THE G~INERATION OF TERM DEFINITIONS FROM AN ON-LINE TEP~NOLOGICAL ~SA\[~S 
John McNaught 
Centre for Computational Linguistics 
bT~IST 
P.O. Box 88 
Manchester UK 
ABSTRACT 
A new type of machine dictionary is 
described, which uses terminological relations to 
build up a semantic network representing the terms 
of a particular subject field, through interaction 
with the user. These relations are then used to 
dynamically generate outline definitions of terms 
in on-line query mode. The definitions produced 
are precise, consistent and informative, and allow 
the user to situate a query term in the local 
conceptual ~vironment. The simple definitions 
based on terminological relations are supplemented 
by information contained in facets and modifiers, 
which allow the user to capture different views of 
the data. 
I Introduction 
This paper describes an on-golng project 
being carried cot at U~T, which is concerned 
with the nature, constructicn and use of 
specialised machine dictionaries, concentrating on 
one particular type, the terminological thesanrus 
(Sager, 1981). ~ system described here is 
capable of c~ynem~ically producing outline 
definitions of technical terms, and it is this 
feature which distinguishes it from other 
automated dictionaries. 
II Background 
A. Published Specialised Dictionaries 
These traditional reference tools, while 
often containing hi~n quality terminology 
collected after painstaking research, do not in 
the normal case afford the user an overall 
conceptual view of the subject field, as they 
exhibit a relative lack of structure. Moreover, 
due to the limitations of the printed page, the 
form%t of the entries is fixed, such that 1~sers 
with differing information needs are obliged to 
search through to them irrelevant data. The only 
real aid ~ich allows the user to place a term 
roughly in the local conceptual environment is the 
conve~.tional def~_nition. However, such definitions 
tend to be idiosyncratic, inconsistent and non- 
rigorous, especially if the subject field is of 
any great size. Contexts, while of some help, are 
* sponsored by the Department of Education 
and Science through the award of a 
Research Fellowship in fx~fo1~tion Science 
notoriously difficult to find and control, and 
should only be seen as supplementary to a rigorous 
definiticn of the term which firmly places the 
term in the conceptual space. Those reference 
tools containing definitions which are rigorous 
exist mainly in the form of glossaries established 
by standards bodies. However, standardisation of 
terminologies is a slow affair, and is restricted 
to certain key terms or fields, such that no 
overall conceptual structure r,~y be obtained from 
these glossaries. 
B. Term Banks and F~chine Dictionaries 
Term Banks offer many advantages over 
traditional dictionaries, and are becoming more 
and more common, especially among organisations 
which have urgent terminolo~ needs, such as the 
Co~ssicn of the European Communities or the 
electronics firm Siemens AG in W. Germar~y. 
National bodies likewise use term banks to control 
the creation and dissemination of new standaraised 
terms, e.g. AFNOR (France) and DIN (W. Germany). 
In the UK, work is going ahead, coordinated by 
UMIST and the British Library, to set up a British 
Term Bank. Other in~portant term banks exist in 
Denmark (DANTe) and Sweden (TE~K). However, 
despite this growth in the number of term b~nks 
and other computer based dictionaries, there 
remains a sad lack of overall structuring of the 
terminological data. In some cases, dictionsries 
have been transferred directly onto computer, in 
other cases, data base management considerations 
have overriden any attempt at systematic 
terminological representation of the data. Some 
term banks have made provision for expressing~ 
relations between terms (AFNOR, DANT~I) but these 
relations are not as yet exploited to their full. 
C. Oocumentation Thesauri (DTs) 
Zhese tools, whether on-line or published 
from nr~gnetic tape, represent gross groupings of 
terms (via descriptors ) for the purpose of 
indexing and retrieval of documents. A 
hierarchical structure is apparent in a thesaurus, 
with general relationships beh~g established 
between descriptors, such as BT (Broad Term), NT 
(Narrow Term) and RT (Related Term). Some thesauri 
further distinguish e.g. BqG (Broad Term Generic), 
~TP (Narrow Term Partitive) ~nd so on. However, 
by its very nature and purpose, a DT is merely a 
tool for selecting :rod differentiating between the 
chosen items of the ~rtificial reference system of 
90 
an indexing language. The existence of overlapping 
and even parallel indexing languages attests the 
inadequacy of Errs for representing generally 
accepted terminological relationships. Other 
problems associated with DTs are highlighted when 
attempts are made to merge DTs and to match 
descriptors across language boundaries. Existing 
DTs also find great difficulty in representing 
polyhierarchies (Wall, 1980) hence the ambiguous 
nature of the RT relation. The best known attempt 
at solving such difficulties is the ~ESAUROFACET 
(Aitchison, 1970) • 
D. Terminological Thesauri (Trs) 
Traditionally, the Tr (as advocated by e.g. 
WGster, 1971) represents relationships between 
concepts rather than descriptors in as much detail 
as possible. As such, it has mainly been the 
preserve of terminologists. The Tr has the 
advantage of precisely situating a term in the 
conceptual environment, through msk_Ing appeal to 
relationships such as generic and partitive (and 
their various detailed subdivisions ), and to 
relations of synonymy (quasi-, full synonyms, etc) 
and antonyrm/. A classic example of the Tr approach 
to structuring data is the Dictionary of the 
Machine Tool (%~dster, 1968), which has served as a 
basis for the present project. 
However, although systematic in conception 
and detailed in execution, this particular work 
displays the constraints inherent in the WGsterian 
approach, which is akin to that of the DT, namely 
reliance on the hierarchy as a structuring tool. 
For example, given the partial sub-tree in figure 
la. : 
PRINTF/q \[...\] 
PAPER TRANSPORT MECHANISM 
FORM FEED 
FF~ RATE CONTROL 
TAPE, CONTROLLED 
TAPE CONTROLI/D PRINTER 
figure la. Problems with a hierarchy 
we would like to be able to relate TAPE CONTEOTI.k"D 
PRINTER to its true superordinate, FRINTF~, to say 
that it is a type of printer. Again, given the 
structure in figure lb. : 
CHARACTER \[...\] 
PRINTABLE 
PRINT CHAPACrER 
COntrOL CHARACTER 
figure lb. Problems with a hierarchy 
we would like to be able to represent the 
relationship of CONTROL CHARACTFJ~ to C~ARACTER 
directly. This is impossible in the hierarchical 
approach, where one is constrained to adopt one 
scheme, and to represent only one possible 
relationship, whereas a term may have multiple 
relationships to multiple telm~s. As with DTs then, 
conventional Trs are incapable of representing 
one-to-n~m%y and msny-to-one relationships. 
E. Sum~ 
There exists a need for a representational 
device which c~n capture the necessary 
relationships between terms in a natural and 
informative manner, and which is not constrained 
by the limitations of the printed page, or the 
mental capacity of the terminologist. 
III %he on-line Terminological Thesaurus 
The present project has concentrated on 
finding a device capable of responding to the 
demands of different users of terminology, and 
which would allow a systematic representation of 
terminological data. We have retained the term 
Terminological Thesaurus, but have given it a new 
meaning. The particular device we have constructed 
combines the advantages of the conventional TT 
(systematic structure, relationships) and of the 
traditional dictionary (definitions). This is 
achieved by using inter-term relationships first 
to construct a highly complex network of terms, 
and subsequently, at the retrieval stage, to 
generate natural langu~e defining sentences which 
relate the retrieved term to others in its 
terminological field. This is done by means of 
templates, such that the user is presented with an 
outline definition of a term (or several 
definitions, if a term contracts relations with 
more than (me term) which will help him to 
circumscribe the meaning of the term precisely. 
Although the particular orientation of the project 
is to generate definitions, the semantic network 
that is constructed could be used for other ends, 
and future work will investigate these 
possibilities. We stress here that the definitions 
that are produced are not distinct texts stored in 
the machine and associated with individual terms; 
rather, the declared relationships between terms 
are used to dynamically build up a definition, and 
terms from the immediate conceptual environment 
are slotted into natural language defining 
templates. These definitions have the advantages 
of being precise, system internal and alws~vs 
correct, providing the correct relationships have 
been sqtered. Preliminary work in this area was 
first carried out at L%ffST in the late 70s, when 
the feasibility of using terminological 
relationships to structure data was shown, and an 
experimental syst~: was implemented, based on a 
hierarchical repre~entation, that output simple 
definitions (Harm, 1978). This was found to be 
inadequate, for the reasons outlined above, hence 
the adoption in the present project of a richer 
data structure. 
The data base for the system is then a 
senantic network. ~s with most semantic networks, 
the most one can really say about it is that it 
consists of nodes and arcs: terms form the nodes, 
and relations between terms the arcs. In actual 
fact, the data base consists of several files, 
with the character strings of ter~ns being assi~ed 
to one file, such that all search and creation 
operations for the network proper eu'e carried out 
91 
using simply logical pointers to bare nodes 
carrying the geometrical information needed to 
sustain the network, thus avoiding the overhead of 
storing variable length strings often in 
duplicate. A virtual memory has been implemented 
such that file accesses are kept to a minimum, and 
all pointer chains are followed in fast core. The 
basic data structure of the network is the ring, 
and the appearance of the network is that of a 
multiway extended tree st~cture. Facilities exist 
for on-line interactive creation and search of the 
network. An important design principle is that the 
computer should relieve the terminologist (or 
indeed the naive user) of the burden of keeping 
track of the spread and growth of a conceptual 
structure. We have already seen how the 
hierarchical approach to terminology failed to 
account for all the facts, and forced the 
terminologist into misrepresenting or distorting 
the conceptual framework. With a network, ease and 
naturalness of representation is achieved, but at 
the cost of increased complexity for the human 
mind. Thus a human will quickly lose track of the 
ramifications of a network, even if he could 
represent these adequately on some two dimensional 
medium. Entrusting the management of the network 
to the computer ensures precision and consistency 
in a very large data base. 
At the input stage, in the simple case, the 
terminologist need give only 3 pieces of 
information: two terms and the relationship 
between them. As the system is open-ended by 
design, the terminologist can declare new 
relationships to the system as he works, i.e. it 
is not necessary to firstly elaborate a set of 
relationships. Further, neither of the two input 
terms need necessarily be present in the data 
base. If both are absent, the system will create 8 
closed sub-network, which will only be linked to 
the .~uin network ~len other liD/as are n~e with 
one or both of these terms. As input proceeds, one 
may have the (perhaps non-consecutive) inputs 
<X rel A> <Y rel A> <Z rel A> 
where {X,Y,Z,A) are terms and <rel> a 
relationship. The system Will link all terms 
related to <A> in a ring having <A> f\]~gged as the 
'head' node. Thus the terminologist is not 
~equired to overtly state the relationships 
between {X,Y,Z}. laaving the computer to establsih 
links among terms from an initial single input 
relationship ensures high recall. Note that choice 
of refined relationships aids hig~ precision, 
although too msny refinements may be detrimental 
~m retrieval, in which case some automatic 
mec~hanism for Widening the search to include 
closely associated relationships would be 
necessary. However, this would imply that 
information be conveyed to the system regarding 
the associations between relationships, and would 
be a strong argument in favour of designing a set 
of relationships prior to the input of tei~s. At 
present, we have no strong views on this subject. 
The syst~n is open-ended to accept new 
relationships; it is up to the terminolo6ist how 
he organises his work. 
In the complex case, where there are perhaps 
several terms having the same relationship as the 
input term to a common 'head', or where the 'head' 
may have several sub-groups (q.v.) associated with 
it, the system interacts with the user to tell him 
there are several possibilites for placing a term 
in the network, and shows him structured groups of 
brother terms having the same relationship as the 
input term to the 'head', where his input term may 
fit in. It is important to realise that the user 
need have no knowledge of the organisation of the 
network. He is asked to make terminological 
decisions about how an input term relates to 
others in the immediate conceptual environment. 
The notion of ' sub-group' is the only one 
which requires explanation in terms of the theor~j 
behind the orgardsation of the system. This notion 
was introduced in an attempt to represent the fact 
that there may be terms that are mutually 
exclusive alternatives, and which attract other 
terms which can cooccur without restriction. A 
simplistic example will make this point clearer. 
For the sake of discussion, we assume the 
following parts of a radio, shown in figure 2. : 
RADIO 
VALVE 
TRANSISTOR 
AERIAL 
figure 2. Simplified parts of a radio 
what we wish to represent is the fact that if a 
radio has valves, it has no transistors, and vice 
versa, but whichever is tl~e case, there is always 
an aerial present. What has happened here, 
terminologically, is that there are two terms 
missing from the concept space, referring to the 
concepts ' valve radio' and ' transistor radio ' 
respectively. Or it my be the case that the 
terminologist has not as yet entered the generic 
subdivisions of radio. Thus there are two 'holes' 
here, as yet unfilled by a term. The solution 
adopted, is to create dun~ nodes in the network, 
which act as ring 'heads' for sub-groups each of 
which contains one of the mutually exclusive 
alternatives, plus any terms that are strongly 
bound to one or both of the alternatives, but not 
themselves mutually exclusive. The dunrnies refer 
back directly to the true head term, and x~v be 
converted at any time into full nodes if the 
tel~ninologist ' s answers to questions about his 
input indicates that a new term ought to occupy 
this position, with this particular relation to 
the original head term and with this particular 
sub-group of terms. Terms which are common to all 
sub-groups,, and which have a relationship to the 
original head term, are merely inserted in the 
ring dominated by the original head, and are by 
default interpreted as belonging to all sub- 
groups. In our present example, this would apply 
to 'aerial'. Various checks are incorporated to 
prevent e.g. terms common to all sub-groups being 
bound to all these groups - that is, if one binds 
a term to every possible sub-group trader an 
original head, this would inTply that it does not 
in f~ct have any special binding power, or' cooccur 
only with terms in these sub-,groups. The resulting 
92 
structure for this ac~ittedly simple example is 
shown in figure 3, where primed nodes are dunmy 
nodes dominating a sub-group ring. : 
RADIO' ~ AERIAL 
figure 3. Representation of alternatives 
basic data structure, with terms ontologically 
related to another term being logically 
subordinated to it, and with several other 
relations being established either automatically 
or semi-automatically in response to user 
interactions, provides enough information for the 
generation at search time_ of outline definitions 
of terms. The main file containing the semantic 
network proper has the record structure shown in 
figure 4.: 
Field Value Type 
1 RELATION C~AR 
2 MODIFTER CHAR 
3 FACET INTEGER 
4 FATHER/BRO~ INTEGF/~ 
5 SON INTEG,~IR 
6 VARIANT INTEGER 
7 CONTENT INTEGER 
8 ALT~ATIVE INTEGF/~ 
9 FLAGS INTEGER 
figure 4. Network file record stn~cture 
The FLAGS field apart, all integer fields are 
logical pointers to other records in the network 
file, except for CONTHNT which points into another 
file containing records which give information on 
the actual character strings of terms. Most of the 
field values are self-explanatory. The 
FATF/~/BROTHER field has a dual value (indicated 
by an appropriate flag) and together with the SON 
field is used to build the basic ring structure. 
The VARIANT field is used to form another ring 
which links nodes representing the same tenm in 
relation to different 'heads', and is commonly 
employed to represent polyhierarchies, which as 
will be recalled posed a problem for DTs and Trs. 
Here the advantage of the CONTF2~T pointer becomes 
apparent, as only the geometrical network- 
sustaining information is duplicated when a term 
enters into relation with more than one 'head'. 
Two fields remain which require more detailed 
explanation, r~mely the MODIFIER field and the 
FACET field. These were introduced to enhance the 
outline definitions the syst~n produced, which, 
although precise and consistent, were found to be 
r~ther uninforn~ative in certain respects. For 
example, to generate the definition 'A vernier is 
a type of scale' leaves something to be desired, 
when the definition in Wflster's dictionary refers 
to 'a small movable auxiliar F scale'. One could of 
course get round this by declaring a new type of 
scale to the system, namely 'auxiliary scale' or 
even 'movable auxiliary scale', if this were 
terminologically acceptable. We think though that 
to append 'small' would be stretching things 
rather far. However the introduction of a MODIFIF~ 
field allows some measure of finer description, by 
allowing the user to specify an adjective or 
adjectival phrase, which in this case, and perhaps 
commonly, would be relational, i.e. 'vernier' is 
seen as small in relation to a larger 'scale', but 
may be large with respect to e.g. 'microvernier'. 
The modifier is thus attached to the geometrical, 
relational node of the network, not to the 
content, stringbearlngnode. 
The FACET field takes its nsn~ from the 
facets well-known in the construction of DTs. A 
facet is here used in a similar manner to a DT 
facet, that is, as a classificatory tool, to give 
a different view of the data. A facet represents a 
gross grouping of terms according to some feature. 
Examples of facets are: 
BY DIRECTION 
BY MATERIAL 
BY SHAPE 
etc. 
BY r,~HOD OF PROPULSION 
BY APPLICATION 
BYMETHOD OF OPEPATION, 
In traditional DT work, though, a descriptor can 
appear only under one facet. In the present 
system, a term can appear under many facets. This 
gives extreme flexibility and allows the 
terminologist to draw fine and not-so-fine 
distinctions between groupings of terms. In most 
DTs, there is little attempt at structuring facets 
- they are used in a fairly ad-hoc manner. In the 
context of the present project, research is being 
carried out by Catherine Yarker into the nature of 
facets, which will shed light on how they could 
best be employed in the system. An interesting 
point to note is that what are normally called 
terminological relationships could justifiably be 
viewed as a subset of facets, the difference being 
that they are more commonly used, display more 
structure, and have undergone systematic 
investigation over the years. 
Output from the system is available in a 
variety of formats, depending on how much, or 
which type of, information the user desires. ~here 
now follow a few examples which show the potential 
of the system: 
Query: CAR 
Response: CAR is a type of VHHICLE, together with 
BUS, IDRRY, TRAIN and TRACTOR. 
Q.: PYLON 
R. : PYLON is a part of tWINI:b1ILL, 
V&NE and GFINERATOR. 
together with 
These show how a simple definition of a term is 
given, by relating it to its generic or partitive 
superordinate, and listing other terms having the 
same relationship to the superordinate as the 
query term. 
93 
Q. : SLUICE VALVE 
R. : SLUICE VALVE is a part of PUMP 
<more? > 
Yes 
R. : SID-ICE VALVE is a type of GATE VALVE 
Q. : GATE VALVE 
R. : GATE VALVE is a type of VALVE together with 
PISTON SLI~ VALVE, PLUG VALVE, IX~ TYPE VALVE 
and CHECK VALVE 
Here the user asks for a further definition of 
SLUICE VALVE, then queries GATE VALVE. 
~he addition of facet information, as we have 
pointed out, gives rise to more informative 
definitions, in that the user can see how a term 
is differentiated from other terms in the 
immediate environment, for example: 
Q. : FLANGE 
R. : FLANGE is a component of FLANGED FITIENG, and 
is related to STEF~ FIANGE by material, to 
DETACHABLE FLANGE by property, to CONNECTING 
FLANGE by method of connection, to BOSSED FLANGE 
by shape and to FLAT FACED FLANGE by flange face 
configuration 
Q. : STEEL FLANGE 
R.: ST~L FLANGE is a type of FLANGE distinguished 
by material. Other types of FLANGE are DETACHABLE 
FLANGE and iCOSE FLANGE distinguished by property, 
CONNECTING FLANGE, SCREWHD FLANGE and WELDF/) 
FLANGE distinguished by method of connection, 
BOSSED FLANGE and OVAL FLANGE distinguished by 
shape and FLAT FACED FLANGE, RAISFD FAGE FLANGE 
and ~\[LL FACFD FLANGE distinguished by flange face 
configuration. 
Experiments are still under waF to determine how 
best to use facets, and how best to formulate the 
definitions. It appears useful, in a definition, 
first to relate a term to another by a common 
terminological relati0nsblp (part of, type of) and 
then to refine the definition by bringing in 
facets. 
There is also the possibility to ask for a 
specific relationship, for example, if one were to 
ask for parts of a wheel, the display might read: 
MTEEL ~s composed of HUB, SPOKE, RIM, 
WH~L CE/~, and TYRE. 
The usefulness of more refined terminological 
relationships is shown by the following examples: 
KEY is a part of KEYBOARD 
WI~k-~.T. is a part of CAR 
RADIO is a part of CAR 
F~GIN\]< is a part of CAR 
where the standard 'part of' relationship proves 
inadequate. Therefore, we introduce subdivisions 
of the partitive relationskip, which generate the 
following outputs: 
K~,\[ is an atomic part of KEYBOARD (i.e. the latter 
consists wholly of the former). 
One or several ~a are contained in CAR 
RADIO is an optional part of CAR 
ENGI/~E is a constituent part of CAR (i.e. 
contains other parts, including ENGINE) 
CAR 
These few examples hopefully give some indication 
of the system's potential. With a complex network 
enriched with refined terminological 
relationships, modifiers and facets, we can look 
forward to the generation of extended, informative 
definitions. It n~ybe argued that problems could 
arise in maintaining the consistency of the 
network, however the interactive input procedure 
is designed to show the consequences of a 
particular choice or insertion before the input is 
recorded definitively in the network. 
Nevertheless, there comes a point when one has to 
rely on the user himself not to make silly 
decisions. Due to the extreme flexibility of the 
system, and the use of a network as a 
representational device, the terminologist is free 
to introduce whichever relationships he desires, 
and to link whichever terms he chooses. This 
freedom may he anathema to those who adhere to the 
rigorous hierarchical approach to terminology, 
however, used with judicious care, the system is 
capable of recording multiple relationships in a 
way denied to the proponents of the hierarchical 
approach, which in the end provide a basis for the 
generation of information that is more fully 
developed, and more illuminating due its richness. 
In the near future, an interactive editor 
will be implemented to help the terminologist 
adjust the data base, in case of error, or to 
monitor the changes brought about by the 
a change of relationship, facet, etc. 
It should be noted that the system is desi~qed to 
be multilingual, and is capable of outputting 
foreign language equivalents. As we have chosen to 
deal with rather normalised terminology, we make 
no claims as to the capability of the system to 
handle more general vocabulary, where there would 
be sometimes radical differences between the 
conceptual systems of different languages. At the 
moment, we work purely with one-to-one mappings 
across language boundaries. However, unlike the 
traditional term bank, which merely enumerates 
foreign language equivalents, this system, on the 
other hand, upon addressing a forei@a language 
equivalent in the data base allows immediate entry 
to a ring of foreign language synonyms, from which 
the entire parallel conceptual network of the 
foreign terminolo~ may be accessed. The 
possibility is then open for further definitions 
in the foreign language to be output, if desired. 
IV ~L~ATION 
The system is completely written in 'C', a general 
purpose system pro~ing language, and is 
implemented on a Z-~O based S-IO0 microcomputer, 
with 64kbyte memory and a 33mbyte hard disk. When 
the system ~s eventually stable, a virtual memory 
routine written in assembly language by Sandra 
Waites will replace the e~tisting 'C' routine, to 
speed up access times. The system runs to several 
thousand lines of code, including utilities and 
94 
basic input/output functions ('C' provides none of 
the latter) and is split into several chained 
programs, for reasons of memory space 
restrictions. Execution time is not therefore as 
fast as it could be, although the hard disk does 
make a substantial difference to access times. 
When mounted on a 16-bit microcomputer running 
under the Unix operating system, as is envisaged 
in the near future, and equipped with improved 
index searching routines (not a primary purpose of 
the project), there should be little delay in 
response time. 
For reasons of economy and experimentation, the 
basic network file record is limited to 16 bytes 
(see figure 4 above), however, in a future version 
of the system, other features may be added, for 
example a ring head pointer in each record, to 
save scanning all ring records to the right of the 
entry point to find the head. Further, the content 
file record, which contains Information on 
character strings, could be expanded to hold the 
types of information found in traditional term 
bank records, e.g. grammatical class, context, 
author, date of entry, sources, etc. This would 
then imply that a full-blown tel~ bank could be 
set up, organised around a semantic network, such 
that the bank would be structured according to 
terminological criteria, not to data base 
n~ment criteria. 
V ACKNOWiZIX\]FMENTS 
I would like to thank Sandra Waites and Catherine 
Yarker for their valuable contribution towards the 
realisaticn of this system, and ~ colleagues Rod 
Johnson and Professor Juan Sager for their advice 
during the course of the project. 
VI REFERENCES 
Aitchiscn, J. The Thesaurofacet: A Multi-Purpose 
Retrieval Language Tool. J. Doc , 1970, 26, 187- 
203. 
Harm, M.L. qhe Application of Computers to the 
Production of S~stematic~ Multilinsual Specialised 
Dictionaries and the Accessing of Semantic 
Information S~sten~. ~.~nchester, UK : CCL/UMIST 
report, 19Z~. 
Sager, J.C. Terminological Thesaurus. iebende 
Sprachen, 1982, I, 6-7. 
Wall, R.A. Intelligent indexing and retrieval: a 
man-machine partnership. Inf. Proc. & Man., 1980, 
16, 73-.cD. 
WGster, E. The Machine Tool : an Interlin~ual 
Dictionsz 7. London, OK : Technical Press, 19(95. 
WOster, E. Begriffs- und Themaklassification. 
Nachrichtun 6 fGr Dokumentaticn, 1971, 22:4. 
95 
