EasyEnglish: A Tool for Improving Document Quality 
Arendse Bernth 
IBM Research 
P.O. Box 704 
Yorktown Heights, NY 10598, USA 
arendse@wat son. ibm. cora 
Abstract 
We describe the authoring tool, EasyEng- 
lish, which is part of IBM's internal SGML 
editing environment, Information Develop- 
ment Workbench. EasyEnglish helps writ- 
ers produce clearer and simpler English by 
pointing out ambiguity and complexity as 
well as performing some standard grammar 
checking. Where appropriate, EasyEnglish 
makes suggestions for rephrasings that may 
be substituted directly into the text by us- 
ing the editor interface. 
EasyEnglish is based on a full parse by 
English Slot Grammar; this makes it possi- 
ble to produce a higher degree of accuracy 
in error messages as well as handle a large 
variety of texts. 
1 Introduction 
Like most other big corporations today, IBM is in- 
terested in cost-effective, yet high-quality informa- 
tion dissemination. Every year, many pages of on- 
line and printed documentation are produced. No 
matter what part of the world the documentation 
is written in, it is normally first written in English, 
and then translated into all the other supported lan- 
guages. IBM has developed a number of tools to help 
writers cope with this task of information develop- 
ment. 
In this paper, we describe EasyEnglish, a tool 
that helps writers produce clearer and simpler Eng- 
lish by pointing out ambiguity and complexity. 
Where appropriate, EasyEnglish makes suggestions 
for rephrasings. The EasyEnglish system can be 
viewed as a "grammar checker++", in that standard 
grammar checking facilities such as spell-checking, 
word count (sentence length), and detection of pas- 
sive constructions are available in addition to the 
checks for ambiguity. Furthermore, facilities for 
user-defined controlled vocabulary are available. To- 
tally, there are currently about forty checks. 
EasyEnglish is part of IBM's internal Information 
Development Workbench (IDWB), an SGML-based 
document creation and document management sys- 
tem. ArborText's Adept editor is used with IDWB 1 
EasyEnglish summarizes the problems encountered 
in a given document by giving an overall rating, the 
Clarity Indez (CI). The CI has to be in a certain 
range before the document can be accepted for pub- 
lication. 
EasyEnglish combines features from both stan- 
dard grammar checkers and Controlled Language 
(CL) compliance checkers with checks for structural 
ambiguity in a way that we believe is general enough 
to be useful for any writer.., not just tec~hnical writ- 
ers. It has been claimed that the restrictions found 
in CLs mostly reflect the inadequacies of the MT 
systems used in conjunction with CLs (Cl~mencin 
1996; van der Eijk et al. 1996; Hayes et al. 1996). It 
is certainly the case that preprocessing a document 
with the same parser that is used for source analysis 
improves the MT results. EasyEnglish uses the same 
parser as LMT (McCord 1989a, 1989b). This offers 
an obvious advantage for MT results. Other MT sys- 
tems, including the KANT system (Mitamura and 
Nyberg 1995; Nyberg and Mitamura 1996), see the 
advantage of this. However, we claim that a docu- 
ment that has been "EasyEnglished" is also easier 
to understand for native speakers as well as non- 
native speakers of English. A similar point has been 
made for Caterpillar Technical English (Hayes ct al. 
1996). We think, however, that our approach is more 
general because our use of a broad-coverage, geaeral 
English grammar 2 allows us to go beyond the con- 
cept of CL to look for more general types of ambi- 
guities. 
I EasyEnglish also works with the XEDIT editor on 
VM and the EPM editor on OS/2. An earlier version 
of EasyEnglish was written in Prolog; however, the cur- 
rent version is written in pure ANSI C, and hence the 
question of platform is mainly a matter of supplying an 
appropriate editor interface. 
~English Slot Grammar (McCord 1980, 1990, 1993) 
159 
2 Controlled Language Checker or 
Grammar Checker? 
The emphasis of a CL compliance checker is on 
ensuring that the input text (document) conforms 
to the restrictions imposed by the definition of the 
CL, whereas the emphasis of a standard grammar 
checker is on ensuring that the text is not ungram- 
matical. Controlled Languages have been invented 
to solve the problems associated with readability and 
translatability, with slight regard to ensuring gram- 
maticality. In fact, the point has been made that it 
is up to the writer to ensure that the text is gram- 
matical (Hayes et al. 1996). Or, in the words of Goy- 
vaerts (1996): " ... it is still possible to write con- 
trolled non-English." A similar point has been made 
for GIFAS Rationalized French (Lux and Dauphin 1996). 
However, the more grammatical the text is, the 
easier it is to read and translate, so it seems that 
this concept of a CL checker is too narrow. On the 
other hand, in many applications it may not be nec- 
essary for writers to restrict themselves to a very 
limited subset of English in order to write easily un- 
derstandable and translatable documents. In this 
sense the concept of a CL checker may be too broad. 
We have developed a system that we believe 
strikes a useful balance between CL checking and 
standard grammar checking. It consists in restrict- 
ing the CL checking to the detection of structural 
(syntactic) ambiguity, complexity, and violations of 
vocabulary constraints. This view is in line with the 
description of Dokamentationsdea~sch in (Schachtl 
1996). Dokumentationsdeutsch is not defined by a 
list of allowed constructions, but rather by a list of 
forbidden constructions, allowing most of standard 
German syntax. In the same way, EasyEnglish al- 
lows most of standard English syntax. Also (Lux 
and Dauphin 1996) point out the importance of the 
linguistic coverage being as broad as possible. At 
the same time, we perform some of the checks that 
a standard grammar checker would perform. 3 
The CL checks of EasyEnglish do work better 
when the text is not too ill-formed grammatically, 
since ill-formedness reduces the chances of the parser 
making good sense of the input. Most grammar 
checkers seem to have a problem with precision, 4 
and this evidently stems from the inability of the 
system to make sense of the input. This is caused 
not only by too narrow coverage of the parser, but 
also by the ill-formed input that a standard gram- 
3We have conflated the notions of grammar errors and 
style tveaknesses. For a good discussion of the differences, 
see (Ravin 1993). 
4We define precision to be the number of relevant er- 
ror reports divided by the total number of error reports. 
In other words, it is a measure of how many irrelevant 
error reports the user will be bothered with. The higher 
the precision, the better. 
mar checker tries to deal with; it is harder to parse 
non-standard constructions correctly. It has been 
pointed out time and again (Richardson and Braden- 
Harder 1993; Wojcik and Holmback 1996; Cl6mencin 
1996) that user acceptance depends on suitably high 
precision. Of course, the user also wants the checker 
to find the problems that need to be corrected, 5 
but this seems to take much lower precedence (Wo- 
jcik and Holmback 1996; C16mencin 1996). 
We have made a small, preliminary study compar- 
ing the quality of EasyEnglish with that of Gram- 
matik and the grammar checker in AmiPro. For 
the study, we used a variety of text types, including 
technical documents, a manager's speech, and an on- 
line job advertisement written by a non-native Eng- 
lish speaker. The (Precision, Recall) figures were: 
EasyEnglish (0.81, 0.87), Grammatik (0.51, 0.86), 
AmiPro (0.50, 0.69). There is overlap in the kinds 
of checks made by these three systems, but we at- 
tempted to evaluate each system on its own terms, 
i.e. on the basis of the collection of checks that it. 
tries to do. That is, these figures show how we\[i 
each system does what it tries to do, rather than 
how useful what it tries to do is. (The recall fig- 
ures for Grammatik and AmiPro may be artificially 
high, since we may not have been able to identify all 
the problems that these grammar checkers intend to 
address.) 
Of course, high precision and recall alone are not 
enough to ensure the usefulness of an authoring tool 
such as EasyEnglish. We agree with (Adriaens and 
Macken 1995; Wojcik and Holmbach 1996) that it is 
also necessary to evaluate how well writers can use 
the system to arrive at a satisfactory document. It 
is our claim that the types of checks EasyEnglish 
performs are vastly more relevant for ensuring high 
document quality than a majority of the checks in 
the above-mentioned grammar checkers (e.g. most 
of the lexically-based checks). It has been claimed 
that standard grammar checkers typically check for 
stylistic issues that are relevant for writers of fic- 
tion (Goyvaerts 1996). But, as Goyvaerts (1996) 
puts it: "Industry does not need Shakespeare or 
Chaucer, industry needs clear, concise communca- 
rive writing -- in one word Controlled Language." 
Of course, standard grammar checkers do also try 
to supply checks that are relevant for non-fictional 
genres. However, some of the standard stylistic rec- 
ommendations are not entirely relevant for technical 
documents at least. It is, for example, rather com- 
mon for a standard grammar checker to discourage 
repetition. For a company that has to pay for doc- 
ument translation on a per word basis, every repeti- 
5We will use the term recall to mean the number of 
relevant problems found divided by the number uf all 
problems occurring in the text. Recall thus describes 
how good the checker is at identifying the problems. The 
higher the recall, the better. 
1 60 
tion means a savings. 
3 Resolution of Ambiguity 
EasyEnglish identifies a number of structurally am- 
biguous constructions and supplies suggestions for 
unambiguous rephrasings. It is then up to the user 
to decide which interpretation is intended. Some 
systems support automatic substitution; since we 
deal with truly ambiguous constructions, we have to 
involve the user in making the choice. The EasyEng- 
lish editor interface, however, does allow the user 
to select an offered rephrasing by mouse-clicking 
and have the selection substituted automatically. 
Other systems, e.g. the Attempto System (Fuchs and 
Schwitter 1996), present the user with a rephrasing 
that illustrates which interpretation the system ar- 
rived at. If that interpretation is not the desired one, 
it is up to the user to construct a rephrasing that will 
result in the desired interpretation. We think it is 
more user-friendly to show the user exactly how the 
construction may be ambiguous and let her make 
her own choice. 
In order for the disambiguation rules to work 
properly, it is crucial to have a deep analysis of the 
text. This deep analysis is provided by English Slot 
Grammar (ESG) (McCord 1980, 1990, 1993) in the 
form of parse trees expressed as a network struc- 
ture. The disambiguation rules explore the network 
to spot ambiguous and potentially ambiguous con- 
structions. 
ESG often provides more than one parse, ranked 
according to a specific numerical ranking system 
(McCord 1990, 1993). But, unlike some other sys- 
tems, e.g. the Boeing Simplified English Checker 
(Wojcik and Holmback 1996), which look at a whole 
forest of trees, it is only necessary for EasyEnglish 
to look at the highest-ranked parse. ESG parsing 
heuristics often arrive at correct attachments in the 
highest-ranked parse. But even when the attach- 
ment is off, EasyEnglish can often point out other 
attachment possibilities to the writer. For exam- 
pie, if a present participial clause is attached to the 
object of a verb, there will also be the possibility 
that the participial clause actually should modify 
the subject instead. However, it is not necessary 
for the parse to reflect this, since this can be re- 
flected in the EasyEnglish rule instead. A simplistic 
view of this rule would be: "If a present participial 
clause modifies the object, suggest two rephrasings, 
one that forces the attachment to the subject, and 
one that forces the attachment to the object". 
An example taken from an IBM manual: "Differ- 
ent system users may operate on different objects 
using the same application program." 
This sentence generates the following message: 
Ambiguous attachment of verb phrase: "us- 
ing the same application program". 
Who/what is "using the same applica- 
tion program", "Different system users" or 
"different objects" ? 
If "Different system users", a possible 
rephrasing would be: "by using the same 
application program"; 
If "different objects", a possible rephrasing 
would be: "different objects that use the 
same application program". 
Notice the additional benefit we get from basing 
the suggestion on a parse: the correct subject-verb 
agreement can be inferred for use in the suggestions. 
Coordination is another source of ambiguity, since 
the scope is not always clear. One type of ambiguity 
occurs when a conjoined noun phrase premodifies a 
noun, as in this example from an IBM manual: 
" It is the number defined in the file or result field 
definition. " 
The phrase "file or result field definition" is am- 
biguous in many ways, as is shown by the output 
from EasyEnglish: 
Ambiguity in: "the file or result field defi- 
nition". Possible rephrasings: 
'`the result field definition or the file" or 
"the file definition or the result field defin- 
ition" or 
"the file field definition or the result field 
definition" or 
"the definition of the file or of the result 
field" or 
"the field definition of the file or of the 
result" 
Another type of ambiguity in coordination con- 
cerns combinations of coordinating conjunctions, as 
illustrated by the following example: "The cat and 
the rat or the mat sat." 
Ambiguous coordination; possible rephras- 
lags: "Either the cat and the rat or the 
mat" or 
"The cat and either the rat or the mat" 
The above cases illustrate constructions that are 
definitely ambiguous; however, some common prob- 
lems involve modification that may or may not be 
correct, depending on domain knowledge, which we 
do not attempt to make use of at present. 
For example, the implicit subject in a nonfinite 
clause premodifying the main clause should be the 
same as the subject of the main clause. It is gener- 
ally not possible to tell, on the basis of syntax alone, 
whether the author has adhered to this rule. But it 
is possible to alert the user to the potential problem. 
The following two examples illustrate the problem. 
The first example, taken from an IBM manual, is 
okay, whereas the second example, taken from (Led- 
erer 1989), is not okay. 
161 
= After signing on, the user has access to all ob- 
jects on the system. " 
Potentially urrong modification: =signing 
on". Okay if subject of "signing on" is "the 
user": 
" As a baboon who grew up wild in the jungle, I 
realized that Wiki had special nutritional needs. " 
Potentially wrong modification; okay if "I" 
is "a baboon who grew up mild in the 
jungle". 
An earlier version of EasyEnglish, written in Pro- 
log, included a pronoun resolution module, RAP 
(Lappin and McCord 1990a,b; Lappin and Leass 
1994). This module, originally written for use with 
LMT, was modified slightly to point out ambiguous 
pronominal references. It has not yet been included 
in the C version of EasyEnglish, and we give here 
an example of its use produced by the Prolog ver- 
sion. The example is taken from (Lederer 1989): 
=Guilt, vengeance, and bitterness can be emotion- 
ally destructive to you and your children. You must 
get rid of them." 
This generates the following message: 
Ambiguous pronoun reference: '2hem". 
4 Vocabulary Functions 
EasyEnglish comes with a built-in general English 
dictionary of about 80,000 words. In addition, 
EasyEnglish has a flexible system for using dictio- 
naries as it does its analysis. Users can specify in a 
user profile which dictionaries they want to call up. 
The specification can include any number of term 
dictionaries, any number of abbreviation dictionar- 
ies, any number of non-allowed word dictionaries, 
and any number of controlled vocabulary dictionar- 
ies. There are EasyEnglish commands for compiling 
a user-maintainable format of these different kinds 
of dictionaries into efficiently useable forms, and for 
creating abbreviation dictionaries from terminology 
dictionaries in maintainance form. 
The dictionaries support three different types of 
vocabulary checks. The first vocabulary check looks 
for restricted words, i.e. words that the writer ei- 
ther should never use, or that the writer should only 
use as certain parts-of-speech. The user may spec- 
ify these words in a specific user dictionary along 
with preferred alternatives. In addition, this cate- 
gory includes slang words, a list of which is system- 
supplied. The second type of vocabulary check iden- 
tifies acronyms or abbreviations in the text and 
checks to see that the first occurrence is properly 
spelled out according to the definition supplied in 
the user dictionary for" acronyms. The third check 
gives the user the option to specify a controlled vo- 
cabulary; all words that are not in the controlled- 
vocabulary file or that are improperly used with re- 
spect to part-of-speech will be flagged, should the 
user decide to turn this check on. User dictionaries 
for restricted words, acronyms, and controlled vo- 
cabulary have been built for the IDWB for certain 
domains. 
The vocabulary checks rely on two things: the 
parser and user dictionaries. It is crucial to be able 
to determine the applicable part of speech with ac- 
curacy. Take for example the word "beef". If this 
is used as a verb ("they beef a lot"), it should be 
flagged as slang; on the other hand, if it is used as 
a noun ("he ate beef"), it should not be flagged. A 
full parse helps decide on this. 
User dictionaries may be built with the help of the 
separate terms module, ETerms, which is run inde- 
pendently of EasyEnglish. ETerms identifies candi- 
dates for new terms by looking for words not found in 
any of the dictionaries 6 as well as multinoun terms. 
The output from ETerms is very accurate due to 
the use of full ESG parsing. For each term, the fre- 
quency is stated, and the user has the choice be- 
tween having the terms sorted either in frequency 
order or alphabetical order. The terms file has a 
format that is directly usable as a user dictionary; 
however, to keep terminology consistent and remove 
misspellings, it is necessary that a terminologist ap- 
prove the content before actual use. 
The terms file may also be sent to the IBM trans- 
lation centers at an early stage. This speeds up the 
task of translation considerably, since their terminol- 
ogists can decide on the proper translations before 
the translators actually start the translation process. 
This list is also a good start on an online bilingual 
dictionary for an MT system. 
5 Standard Grammar Checking 
In addition to spotting ambiguity and providing 
terminological support, EasyEnglish also performs 
more traditional grammar checking. It is a deli- 
cate balance to process text that has grammatical 
errors; the parser needs to be able to make reason- 
ably good sense of the text in order for the checking 
component not to overflag problems. The grammat- 
ical checks fall into three different categories, which 
we will treat separately: Syntactic problems, lexical 
problems, and punctuation problems. 
5.1 Syntactic problems 
This category is obviously the category most sensi- 
tive to parsing problems. However, we have found 
that a number of checks can be implemented success- 
fully, including, but not limited to, checks for lack 
of parallelism in coordination and in list elements, 
passives, double negatives, long sentences, incom- 
plete sentences, wrong pronoun case, and long noun 
strings. 
6Since these could also be misspellings, they are also 
flagged by EasyEnglish itself. 
162 
To illustrate the function of these checks, let us 
look at the checks for passives. When a passive 
construction is encountered, an active transforma- 
tion provides the desired suggested rephrasing, pro- 
vided the logical subject is available. If the logical 
subject is not available, the passive is pointed out, 
but no rephrasing is offered. Some standard gram- 
mar checkers insist on supplying an active rephrasing 
even in this case, and they do that by introducing a 
fake subject 'T', "they", or "he". In our view, this 
rarely provides a reasonable iephrasing. 
The following sentence from an IBM manual illus- 
trates both cases: "The format is defined in the file 
which was not included by the header file." 
This sentence generates two messages for the pas- 
sives, one without a rephrasing, and one with a 
rephrasing: 
Passive construction: ~is defined in the file 
which was not included by the header file". 
Passive construction: "was not included 
by the header file". Possible rephrasing: 
"which the header file did not include" 
The parse supplies the information necessary to 
decide on the correct word order and tense used in 
the rephrasing. 
In the case of a double passive, there is the ad- 
ditional problem of ambiguity, as illustrated by the 
following example from (Lederer 1989): "Two cars 
were reported stolen by the Groveton police yester- 
day." 7 
Ambiguous passive construction. Is the 
subject of "s~olen': '2he Groveton police"f 
In contrast to this group of syntactic problems, a 
check for subject-verb agreement is much harder to 
implement reliably. This is due to the ambiguity of 
part-of-speech that is so prevalent in English. Many 
verbs can also be nouns and vice versa. When there 
then is a mistake in subject-verb agreement, it be- 
comes very hard to produce a reliable parse. (We are 
assuming a strictly syntactic approach). Standard 
grammar checkers seem to have even worse prob- 
lems with this check (on the order of a precision of 
less than 10 percent). 
5.2 Lexical Problems 
Lexical problems, on the other hand, are not very 
much affected by bad parses and can be spotted with 
a high degree of reliability. These include misspelled 
or unknown words, duplicated words, and the like. 
5.3 Punctuation 
Using a full parse, EasyEnglish is able to spot a vari- 
ety of punctuation errors, including, but not limited 
to, missing commas ill conjoined clauses and noun 
7This sentence is actually ambiguous in many ways; 
here, we shall not address the other ambiguities. 
phrases, comma splices, missing hyphens, missing 
punctuation at the end of a segment, and questions 
with a final period instead of a question mark. 
6 The Use of Formatting Tags 
EasyEnglish works with SGML, Bookmaster, or IP\[,' 
formats as well as with plain text. Dealing with 
formatting tags is a necessary, but rather complex, 
task, which is often underestimated (as pointed out 
by Cl~mencin (1996)). But the trouble of building 
a good tag-handling system is well-rewarded. For- 
matting tags are of great help in the segmentation 
process and may be enlisted for identifying condi- 
tions such as missing periods (or other sentence de- 
limiters) and lack of parallelism in lists, both of 
which are handled by EasyEnglish. It is also useful 
to be able to identify tables and displays, thereby 
allowing differential treatment of them. Further- 
more, it can be helpful for the parser to take the 
tags into account, especially quote and highlighting 
tags, which may delimit complete phrases; header 
tags can influence the parser to prefer noun phrase 
analyses over sentence analysis. 
Another, very important, use of formatting tags is 
checking of revised text only. The so-called reviswn 
tags indicate revisions to earlier versions of the d,,e- 
ument. Being able to properly identify revised parts 
means that the user can elect to check only revised 
parts. This is a great time saver, considering the 
extensive use of previously written documents in a 
technical environment (Means and Godden 1996). 
7 Conclusion 
One of our greatest concerns has been to provide a 
system that is both useful and acceptable to the user. 
We have addressed this issue on four fronts: High 
precision, generality of the problem types EasyEng- 
lish is able to identify, customizability, and user- 
friendly interfaces. High precision is attained by 
the use of a high-quality, robust, broad coverage 
grammar (ESG) that delivers dependably consistent 
parses with great detail. Generality is attained by 
addressing generally ambiguous constructions rather 
than restricting ourselves to a specific CL. This way, 
the user does not have to learn a CL, either, which 
can be a quite difficult task (Wojcik and Holmback 
1996; van der Eijk et al. 1996; Douglas and Hurst 
1996; Ooyvaerts 1996). Customizability is attained 
by allowing the user to specify in a user profile which 
checks should be applied, as well as which user dic- 
tionaries should be used. User-friendliness is at- 
tained by integrating EasyEnglish with suitable edit- 
ing environments in such a way as to make changes 
easy, and to keep the EasyEnglish information up- 
to-date with these changes. Error statistics are co,- 
stantly updated as the user corrects mistakes, so 
that once a mistake is corrected the user will not 
be bothered with it again. 
163 
Judging from the feedback from our users, this 
approach seems to have paid off. Users generally ex- 
press enthusiasm about using EasyEnglish, and the 
IBM translation centers have reported that they find 
the =EasyEnglished" documents easier to deal with. 
This is informal evidence that our goal of easing the 
task of translation has been accomplished; however, 
we still need to make formal studies to be able to 
quantify the exact savings. 
8 Acknowledgements 
I would like to thank the following persons for contri- 
butions to EasyEnglish and to this paper: Michael 
McCord of IBM Research for use of his ESG gram- 
mar and parser, for contributing ideas to the design 
and implementation, for extensive work on the lex- 
icons and lexical utilities, and for commenting on 
this paper; Andrew Tanabe of the IBM AS/400 Di- 
vision for contributing ideas for some of the rules, 
for coordinating users and user input, for extensive 
testing, and for his role in incorporating EasyEng- 
lish in IDWB; Sue Medeiros of IBM Research for 
reading and commenting on this paper. 

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