An Evaluation of METAL: 
the LRC Machine Translation System 
Jonathan Slocum 
Microelectronics and Co~uter Technology Corp. 
Winfield S. Bennett 
LesleyWhlffin 
EddaNorcross 
Siemens Co~mmmllcation Syst~-~q, Inc. 
AbstraCt 
The Linguistics Research Center (LRC) 
at the University of Texas at Austin is 
currently developing METAL, a 
fully-automatlc high quality machine 
translation system, for market introduction 
in 1985. This paper will describe the 
current stat~s of METAL, e~phasizing the 
results of the most recent post-edltors' 
evaluation, and will briefly indicate some 
future directions for the system. A 6-page 
German original tex~ and a raw (unedIt~3d, 
but automatically reformatted) METAL 
translation of that text into English are 
included as appendices. 
Introductlon 
The Linguistics Research Center (LRC) 
at the University of Texas at Austin is 
currently developing METAL, a 
fully-automatic high quality machine 
translation system, for market introduction 
in 1985. This paper wlll describe the 
curren~ statn/s o f METAL, including the 
results of the most recent evaluation, and 
will briefly indicate some fur%Ire directions 
for the system. Exhibits A and B (attached) 
are, respectively, a German original text 
and a raw (unedlted, but automatically 
reformatted) METAL translation of that 
into English. 
History and Status 
Machine translation research at the 
University of Texas began in 1956: the LRC 
was founded in 1961. Eor much o f the 
hi~cory of. this project, funding was 
provided by the U.S. Air Force's Rome Air 
Development Center and other U.S. gove~,m~nt 
agencies. In 1979, Siemens AG began funding 
the development phase of the METAL machine 
translation sy~cez, at which point 
i~lementatlon of the current system was 
initiated. A prototype has recently been 
delivered to the sponsor for market testing. 
The current system is a unidirectional 
German-English system, although work to add 
ot/%er target languages, as well as creating 
an English-German MT system, is now 
underway. The present staff for the METAL 
project consists of seven full-ti~e and five 
half-tlme personnel. 
Application Environment 
Software has been developed to handle 
the formatting problems associated with 
technical manuals. This software, written 
in SNOBOL, automatically marks and prepares 
texts for the METAL translation system 
\[Slocum and Bennett, 1982; Slocum eu al. 0 
1984\]. The only human intervention prior to 
translation is checking and correcting the 
results o f t_he automatic formatting 
routines. Postediting is expected for the 
output t~. The system does not expect 
(or provide for) human intervention during 
the actual translation phase. 
Pre-processing and post-edlting are 
presantly done on a DEC-2060; the actual 
translation, on a Symbolics Lisp machine. 
The "proch/ction ~" design envisions a 
Lisp Machine as the translation unit 
co, necked to 4-6 ~ranslator workstations, 
from which t,he prepared ~ will be sent 
to the translation unit and on which the 
output texts will be postedlted. 
METAL uses a transfer approach for 
translation. The entire process consists of 
four phases : analysis, integration, 
transfer, and generation (synthesis). The 
integration phase works with whole parse 
tree st-ruc~ures, following analysis and 
preceding transfer. Until recently, 
transfer and generation were essentially a 
single phase, but work is currently underway 
to separate this single phase into ~wo, with 
a much more powerful generation phase. 
LlngulsKic Component 
The curren~ METAL lexicon consists of 
over 20,000 German and English monolingual 
entTies, cor~i~clng of morphological, 
syntactic, and s~ntlc features and values, 
and an appropriately large number of 
transfer entries. The featnlres and values 
in monollngual lexlcal entries supply 
necessary information for the analysis 
and/or synthesis of these it~m~ during the 
mach/x~ translation process. Most entries 
are reasonably s4~le, but entries for verb 
st~m~ are significantly more complex. 
Inflected adjectives, nouns, and verbs are 
parsed by word-level gr~m-~r rules, with the 
stems and e~dlngs assigned to appropriate 
lexical categories. 
62 
Each t-Fans fer lexical entry is a 
structure equating the source language 
canonical form with an appropriate target 
language canonical form. Certain 
significant information (i. e., lexical 
category, subject area, and preference) is 
coded in the entry to guide the system in 
selecting the appropriate translation. 
Furthermore, tests and operations (including 
transformations) may be included within 
transfer en~rles. 
The gr~r for METAL consists of over 
600 augmented phrase s~ructure rules, each 
of which is used in both analysis and 
trans fer/generatlon. METAL' s gr~-~-r rules 
are used in the parsing of all levels of 
structure from the word level to the 
sentence level, including phrases and 
clauses. A METAL grammar rule consists of 
five analysis sections, plus an additional 
section for each target language: a top llne 
describing the phrase structure (with an 
optional enumeration of each constituent); a 
series of restrictions, which test the 
appropriateness of individual constituents 
on the right-hand side of the rule; TESTs, 
which enforce agreement among the right-hand 
constituents; a CONSTR section, which 
constructs the analysis of the phrase; an 
INTEC~ section, which is executed (once a 
complete analysis of the sentence is 
achieved) in order to, e.g., resolve 
anaphoric references; and one or more 
target-language-dependent Transfer sections, 
which control lexlcal and structn/ral 
translation into the target language. 
Homograph resolution and dis~mhiguatlon 
are handled uniformly (i.e., without special 
passes) , in various ways : by orthographic 
tests, such as t_he test to ensure that a 
word that looks llke a German noun is not 
ali lower case; by positional constraints, 
which disallow co-occurrence of -mhlguous 
strings in the same clause location; and, 
most especial ly, by the case frame 
mechanism. 
The case (valency) frame mechanism is 
vital in METAL's analysis of German source 
language sentences. This mechanism is 
invoked in clause-level rules and uses 
features on the verb stem to define the 
functions of the various central ar~Jments 
to the predicate. In additlon, the case 
frame mechanism is used to test for such 
t/llngs as subject-verb agreement. 
The METAL gramm=ar makes extensive use 
of transformations to modify structure or 
perform certain tests. Transformations may 
be used in the TEST, CONSTR, INTEr, and 
Transfer phases of the rules, 
transformations may also be used in transfer 
lexlcal entries. A transformation may be 
written as part of a rule or called by name. 
Computational Component 
The lexicon for METAL is maintained via 
a DBMS written in LISP. Input of lexical 
entries is facilitated by an INTERCODER, a 
menu-drlven system whlch asks the user for 
information in English and encodes the 
answers into the internal form used by the 
system. An integral part of the INTERCODER 
is the "lexical default" program which 
accepts" minlm~l information about the 
• particular entry (root form and lexical 
category) and encodes most of the remaining 
necessary features and values. Entries may 
also be created using any text editor, 
without the aid of the INTERC0DER or lexical 
defaulter. 
Interfacing with the lexical database 
is done by means of a number of menu-driven 
functions which permlt the user to access, 
edit, copy, and/or delete entries 
individually, in groups (using specific 
features), or entirely. In order to assure 
a high degree of lexicon integrity the METAL 
system includes validation progr~m~ which 
identify errors in format and/or syntax. 
The validatlon process is automatically used 
to check lexlcal it~m~ which have been 
edited, to ensure that no errors have been 
introduced during editing. 
The grammar is also in a database and 
may be-accessed and/or edited in much the 
same way as the lexicon. System software 
and named trans formations are stored in 
individual source files. 
METAL's parser is a "some-paths, 
parallel, bottom-upparser" \[Slocum et al., 
1984\] . It may be considered to be 
"some-paths" because the grammar rules are 
grouped into numerically indexed "levels" 
and the parser always applies rules at a 
lower level before applying rules at a 
higher level. Once the parser has 
successfully built one or more Ss at a given 
level, it will halt; until it discovers one 
or more S readings, the parser will continue 
to apply rules in each successive level. 
Extensive experimentation with the system 
has found that the present parser 
configuration is the most efficient one for 
METAL \[Slocum et al., 1984\]. 
Post-Edltors' Evaluation 
In June, 1984, the METAL system was 
used to translate 82.6 pages of text into 
English; the material varied from a sales 
prospectus (for a speech recognition system) 
through various general hardware and 
software syste~ descriptions to highly 
technical documentation. The output was 
then edited by ~wo Siemens revisors (one a 
m~mher of the METAL project, one not) . This 
section describes the revisors ' obJective 
performance and subjective reactions 
(including comparison with earlier versions 
of METAL) during this experience. 
63 
Post-Editor ist pass 2nd pass 3rd pass Min/Pg Pgs/Hr. Pgs/Day 
#i 9hr 10mln 3hr 40min 2br 10min 10.9 5.5 44.1 
#2 13hr 40min 3hr 55min 12.8 4.7 37.6 
(N.B. The number of pages of text was computed automatically on the basis of 
"Siemens standard pages": 26 lines x 55 characters = 1430 characters/pg.) 
The table above summarizes the editors' 
revision times. They employed rather 
dlfferent editing techniques (editor #i 
working in three passes, #2 in Just two), 
but their times are relatively close. 
Comments by Editor #i : 
~he 3rd Pass\] tends to be concerned 
with sTylistic i~provements, formatting 
changes and t~2plng errors. The last part of 
this stage involves running the spelling 
checker on the file to eliminate remaining 
typing errors. 
The ~mpression of post-editing was that 
there have been many improvements over 
previous test runs. This was evidenced by 
the fact that on t/lls post-edlting run less 
than 57 o of sentences were re-translated from 
scratch. The major task in post-editing is 
now changing word order, changing verb 
agreement and re-translatlng the more 
idiomatic usages. Considerable l~rovemen~s 
in format made post-edlting easier, although 
there is still room for further enhancement. 
and 3rd phases of post-edltlng continued as 
normal. The previous problems wir/~ 
post-edlting a highly formatted text meant 
that whenever a textual change was made in 
the the te2Cc then the format had to be 
re-modi fled. The method o f post-editing 
u~ed in T-hls test proved to be considerably 
faster and easier to handle .... ~he 
results\] demonstrate that the time saving 
lles in the initial post-edlt phase which is 
when the most changes are made and which is 
most time intensive with regard to 
re- formatting text. 
Comments by Editor #2: 
As compared to the last run in February 
1984, the June 84 output showed considerable 
i mprovement. A greater number o f sentences 
was useable and m~ny required a change in 
word order only. Placement o f the 
determiners has been improved. \[Certain\] 
points should be considered to Improve 
future translations. 
Future Directions 
One of the greatest changes affecting 
post-edlting was the fact that since the 
initial output \[co~pared to earlier 
versions\] of METAL was deemed to have 
i "~r oved, the dl f fermi stages 0 f 
post-edlting were more clearly defined. 
That is to say, it was easier to produce an 
adequate translation during the first run 
through the tex~ ~- using the reformatted 
output on the screen and a hardcopy of the 
source text for reference -- than in 
previous tests. In the second run through a 
tex~c -- using a hardcopy of the METAL output 
upon which preliminary post-edlting has been 
performed -- it was easier to concentrate on 
polishing the translatlon. In the third and 
final post-edlt stage, one was able to make 
a final check for stylistic weaknesses, 
spelling mistakes and typing errors. This 
was the same method as used in previous 
tests but one was better able to distinguish 
beUween the stages (initial teckulical and 
stylistic post-edlting; polishing output; 
final stylistic check) and the entire 
process was less tiring than in the past. 
Although the overall format of the 
output has i~3roved...there are still \[some\] 
problem areas \[with the automatic 
reformatting program\] . 
As an experlment, the unformatted, 
interlinear \[German-English\] version was 
used for the initial post-edlting phase. 
The text was then reformatted...and the 2nd 
The METAL German-Engllsh configuration was 
released for market testing in January 1985. 
Current plans are to continue Imp~ rovement on 
the present system and to branch off into 
other target languages, specifically Spanish 
and Chinese. We estimate that a 
German-Spanish system should be ready for 
testing sometime in 1986, with a 
German-Chlnese system sometime thereafter. 
We have also begun working on an 
Engllsh-German system. If the planned work 
is success ful, work wll I begin on 
English-Spanish and English-Chinese MT 
syst~m~. 
References 
Slocum, J., and W. S. Bennett, "The LRC 
Machine Translation System: An Application 
of S~ate-of-the-Art Text and Natural 
Language Processing Techniques to the 
Translation of Technical Manuals, " Working 
Paper LRC-82-1, Linguistics Research Center, 
University of Texas, July 1982. 
Slocum, J., et al., "METAL: The LRC Machine 
Translation System, " presented at the ISSCO 
Tutorial on Machine Translation, Lugano, 
Switzerland, 2-6 April 1984. Also available 
as Working Paper LRC-84-2, Linguistics 
Research Center, UniversiTy of Texas, April 
1984. 
64 
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69 
