Strategies for Interactive Machine Translation: 
the experience and implications of the UMIST Japanese project * 
P. J. Whitelock, M. McGee Wood, B. J. Chandler, 
N. Holden, and H. J. Horsfall 
Centre for Computational Linguistics 
University of Manchester Institute of Science and Technology 
P. O. Box 88, Manchester M60 IQD 
United Kingdom 
1, Introduction 
At the Centre for Computational 
Linguistics, we are designing and implementing 
an English-to-Japanese interactive machine 
translation system. Tile project is funded 
jointly by the Alvey Directorate and 
International Computers Limited (ICL). 'Pile 
prototype system runs on the ICL PERQ, though 
much of the development work has been done on a 
VAX \]\]./750. It is implemented in Prolog, in the 
interests of rapid protohyping, but intended for 
optimization. The informing principles are those 
of modern complex-feature-based linguistic 
theories, in particular Lexical--Functional 
Grammar (Bresnan (ed.) 1982, Kaplan and Bresnan 
1982), and Genera\]ized Phrase Structure Grammar 
(Gazdar et al. 1985). 
For developntent purposes we are using an 
existing corpus of 10,000 words of continuous 
prose from tile PERQ's graphics documentation; in 
the long term, the system will be extended for 
use by technical writers in fields other than 
software. At the time of writing, we have well- 
developed system development software, user 
interface, and grammar and dictionary handling 
utilities. Tile English analysis grammar hand\]es 
most of the syntactic structures of the corpus, 
and we have a range of formats for output of 
linguistic representations and Japanese text. A 
transfer g:camnlar for English-Japanese has been 
prototyped, but is not *lot yet fully adequate to 
handle all constructions in the corpus; a 
facility for dictionary entry in kanJi is 
incorporated. The aspect of the system we will 
focus on in the present paper is its interactive 
nature, di,qcussing the range of different types 
of interaction which a're provided or permitted 
for different types of user. 
2. %'he relationship between buman and machine 
The complexity of the translation task, and 
the dlver.~:kty of the knowledge types involved, 
makes the implementation of all MT system a 
research problem in knowledge engineering. In 
order for intermediate results to be of 
practlcal value, it is necessary to integrate 
human expertise into the machine translation 
process. After this input, the machine's 
knowledge must be complete, adequate for 
carrying out all later stages in the translation 
chain. Three strategies are recognized for this 
involvement, post-editlng, pre-edit ing, and 
interactive translation (see further Whitelock 
(ed.) 1985). 
Of these three strategies, post-edited 
translation is obviously the safest; the human 
has the final say, and so can correct any 
translation e, rrors made by tile machine. However, 
• tile post-ed~tor must be expert in the source 
language (at least for the text-type), target 
language, and subject inatter, i.e. a competent 
translator in his/her own right. The majority of 
current machine translation systems are of this 
type - it has proved to be cost effective - but 
post-editing is both revetitive and totally 
indispensable. Current interactive systems, too, 
typically require a high degree of bilingual 
competence on the humen's part. 
The pre-editing option assumes input which 
has been either drafted or edited to use only a 
restricted sub<language. Despite its 
demonstrated utility (e.g. Meteo (Chevalier et 
al. 1978), Xerox Systran (Ruffino 1982)), it is 
often viewed as a poor alternative, conveying 
connotations of severe restrictions on input. We 
believe that the notion of pre-editing should be 
reexamined in the light of Kay's remark that 
machine translation :is in principle possible 
only between formal languages (fn 1). Any MT 
system will produce intelligible output from 
only a proper subset of texts in what is claimed 
• to be the source language. Translation of a 
natural language in its entirety is an illusory 
goal. If the particular subset which can be 
automatically translated is not formalised 
independentl V of its instantiation as a computer 
system, the entire output must be checked after 
translation, in conjunction with the source 
text. We believe that it is preferable to define 
explicitly the subset of the source language 
tbat the machine can translate. Moreover, we 
believe that the drafting of texts in such a 
restricted language is an ideal candidate for 
automation. 
We have therefore designed a system to 
effect monolingual interactive pre-editing for 
pre-edited translation, questioning the human 
user about the source text, not about its 
translation (cf. Johnson & Whitelock 1985). An 
interactive system of this type should be able 
to accept an adequate subset of grammatically 
well-formed input, querying the user to resolve 
ambiguities or indeterminacies unti 1 a 
representation is reached which is sufficiently 
detailed and precise to guarantee acceptable 
translation to a given language (fn 2). A 
i, onolingual writer can thus produce finished 
target language text wihout further human 
intervention. As an incidental benefit, s/he can 
be expected to learn from experience which 
sentence patterns will not be accepted and which 
will give many ambiguities, and avoid them. 
Indeed it could be argued that such a system is 
valuable even monolingually, as an 'intelligent' 
style checker, with translation capability as an 
incidental benefit. 
329 
Thus we do not concur with Slocum's (\].985) 
assessment of the potential of interaction. 
Slocum characterizes interactive machine 
translation as "Human Assisted Machine 
Translation" as distinct from 'full' MT, on the 
grounds that the exploitation of the bilingual 
expertise of a human is interleaved with that of 
the machine. It appears that the machine is not 
carrying out the task of translation 
automatically. 
However, it seems more appropriate to 
consider the complete chain of processes from 
source language text composition to target 
language text completion. From this perspective, 
any type of machine translation is human 
assisted. It is important to assess the quantity 
and character of huma~ intervention as well as 
its position in the system. A post-edlted system 
resigns itself from the start to inadequacy, 
building in the requirement for (more or less) 
radical human revision of its output, so that it 
might better be called pro-translation than 
translation proper; while many current pro- 
editing systems, although offering fully 
automatic production of target language text 
from source language text, require a human 
contribution in the pre-input stage, controlling 
and restricting that source text, which 
qualitatively far exceeds the demands of on-line 
interaction (fn 3). 
Moreover, the future of machine 
translation, and natural language processing in 
general, seems certain to lie with systems based 
on A* techniques such as the use of inference 
for ambiguity resolution. A primary 
consideration will be to facilitate the transfer 
of expertise from human to machine, by means of 
modular programming, knowledge engineering 
techniques, and, ultimately, machine learning. 
Interactive system design may well be the type 
most readily extended to incorporate such 
techniques as they are developed; the forms of 
interaction implemented for the present human 
user can be progressively delegated to a virtual 
or machine "user". Thus despite the admitted 
limitations of interactive translation per se, 
systems including some sort of interaction offer 
bQth the most efficient use of current resources 
and the most convincing basis and model for 
research aimed at greatly improving translation 
quality. 
3. System development tools 
With the aim of producing a tool for 
continuing research as well as a system of 
practical utility, we have conceived our 
translation system itself and the system 
development tools as an integrated entity. 
Recognising a variety of types of 'user', from 
end-user to system designer, our development 
system is organized as a tree of facilities, 
where different types of user are allowed or 
offered access at different levels. Facilities 
supported include: 
i) using the system for writing, editing 
and translating, 
2) writing the grammars, 
3) developing the grammatical theory and 
the translation chain, 
4) designing the system itself. 
All tasks are carried out by traversing the tree 
under the guidance of menus. The menu system is 
designed to allow non-programmers (fn 4) to 
specify both the conversion of linguistic data 
to menus, and the interpretation of menu 
choices. This provides the organisation 
necessary to control : 
a) different views of the data by 
different users, and 
330 
b) different processing/compilation of 
data according to its type. 
Corresponding to the four types of task 
given above, we recognise four (idealised) types 
of user: 
1 the end user, 
2 thehigh-level linguist (grammar 
writer), 
3 the low-level \]inguist (grammar 
designer), 
4) the system designer~ 
They have access rights as follows: 
i) The end user will be a monolingual 
(English) technical writer, with expert 
knowledge of the technical field and its 
terminology, but no knowledge of the target 
language. (For development purposes we are 
working with extant texts chose*\] to be typical 
of their kind; but the intention is to provide 
the writer with a tool for the initial 
composition of such texts. The end user will 
thus be able to respond .lore flexibly to the 
system, and make better use of its facilities, 
than we can ourselves do at the moment; although 
we intend it to produce its own documentation.) 
The facilities available to the end user will 
include: 
a) standard monolingual text/document 
processing facilities, 
b) on-line monolingual dictionary 
update, into "supplementary" dictionary files 
for later bilingual completion and full 
incorporation by some lower-level user, 
c) tree-structured document 
organisation, with an associated dictionary 
structure, that handles terminology, including 
proper (e.g. procedure) names, at different 
levels of generality. This is important from 
both monolingual and bilingual perspectives. 
Monolingually, it provides a basis for indexing, 
document retrieval, glossary production, 
spelling checks etc. Bilingually, in terms of 
translation into Japanese, these distinctions 
map well onto orthographic conventions: general 
vocabulary is represented in kanji (ideographic) 
script, Japanese technical vocabulary from 
foreign languages in kana (Japanese syllabic) 
script, and proper nouns such as procedure names 
are simply carried over in Roman (alphabetic) 
script. 
2) The second level of user, the high-level 
linguist, is responsible for writing the rules 
which compute well-formed sets of feature 
specifications (e.g. F-structures) from other 
sets, for source language analysis, transfer, 
and target language synthesis. A variety of ruIe 
types could be provided for these purposes. The 
system as implemented supports the following: 
a) dictionary entries, which specify 
idiosyncratic information of all kinds. These 
define a mapping between lexemes and 
(underdeterminsd) sets of feature 
specifications, for analysis, and between pairs 
of sets of feature specifications, for transfer. 
b) Context-free rules, augmented in 
the manner of LFG or PATR II (Shieber 1984), 
that is, regular expressions over strings of 
sets of feature specifications (i.e. lexical 
entries) that define a mapping to hierarchical 
(dependency) representations. 
e) recursively structured sets of 
features, permitting grouping of features along 
various dimensions, e.g. noun/verb, 
syntactic/semantic, lexical/phrasal, etc. 
d) feature co-occurrence restrictions 
(FCRs) in the manner of GPSG. These can be used 
to define sets of features as mutually 
exclusive, and to specify that certain feature 
values necessarily follow from the presence or 
values of other features. 
e) default .values of lexical feature 
specifications. 
f) rules which determine (surface) 
relational labels ,on the basis of feature 
values. By recognising these as a distinct rule 
type, we make a substantive claim equivalent to 
the formal claim embodied in the typical LFG 
analysis of prepositional phrases - that the 
value of a prepositional feature becomes the 
relation of the (F-structure of the) PP to (that 
of) its head. 
g) subcat rules, which relate 
subcategorisatlon features from the lexicon to 
function-argument (deep to surface) mappings. 
Such features may be specified in a lexical 
entry itself, or filled in by FCR. Function- 
argument mappings are merely pairs of atoms, 
that is, each constituent is mapped 
independently of its sisters. This allows us to 
define effioient control strategies over these 
rules for use in either direction - analysis or 
synthesis. The control strategy, in combination 
with the uniqueness condition on f-structures, 
embodies the function-argument biuniqueness 
principle of Bresnan (1982,p163), and realises 
the coherence condition. Completeness is 
specified independently, or, in the case of 
Japanese, not at all. 
The task of the hlgh-level linguist is to 
define particular instances of rules of these 
types, for the purpose of describing texts in a 
particular language and "the relationship 
between texts in a particular pair of languages. 
3) The low-level lingu:\[st (the grammar 
designer) is responsible for defining the 
formalism, or metatheory, in which the high- 
level linguist will work (cf. Shisber 1985). 
This includes: 
a) defining the nature and number of 
levels of text representation during the 
translation process• This includes deciding 
between phrase structure and dependency 
represe*rtatlons, the partition between the 
lexical and syntactic colaponents in analysis, 
and the partition between analysis and transfer. 
b) defining the rule types to reflect 
these partitions and specify the mappings 
between levels. 
c) definition of the declarative 
semantics of the operators by which the rules of 
various types are applied, and thence the 
definition of the compilation of linguistic 
information. 
4) The system designer is concerned with 
both the highest and lowest levels of the 
system: on the one hand, with the most general 
overall considerations of system architecture, 
including the points and types of interaction; 
on the other, with ensuring that the 
metalinguistic decisions made by tbe grammar 
designer have a tractable computational 
realisation (procedural semantics) and can be 
integrated with interaction. 
For each level of user, there is a 
different, appropriate correspondence of 
privilege and responsibility; each should be 
able to use his/her specialist competence 
(monolingual technical writing, the writing of 
grammars, the design of grammatical theory, and 
the desigh of knowledge-based systems) with the 
full benefit of al I facilities defined at lower 
levels, without c'oncern for the particular 
details of either lower-level implementation or 
higher- level application. 
Further corresponding to these four classes 
of user, the CCL Japanese system incorporates 
interactive routines of variable 'user- 
friendliness' appropriate to the presumed 
competence of a user at that level. 
The linguist, for example, can enter the 
grammar to revise or expand it. The menu of the 
"Grammar Development System" at which the high 
level linguist is rooted provides the option 
Edit a file of linguistic data. 
This takes one to n nested menu which 
provides the alternatives: 
I. lexicon 
2. grammar 
3. feature system 
Selecting "2" takes one to a further menu 
controlling the editing of the augmented phrase 
structure rules, from which one can choose the 
appropriate rule, e.g. 
i. sentence 
2. nounphrase 
3. verb phrase 
M\[ remove nonterminal category 
N. add new nonterminal category 
Control ling access to linguistic 
information by means of menu ensures that the 
updated files are appropriately recompiled into 
the form used by the program. For instance, when 
the grammar writer updates the definition of 
feature sets and/or FCI~s, a compilation process 
is initiated. This expands the tree structure 
into an extensional definition of the procedure 
which adds a feature specification to an f- 
structure. This realises f-structure (graph) 
unification as Prolog (term) unification, 
greatly enhancing the efficiency of parsing. 
An example of variable interaction 
strategies :\[or different types of user is 
provided by the dictionary creation and update 
procedures. The dictionary can be modified 
either en bloc for systematic large-scale 
creation or expansion, typically by the high- 
level linguist; or on-line, during analysis, by 
an end-user. 
The linguist will enter dictionary creation 
by taking first the top level menu option "edit 
a file of linguistic data", then the option 
"lexicon". The end use\]::, when s/he enters a word 
for which there is no existing dictionary entry, 
is offered the menu options "proper noun", 
"misspelling", "enter dictionary creation". 
The dictionary creation process is driven 
by the tree-structured menu system, rooted in 
the choice of grammatical category" and here 
again different procedures are available for 
different predicted levels of use. It is 
presumed that closed class words such as 
determiners, quantifiers, and conjunctions will 
only be added by the linguist; therefore, when 
such classes are selected, tile user sees lexical 
entries exactly as interpreted during 
translation. 
For open class words, on the other hand, 
where update by the end-user is the norm, 
interactive routines are provided. In these 
cases the user never sees the program form. 
Questions are asked enabling the system to 
determine the appropriate inflectional paradigm: 
syntactic category, mass (i.e. without a plural 
form) or count, etc. Plausible surface forms are 
then generated by a morphological component, and 
presented to the user for confirmation or 
correction. The same component is used during 
morphological analysis. Thus if the user 
confirms the machine-generated form, the machine 
will be able to analyse that form when it 
appears in a text, and need not store it. 
331 
The syntactic and semantic feature 
specifications for new dictionary entries are 
also built up interactively. Where reasonable 
defaults can be established, these are presented 
to the user for confirmation or override. Verbs, 
for example, are assumed to be transitive unless 
the user exercises the option to specify some 
other valency pattern; nouns are assumed to be 
countable. Where a value is less predictable, 
the user is simply asked to provide it: does a 
given noun denote a physical object, a software 
object, or an abstraction? Verbs are described 
within a modified Vendler/Dowty-type 
classification (Vendler 1967, Dowry 1979, 
Steedman &Moens 1986); the user is asked to 
specify the appropriate value from a set 
including state, activity, achievement, and 
accomplishment. 
The menu interpreter creates and stores 
from this input a dictionary entry in a neutral 
format. Subsequently, this is compiled to a 
program form entry. The new entries thus created 
are not added immediately to the master files, 
but are held in supplementary files, where they 
are available to the system, but also clearly 
isolated for the high-level linguist, who will 
eventually add translation equivalents (of which 
the end-user is presumed to be ignorant) and 
incorporate the completed entries into the 
master dictionary(s). 
The creation of an intermediate neutral- 
form dictionary offers a facility for global 
revision of the program form of the complete 
dictionaries. The neutral form and program form 
are related by FCRs which embody generalisations 
about the syntactic behaviour of various Iexical 
features. For instance, the count/mass feature 
on noun entries is related to two features in 
the program form specifying the values for 
number agreement and eoocurrence with an 
article. The low-level linguist need only change 
such facts and recompile the relevant neutral 
form files to generate a new program-form 
dictionary. 
Currently, the dictionary creation menu 
system must be written by hand. We are 
experimenting with the possibility of 
constructing it automatically from the feature 
system. 
4o Interactive disambiguation 
The two principal considerations relevant 
to interactive disambiguation are at what point 
it should take place, and what form it should 
take. We will discuss these in order° 
i) Where should disambiguation take place? 
One answer to the question of when to 
interactwith a user is : st different points 
according to the type of ambiguity. We believe 
that this is not the correct answer, but that 
all ambiguity resolution should be deferred to 
transfer. A distinction between types of 
ambiguity according to their point of origin 
does not help in their resolution. Nor is it 
possible to draw a sharp dividing line between 
'spurious' and 'real' ambiguities. Rather, we 
derive a characterisation of ambiguity types 
from the types of knowledge needed to resolve 
them. 
Ambiguities resolvable by syntactic 
knowledge, such as the ambiguities in major 
syntactic category so common in English, seem to 
present little problem. MT systems whose output 
is intended for post-editlng often include a 
'homograph resolution' phase devoted to this 
type of ambiguity resolution. Though largely 
successful, such an approach is obviated by the 
332 
use of the simplest phrase structure grammars. 
Conversely, explicit homograph resolution seems 
unavoidable when the system must not, under any 
circumstances, reject input as ill-formed and 
untranslatable. (fn 5) 
Ambiguities resolvable by consideration of 
the sub-categorisation/valency/case patterns of 
lexical items include both lexical and 
attachment ambiguities, but not all cases of 
either. For instance: 
"... provides the interface to the system" 
appears to require domain specific knowledge; 
and 
"...is achieved by calling theprocedure 
X" 
requires fairly sophisticated knowledge 
concerning the relative likelihood of achieving 
s state by giving an entity a particular name or 
giving it control. 
The question of how an ambiguity is 
resolved is thus almost independent of how it 
arises. Even word-class ambiguities occasionally 
persist through a syntactic analysis and require 
knowledge of the discourse for resolution, e.g. 
"loading instructions will start 
processing" 
A view of organising resolution so that 
each stage of processing resolves the 
ambiguities introduced by the previous stage is 
thus naive. 
In terms of interaction, questioning the 
user too early in the translation chain will be 
unacceptable. The user must appear to the 
disambiguator as just another knowledge source, 
the last to be exploited. 
If ambiguities are to remain unresolved 
through several stages of processing, compact 
representations of multiple readings of texts 
seem essential. The chart (Kay, 1973, Martin et 
al., 1981), and similar devices such as Tomita's 
(1985) 'shared packed forest' are important 
contributions to the solution of this problem. 
The approach to ambiguity typical in 
linguistic theory is to allow the grammar to 
induce it, and to treat the question of its 
compact representation as a matter for parsing, 
irrelevant to declarative description. We are 
investigating the alternative notion that 
linguistic description itself should explicitly 
MndeKdeterm!ne representation. An approach to 
syntactic underdetermination is that of Marcus 
(1985). We have not yet examined its 
applicability to the current task. The 9R~\[~ 
semantics of Aronoff (1980, see also Miller 
(197--87 ~-- Wood (1985)) is a theory of 
underdetermination of lexical entries. Such 
lexical entries become more fully determined in 
context. One might say that they become 
ambiguated and resolved simultaneously. (\]in 
fact, depending on the use which is %o be made 
of the results of analysis, they may never 
become determined.) This approach is applicable 
even to ambiguities in major syntactic category. 
Then parsing can be considered as ambiguating 
them to the extent licensed by the phrase 
structure rules and textual context. 
Such ideas are particularly interesting in 
the context of our system. The GPSG-Iike feature 
system is a means for describing the 
redundancies in the lexicon; the LFG-like notion 
of multi-level linguistic description (see 
l<aplan 1985) offers the possibility of utilising 
such descriptions to 'expand' the lexicon in 
several stages. In our system, ambiguities in 
subcategorisation behaviour (including that 
between past and passive participles) do not 
exist during surface syntactic parsing. We think 
of such an item as being a single morph- 
syntactic entity, but a pair of 'semantic' ones. 
Thi's is important in translation, since the 
indeterminacles of the source language may or 
may not become ambiguities in translation. For 
example, the state-event ambivalence of passive 
participle,~\] in many languages must be recognised 
and resolved in transfer to Japanese (though not 
in going from French to English, for example). 
For a linguistic description of the source 
language not to include this ambivalence would 
render it incomplete; for analysis to treat it, 
and many similar cases, as genuine ambiguities 
would be problematic COlnputationally, 
We believe that tile invocation or 
application of monolingual (source) knowledge by 
a billngua\] component is an attractive approach 
to this problem. A good human trans\].ator infers 
from the source text what is needed for 
translation, and a machine system should exhibit 
this same, goal-driven, behaviour. In the same 
way that a human translator, in the event of 
being unable to resolve an ambiguity whose 
resolution is crucial, for translation, migIlt 
contact the original author, so the machine's 
knowledge must be organised to allow the same 
fail-safe interaction. 
2) What form should interaction take? 
We can recognise a variety of forms that 
interaction could take, on a scale of increasing 
independence from linguistic analyses, as 
fol lows : 
a) Presentation of alternatives as 
their linguistic representations (e.g. trees). 
Though unsuitable for a linguistlcally-naive 
end-user, this type of interaction is important 
during system development. While the high-level 
linguist is experimenting with different ways in 
whicIl the s~stem's knowledge can be deployed for 
sutomatic ambiguity resolution, s/he must be 
able to .inspect a detailed representation of 
those cases where tile current strategy and/or 
knowledge are inadequate. In addition, this form 
of presentation is a prerequisite 'to defining 
more user-friendly forms° 
b) String template presentations. At 
its simplest, for, say, attachment ambiguities, 
this involves presenting tile ambiguously 
attached string with a slot filled by the 
different heads. This was the appnoach adopted 
in Kay's (1973) MIND system, eog° 
"They filled the tank with gas" 
This means: 
1. Filled with gas 
2. Tank with gas 
A more sophisticated template structure is 
used by Tomita (1985). This involves the use of 
what Hudson (1985) has termed 'natural 
metalanguago', e.g. 
"I saw a man in 'the park" 
i° The action \[saw\] takes place \[in the 
park\] 
2. \[a man\] is \[in the park\] 
We believe that this is an important 
direction to explore, though it may lead to 
obvious absurdities, depending on the 
sophistication with which templates are defined 
and chosen, e.g. 
"This module provides tile interface to tile 
system" 
io The action \[provides\] takes place \[to 
tile system\] 
2. \[Tile interface\] is \[to the system\] 
C) Disambiguatlng paraphrase. This car* be 
illustrated for the same sentence as above: 
I. The interface to the system is 
provided by this module. 
2. This module provides the system 
with an interface. 
The success of this approach depends 
crucially on finding the set of relational rules 
(in the example, passive and benefactive) that 
wil\] generate disambiguating paraphrases. We 
hope that our approach 'to subcategorisation, 
with independent function-argument mappings for 
each constituent, will make this possible, but 
it is too early to say. 
5. Implications and conclusions 
Our practical experience of implementing 
the CCL Japanese t:ranslation system, some 
aspects of which we have described above, 
suggests a number of points of more general 
interest and significance for machine 
translation and indeed for any computational 
treatment of natural language. We will end our 
paper with an indication of a few of these wider 
implications and conclusions. 
It becomes increasingly clear with time and 
experience that machine translation and 
linguistic theory can be of great mutual 
benefit° Early attempts at MT, which made little 
or no use of any sort of linguistic theory, can 
now be seen as, in principle, dead ends, despite 
the commex?cial success of some (cf. Hutchins 
1982). We can now draw on a valuable body of 
research, particularly on syntax and semantics, 
which allows us to handle language with a depth 
and sophistication, and thus a chance of 
adequate translation, far greater than was 
possible for tile early pioneerSo 
Conversely, as well as putting a practical 
task on a sound footing, tile grounding of MT in 
linguistic theory provides an ideal test-bed for 
evaluation and development of such a theory. 
Even monolingual computational imp\].ementation 
imposes valuable demands of explicitness and 
accuracy, and can have a significant influence 
on the organization, content, and notation of a 
theory (cf. the evolution of GPSG, as described 
in Gazdar et al. 1985); translation requires a 
comprehensive and tractable account of (at 
least) two languages and of the mappings between 
theta. It is also easy to evaluate one's results 
for beth thoroughness of coverage and quality of 
output° In other words, the practice of machine 
l:ranslation should be seen as a resource for 
research in linguistic theory° 
Most importantly, we would like to re-. 
affirm our espousal of interactive system 
design. It should be uncontentlous that the 
principal problem in the design of any 
knowledge-based system is the transfer of 
expertise from human to machine° 
Thus we have designed our system with three 
particular aims: 
i) to provide a means of expressing easily 
and natu~-a\] ly the forms of knowledge we 
currently understand; 
2) to recognise and cope with tile limits of 
currently formallsed knowledge, by interaction; 
3) to provide an environment within which we 
can experiment with redefining those limits. 
Footnotes 
* The work on which this paper is based is 
supported by International Computers Limited 
(ICL) and by the UK Science and Engineering 
Research Council under the Alvey program for 
£esearch in Intelligent Knowledge Based Systems. 
The first-named author is the project director; 
the two first-named authors are the principal 
paper-writers, and as such can be held 
£esponsible for any errors, unclarities, or 
misrepresentations which may have escaped the 
333 
careful and valuable scrutiny of the others. We 
are grateful for the support and comments of our 
colleagues in COL, especially to Rod Johnson. 
i. Remark during discussion of King (1984). This 
viewpoint, of course, begs the question of the 
possibility of human translation, as Pierre 
Isabella pointed out in a formal language 
closely resembling English. 
2. We have glossed over the matter of transfer 
ambiguities. We assume that these can be 
expressed in source language terms for 
interactive disambiguation. In this respect, the 
machine is in a preferable position to that of a 
human translator, who must in most cases 
determine the resolution of such ambiguities 
from the text alone. Were our assumption 
incorrect, it would throw serious doubt on the 
possibility of human translation. 
3. We might even suggest that there is something 
positively perverse about the assumption that a 
machine which can in isolation convert raw to 
half-baked (post-edlted) or pre-cooked to 
finished text (pre-edited) is in some way 
superior to one which can carry out the entire 
process asked of it, recognizing the points at 
which it needs help and taking appropriate 
action. 
4. It should be pointed out here, however, that 
we do not see programming as inherently 
radically distinct from other types of formal 
description. This is particularly true for a 
high-level "programming language" like Prolog. 
5. This is a good example of how 'have a go at 
anything' systems may be hindered from 
incorporating linguistically motivated 
techniques. 

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