out of 3: MANNER 
third subject: MANNER/USE 
DM: USE 
strengthen with or as if with buckram 
4 subjects out of 4: ALTERATION 
DM: USE 
In the remaining 11 strings, there was an even 
split in the human judgements between two 
with-links, indicative to some extent of genuine 
overlap. For example, "treat with a bromate" 
was interpreted as USE by two participants 
and as ALTERATION bytwo others. One 
participant explained that his choice depended 
on the implied object: he would categorize 
treating a patient with medicine as USE but 
treating a metal with a chemical substance as 
ALTERATION. The DM choice was identi- 
cal to one of the two altemative human 
choices in 10 out of these 11 strings. That is, 
in 10 out of 11 cases, our judgement of cor- 
rectness fits one of the two choices made by 
others. 
To summarize, our judgements of correct- 
ness were validated by others in 51 cases out 
of 56 (or 91%). Our practical conclusion from 
this experiment is simply that our semantic 
judgements concerning the meaning of with in 
context coincides with those of others often 
enough to allow us to rely on our intuitions 
when informaUy evaluatinAg the results of our 
program. More generally, this experiment 
seems to indicate that people reach consensus 
on the meaning of prepositions once they are 
given a set of alternatives to choose from, even 
though they may fmd it very difficult to define 
the meaning of prepositions themselves. The 
significance of the unclear cases and the over- 
lap cases in the experiment requires further 
study. 
CONCLUSION 
As our evaluations indicate, the DM 
which we are developing is quite successful in 
identifying the correct semantic relation that 
holds between the terms of a definition string. 
In identifying this relation, the DM also par- 
tially disambig.uates the senses of the definition 
tema" s. In ass,gning MANNER, for example, 
to utter with accent , DM selects two senses 
of accent as relevant, from among the nine 
listed in its W7 entry. In assigning ALTER- 
ATION to mark with a written or printed 
accent", it selects 3 completely different senses 
of accent as relevant. Thus, the same noun 
(accent), occurring in identical syntactic struc- 
tures ("VERB with NP') is assigned different 
sense(s), based on its semantic link to its head. 
Interpreting the semantic relations between 
genus and differentia and disambiguating the 
senses of de\[ruing terms are both crucial for 
our lgeneral goal - the creation of a compre- 
henswe, yet disambiguated, lexical database. 
There are other important applications: the 
heuristics that have been developed for the 
analysis of dictionary definitions should be 
helpful in the disamb,guation of PPs occurring 
in free text. In cases of syntactic ambiguity, 
the need to determine proper attachment is 
evident. In addition, we should point out that 
there is a need to identity the semantic relation 
between a head and a PP, even when attach- 
ment is clear. In translation, for example, re- 
solving the semantic ambiguity of a source 
preposition is needed when ambiguity cannot 
be preserved in the target preposition. Finally, 
we hope that the computational 
disambiguation of the meanings of prep- 
ositions will contribute interesting insights to 
the linguistic issues concerning the distm" ction 
between adjuncts and complements. 
ACKNOWLEDGMENTS 
I thank John Justeson (Watson Research Ctr., 
IBM), Martin Chodorow (Hunter College, 
CUNY), Michael Gunther (ASD, IBM) and 
Howard Sachar (ESD, IBM) for many critical 
comments and insights. 
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