applied psycholinguistics volume 10 issue 3 1989 [doi 10.1017%2fs0142716400008675] charles, walter...

8/10/2019 Applied Psycholinguistics Volume 10 Issue 3 1989 [Doi 10.1017%2Fs0142716400008675] Charles, Walter G.; Miller

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Applied Psycholinguistics (1989) 10, 357-375

Printed in the United States of America

ontexts of antonymous adjectives

WALTER G. CHARLES

Oregon State University, Corvalis

GEORGE A. MILLER

Princeton University

ADDRESS FOR CORRESPONDENCE

George A. Miller, Green Hall, Princeton University, Princeton, NJ 08544

ABSTRACT

The method of sorting is used to compare sets of adjectival contexts. Contexts of directly

antonymous adjectives are found to be highly discriminable, both with sentential and phrasal

contexts. These results are used to argue tha t words with different meanings normally appear in

discriminably different contexts, and that the cue for learning to associate direct antonyms is

not their substitutability, but rather their relatively frequent co-occurrence in the same sentence.

In an early attempt to provide an objective basis for psychological discus-

sions of meaning, Deese (1965) proposed a method using distributions of

responses on word association tests in order to obtain a measure of semantic

similarity. The general idea was that two words that evoke many of the same

associative responses can be said to have similar meanings:

insect

and

bug,

for example, would evoke many of the same associations from a population

of subjects, whereas insectand hat would not. Since two closely related

words are likely to evoke one another, an important feature of Deese's meth-

od was the assumption that the stimulus word itself should be counted as a

response by every subject. Thus, for example, everyone can be counted as

responding insect toinsect(and bug to

bug),

so tha t responding insect

to

bug

(and bug to

insect)

would count as a common associative response

and so would contribute to the similarity of the two response distributions.

Given this plausible assumption, a simple computation of the intersection of

the two distributions yielded a coefficient of correlation between them ,

which Deese interpreted as a measure of semantic similarity.

Although the basic assumption underlying this approach - that the mean-

ing of a word is all the other words it makes you think of - was never

universally accepted, Deese maintained that his method could provide ob-

jective evidence for answering questions that otherwise required subjective

judgments. Antonymous adjectives provided a good example. The claim

that two adjectives are antonyms - wetanddry,for example - had previous-

ly rested solely on the subjective judgments of lexicographers. With his

measure of associative overlap, Deese (1964) was able to provide objective

1989 Cambridge University Press 0142-7164/89 $5.00 + .00


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Applied Psycholinguistics 10:3 358

Charles & Miller: Antonymous adjectives

evidence to support that opinion, thus putting the whole matter on a firm

scientific base. If, for example, word associations towetanddryare collect-

ed, it is found that each is the primary response to the other. This kind of

reciprocity was proposed as an objective definition for the semantic relation

of antonymy.

Moreover, since Deese found that all of the most frequently used English

adjectives enter into such reciprocal relations, he concluded that antonymy

must be the basic organizing principle for learning and remembering the

meanings of adjectives: A simple pattern of organization , then , emerges

for common English adjectives. The pattern is one of contrast. . . . The

existence of such a strong pattern among the most basic adjectives suggests

that the structure of adjectives is fundamentally different from that of

nouns (Deese, 1965, 111).

Such claims raise certain problems, as Deese was well aware. For one

thing, words that share similar associative distributions were supposed to be

similar in meaning, yet the definition of antonymy implies that antonyms

have contrasting meanings. How can the meanings of antonymous adjec-

tives be similar and contrasting at the same time? For another, many adjec-

tives do not seem to have antonyms. Deese himself considered the problem

of

nice,

which was one of the few common adjectives he studied that does

not enter into a reciprocal associative relation with any other adjective.

Such questions are not unanswerable, of course, and they should not be

allowed to obscure the importance of Deese's observation that antonymy is a

central principle organizing semantic memory for adjectives. Indeed, an-

tonymy seems to play much the same role for adjectives tha t class inclusion

plays for nouns. But the assumption that word associations provide the

optimal method for studying such questions is more debatable.

Deese's general argument for the plausibility of an associative approach

rested heavily on assumptions about the learning process that is responsible

for forming word associations. Two words become associated by virtue of

sharing contexts: the extent to which words share associative d istributions

is determined by the extent to which they share contexts in ordinary dis-

course (Deese, 1965, 128). Since antonym ous adjectives share associative

distributions, Deese assumed that they must share contexts in ordinary dis-

course.

Although what it means for words to share contexts is open to more

than one interpretation, Deese did not pursue the question. He seems, in-

stead, to have considered the explanation of how antonymous relations are

learned to be a special case of a more general explanation, widely discussed

at the time, for how parts of speech are learned. The linguist Fries (1952)

had proposed that two words are in the same form class if both can be

substituted into particular sentential contexts.Carand lunch, for example,

are both in the same form class because both can be inserted into the

sentential context: The isgood. For many psychologists, this pro-

posal seemed to define what people learn when they learn the part of speech

of a new word: they learn to recognize the contexts into which it can be

inserted. Thus, the fact that people can recognize that wetanddryare both


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adjectives must mean that they have learned that these words are inter-

changeable in particular grammatical slots. It was not necessary to pursue

the question of interchangeability into the actual contexts of antonymous

adjectives in everyday discourse.

That neglected thread is picked up in the present study. Although it may

be correct in principle to say that antonymous adjectives can be inter-

changed in sentential contexts, is it correct in fact? Are the sentences that

people actually use such that replacing an adjective by its antonym always

(or nearly always) produces a nonanomalous result? For example, either wet

or dry can occur in such contexts as: He wiped the surface with

a rag,

or

A climate is good for these plants.

But are such

contexts typical?

This article reports on the use of the method of sorting sentential con-

texts, introduced by Charles (1988a, 1988b), to investigate the contexts of

antonymous adjectives. In this method, many sentential contexts for two

different words are shuffled together, and subjects are invited to sort them

out. If all the contexts of wetanddry,for example, were like the previously

mentioned contexts, subjects would have difficulty determining what the

author's choice might have been. On the other hand, if such contexts are

atypical, subjects should be able to distinguish wetcontexts from drycon-

texts with some accuracy.

In studies with pairs of nouns, Charles found that the discriminability of

their sentential contexts decreases as the judged semantic relatedness of the

nouns increases. The limiting case of this relation would be perfect syno-

nyms,

interchangeable in all contexts, where presumably it would be impos-

sible to tell from context alone which synonym an author had used. The

present article extends this work to adjectives, with special attention to the

kind of semantic relatedness involved in antonymy: can the finding that

words occurring in similar contexts tend to have similar meanings be extend-

ed to antonymous adjectives, which can occur in similar contexts, yet have

contrasting meanings? If two samples of sentential contexts for an antony-

mous pair - one sample, for example, in which wetoccurred and another in

which

dry

occurred - were both collected haphazardly from ordinary textual

materials, would subjects be able to discriminate between them?

ANTONYMO US ADJECTIVES

This discussion will be limited to predictive adjectives, a limitation that has

been implicit in most psycholinguistic studies of adjectives. A simple test of

whether an adjective is predictive is whether it can be used in sentences of

the following form: NP is Adj. For example,

wet

is predictive because

the

wet mayor

and

the mayor is wet

are both admissible, whereas

former

is

nonpredictive because the former mayor is admissible but the mayor is

formerisnot. Some adjectives can be used either way:logicalispredictive in

thelogicalargument,but nonpredictive inthe logical fallacy.

As Deese observed, associative pairing is a special feature of adjectives. In

the case of antonymous adjectives, pairing is understandable: predicative


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Charles

&

Miller: Antonymous adjectives

adjectives express values of attributes, and most attributes are bipolar. There

is usually an adjective for the positive pole of an attribute and an antony-

mous adjective for the negative pole - where the negative is often indicated

by some such prefix as

un-,

as in

real/unreal

or

common/uncommon.

What is not so easily explained is how particular words are selected

to stand in this antonymous relation. Consider an example. English has

a number of adjectives that denote wetness: wet, dam p, moist, soggy,

drenched, sodden, humid

all express slightly different senses of this lexical

concept. Similarly, a number of adjectives denote dryness:

dry,

arid,

parched, dehydrated, dessicated, thirsty, bone-dry

all express mo dulatio ns

of a single concept. As far as their meanings are concerned, any member of

these two sets of synonyms might have been selected as a contrasting term.

Yet there is a consensus among native speakers of English that only

wet

and

dry

are antonyms. For example,

drenched

is a near-synonym of

wet

and

parched

is a near-synonym of

dry,

but most people reject

drenched/parched

as an antonymous pair. In short, antonymy is not a contrast between lexical

concepts - it is a contrast between associatively paired words. But how is it

learned that wet and dry have been selected as the pa rticu lar pair of w ords to

be paired in this m ann er?

This situation has been noted by Gross, Fischer, and Miller (1989), who

distinguish between direct and indirect antonyms. Both direct and indirect

antonyms express conceptual contrasts, but only direct antonyms are asso-

ciatively paired. For example,

moist

does not have a direct antonym, nor

does arid. The direct antonyms are wet/dry. Moist/dry and wet/arid are

indirect antonyms.

Using this terminology, the question becomes: How are specific words

selected as direct antonyms? Or, perhaps more answerable: how do people

learn that the direct antonymy of

wet/dry

is som ehow different from the

sam e con ceptu al o pp ositio n when it is expressed by, say,soggy and arid?

A

plausible assumption would be that this antonymous associative bond

is learned from the contexts that these words share in ordinary text and

discourse. But there are at least two different ways to characterize shared

contexts. Two different hypotheses, which can be called co-occurrence and

substitutability, might account for the development of this word-specific

associative relation. The simpler hypothesis is association through co-occur-

rence.

1. Co-occurrence: Two adjectives are learned as direct antonyms because

they occur together (are heard together and are spoken together) in the

same sentences more frequently than chance would allow.

The sub stitutability hypothesis is mo re com plex.

2. Substitutability:

Two adjectives are learned as direct antonyms because

they are interchangeable in most contexts, i.e., because any noun phrase

that can be modified by one member of the pair can also be modified by

the other.

The co-occurrence hypothesis conforms to traditional association theory,


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where contiguity and frequency are assumed to be primary factors. The

substitutability hypothesis requires mediation: the association between an

adjective and its direct antonym is assumed to be mediated by the context

into which both can be substituted.

Parsimony would seem to favor the co-occurrence hypothesis, but there is

need for the substitutability hypothesis, too. How people learn that one

response can be substituted for another in particular contexts is a general

question that arises in many situations. As Ervin-Tripp (Ervin, 1961) point-

ed out, association theorists require a substitutability hypothesis, or some-

thing like it, because the word-association responses of adults are so often

the same part of speech as the stimulus word. Ervin-Tripp proposed an

explanation of how such learning could occur. As one theorist described it,

she assumed that as one listens to speech, a sentence environment which

has been shared previously by two words can elicit either word as a covert

anticipation. A contiguity between these words would occur whenever there

is an error of anticipation - one word is anticipated but the other is heard

(McNeill, 1963, 251). Using more recent terminology, one might say that

words in the same form class are associated because they compete to fill

syntactic slots (MacWhinney, 1987).

Since a theory of how people learn what can be substituted for what

seems to be required for other reasons, it is not unreasonable to wonder

whether that theory might also explain how people learn associative bonds

between pairs of antonymous adjectives. The argument of the present paper,

however, is that this generalization is not correct. Our experimental results

indicate that the actual sentences used in everyday discourse do not provide

contexts that can elicit either word. Although substitutability may be critical

for learning parts of speech, we need not explore the various theories of this

kind of learning in any detail, since it can have little or nothing to do with

learning the pairings of antonymous adjectives.

EXPERIMENT 1

The first two experiments not only compared the contexts of direct antonyms;

they were extended to include comparisons of the contexts of indirect anto-

nyms as well. The reasoning was that, if the substitutability hypothesis is

correct, contexts of direct antonyms should be more similar (harder to dis-

criminate) than contexts of indirect antonyms. Thus, the indirect antonyms,

which are semantically similar, provide a control condition against which the

discriminability of the contexts of direct antonyms can be compared.

ethod

Materials.

For the first study, the direct antonyms

strong/weak

were chosen.

The choice was constrained by several considerations: (1) both should be

predictive adjectives; (2) they should be common enough that no subjects in

the experiment could fail to know them; (3) they should satisfy Deese's

(1964) criterion that each would be the most frequent associate of the o ther;


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(4) they should occur frequently enough in the Brown Corpus (Francis &

Kucera, 1982) that an adequate sample of sentences containing them could

be easily and objectively collected by searching that Corp us.

The indirect antonyms chosen to go with

strong/weak

were

powerful

and

faint. These were chosen to satisfy similar criteria: (1) both were predicative

adjectives; (2) they were common enough that all of our subjects would

know them; (3) they had been found (Gross et al., 1989) to be similar in

meaning to the direct antonyms; (4) the Brown Corpus has a sufficient

number of sentences containing them.

The Brown Corpus (Francis & Kucera, 1982) is available in machine-

readable form on a Princeton computer. Consequently, it was a simple

matter to search this Corpus of approximately one million running words in

order to retrieve all sentences containing these four words. The smallest

number of sentences found was 25 (for faint), so 25 sentences were selected

to represent each adjective. For the other three adjectives, this selection was

made, first, by excluding all sentences in which more than one of these four

adjectives occurred and, second, by a random choice among the remaining

candidates.

Once the sentences were selected, the target adjectives were replaced by

blanks in order to convert the sentences into sentential contexts. For exam-

pie:

Third,

there were those notably Patrice Lumum ba who favored a Unified

Congo with a very central

government.

It isno harderto raisebig, healthy, blooming plants than , sickly, little

things;

in

fact it

iseasier.

Large,long-range bombers can be developed which would have the capa-

bility to take off from 3,000-foot runways, but they w ould require

more enginesthan wehave today.

One couldheara very ,ladylike sighof

relief.

Each context was printed on a separate

4

x

6

inch card.

Subjects. Eight Princeton University undergraduates, all native speakers of

English, participated as paid volunteers in each of the conditions.

Procedure.

Sets of contexts were compared two at a time; with four terms,

there were six pairwise comparisons of each set of adjectives. For each

comparison, a subject was given a thoroughly shuffled pack of 50 cards,

with one context printed on each card. Subjects were tested individually. No

subject was given the same set of contexts to sort more than once .

Instructions.Subjects were advised to read the contexts carefully and to try

to infer the word that was missing. They were asked to sort the contexts into

groups such that the same word was missing from all examples included in

any group. They were not told what the target words were or how many

groups to use, and they were allowed to re-sort (to change previous deci-

sions) and to continue sorting and re-sorting as long as needed. When they


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finished, they were asked to label the groups of contexts they had created

with the words they thought were missing from the contexts in each group.

Results

The data for each pairwise sorting has been summarized in tables giving the

number of times a context was correctly recognized, was confused with its

alternative, or was taken to be a context for some word other than the words

being compared.

Table 1 summarizes the results for sorting contexts for the direct anto-

nyms,

strong/weak.The rows represent the stimulus materials, and the col-

umns represent the subjects' responses. Since there were

25

contexts per term

and 8 subjects per condition, a total of

200

judgments are available for each

set of contexts.

From Table 1 it is seen that

strong

contexts were recognized correctly

89.5%

of the time, and weak contexts 82% of the time. Only 4.3% of the

responses confused one of these contexts with the other, with a small re-

sponse bias favoring the unmarked adjective strong. The 40 instances in

which subjects labeled their groups with something other than strongor

weakare tabulated in the footnotes to Table 1; they are scattered over 8 and

12 different labels, respectively. Few of these other responses seem to be

closely related semantically to the target term s.

Table 2 reports the results for sorting contexts of indirect antonyms:

strong/faint, powerful/weak,

and

powerful/faint.

From these data it is ap-

parent that the contexts of indirect antonyms are less discriminable than

those of direct antonyms. There were fewer correct sortings of the contexts

of indirect antonym s, largely because of the increased number of other

responses; confusions between antonym s continued to be relatively rare.

The choice offaint as a near-synonym of weakwas clearly not optimal.

When sentential contexts of

faint

were mixed with contexts of either

strong

or powerful, the accuracy of recognition was lowest, the confusions with the

alternative contexts was highest, and the greatest number and variety of

o ther responses were elicited. The strength of the response faint is obvi-

ously relatively low, and in some contexts it almost never occurred to sub-

jectsthat faint was the missing word:

/

worea new double-breasted brown worstedsuit with a herringbone

design

and

wide lapels

like a

devil s

ears.

With heart and abravesm ile, I enduredhis long absences from Cha-

teauBelltech, his coldness, his indifference, his slightsand hisabuses.

To

his

surprise

Russ h eld up his

hand.

Table

3

summarizes the results when the contexts to be sorted were for the

near-synonyms,strong/powerfuland weak/faint.Althoughfaint is still the

hardest to recognize, the general level of discrimination between these sets of

contexts was even poorer than between the indirect antonyms. Contexts for

strongandpowerful were confused with one another more often here than


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Table1.

Sorting data for direct antonyms:

strong/weak

Stimulus

Strong

Weak

Sum

Strong

179

13

192

Response

Weak

4

164

168

Other

17

23

40

Sum

200

200

400

ardent4,great4,political3,vital2,little 1,mixed 1,public 1,superior 1 (8).

declining6,vital 3, inadequate 2, innocent2,little2,unstable 2, ardent 1,injured 1,

mere 1,normal 1,political 1,public 1 (12).

when they were tested against antonymous contexts, and

faint

contexts were

often grouped with those labeled weak.

Finally, a general comment about the results of Experiment 1: the many

other responses elicited by these contexts seem to be largely unrelated in

meaning to the target terms, and the other responses unrelated to one

another. In this respect, they contrast with other responses obtained when

the target words were nouns (Charles, 1988a, 1988b).

iscussion

The substitutability hypothesis - that adjectives involved in a relation of

direct antonymy are set apart from other adjectives that have similar mean-

ings because they are substitutable for one another in the same contexts -

implies that, in a context-sorting task, their contexts should be more dif-

ficult to distinguish from one another than from the contexts of other,

semantically similar terms. From the data presented here, it is clear that the

opposite is the case in representative usage: sentential contexts in which

either direct antonym is equally appropriate are relatively rare. This result

weakens the case for a substitutability hypothesis.

The results of Experiment1 also show a strong and consistent bias against

the response faint. Indeed, the overall pattern of response biases order

these four adjectives: strong> weak>powerful>faint, where the adjective

earlier in this ordering is favored over the following adjectives. In similar

studies with noun contexts, Charles (1988a) found evidence that such re-

sponse biases depend on relative frequencies of occurrence. The frequencies

of these four adjectives in the Brown Corpus (Francis & Kucera, 1982) are:

strong,

198;

weak,

32;

powerful,

63;

faint,

25, which only approximates

Charles' observation. Such correspondences are difficult to interpret, how-

ever, because different word counts disagree with one another. For example,

the corresponding frequencies in the Lorge magazine count (Thorndike &

Lorge, 1944) are 770, 276, 186, and 308, and in the Dahl count of spoken

words (Dahl, 1979) are 198, 74, 32, and 3. The only clear agreement among

these three tabulations is thatstrongis used most frequently.


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Charles&Miller: Antonymous adjectives

Tkble 2.

Sorting data for indirect antonyms:

strong/faint, powerful/weak,

powerful/faint

Response

Stimulus Strong Faint

O ther Sum

Strong

Faint

Sum

113

23

136

Powerful

100

7

107

1

45

46

Wea

5

134

139

86

132*

218

Other

200

200

400

Powerful

Weak

Sum

Powerful Faint

c

r f

154

Other

200

200

400

Powerful

Faint

Sum

125

12

137

0

60

60

75*

128/

203

200

200

400

great 13, quiet 11, new 8, firm 7, big 3, staunch 3, violent 3 , weak 3, dem ocratic 2 ,

greater 2, growing 2, magnificent 2, mixed 2, sudden 2, talented 2, certain 1, corpo-

rate 1, da rk 1, dist ant 1, distinctive 1, fortified 1, IBM 1, little 1, loud 1, m any 1,

necessary 1, open 1, perfect 1, silent 1, unique 1, temporary 1, toned 1, true 1, united

1, wondrous 1, young 1 (36).

^distant 13, quiet 13, dark 12, great 9, small 9, loud 8, magnificent 6, weak 5, slight

4 ,

sudden 4, dull 3, growing 3, new 3, quick 3, wide 3, certain 2, light 2, little 2,

perfect 2, shado w 2 , simp le 2, strange 2, won dro us 2, bad 1, beautiful 1, big 1, dizzy

1,

familiar 1, figure 1, fine 1, headlight 1, heavy 1, precise 1, refined 1, silent 1, slow

1,

soft 1, stau nch 1, unea sy 1, unlikely 1, violent 1 (41).

^strong 50, important 9, large 9, able 3, opposing 3, grotesque 2, packed 2, small 2,

broken 1, dominant 1, influential 1, labor 1, lacking 1, leg 1, long 1, loud 1, many 1,

minor 1, muscular 1, presidential 1, sharp 1, strict 1, water 1 (23).

^strong 15, small 6, important 4, trembling 4, negative 3, able 2, large 2, light 2,

alcoh olic 1, brok en 1, difficult 1, distress 1, do m ina nt 1, helpless 1, im po tent 1,

injured 1, leg 1, loud 1, many 1, mere 1, more 1, my 1, non-alcoholic 1, nonviolent 1,

primitive 1, red 1, short 1, unique 1, weather 1 (29).

^strong 32, quiet 8, new 7, prominent 5, dark 3, famous 3, small 3, figure 2, impor-

tant 2, staunch 2, advanced 1, clear 1, complete 1, dear 1, possible 1, reckless 1,

slight 1, thick 1(18).

/weak 22, quiet 18, small 16, slight 11, soft 7, strong 7, dark 6, deep 5, sharp 5, new

4,

discernible 3, figure 3, forbidding 3, clear 2, complete 2, empty 2, false 2, pale 2,

prominent 2, cold 1, famous 1, fine 1, form 1, staunch 1, thick 1 (25).

Some of the effects of response bias can be eliminated if these data are

analyzed by signal-detection theory. In Table 1, for example, if strong is


10/19


Charles

&

Miller: Antonymous adjectives

Table 3.Sorting data for near-synonym s: strong/powerful, weak/faint

Response

Stimu lus Strong Powerful O ther Sum

Stro ng 122 22 56 200

Powerful 45 91 64* 200

Sum

167 113 120 400

Weak Faint Other

Weak

Faint

Sum

122

17

139

2

22

24

76^

161

rf

137

200

200

400

firm 15, united 7, new 5, good 4, respected 4, unified 3, vehement 3, major 2,

busine ss 1, clean 1, clear 1, devious 1, protec tive 1, resolute 1, significant 1, solid 1,

staunch 1, top 1, unsavory 1, unsuitable 1, wide

1

(21).

*firm 10, united 5, clear 4, respected 4, large 3, muscular 3, new 3, villainous 3,

bloody 2, old 2, real 2, solid 2, clean 1, company 1, dapple 1, devious 1, firm 1, hard

1,

important 1, infamous 1, influential 1, leading 1, lucid 1, major 1, quiet 1,

reso lute 1, secret 1, significant 1, slight 1, stocky 1, tho ug htf ul 1, useful 1, wide 1

(33).

^strong 8, pale 5, bright 4, weary 4, common 3, downtrodden 3, mere 3, sick 3, slight

3,active 2, normal 2, poor 2, quiet 2, shameful 2, small 2, able 1, annoying 1, boring

1,

clear 1, controversial 1, damaged 1, dry 1, favorable 1, important 1, leg 1, light 1,

loud 1, mild 1, mixed 1, more 1, my 1, only 1, precise 1, sickly 1, soft 1, some 1,

striking 1, sudde n 1, surprised 1, tiny 1, uneasy 1, unnece ssary 1, wron g 1 (43).

S tr on g 2 6, slight 1 3, soft 13, bright 9, deep 9, quiet 7, dark 6, loud 5, small 5,

fleeting 4, clear 3 , dry 3, pale 3, striking 3, subtle 3, sudde n 3, vague 3, distinguished

2,

light 2, menacing 2, mere 2, perfect 2, pleasant 2, single 2, slow 2, tiny 2, big 1,

broken 1, casual 1, childish 1, common 1, fine 1, great 1, indistinct 1, leg 1, mild 1,

only 1, own 1, nauseous 1, precise 1, reassuring 1, sick 1, sickening 1, sickly 1, still 1,

strange 1, sweet 1, the 1, triple 1, vain 1, wide 1 (51).

taken as the signal and everything else is noise, then the probability of a hit,

/7( strong | strong),can be estimated as 179/200=0.895, and the probabili-

ty of a false alarm, /(( strong | weak),can be estimated as 13/200=0.065.

These probabilities correspond to d =2.11. Similarly, if weakis taken as the

signal in Table 1, then the estimated probabilities for a hit and a false alarm

are 0.82 and 0.02, with

d =2.91.

Thus, the average

d

for direct antonyms is

2.87.

When similar calculations are performed using the data ofTable2, the

average d for indirect antonyms is 1.89. And the data of Table 3 give an

average d for similar adjectives of 1.22. This method of analysis confirms

the conclusion that contexts of direct antonyms are easier to discriminate

than are other sets of adjectival contexts.

Finally, it should be noted that these data for adjectives extend Charles'


11/19



(1988a) observation for nouns. He found that nouns with similar

meanings tend to occur in similar contexts. Here it seems that adjectives

with similar meanings - strong/powerfuland weak/faint -occur in contexts

that are harder to discriminate than are the contexts of adjectives with

contrasting meanings.

EXPERIMENT 2

Conclusions reached after an analysis of just four related adjectives may or

may not generalize. It is not feasible to test all possible pairs of direct

antonyms in this manner, of course, but at least one replication seemed

necessary. So Experiment1was repeated exactly, except that the direct anto-

nyms used were public and private, with open and secret as the indirect

controls. The same constraints governed the choice of these adjectives as

governed the choice in Experiment 1.

ethod

The method was the same as in Experiment 1, but new sets of25sentential

contexts for the adjectives public, private, open,and

secret

were taken from

the Brown Corpus. The principal caution required was that the sentences

containing

open

should use it in the appropriate sense, and not as an anto-

nym of

shut

or

closed.

The following illustrate the kinds of sentential con-

texts tha t were constructed in this way:

Pastpolls of opinion showpopular favor for this policy.

The current exhibition, which remains on view through October 29, has

tapped14major collectionsand many sources.

Mr. Black s life is an

book,

so to

speak,

from his birth in Jackson,

Mississippi, through hisbasketball-playingdays in L.S.U.,and his attain-

ment of

a

B.A. degree, which

has presumably prepared him

for his

career

as district sales

manager for

Peerless BusinessMachines.

When I returned to make my report, the Hetman did not remember ha ving

sent me on the mission.

Results

The sorting data for public, private, open, and secret are summarized in

Tables 4, 5, and 6. Table 4, which corresponds to Table1 for Experiment 1,

shows the results for the direct antonyms public/private. Public contexts

were recognized correctly 88% of the time, andprivatecontexts

71%. The

most frequent error was to call

private

contexts personal ; except for that ,

o ther responses seem to differ rather widely in meaning from the targets

and from one another.

Table 5, which corresponds to Table 2 for Experiment 1, summarizes the

results for sorting contexts of the indirectly antonymous pairs of adjectives

public/secret, open/private, and open/secret. These sets of contexts were

also well discriminated, although not quite as accurately as in the case of the


12/19



Table 4.

Sorting data for direct antonyms:

public/private

Stimulus

Public

Private

Sum

Public

176

11

187

Response

Private

4

142

146

Other

20

47*

67

Sum

200

200

400

popular 4,personal 3,civic2, all 1,civil 1,close 1,decisive 1,free 1,governing1,

land 1,opposing1, own 1,real 1,true

1

(14).

*personal 30, true 4 , free 2, opposing 2,own 2,real2,civic1,different 1,ordinary1,

popular

1,

rural

1

(11).

pair of direct antonyms. Contexts for one adjective were seldom grouped

with contexts for its indirect antonyms. None of the words in this experiment

has the low response strength observed forfaint in Experiment 1. However,

some subjects were unable to assess any label to some of these contexts, and

those cases are reported simply as no response.

Table 6, which corresponds to Table 3 for Experiment 1, summarizes the

results obtained when sets of contexts for nearly synonymous adjectives,

public/open

and

private/secret,

were compared. These contexts were surpris-

ingly well discriminated, which suggests that not even these similar adjec-

tives are interchangeable in sentential contexts.

iscussion

The results for these

public

adjectives followed the same pattern as did the

strong

adjectives, although the contexts in Experiment 2 were more accu-

rately discriminated than were those in Experiment 1. But contexts of direct

antonyms are not harder to discriminate than are the contexts of related

words, so the inference that the substitutability hypothesis is implausible is

again supported by this replication.

The response biases in Experiment 2 are not as exaggerated as in Experi-

ment 1, but there is still a clear ordering: publioprivate>secret> open.

The frequencies of these four adjectives in the Brown Corpus (Francis &

Kucera, 1982) are, respectively, 306, 185, 46, and 242, which can be recon-

ciled with the preferences of the subjects in this experiment if it is assumed

that the adjective openhas more than one sense and that the sense used in

this experiment is not the most frequent. The Lorge magazine count (Thorn-

dike & Lorge, 1944) and the D ahl count of spoken English (Dahl, 1979) are

not broken down by part of speech. These sources cannot be used to check

on the Francis and Kucera data because public, private, and secretare

frequently used as nouns and openis also a verb.

The results of Experiment 2 were analyzed by signal detection techniques

just as those of Experiment 1 were. From Table 4 the average

d

for direct


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Applied Psycholinguistics 10:3

369


Table 5.

Sorting data for

indirect

antonyms:

public/secret, open/private, open/secret

Response

Stimulus Public Secret

Other

Sum

Public

Secret

Sum

166

17

183

Open

0

98

98

Private

34

85

119

Other

20 0

20 0

40 0

Open

Private

Sum

127

5

132

Open

162

170

Secret

33d

98

Other

20 0

20 0

400

O p e n

Secret

u

36

7

43

53

64

5

V

93

2

2

4

much4,new4, the 4,massive3,private3,good2,passive2,prior 2,another1,

competitive 1,confidential 1,diverse 1, few 1,great 1,kind 1,rest 1,special1,

unnecessary

1

(18).

*private 26, confidential

21

new 14, the 4, great 3 , military 2, prior 2, entire 2, good

2

convincing 1,heavy 1,inside 1,material 1,materialistic 1,passive 1,special1,

sure 1, violent 1(18).

'public 24, personal 5, strong 5, democratic 4, informal 4, violent 4, (no response)4,

obvious 2,other 2, town 2, accepted 1,avid 1,biting 1,distracting 1,entire1,

modern 1, interested 1, second 1, world

1

(18).

^public 11, personal6,legal4,different 2,real2,respected 2,obvious 1,other1,

radical 1, second 1, trivial 1, volunteer

1

(12).

e

heavy 11 autonomous 9, (no response) 8, public 5, democratic 4, severe 4, closed2,

anonymous 1, display 1, editorial 1, empty 1, high 1, legal 1, loud 1, private 1, strict

1

well-kept 1

16).

/my steriou s 12, original 4, private 4, severe 3, amb itious 2 , closed

2,

own 2, strict 2,

no

response)

2,

democratic

1,

material

1, no 1,

original

1,

proven

1,

public

1, two 1 15).

antonyms is 2.69, from Table 5 the average for indirect antonyms is 2.40,

and from Table 6 the average for similar adjectives is 2.00. The order of

discriminability is the same as before, although the range is narrower.

In general, contexts of thesepublic adjectives are more recognizable than

are contextsof strongadjectives. The finding that contexts of similar adjec-

tives - public/open andprivate/secret - are so easily distinguishable was

unexpected, but it does not change the evidence that contextual substituta-

bility does not explain how pairs of antonymous adjectives come to be so

strongly associated.


14/19



Table6.

Sorting data for near-synonyms:

public/open, private/secret

Response

Stimulus Public Open Other Sum

Public 163 10

Open 41 141

Sum

204 151

Private Secret Other

27

18*

45

200

200

400

Private

Secret

Sum

159

27

186

7

127

134

46


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Applied Psycholinguistics 10:3 37 1


ethod

Materials.Only the contexts for the directly antonymous pairsstrong/weak

and

public/private

were used in Experiment 3. The same sentences from the

Brown Corpus were used again, but the amount of context was reduced to

merely the noun phrases containing these adjectives: a determiner, if there

was one; any other adjectives, if there were any; and the noun that the target

adjectives modified. This way of constructing phrasal contexts meant that

often only two or three words of context were available to the subjects. For

example:

a very central government

,

sickly, little things

the eye

many sources

As before, each context was printed on a separate 4x 6 inch card.

Subjects. Eight Princeton University undergraduates, all native speakers of

English, participated as paid volunteers.

Procedure.

The method of sorting contexts was continued, but instead of

pairwise comparisons of different sets of contexts, subjects were given all

four sets of phrasal contexts simultaneously. Thus, each subject was present-

ed with a thoroughly shuffled pack of100cards to sort. Subjects were tested

individually.

Instructions.

Unlike Experiments 1 and 2, subjects in Experiment 3 were

explicitly told the four terms under which contexts should be sorted. They

were asked to read the phrasal contexts carefully and to sort each card under

one of the four adjectives,

strong, weak, public, private,

whichever fitted

best into that context. Since the four possible responses were known to the

subjects in advance, other responses are eliminated, and when subjects

finished they were not asked to label the groups they had created.

Results

The results of Experiment 3 are summarized in Table 7. As expected, there

are far more false alarms when only phrasal contexts are available. In partic-

ular, contexts of

weak

were sorted under the heading

strong

almost as often

as under

weak,

thus creating a large response bias in favor of the unmarked

adjective. But the other three adjectives were better recognized. And con-

texts of the strong/weak pair were not often mistaken for contexts of the

public/private pair, although strong and public contexts were sometimes

confused. Overall, however, subjects were able to discriminate among the

contexts reasonably well:

58

of the contexts were sorted correctly.


16/19



Table 7.

Sorting data for phra sal contexts:

strong, weak, public, private

Response

Stimulus

Strong

Weak

Public

Private

Sum

Strong

132

86

33

19

270

Weak

29

96

11

11

147

Public

27

8

113

47

195

Private

12

10

43

123

188

Sum

200

200

200

200

800

iscussion

The contexts of direct antonyms became less discriminable when the am ount

of context was reduced from a sentence to a noun phrase, which confirms

Charles' (1988a) results when he reduced the amount of context for nouns.

Although discriminability is reduced, it does not fail completely. An ap-

proximate signal-detection analysis can be performed, as follows. For exam-

ple, using the data for strong, the probability of a hit can be estimated as

132/200=0.66, and the probability of a false alarm as (86+33 + 19)/600=

0.23;

then

d =lA5.

Following this method, the values of

d

for

weak,

public, andprivate are 1.32, 1.26, and 1.53, respectively. These values ofd

are inflated, of course, by the relative ease of discriminating strong/weak

from public/privatecontexts. A more conservative approximation forstrong

would use 86/200=0.43 to estimate the false alarm probability, in which case

rf'=0.59. Following this method, the values of d for weak/public, and

privateare 1.01, 0.89, and 1.08, respectively.

The source of this discriminability becomes clearer when individual phra-

sal contexts are examined. For example, hintsand compulsionsare strong,

not weak.

Wheezes

and

sickly little things,

on the other hand, are more

likely to be weak than strong. Similarly, public goes with a better

imageand honest and spirited,whereasprivate goes with the fic-

tional eyeor a hospital nurse. Some of these collocations

are almost compound nouns. The point, however, is tha t it is simply not true

that any noun phrase that can take one adjective can equally well take its

direct antonym. Hence, even though substitutability might provide an im-

portant cue for learning which contrasting adjectives to pair as direct anto-

nyms it is still not an attractive hypothesis.

Table 7 shows considerable confusion between

strong

and

public

contexts.

This result may say something about the importance of marking. Presum-

ably, the unmarked terms, strongandpublic, are more salient semantically,

are governed by fewer restrictions on their use, and are learned earlier by

children (Clark & Chase, 1972). Alternatively, this result may say something

about the importance of frequency of

use.

Unm arked terms tend to be used

more frequently (Greenberg, 1966), presumably because there are more dif-


17/19



ferent contexts in which they can occur. Or, to put it the other way around,

words that are used infrequently tend to be used only in specific contexts.

GENERAL DISCUSSION

The results of this series of experiments using the method of sorting contexts

confirm for adjective contexts some of the general observations made by

Charles (1988a) when he used the method to study noun contexts:

1. The method of sorting contexts is robust and gives intuitively plausible

answers to questions about linguistic contexts.

2. Words with similar meanings tend to occur in similar contexts.

3.

Response biases in sorting are largely attributable to differences in the

frequency of use of the terms involved.

4. The greater the amount of context provided, the more discriminable the

contexts will be.

Such results encourage further explorations using this method.

The results also cast doubt on substitutability as an important cue for

learning to pair direct antonyms. The substitutability hypothesis may (or

may not) be required for an associative account of learning syntactic catego-

ries, but it is simply not available as an explanation for learning pairs of

antonymous adjectives.

Showing that substitutability is an improbable explanation does not

prove, of course, tha t antonymous pairing is learned as a consequence ofco-

occurrence. At the anecdotal level, however, while making up the stimulus

sets we found five sentences in the Brown Corpus where strongandweak

both occurred. For example: Strong hands act; weak hands reactand . . .

for the purpose of

understanding

strong and

weak

points of

an

individual.

But no sentences were found in which the indirect antonyms strongand

faint, powerful and weak,orpowerful andfaint co-occurred. Similarly, we

found 17 sentences in which

public

and

private

were both used, whereas the

indirect antonyms were used together far less often: public/secretoccurred

once,p rivate/opentwice, and

open/secret

once.

These observations are suggestive, but these samples from the Brown

Corpus are too small to disconfirm a reasonable null hypothesis. An analy-

sis of a larger corpus would be required in order to determine whether

antonymous adjectives are regularly used together in the same sentences

more frequently than would be expected by chance.

The following data seem relevant, however. The adjectives big, little,

large,andsmalloccur with sufficient frequency in the Brown Corpus to give

a more reliable estimate of their relative frequencies of co-occurrence. More-

over, these four adjectives illustrate the specificity of antonymous pairing.

Although bigandlargeare closely similar in meaning, as arelittleandsmall,

they are generally paired off antonymously asbig/littleandlarge/small. Big/

small does not sound quite right; large/little sounds definitely wrong. Al-

though the conceptual opposition is the same, the associative pairings are


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Applied Psycholinguistics 10:3 37 5


REFERENCES

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contextual

information.

Unpublished doctoral dis-

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(1988b). The categorization of sentential contexts.

Journal of

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Clark, H. H., & Chase, W. G. (1972). On the process of comparing sentences against pictures.

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Dahl, H. (1979).

Word

frequencies

of spoken

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Deese, J. (1964). The associative structure of some common English adjectives. Journal of

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(1965). The

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C. C. (1952).

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Greenberg, J. H. (1966). Language universals. In

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III: Theoretical foundations.

The Hague: Mouton.

Gross,

D., Fischer, U , & Miller, G. A. (1989). Antonymy and the representation of adjectival

meanings.Journalof Memory and

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MacWhinney, B. (1987). The competition model. In B. MacWhinney (Ed.),

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applied psycholinguistics volume 10 issue 3 1989 [doi 10.1017%2fs0142716400008675] charles, walter...

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