METONYMY: REASSESSMENT, SURVEY OF ACCEPTABILITY, 
AND ITS TREATMENT IN A MACHINE TRANSLATION SYSTEM 
Shin-ichiro Kamei* & Takahiro Wakao 
Computing Research Laboratory 
New Mexico State University 
Las Cruces, New Mexico 88003 
Tel : 505-646-5466 Fax : 505-646-6218 
Interact: skamei@nmsu.edu & twakao@nmsu.edu 
* visiting researcher from NEC Corporation in Japan 
ABSTRACT 
In this article we outline a basic approach 
to treating metonymy properly in a multil- 
ingual machine translation system. This is 
the first attempt at treating metonymy in an 
machine translation environment. The 
approach is guided by the differences of 
acceptability of metonymy which were 
obtained by our comparative survey among 
three languages, English, Chinese, and 
Japanese. The characteristics of the 
approach are as follows: 
(1) Influences of the context, individuals, 
and familiality with metonymy are not 
used. 
(2) An actual acceptability of each meto- 
nymic expression is not realized 
directly. 
(3) Grouping metonymic examples into 
patterns is determined by the accepta- 
bility judgement of the speakers sur- 
veyed as well as the analysts' intui- 
tion. 
(4) The analysis and generation com- 
ponents treat metonymy differently 
using the patterns. 
(5) The analysis component accepts a 
wider range of metonymy than the 
actual results of the survey, and the 
generation component treats meto- 
nymy more strictly than the actual 
results. 
We think that the approach is a start- 
ing point for more sophisticated approaches 
to translation in a multilirtgual machine 
translation environment. 
INTRODUCTION 
Among others, both Lakoff and Johnson 
(1980), and Fass (1991) divide metonymic 
expressions into several fixed patterns such 
as Part-For-Whole and Container-For- 
Content. Sentence (1) is a typical 
Container-For-Content metonymy and "this 
glass" is replaced with "the liquid in this 
glass" in its metonymic reading. 
(1) "He drank this glass." 
One of the things that has been less 
focused on in previous literature on meto- 
nymy is the problem of generation typically 
in a machine translation system. For exam- 
ple, even though the analysis component of 
a machine translation system produces a 
correct metonymic reading for sentence (1), 
i.e. "the liquid in this glass" for "this 
glass", if the result of the analysis com- 
ponent is translated directly in word-for- 
word manner, such an output sentence may 
not be natural in the target language. On 
the other hand, it may not be appropriate 
either for the generation component to pro- 
duce a sentence which is a direct transla- 
tion of the original metonymy if the target 
language does not allow such expression. 
We think it is necessary for a multil- 
ingual machine translation system to have 
not only understanding of metonymy which 
most previous works on metonymy have 
focused on, but also proper ways to handle 
generation of metonymy. In order to find 
out ways to treat metonymy properly in a 
multilingual environment, we have con- 
ducted a survey on acceptability of various 
examples of metonymy among English, 
Chinese, and Japanese. The patterns of 
previous works (Fass 1991, Lakoff and 
309 
Johnson 1980, Yamanashi 1987) seem to 
be obtained from the intuition of the 
analysts. However, we think that the pat- 
terns which are based on the analysts' 
intuition to begin with should be supported 
and determined more precisely by the result 
of this kind of survey. An analysis based 
on actual data allows us to establish a clear 
set of patterns and sub-groups, for example 
to decide whether we require either 
Producer-For-Product (Lakoff and Johnson 
1980) or Artist-for-Artform (Fass 1991), or 
both of them. 
A SURVEY OF METONYMY 
A comparative survey on acceptability of 
metonymic expressions in English, Chinese 
and Japanese has been conducted. All of 
the 25 sentences which are used in the sur- 
vey are taken from metonymy examples in 
English in previous works (Lakoff and 
Johnson 1980, Fass 1991, Yamanashi 
1987). We asked native speakers of the 
three languages to score the acceptability of 
each sentence. Direct translations were 
used for Chinese and Japanese. The dif- 
ferent languages show differences in accep- 
tability (for the details, Kamei and Wakao 
1992). 
Based on both intuitive analyses and 
the result of the .survey, we have esta, 
blished four major patterns, and several 
sub-groups for the first pattern (Locating) 
as shown in Appendix A. The patterns are 
1) Locating, 2) Emphasis of one aspect, 3) 
Abstract and collective entity for its con- 
sisting concrete items, and 4) Information 
conveyer for information giver. 
For example, sentence (2) belongs to 
the second group of Locating pattern (Pro- 
ducer for Product). Examples of "Ford", 
"Picasso", "Steinbeck" and "Bach" also 
belong to this group (see Appendix A 1.2). 
These sentences are fully acceptable in 
English and Japanese, however, their 
acceptability is low in Chinese and sen- 
tence (2) is completely unacceptable. 
(2) "He read Mao." 
On the other hand, sentence (3) 
belongs to the fourth pattem, information 
conveyer and giver. The tendency of the 
pattern is that those examples in this pat- 
tern are acceptable in English and Chinese, 
but not in Japanese. 
(3) "The sign said fishing was prohibited 
here." 
AN APPROACH TO TRANSLATING 
METONYMY 
An important point to realize is that actual 
computational treatment of metonymic 
expressions is determined by the accepta- 
bility of the pattern to which the expression 
belongs. Another important point is that 
the analysis and generation components of 
a machine translation system should treat 
metonymy differently. 
We believe that the main factors for 
treating metonymy correctly in a multil- 
ingual machine translation system are 1) its 
universality, which can be a guideline for 
the analysis component, 2) language depen- 
dency, which can be used for generation, 
and 3) others such as the context, culture, 
and familiarity. We think that it seems 
unrealistic to expect an actual machine 
translation system to cope well with the 
third of these factors at present. Given the 
lack of such knowledge, our basic heuris- 
tics for treating metonymy are as follows: 
Even if some language shows the ten- 
dency of unacceptability, if one or more 
languages show acceptance in the group to 
which the expression belongs to in the 
result of the survey, the system should 
accept it for analysis, and come up with 
some metonymic reading using its infer- 
ence mechanism (Iverson and Helmreich 
1992, Fass 1991). Given such information, 
the generation component should look at 
the tendency of each language. If the tar- 
get language allows a metonymic expres- 
sion which corresponds to the original 
form, then the system should produce a 
direct translation since the translation 
preserves the naturalness. However, if the 
310 
target language does not allow a meto- 
nymic expression which corresponds to the 
original form, then the system should use 
the result of the metonymic inference and 
come up with an acceptable translation. 
We think that these basic heuristics 
are a good starting point for more sophisti- 
cated approaches to translation in a multi- 
lingual environment. We intend as our 
next step to implement our ideas using 
existing systems such as the ULTRA MT 
system (Wilks and Farwell 1990) and the 
Metallel metonymic analysis program 
(Iverson and Helmreich 1992). 
APPENDIX A 
Some of the metonymic sentences used in 
the survey. 
1. Locating 
1.1 Container for Content 
Dave drank the glasses. 
The kettle is boiling. 
1.2 Producer for Product 
He bought a Ford. 
He's got a Picasso in his room. 
Anne read Steinbeck. 
Ted played Bach. 
He read Mao. 
2. Emphasis of one aspect 
We need a couple of strong bodies for 
our team. 
There are a lot of good heads in the 
university. 
3. Abstract entity for concrete entity 
Exxon has raised its price again. 
Washington is insensitive to the needs 
of the people. 
4. Information conveyer for information 
giver 
The T.V. said it was very crowded at the 
festival. 
The sign said fishing was prohibited 
here. 

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