Document generation apparatus and methods

A document generation system which employs a definition-based expert system and an editor to produce an output document from a template document and expert system responses. The knowledge base of the expert system consists of a hierarchy of terms and their definitions. To produce an expert response, an inference engine component of the expert system evaluates a term by evaluating all of the definitions for the terms which are in that term's hierarchy of definitions. In the document generation system, the terms include fragment terms which are defined as portions of the template document.

BACKGROUND OF THE INVENTION 
1. FIELD OF THE INVENTION 
The present invention relates to document generation systems implemented by 
means of digital computers and more particularly to document generation 
systems employing expert systems and to the knowledge base and inference 
engine components of expert systems. 
2. Prior Art Many business and legal documents are "written" by combining 
pieces of pre-existing text (often called "boilerplate" a required by the 
situation for which the document is being written and then adding to or 
editing the result, again as required by the situation. Many documents 
involving boilerplate were formerly produced rising forms from form books. 
The form's text contained the information which did not vary from 
transaction to transaction, while blanks were left for varying 
information. 
With the development of text editing programs (generally termed "editors") 
for computers, it became possible to automate the form book. The 
originator of the form provided a template document which was stored in 
the computer, and people using the editor to make documents which used the 
form simply copied the template document into the document they were 
making and then filled in the missing information. The automation rapidly 
went beyond making a template document and copying it, and a class of 
systems called document generation systems emerged. A document generation 
system employs a template document and information provided interactively 
or from a data base to generate a document which is specifically tailored 
to the situation for which it is assembled. A survey of such systems may 
be found in the following article: 
James A. Eidelman, "The Computer as Electronic Form Book, Available 
Software Tools", Legal Economics, May-June 1988 
Various approaches have been taken to document generation. Some editing 
programs have macro languages, which permit the user to write programs 
executed by the editor. By including such a program with a template 
document, the template document became a document generation system. Other 
document generation programs separate the program which uses the template 
from the template. Some document generation systems even employ expert 
systems with knowledge bases. The information in the knowledge base is 
used to determine what questions should be asked the person for whom the 
document is being prepared and to determine to determine what information 
should be included in the document being generated. 
A persistent problem in the design of document generation systems has been 
achieving power without undue complexity. Powerful document generation 
systems generally required that the person designing the system have a 
programmer's skills; document generation systems which did not require 
such skills often did little more than permit the user to select among 
parts of the template. In the case of document generation systems using 
expert systems, a particular problem has been the integration of the 
expert system which provided the information needed to produce the 
document with the editor which actually produced it. The foregoing and 
other problems are solved by the document generation apparatus and methods 
disclosed herein. 
SUMMARY OF THE INVENTION 
The document generation apparatus of the present invention is an expert 
system for generating an output document. The system includes a template 
document, a knowledge base for storing knowledge base items, an editor for 
editing the template document and an output document produced by the 
document generation apparatus, a knowledge base definer for defining 
knowledge base items in the knowledge base, and an inference engine which 
responds to inputs of information by using the knowledge base to produce 
an expert response based on the information. The knowledge base includes a 
document portion definer which responds to first user inputs to define a 
document portion knowledge base item which is associated with a portion of 
the document template. The document portion definer provides the editor to 
the user to edit the portion and associate the edited portion with the 
document portion knowledge base item. The inference engine includes an 
output document generator which responds to a document portion knowledge 
base item by employing the editing means to provide the document portion 
associated with the document knowledge base item to the output document 
when the document knowledge base item and the second user inputs so 
require. 
In another aspect of the invention, the expert system of the invention is a 
definition-based expert system of the type disclosed in the parents of the 
present application and the document portions are associated with terms 
defined in the definition-based expert system's knowledge base. The 
portions in the template document may further contain other terms defined 
in the definition-based expert system's knowledge base, including other 
terms associated with document portions. When the output document 
generator encounters such a term, the output document generator obtains 
the term's present value from the knowledge base and outputs the output 
document with the value in the place of the term. Further, when the user 
of the document portion definer has finished defining a portion of the 
template document, the document portion definer determines whether the 
other terms in the portion have definitions in the knowledge base; if they 
do not, the knowledge base definer asks the user to provide a definition. 
It is thus an object of the invention to provide improved apparatus and 
methods for generating documents. 
It is another object of the invention to provide improved document 
generation apparatus and methods which employ expert systems. 
It is a further object of the invention to provide document generation 
apparatus and methods which employ definition-based expert systems. 
It is an additional object of the invention to provide a definition-based 
expert system in which a term may be defined as a portion of text and the 
portion of text may itself include terms defined in the definition-based 
expert system.

For ease of reference to figures, the reference numbers used in the 
description of the preferred embodiment have three digits. The two 
least-significant digits are reference numbers within a drawing; the most 
significant digit is the drawing number. For example, the reference number 
901 refers to an item shown in FIG. 9. 
DESCRIPTION OF A PREFERRED EMBODIMENT 
The following description of a preferred embodiment first presents a 
conceptual overview of the expert system and expert system shell of the 
present invention and then presents a detailed description of a first 
prototype implementation of the invention. Certain improvements made in a 
second prototype implementation are discussed. Material added to this 
disclosure in the present continuation in part begins at Section 23. 
1. Conceptual Overview of the Expert System Shell and Expert System of the 
Present Invention: FIG. 2 
FIG. 2 is a conceptual block diagram of expert system shell 201 and expert 
system 202 of the present invention. Expert system shell 201 has four 
components: command processor (CP) 203, definition processor (DP) 207, 
term store (TS) 215, and term inference engine (TIE) 219. Expert systems 
202 produced using expert system shell 201 have all of these components 
but DP 207. As will be explained in more detail below, CP 203 receives 
commands from users of shell 201 and system 202 and provides them to the 
other components; DP 207 processes definitions; TS 215 stores defined 
terms and their definitions; TIE 219 uses a term's definition from TS 215 
to evaluate the term and perform other operations on it. 
CP 203 converts commands from users of shell 201 and expert systems 202 
into definition processor commands (DPCs) 204 and inference engine 
commands (IECs) 217. In the prototype, DPCs 204 permit the user of shell 
201 to define a term, redefine a term, undefine a defined term, view a 
term's definition, save a set of definitions, and restore a set of 
definitions. IECs 217 permit the user of shell 201 or an expert system 202 
produced by shell 201 to determine the current value of a term, find out 
how expert system 202 reached that value, have expert system 202 assume a 
different value for a term and see how that affects the value of other 
terms, reset the value of any one or all of the terms, and when the 
determination of the current value of a term requires a value to be 
supplied from outside the definition, to ask expert system 202 why the 
value is required. 
Definition processor 207 defines TERMs 206. When a TERM 206 has been fully 
defined, TS 215 contains a defined term (DTERM) 211 corresponding to TERM 
206 and a definition (DEF) 213 for DTERM 211. TERM 206 may be received 
either in a DPC 204 or from a description (DESC) 205 DP 207 requested from 
the user of expert system shell 201 in response to a TERM 206. DP 207 
first determines whether there is already a DTERM 211 corresponding to 
TERM 206, i.e., whether TERM 206 is already defined. If it is, DP 207 
retrieves DTERM 211 corresponding to TERM 206 from TS 215 and prepares it 
for use in the definition DP 207 is currently constructing. If it is not 
defined, DP 207 outputs a description request (DESC REQ) to the user of 
shell 201. The user provides a description (DESC) 205 of TERM 206 to DP 
201, which then makes a DEF 213 for TERM 206 using the information in DESC 
205. As will be described in more detail below, DESC 205 is written in a 
definition language which permits the user to specify other TERMs 206, 
constant values, and that a value is to be obtained from outside expert 
system 206 for which the definition is being provided. The definition 
further specifies operations which may be performed on the values 
represented by TERM 206, constants, and external values in the definition. 
If DESC 205 contains TERMs 206, DP 207 treats those TERMs 206 in the 
manner just described. If there is a DTERM 211 corresponding to TERM 206, 
DTERM 211 is used in DEF 213 being constructed; if there is not, DP 207 
requests a DESC 205 defining TERM 206 and processes it as just described. 
The repetitive operation of DP 207 is shown in FIG. 2 by arrow 208 showing 
how UDESC 210, which contains at least one TERM 206, is again processed by 
DP 207. Processing continues in this fashion until the original DESC 205 
and all of the TERMs 206 in any DESCs 205 produced for TERMs 206 required 
to define the TERMs 206 in the original DESC 205 have been defined, i.e, 
have corresponding DTERMs 211 and DEFs 213 in TS 215. 
The DTERMs 211 and DEFs 213 resulting from operation of DP 207 are placed 
in TS 215. DTERM 211 may be located in TS 215 by name. DEF 213 
corresponding to DTERM 211 is associated with DTERM 211, and may thus be 
used once DTERM 211 is located. Included in DEF 213 is a modified version 
of DESC 205 from which DEF 213 is derived. 
The remaining operations specified by DPCs 204 are carried out in DP 207 
and TS 215 as follows: when a TERM 206 is undefined, DP 207 removes the 
corresponding DTERM 211 and DEF 213 from TS 215; when a TERM 206 is 
redefined, DP 207 removes DEF 213 corresponding to TERM 206 and requests a 
new DESC 205 for TERM 206. That DESC 205 is then processed in the manner 
just described. When a DPC requests that a TERM 206's definition be 
displayed, DP 207 displays the DESC 205 which was incorporated into the 
DEF 213 for DTERM 211 corresponding to TERM 206. Finally, the save 
operation saves the contents of a given TS 215 to a file for later use and 
the restore operation restores the contents of the file to TS 215. 
Term inference engine (TIE) 219 performs operations using the DTERMs 211 
and DEFs 213 in TS 215. The primary operation is the what operation, which 
determines the value of a DTERM 211 from its definition and external 
values provided by the user of expert system 202 or shell 201. TIE 219 
performs the what operation in response to an IEC 217 specifying the 
operation and a TERM 206 from CP 203. TIE 219 uses DTERM 211 corresponding 
to TERM 206 to locate DTERM 211's DEF 213 in TS 215. It then performs the 
operations specified in DEF 213 using the DTERMs 211, constants, and 
external values specified in the definition and returns the result, TRES 
227, to the user of system 202 or shell 201. 
The constants in DEF 213 are available for immediate use in calculating the 
value of DTERM 211; in the case of the external values, DTERM 211 contains 
a description of how the external value is to be obtained. TIE 219 uses 
the description to make a request for an external value (EXVAL REQ) to the 
source of the external value EXVAL) 225 and receives EXVAL 225 from the 
source. In the simplest case, the source is the terminal being used by the 
user of system 202 or shell 201 and the information is obtained by putting 
a question on the user's terminal screen and receiving his input; in more 
complex cases, the source may be a file or a data base. 
In the case of a further DTERM 211 in DEF 213 for the DTERM 211 being 
evaluated. TIE 219 obtains the further DTERM 211's DEF 213 and computes 
that DTERM 211's value from its DEF 213, evaluating as it does so any 
DTERMs 211 in that DEF 213, and continuing thus until all DTERMs 211 from 
which the DTERM 211 whose value is being sought in the what operation is 
dependent have been evaluated. The constants, external values, and DTERMs 
211 specified in each DEF 213 are dealt with in the manner just described. 
When all DEFs 213 have been evaluated the value of DTERM 211 whose value 
is being sought is computed and returned as TRES 227. 
In a preferred embodiment, EXVALs 225 which are obtained during evaluation 
of a given DEF 213 become part of that DEF 213's definition; thus, if the 
what operation is performed a second time on DTERM 211, TIE 219 will not 
produce any EXVAL REQs, but will simply use the stored EXVALs 225 to 
recompute the value of DTERM 211. A preferred embodiment has two IECs 217 
for modifying the stored EXVALs 225. The first, reset, simply removes all 
of the stored EXVALs 225 from the DEFs 213 for the DTERMs 211 specified in 
the reset command. Thus, when what is again performed, a new EXVAL 225 
will be obtained as previously explained. The second, assume, permits a 
new EXVAL 225 to be provided to DEF 213 for TERM 206 specified in the 
assume command. When what is again performed in this case, the specified 
EXVAL 225 is used to derive the value of DTERM 211 for which the what 
operation is being performed. 
If a user of shell 201 or system 202 wants to know why TIE 219 is asking 
for a given EXVAL 225, he can respond to an EXVAL REQ with the command for 
the why operation. In response to that command, TIE 219 outputs DESC 205 
from DEF 213 for the DTERM 211 whose value was being computed when the 
EXVAL 225 was required, and the user can determine from DESC 205 why the 
given EXVAL 225 is important. The user can further use why to ask why any 
of the DTERMs 211 whose values are required to obtain the value of the 
DTERM 211 whose evaluation produced the EXVAL REQ are required, and TIE 
219 provides the DESCs 205 for those DTERMs 211. 
3. The Hierarchy of Definitions: FIG. 3 
In defining any term, DP 207 produces a hierarchy of DEFs 213. If DEF 213 
for the term being defined itself contains no terms, the hierarchy has 
only one level. If DEF 13 for the term contains a further term, that term 
must be defined before the first term can be defined, and the first term 
is the top term in a hierarchy with two levels. If any of the DEFs 213 at 
the second level contains a further term, that term must be defined, and 
the hierarchy has three levels. The hierarchy thus continues to deepen 
until none of the DEFs 213 for the terms upon which other terms depend 
contains a further term, but is instead defined solely in terms of 
operations on constants or external values. As is clear from the above 
discussion, a DEF 213 is always the top DEF 213 in the hierarchy of DEFs 
213 required to define the DTERM 211 which DEF 213 defines, but may at the 
same time be at a lower level in the hierarchy of DEFs 213 required to 
define some other DTERM 211. 
FIG. 3 is a conceptual illustration of one such hierarchy of DEFs 213. 
Hierarchy 305 contains DEFs 213(A) through 213(E) corresponding to DTERMS 
211(A) through 211(E) belonging to set of DTERMS 301. The topmost 
definition in hierarchy 305 is DEF 213(A), corresponding to DTERM 211(A). 
The notation OP(B,C) in DEF 213(A) indicates that DEF 213(A) specifies 
that the value of DTERM 211(A) is obtained by performing an operation on 
the values of DTERMs 211 (B) and (C). Similarly, DEF 213 B specifies that 
the value of DTERM 211(B) is obtained by performing an operation on the 
values of DTERMs 211(D) and (E). Consequently, hierarchy 305 for DEF 
213(A) has three levels: level 1 307, containing only DEF 213(A), level 2 
309, containing DEF 213(B) and DEF 213(C), and level 3 311, containing 
DEFs 213(D) and 213(E). DEFs 213(C), 213(D), and 213(E) do not define 
DTERMs 211 C, D, and E with other DTERMs 211, and cannot give rise to 
lower levels. Such DEFs 213 are termed terminal definitions 312. 
In constructing hierarchy 305 DP 207 begins with TERM 206(A) corresponding 
to DTERM 211(A), which it receives from a DESC 205 from which a DEF 213 at 
a higher level is being constructed or from a define or redefine DPC 204 
DP 207 then requests a DESC 205 for DTERM 211(A). DESC 205 defines DTERM 
211(A) in terms of an operation on two TERMS 206, B and C. If DEF 213(B) 
and DEF 213(C) already exist, DP 207 can make DEF 213(A) and need go no 
further. If either DEF 213(B) or DEF 213(C) does not exist, DP 207 must 
produce those DEFs 213 before it can make DEF 213A. DP 207 thus asks for a 
DESC 205 for TERM 206(B) and for TERM 206(C). In the case of TERM 206(C), 
DESC 205 defines TERM 206(C) only in terms of EXVAL(C) 225, and DEF 213(C) 
can be constructed immediately. In the case of TERM 206(B), DESC 205 
defines TERM 206(B) in terms of two additional TERMs 206, D and E; 
consequently, DP 207 must descend another level and produce DEFs 213 for 
those TERMs 206. Again, DP 207 requests DESCs 206 for those terms. In both 
cases, the TERMs 206 are defined in terms of EXVALs 225, and consequently, 
both DEFs 213 can be constructed. DEFs 213 for all TERMs 206 involved in 
the definition of TERM 206 A have now been constructed, DTERMs 211(B) 
through (E) corresponding to TERMs 206 (B) through (E) exist, DEF 213(A) 
can be constructed, and TERM 206(A) now has a DTERM 211(A) corresponding 
to it. 
Because hierarchy 305 is constructed repetitively beginning with the top 
DEF 213 in hierarchy 305 and only TERMs 206 which have no corresponding 
DTERM 211 are defined, no DTERM 211 can have two DEFs 213 and no DEF 213 
in hierarchy 305 can refer to a DEF 213 which is above it in hierarchy 
305. Consequently, the DEFs 213 in hierarchy 305 are necessarily complete 
and consistent with regard to DEF 213(A) in hierarchy 305 or to the top 
DEF 213 in any hierarchy incorporating DEF 213(A). 
4. The Description Language for Descriptions 205 
As previously indicated, DP 207 makes DEFs 213 from descriptions (DESCs) 
205. In the prototype, DESCs 205 are made using a description language. 
The description language includes predefined terms specifying operations 
on terms, a case statement, and operations for obtaining external values. 
The operations include Boolean operations, arithmetic operations, and text 
concatenation. The case statement is a list of boolean expression-value 
pairs of the form: 
______________________________________ 
(boolean.sub.-- exp.sub.-- 1) value 1 . . . (boolean.sub.-- exp.sub.-- n) 
value.sub.-- n 
(OTHERWISE) otherwise.sub.-- value 
______________________________________ 
When DEF 213 containing a case statement is evaluated, the boolean 
expressions 1 through n are evaluated in order until one of them is true. 
The value corresponding to the true boolean expression becomes the value 
of DTERM 211 defined by DEF 213. If none of the boolean expressions is 
true, the value corresponding to OTHERWISE becomes the value of DTERM 211. 
The description language of the prototype permits specification of two 
classes of operations for obtaining external values. The first class, the 
ASK operations, obtains values from the terminal of the user of expert 
system 202. The first class, the ASK operations, are used to obtain 
external values from the terminal. The second class, the RECORD 
operations, are used to obtain external values from a data base system. In 
both cases, the external values may be numbers, text strings, or boolean 
values, or they may select one of a set of alternative literal terms, 
i.e., terms which represent nothing but themselves. 
ASK to obtain a numeric value has the form: 
EQU ASK NUMBER "prompt.sub.-- string" 
When the DEF 213 containing such an ASK operation is evaluated, DP 207 
outputs the prompt string to the terminal and waits for a number input 
from the terminal. That number is then used in the evaluation of DEF 213. 
The prompt string ma itself contain a previously-defined term, and 
consequently, a user's response may be made to depend on the value of a 
previously-evaluated term. The ASK operations for boolean and text string 
values are specified in the same fashion as the ASK operation for numeric 
values, except that NUMBER in the above operation is replaced by YES-NO 
when a boolean value is sought and TEXT when a text string is sought. 
ASK which selects one of a number of literal terms has the form: 
______________________________________ 
ASK CHOICE "prompt.sub.-- string" 
(literal.sub.-- term.sub.-- 1 . . literal.sub.-- term.sub.-- 
______________________________________ 
n) 
When the DEF 213 containing ASK CHOICE is evaluated, the prompt string is 
output and the user is asked to select one of the literal terms. That 
literal term may then be used in DEF 213 to compute the value of DTERM 211 
defined by DEF 213. 
The RECORD operations are generally analogous to the ASK operations, except 
that the RECORD operation specifies how the external value is to be 
located in the data base and the data base supplies the value at the 
specified location. 
5. Operation of Shell 201 and System 202: FIG. 4 
The operation of shell 201 will be explained in detail using a hierarchy of 
definitions from which it may be determined whether someone has been 
defrauded. The legal definition of fraud requires that one party knowingly 
made a misrepresentation to the other party and that the other party 
relied on the misrepresentation to his detriment. FIG. 4 shows a hierarchy 
of DTERMs 211 which corresponds to that legal definition. 
Creation of the hierarchy of FIG. 4 begins when CP 203 receives the DEFINE 
FRAUD command. CP 203 then passes TERM 206 FRAUD to DP 207, which requests 
a DESC 206 from the expert making the definition. The expert provides the 
DESC 206 
EQU KNOWING.sub.-- MISREPRESENTATION AND DETRIMENTAL.sub.-- RELIANCE 
This DESC 206 contains two further TERMs 206 and the boolean AND operator. 
Thus, the value of FRAUD is to be computed by obtaining the values of the 
DTERMs 211 corresponding to the TERMs 206 and performing an AND operation 
on them. 
Since the further TERMS 206 are undefined, DP 207 asks for their 
definitions. The expert provides the DESC 205 
EQU MISREPRESENTATION AND DEFENDANT.sub.-- KNEW.sub.-- MISREPRESENTATION 
KNOWING.sub.-- MISREPRESENTATION and the DESC 205.sub.-- RELIANCE.sub.-- BY 
PLAINTIFF AND LOSS.sub.-- BY.sub.-- PLAINTIFF for DETRIMENTAL.sub.-- 
RELIANCE. Again, these further TERMs 206 are undefined, so DP 207 asks for 
their definitions and the expert provides the definitions show in FIG. 4. 
While DP 207 may ask for definitions in any order, a preferred embodiment 
defines all TERMs 206 necessary to define a given undefined TERM 206 
before going on to the next undefined TERM 206. 
In the above example, the DESCs 205 for MISREPRESENTATION, DEFENDANT.sub.-- 
KNEW.sub.-- MISREPRESENTATION, RELIANCE.sub.-- BY.sub.-- PLAINTIFF, and 
LOSS.sub.-- BY.sub.-- PLAINTIFF all contain only the system-defined DTERMS 
211 used in the ASK YES-NO operation, so DP 207 is now able to produce 
DEFs 213 for all of the terms in the hierarchy. The values of all of the 
DTERMs 211 in the hierarchy depend ultimately on the values which the ASK 
YES NO operation requests from the user of expert system 202 which employs 
the FRAUD definition, and thus depends ultimately on what the plaintiff 
says about what happened to him. 
Use of the FRAUD definition hierarchy in expert system 202 begins with the 
WHAT FRAUD command which the user of expert system 202 inputs to CP 203 CP 
203 generates a corresponding WHAT FRAUD IEC 217 for TIE 219. TIE 219 then 
determines the value of FRAUD by evaluating its DEF 213. In order to do 
that, it must evaluate the DEFs 213 for other DTERMs 211 in the hierarchy, 
beginning with KNOWING.sub.-- MISREPRESENTATION. The evaluation of 
KNOWING.sub.-- MISREPRESENTATION requires the evaluation of 
MISREPRESENTATION. The evaluation of that DTERM 211 results in the 
execution of the WHAT YES-NO operation in its DEF 213, and TIE 219 outputs 
the prompt "Did he tell you anything that wasn't true?" If the user 
answers "no", MISREPRESENTATION is false, KNOWING.sub.-- MISREPRESENTATION 
is false, and FRAUD is false, so TIE 219 returns TRES 227 to the user 
indicating that there is no fraud. If the user answers "yes", TIE 219 
evaluates DEFENDANT.sub.-- KNEW.sub.-- MISREPRESENTATION, which again 
results in a question to the user. Depending on the answer to the 
question, evaluation continues or is finished. TIE 219 proceeds in the 
above fashion until it has computed a value for FRAUD. 
As previously mentioned, a user of expert system 202 may use the HOW user 
command to determine how expert system 202 arrived at its value for FRAUD. 
Assuming that the user answered "no" when asked "Did he tell you anything 
that wasn't true" (in the definition of MISREPRESENTATION), TIE 219 in the 
prototype will respond to HOW FRAUD by outputting 
______________________________________ 
FRAUD is defined to be (KNOWING.sub.-- MISREPRESENTA- 
TION AND DETRIMENTAL.sub.-- RELIANCE) where 
(KNOWING.sub.-- MISREPRESENTATION) equals FALSE. 
______________________________________ 
As previously mentioned, DP 207 places DESC 205 for a DTERM 211 in the 
DTERM 211's DEF 213, and TIE 219 also stores the external values it 
receives in evaluating a DTERM 211's DEF 213 in DEF 213. In performing the 
HOW operation, TIE 219 first fetches and outputs DESC 205 from DEF 213 for 
the DTERM 211 being inquired about and then evaluates the DTERMS 211 in 
DEF 213 as required to obtain the value of DTERM 211 being inquired about. 
The DTERMs 211 are then output together with their values. If a user 
wishes to inquire further, he need only repeat the HOW operation on the 
other DTERMS 211 specified in the DESC 205 output in the HOW operation. 
As also previously mentioned, a user may respond to a request for an 
external value with the WHY command instead of a value. If a user responds 
in the case of the FRAUD example with WHY when TIE 219 asks "Did he tell 
you anything that wasn't true", TIE 219 responds with: 
______________________________________ 
MISREPRESENTATION is needed to determine the value of 
KNOWING.sub.-- MISREPRESENTATION, which is defined to be 
MISREPRESENTATION AND SUBJECT.sub.-- KNEW.sub.-- 
MISREPRESENTATION 
______________________________________ 
and repeats the question. 
Again, the information used to respond to the WHY command comes from the 
DESCs 205 stored in the DEFs 213 in the hierarchy used to define FRAUD. If 
the user wants to know more at this point, he can apply HOW to the DTERMs 
211 mentioned in the response to the WHY command. 
6. The LISP Environment of the Prototype Embodiments: FIG. 5 
Having thus provided a conceptual overview of the structure and operation 
of shell 201 and system 202, the discussion proceeds to a detailed 
description of the implementation of the first prototype. 
Both the first and second prototype embodiments are implemented in the LISP 
programming language and execute in the LISP environment. The LISP 
programming language and environment are frequently used to implement 
prototype and production expert systems and are well-known in the expert 
system art. The specific LISP dialect used for the prototype embodiments 
is COMMON LISP, which is described in Guy L. Steele, Jr., COMMON LISP, the 
Language, Digital Press, 1984. Only so much of the LISP environment and 
language are described here as is required for a clear understanding of 
the mode of operation of the prototype embodiments. 
Beginning with the LISP language, the language differs from languages such 
as FORTRAN or PASCAL in that is is chiefly concerned with the processing 
of symbols, as opposed to the processing of data which is represented in a 
program by symbols. The fundamental components of a LISP program are 
atoms. An atom may be a symbol, such as ABC, or a constant. The components 
are organized into programs by means of lists which may have no members or 
members including atoms and other lists. A list is made by enclosing its 
members in parentheses: (ABC) is a list with one member, the symbol ABC. 
Functions appear in LISP as lists in which the first symbol in the list 
represents the function and the other atoms represent the function's 
arguments. For example, the add function is represented in LISP by the 
symbol +, and the list (+2 3) specifies that the + operation is to be 
applied to the atoms 2 and 3. Any atom or list which has a value when 
evaluated by a LISP interpreter is called a form. 5 and (+2 3) are forms, 
and if the symbol ABC has a value, it is a form. 
Functions are defined in LISP by means of the DEFUN function, in which the 
remaining items of the list define the function's name, its arguments, and 
the value it returns. For example, (defun five () 5) defines a function 
which takes no arguments and always returns the value 5. 
Among the things LISP programs can do with symbols and lists is make them. 
Since a function definition is only a kind of list, a LISP program can 
provide a symbol to DEFUN as the name of the new symbol being created by 
DEFUN and then use the symbol to execute the newly-created function. 
Symbols may either represent themselves as symbols or values. When a 
symbol is representing itself as a symbol in a LISP list, it is preceded 
by a' mark. In the case of symbols representing functions, the value of 
the symbol is the function. However, if the function is placed in a list 
with its arguments and the list evaluated, the result is the value of that 
execution of the function. Thus, 'five represents the symbol five, while 
five represents the function defined by DEFUN above, and (five) represents 
the value of an execution of the function five, i.e., 5. 
LISP programs are written and executed in a LISP environment. That used for 
the prototype embodiments was made by Gold Hill Computers, Inc. for the 
Professional Computer manufactured by Wang Laboratories, Inc. FIG. 5 is a 
conceptual block diagram of a typical LISP environment 501. Environment 
501 has two main components, LISP interpreter 503, which evaluates LISP 
forms, and LISP symbol space 505, which stores LISP symbols (SYM 501) and 
their definitions (SYMDEF 509). DEFUN and certain other LISP functions 
create and define new LISP symbols or redefine previously-existing LISP 
symbols when they are evaluated; consequently, LISP interpreter 503 may be 
seen as not only an evaluator of symbols, but also as a creator, definer, 
and redefiner of symbols. 
Operation of LISP environment 501 is as follows: when a user of LISP 
environment 501 types a list containing a form such as (five), LISP 
interpreter 503 evaluates the form by locating the symbol five in symbol 
space 505, determining what its SYMDEF 509 is, and then interpreting 
SYMDEF 509 to compute the value of five. In this case, SYMDEF 509 is the 
code for the function five which was created by evaluation of the DEFUN 
expression, and its interpretation produces the value 5, which the 
interpreter returns to the user as the value of (five). 
Because LISP interpreter 503 is able to create SYMs 507 and their 
corresponding SYMDEFs 509, store them in symbol space 505, and locate them 
in symbol space 505, LISP environment 501 automatically performs 
operations which are difficult to implement in other languages and which 
are essential for the operation of expert system shells and expert systems 
For that reason, LISP environments 501 have been the preferred 
environments for the creation of prototype expert systems and expert 
system shells As will be seen in the ensuing discussion, the prototypes of 
the present invention take full advantage of the symbol creation, 
definition, and location operations 
7. Overview of the First Prototype Embodiment: FIG. 6 
In the first prototype embodiment, the components of expert shell 201 and 
expert system 202 are implemented by means of LISP functions. FIG. 6 gives 
an overview of the functions and relates them to the components of FIG. 2 
and the inputs and outputs of those components. Thus, the LISP functions 
making up CP 203 are contained in the dashed box with that label, the 
functions making up DP 207 are in the dashed box with that label, and 
those making up TIE 219 are in the dashed box with that label. TS 215 is 
embodied in the first prototype by LISP symbol space 505, which stores 
LISP symbols and their definitions. The components of the first prototype 
embodiment should also be understood to include LISP interpreter 503, 
which executes the LISP functions making up the components, places the 
SYMs 507 and SYMDEFs 509 created by the components in symbol space 505, 
and manipulates the SYMs 507 and their SYMDEFs 509. 
Beginning with EXPERT 603, EXPERT 603 performs the functions of CP 203 in 
the prototype. EXPERT 603 receives an input string, puts parentheses 
around it to produce a LISP form termed CFORM 605 in FIG. 6, and performs 
the EVAL operation on it. When LISP interpreter 503 evaluates the form, it 
treats the first symbol in the form as a LISP function name and the 
remaining items in the form as a list of arguments for the named function. 
Expected input strings for EXPERT 603 are the commands for DP 207, namely 
DEFINE, REDEFINE, UNDEFINE, and the commands for TIE 219, namely WHAT, 
HOW, ASSUME, RESET, DEFINITION, SAVE, WHY, and RESTORE. DEFINE, REDEFINE, 
and UNDEFINE correspond to the DPCs 204 of FIG. 2 and the remaining 
strings correspond to the IECs 217 of that figure. In the first prototype 
embodiment, there is no error detection in EXPERT 603; however, in a 
commercial embodiment, EXPERT 603 would include code for detecting and 
responding to improper input. 
As may be seen from FIG. 6, DP 207 is embodied in the first prototype by 
the LISP functions DEFINE, REDEFINE, and UNDEFINE. When EXPERT 603 
receives the DEFINE command with a TERM 206 such as FRAUD, and presents it 
to the LISP interpreter as (DEFINE FRAUD), LISP interpreter 503 invokes 
the function DEFINE with the argument FRAUD. DEFINE requests a DESC 205 
from the user and uses DESC 205 to produce the DEF 213 for FRAUD. As will 
be explained in greater detail below, the result of the invocation is a 
LISP function named FRAUD for which the DEFUN would look like the 
following: 
______________________________________ 
(defun FRAUD () 
(prog2 
(push 'FRAUD arg-stack) 
(AND (KNOWING.sub.-- MISREPRESENTATION) 
(DETRIMENTAL.sub.-- RELIANCE)) 
(pop Arg-stack) 
) ) ) ) 
______________________________________ 
In the course of defining FRAUD, KNOWING.sub.-- MISREPRESENTATION and 
DETRIMENTAL.sub.-- RELIANCE and the DTERMs 211 required for their 
definitions are all defined as LISP symbols representing LISP functions. 
AND is a predefined LISP function which performs the AND operation on its 
arguments. The value returned by the function FRAUD is the result of the 
AND operation. 
The DTERMs 211 which have been defined as LISP symbols representing LISP 
functions are termed TSYMs 615 in the following discussion, and their 
definitions, which are the prototype's implementation of DEFs 213, are 
termed TDEFs 617. As the LISP interpreter produces TSYMs 615 and TDEFs 617 
in response to the DEFINE function, it places them in symbol space 505. 
TDEF 617 in the first prototype is shown in FIG. 7. As shown there, each 
TDEF 617 contains TFUNC 701, the LISP function represented by TSYM 615, 
TDESC 705, a modified copy of DESC 205 which was the source of TSYM 615's 
definition, and TEXVAL 703, which contains the last EXVAL 703 specified by 
a user of expert 202 for TSYM 615. 
The remaining functions in DP 207 are invoked in the same fashion as DEFINE 
from EXPERT 603. REDEFINE first employs LISP operations which remove TFUNC 
701 and TDESC 705 from TDEF 617 for TSYM 615 being redefined and then 
invokes DEFINE to make new values for TFUNC 701 and TDESC 705 in TDEF 617. 
UNDEFINE simply removes TFUNC 701 and TDESC 705 without making a new 
definition of TSYM 615. 
Continuing with the implementation of TIE 219 in first prototype embodiment 
601, when LISP interpreter 503 receives a CFORM 605 from EXPERT 603 which 
represents an IEC 217, it executes the function in TIE 219 specified in 
CFORM 605. As the functions in TIE 219 are executed, they provide forms 
(TFORMS 639) made from TSYMS 615 to Interpreter 505, which evaluates them 
and returns the results (TFORM RESULT) to the function being executed. 
The functions in TIE 219 employ data structures in TIE 219, ARG-STACK 635, 
TERMS-STACK 613, and SYM-BOUND-LIST. Beginning with ARG-STACK 635, 
ARG-STACK 635 is used to store a TSYM 615 while the values of the TSYMs 
615 with which it is defined are computed. As may be seen in the code for 
the procedure FRAUD above, the symbol FRAUD is pushed to ARG-STACK before 
the AND operation which defines FRAUD is executed and is popped from 
ARG-STACK thereafter. TERMS-TACK 613 is a stack of TSYMs 615. The stack is 
ordered by when a TSYM 615's TDEF 617 was created, with the first TSYM 615 
to have its TDEF 617 created at the bottom and the last at the top. As 
will be explained in detail below, the last TSYM 615 is normally the one 
whose TDEF 617 is at the top of the hierarchy of definitions. SYM.sub.-- 
BOUND.sub.-- LIST 637 is a list of TSYMs 615 which currently have EXVALs 
225 assigned to them. 
Beginning the discussion of the LISP functions in TIE 219 with WHAT 
function 619, that function is executed in response to the WHAT command to 
EXPERT 603. That command has the form WHAT DTERM 611. For FRAUD, it would 
be WHAT FRAUD, which EXPERT 603 turns into (WHAT FRAUD). WHAT function 619 
first uses a LISP function to determine whether its argument is a TSYM 
615, and if it is, uses another LISP function which takes a symbol which 
is a function name as an argument and invokes the function, in this case, 
FRAUD. The result is the execution of TFUNC 701 in TDEF 617 for FRAUD. 
When that TFUNC 701 is executed, the TFUNCs 701 for MISREPRESENTATION and 
DETRIMENTAL.sub.-- RELIANCE are executed until the value of FRAUD has been 
determined. When a TFUNC 701 for a given TSYM 615 is executed, the TFUNCs 
701 for any TSYMs 615 required to find the value of the given TSYM 615 are 
executed. When all of the necessary TFUNCs 701 have been executed, the 
value resulting from those executions is returned to the user of system 
202 as TRES 227. If a TSYM 615 whose TFUNC 701 requires an EXVAL 225 
already has such a value, the TSYM 615 is on SYM-BOUND-LIST 637 and TFUNC 
701 uses TEXVAL 703 in TDEF 617 for TSYM 615; otherwise, TFUNC 701 
generates an EXVAL REQ and obtains EXVAL 225 from the user. Thus, the WHAT 
function, together with LISP interpreter 503, operate as an inference 
engine for determining the value of the TSYM 615 whose definition is at 
the top level of the hierarchy as determined by external values. Further, 
as long as a TFUNC 701 invoked as a consequence of the WHAT operation is 
active, its corresponding TSYM 615 is on ARG-STACK 635. 
HOW function 623 is executed in response to the HOW command, which 
specifies a TSYM 615. HOW function 623 takes that TSYM 615 as an argument 
and uses another LISP function, SYMBOL-FUNCTION with the argument TSYM 615 
to obtain the list used with DEFUN to define TFUNC 701 corresponding to 
TSYM 615 and other LISP functions to obtain the third element in the third 
list in TFUNC 701. As may be seen from the FRAUD function above, that 
element is the list defining the operation by which the function's value 
is derived, i.e., in FRAUD, the list (AND (KNOWING.sub.-- 
MISREPRESENTATION) (DETRIMENTAL.sub.-- RELIANCE)). The HOW function 
retrieves that list, uses TIE 219's DEFINITION function to display TDESC 
705 for TSYM 615 used in the HOW command, and then evaluates the TSYMs 615 
in the list retrieved from TFUNC 701, and outputs the results with 
suitable explanatory text. 
The user of expert 202 may input the WHY command either to EXPERT 603 or to 
TIE 219 in response to an EXVAL REQ output during evaluation of a TSYM 
615. The WHY function may be invoked either with or without a TSYM 615 as 
an argument. In the first case, the function works with the TSYM 615 
currently at the top of ARG-STACK 635, which is the TSYM 615 corresponding 
to TFUNC 701 currently being evaluated and whose evaluation produced the 
EXVAL REQ to which the user may be responding, and in the second case, it 
works with TSYM 615 provided by the user. In either case, the next step is 
to locate the preceding TSYM 615 in ARG-STACK 635, which is the TSYM 615 
corresponding to the TFUNC 701 whose evaluation led to the evaluation of 
the function corresponding to TSYM 615 being processed by WHY. If there is 
no preceding TSYM 615, the WHY command is meaningless, and a corresponding 
message is output to the user; if there is a preceding TSYM 615, then 
DEFINITION is used to output the definition for the preceding TSYM 615 
together with suitable explanatory text. 
Continuing with the DEFINITION function, the command to EXPERT 603 which 
invokes the function may have either a TSYM 615 as an argument or no 
argument. In the first case, TDESC 705 in TDEF 617 is output; in the 
second case, the TDESCs 705 for all TSYMs 615 on TERMS-STACK 613 are 
output. 
The ASSUME function is invoked with the ASSUME command, which specifies a 
TSYM 615 and a value. The TSYM 615 must be one whose TFUNC 701 requests an 
EXVAL 225. ASSUME first empties ARG-STACK 635, so that the TSYM 615 will 
be reevaluated before a WHY command succeeds, then sets TEXVAL 703 in TDEF 
617 to the value received as an argument, and puts TSYM 615 on SYM-BOUND 
LIST 613 to indicate that it has a TEXVAL 703. 
The RESET function is invoked with the RESET command, which may or may not 
specify a TSYM 615. In the first case, only TEXVAL 703 in TDEF 617 
corresponding to TSYM 615 is reset; in the second case, all TEXVALs 703 
are reset. The RESET function first empties ARG-STACK 635 for the reason 
previously described. If a TSYM 615 is specified, the RESET function 
unbinds TEXVAL 703 from TSYM 615, effectively removing it from TDEF 617, 
and removes TSYM 615 from SYN-BOUND-LIST 637. If no TSYM 615 is specified, 
RESET performs the above operation for every TSYM 615 on SYN-BOUND-LIST 
637 
The SAVE function makes a file which contains a DEFINE command for each 
TSYM 615 followed by TDESC 705 for the TSYM 615. The DEFINE commands occur 
in the order in which TSYMs 615 occur in TERMS-STACK 613. SAVE works by 
outputting the following to the file for each TSYM 615 in TERMS-STACK 613: 
the string DEFINE, a string representing TSYM 615, and a string 
representing TDESC 705 for TSYM 615. The resulting file contains the 
TDESCs 705 in the order in which the DESCs 205 upon which they are based 
were input to DP 207. 
The RESTORE function restores the TSYMS 615 which were previously saved. It 
does so by performing a LISP load operation on the file. In the load 
operation, the LISP symbols in the file are evaluated. In this case, the 
result of the evaluation is the production of the TSYMs 615 and their 
TDEFs 617 specified in the DEFINE commands in the restored file. 
10. Detailed Description of DEFINE 607: FIG. 8 
FIG. 8 shows how the DEFINE functions and functions invoked by it 
recursively create the hierarchy of TDEFs 617 for a given set of TSYMs 
615. As previously mentioned, the manner in in which DEFINE creates the 
hierarchy of TDEFs 617 guarantees that each TERM 206 is completely defined 
and that a given TERM 206 has only a single definition. 
FIG. 8 shows DEFINE, the major functions invoked by DEFINE, and the manner 
in which the data from which TSYMs 615 and TDEFs 617 are created flows 
between the functions 
DEFINE 607 produces DTERMs 211 from TERMs 206. When DEFINE returns DTERM 
211, TSYM 615 and TDEF 617 corresponding to DTERM 211 have been created. 
DEFINE 607 is invoked by EXPERT 603 and RESTORE 633; additionally, it is 
recursively invoked by itself and by PROCESS-FUNCTION 811. EXPERT 603 
provides CFORM 605 containing the DEFINE symbol and a TERM 206 to be 
defined; RESTORE 633 provides a CFORM 605 containing the DEFINE symbol and 
a TERM 206 which is a copy of a previously-saved DTERM 211 and a copy of 
TDESC 705 for that DTERM 211. When DEFINE 607 is recursively invoked, its 
input is a TERM 206 which is is used in the DESC 205 of another TERM 206 
being defined. 
Generally speaking, TERM 206 is a single symbol; however, when DESC 205 
includes a case statement, TERM 206 may be a list; in that case, DEFINE 
invokes CONVERT 809 to convert the list to a LISP form and then 
recursively invokes itself to define each of the undefined TERMs 206 in 
the LISP form. Next, DEFINE 607 determines whether TERM 206 is a LISP 
symbol; if it is not, DEFINE 607 simply returns TERM 206 unchanged. If it 
is, DEFINE 607 determines whether TERM 206 was provided by RESTORE 633; if 
it was, DEFINE 607 provides TERM 206 and the copy of TDESC 705 to GETDEF 
805 and returns the value returned by GETDEF 805, namely a list whose 
element is TERM 206. If TERM 206 was not provided by RESTORE 603, DEFINE 
607 determines whether there is already a TSYM 615 for TERM 206 or if TERM 
206 is a literal (i.e, there was no copy of TDESC 705). If either is the 
case, DEFINE returns a list whose element is TERM 206. If none of the 
other cases was true, GETDEF 805 is invoked by DEFINE 607 without a copy 
of TDESC 705. 
GETDEF 805 receives an undefined term (UTERM) 803 from DEFINE 607 and may 
also receive a copy of TDESC 705 for the term. In the first case, GETDEF 
obtains DESC 205 from the user; in the second case, it simply uses TDESC 
705. Next it invokes CONVERT 809 to convert it to CDESC 807, which is a 
LISP form. Next, UTERM 803 and CDESC 807 are provided to PROCESS-FUNCTION 
811, which returns TFUNC 701 for UTERM 811. Finally, GETDEF 805 places 
TSYM 615 on TERMS STACK 613, and returns a list consisting of DTERM 211 
corresponding to UTERM 803 to DEFINE 607. CONVERT 809 is invoked by DEFINE 
607 or GETDEF 805. It receives a DESC 205 from its invoker and converts it 
to a LISP form, CDESC 807, which it returns to the invoker. 
PROCESS-FUNCTION 811 receives UTERM 803 and CDESC 807, passes UTERM 803 to 
DEFINE-FUNCTION 813, receives TFUNC 701 from DEFINE-FUNCTION 811, returns 
TFUNC 701 to GETDEF 805, and produces UTERML 815, which is a list of the 
UTERMs 803 from CDESC 807 which have not yet been defined. 
PROCESS-FUNCTION then invokes DEFINE 607 for each UTERM 803 on UTERML 815. 
DEFINE-FUNCTION 803 finally, creates and evaluates a DEFUN for TFUNC 701, 
thereby creating TFUNC 701, which it returns to PROCESS-FUNCTION 811, 
which in turn returns it to GETDEF 805. 
As can be seen from the above description, recursive invocations of DEFINE 
607 continue until all of the TERMs 206 required to define the TERM 206 
for which DEFINE was invoked have been defined; only at that point, DEFINE 
606 returns DTERM 211 corresponding to TERM 206. Since the user of Shell 
201 must define all of the TERMs 206 required to define a given TERM 206 
and can give TERM 206 only a single definition, DEFINE 606 guarantees that 
a set of definitions for a term 206 is complete and consistent. 
11. Prototype Embodiment 2: FIG. 9 
Prototype embodiment 2 contains many improvements over prototype embodiment 
1, including a better interface to the user and more robust recovery from 
user errors. Among the most important improvements included in prototype 
embodiment 2 are the alternate embodiments of TDEF 617 and WHAT shown in 
overview in FIG. 9. 
TDEF 901 contains TDESC 705 and TEXVAL 703 as did TDEF 617; it does not 
contain TFUNC 701, and contains two new fields: TFORM 903 and TTYPE 905. 
The change was made to eliminate a difficulty with prototype embodiment 1: 
namely, that the TERM 206 to be defined might correspond to some other 
LISP symbol already in symbol space 505. In that case, the definition 
produced by DEFINE 607 for TERM 206 would supersede the 
previously-existing definition of the symbol. The problem is solved in 
prototype embodiment 2 by replacing TFUNC 701 with TFORM 903, a LISP form 
which is not itself executable as a function but may be executed by an 
EVALUATOR function 911 in TIE 219. TTYPE 905 contains information about 
the kind of value returned when TFORM 905 is executed by EVALUATOR 911. 
The remaining portion of FIG. 9 shows the relationship between WHAT 
function 907 and EVALUATOR 911 in prototype embodiment 2. WHAT 907 
receives the WHAT CFORM 605 from EXPERT 603 as before, but instead of 
simply performing a LISP eval operation on TSYM 615 provided as an 
argument to WHAT, it provides TFORM 903 from TDEF 901 for TSYM 615 to 
evaluator 911, which in turn produces LISP forms to perform the operations 
specified in TFORM 903 and provides them to LISP interpreter 503. LISP 
interpreter 503 returns the results of the evaluation of the LISP forms to 
evaluator 911, which then makes these results into TRES 227, which it 
returns to WHAT 907, which in turn returns it to the user. 
12. Further Development of Definition-based Expert Systems 
Further experience with and development of the definition-based expert 
system described in the foregoing portion of the present patent 
application has shown that definition-based expert systems are even more 
broadly applicable than previously thought. The further development has 
also resulted in the creation of a number of new operations which may be 
specified in the definition of a term and the development of new value 
types. The following additional material will first explain how a 
definition-based expert system may be employed as an application 
development system and how certain of the new operations greatly increase 
the usefulness of such a definition-based expert system and will then 
disclose other new operations and the new value types. 
13. Application Development Systems Employing Definition-based Expert 
Systems 
Historically, applications for computers have been written in languages 
such as COBOL or C by computer programmers with specialized knowledge of 
those languages and of the computer system the application is being 
developed for. This fact has had a number of undesirable consequences. 
First, writing applications in standard computer languages is a laborious 
process; even a simple application may require thousands of statements. 
Second, the technical skills required for programming in the standard 
programming languages have made programmers scarce and expensive. Third, 
and perhaps most important, there have been communication difficulties 
between the programmers, who understand programming languages and computer 
systems, but not the task the application program is intended to perform, 
and the intended users of the application program, who understand the 
task, but know nothing of programming languages and computer systems. As a 
consequence, it often happens that an application program must be 
rewritten several times before it does what its users want it to do. 
The problems described above had lead in recent years to the creation of 
application development systems which are task-oriented, i.e., they 
describe an application in terms familiar to those who work in the area 
the application is intended for. The advantages of such an application 
development system are clear: in many cases, the applications can be 
developed by their users and programmers are no longer required. Even 
where programmers are still required, the use of a task-oriented 
application development system reduces the probability of design errors, 
simplifies communication between the programmer and the users, and greatly 
reduces the amount of code that must be written. The definitional expert 
system described in the present patent application is an example of such a 
task-oriented application development system. While prior-art rule-based 
expert systems often required specialized knowledge engineers and computer 
programs, the definition-based expert system of the present patent 
application can be developed by anyone who can express a body of knowledge 
as a hierarchy of definitions. For example, as shown in the patent 
application, a lawyer who understands the legal definition of fraud can 
develop a definitional expert system which permits a lay person to 
interactively determine whether a fraud has occurred. Similarly, a banker 
who understands how his bank determines whether to grant a loan to an 
applicant can develop a definitional expert system to interactively 
determine whether a loan should be granted. 
The usefulness of the definitional expert system as a task-oriented 
application development system has been greatly increased by certain new 
operators in definitions which cause the computer system to perform 
operations in addition to obtaining values when the term to which the 
definition belongs is evaluated. With the addition of these new operators, 
the definitional expert system has become a general application 
development system for developing highly-interactive applications. An 
example of such an application is one which might be termed an "automatic 
realtor". The application interactively prompts the user to provide 
information concerning the user's space requirements, architectural 
preferences, and financial circumstances and then shows the user images of 
houses which are presently on the market and meet the user's requirements. 
14. The "Side Effect" Operators 
As explained in the foregoing patent application, when term inference 
engine (TIE) 219 (FIG. 2 responds to a WHAT inference engine command 217 
to produce an expert response regarding a particular defined term (DTERM) 
211, it produces the expert response by evaluating defined term 211's 
definition (DEF) 213. If that definition involves other defined terms 211, 
the definitions 213 for those terms are evaluated until every defined term 
211 in the hierarchy of definitions for the particular defined term 211 
has been evaluated. As may be seen from the above, every DEF 213 must 
return a value when the definition is evaluated. However, the evaluation 
of a definition may do more than produce a value. For example, the ASK 
operator as disclosed in the foregoing patent application has the form: 
EQU ASK NUMBER "prompt string" 
When a term 211 whose definition 213 includes this operator is evaluated, 
the prompt specified by "prompt string" is output to the display and the 
user's response to the prompt is returned as the value of the operator. In 
this case, evaluating the term 211 not only resulted in the return of the 
value specified by the user's response, but also resulted in the 
performance of display-related operations including the output of the 
prompt to the display and receiving the input value. These other 
operations are termed generally "side effects" because they are side 
effects of the evaluation of definition 213. 
In the course of the further development of the definition-based expert 
system, it has turned out to be useful to include operators whose primary 
purpose is the side effects they produce. In a presently-preferred 
embodiment, each of these operators gives the term it is used to define 
the Boolean value TRUE when the operation succeeds and otherwise indicates 
an error. Moreover, information required for the operation may itself be 
specified by means of a term 211. The operators in a presently-preferred 
embodiment include the following: 
COPY copies one file specified in the operator to another file specified 
therein. 
DELETE deletes a file specified in the operator. 
DISPLAY displays information on the display. The source of the information 
may be a text string defined in the operator, a text file, or an image. 
PRINT prints a text expression specified in the operator to a file 
specified in the operator. 
RENAME renames a file specified in the operator. 
A detailed discussion of the DISPLAY operator will serve to exemplify the 
principles involved in the above operators. 
15. Detailed Discussion of the DISPLAY Operator 
In the following, a discussion of the syntax and function of the DISPLAY 
operator will be followed by a discussion of the implementation of the 
operator. The syntax of the DISPLAY operator will be shown using the 
following conventions: 
1. Upper-case names indicate terms 211 or expressions. An expression may be 
anything which has a value, including a term 211. 
2. Square brackets indicate optional items. 
In a presently-preferred embodiment, there are two classes of the DISPLAY 
operator. Evaluation of a term 211 defined with class of the operators 
results in the display of text; the other results in the display of an 
image. Beginning with the first class, there are two operators: DISPLAY 
and DISPLAY FILE. With the DISPLAY operator, the displayed text is 
internal to the definition-based expert system; with the DISPLAY FILE 
operator, the text is contained in a MSDOS file. 
The syntax of the DISPLAY operator is as follows: 
EQU display TEXT-EXPRESSION [TEXT-EXPRESSION . . .] 
DISPLAY thus specifies a list of one or more text expressions to be 
displayed. The text expression may be any construct in the definion-based 
expert system which yields a text string as a value. The expression may 
thus be a constant, a term 211 which evaluates to a text string, or a 
combination of constants, terms 211, and operators which yield text string 
results. Of course, as in other definitions, if a term 211 in the DISPLAY 
operator has not yet been defined, definition processor 207 will request a 
definition for the term. For example, a term 211 SAY.sub.-- HI defined 
with the following display operator: 
EQU display "Hi" 
would, when evaluated, cause "Hi" to appear on the display. 
With DISPLAY FILE, the text is contained in an MSDOS file external to the 
definition-based expert system. The syntax of DISPLAY FILE is 
EQU display file TEXT-EXPRESSION 
For this operator, the value of TEXT-EXPRESSION must be the name of a MSDOS 
text file. Evaluation of the term 211 defined with this operator causes 
the contents of the file identified by TEXT-EXPRESSION to appear on the 
display. 
The first of the two display operators for images is DISPLAY PICTURE, which 
displays an image which is stored in a MSDOS file in one of a number of 
standard image formats. The syntax is as follows: 
EQU display picture TEXT-EXPRESSION [SIZE] 
The value of TEXT-EXPRESSION must be the name of an MSDOS file containing 
the image. SIZE may have one of four values which determine the initial 
size of the image: tiny, small, normal, and large. When the term 211 
defined with the operator is evaluated, the image in the file appears on 
the display. 
The second display operator for images displays an image which is provided 
by a Wang Laboratories, Inc. image management system called PC-WIIS. 
PC-WIIS is implemented in personal computers of the IBM PC type which are 
running the MSDOS WINDOWS display management system. The operator has the 
syntax: 
EQU display "*WIIS*" TEXT-EXPRESSION 
In this case, the value of TEXT-EXPRESSION must be the pathname of a 
PC-WIIS image file. When the term 211 defined with this operator is 
evaluated, PC-WIIS displays the image in the file on the display. 
The side effect operators, like the operators previously discussed in the 
application, are implemented by means of LISP functions which are stored 
in LISP environment 501 (FIG. 5) and executed by LISP interpreter 603. 
LISP environment 501 includes built-in LISP functions which open MSDOS 
files, close them, read them, delete them, and indicate whether a given 
MSDOS file exists. These functions are used to implement the LISP 
functions for the DELETE, RENAME, DISPLAY, and DISPLAY FILE operators. The 
other functions are implemented by means of a built-in LISP sys:dos 
function which specifies a program to be executed by MSDOS and parameters 
for the program. When the LISP interpreter executes the sys:dos function, 
the result is a software interrupt to MSDOS, which interrupts execution of 
the LISP interpreter and executes the program specified in the sys:dos 
function. At the end of execution of the program specified in the sys:dos 
function, execution of the LISP interpreter resumes. 
The DISPLAY operators for images may serve as examples of the use of 
sys:dos. In the case of DISPLAY PICTURE, the program executed by means of 
sys:dos determines the format of the image to be displayed and then 
displays the image; after the display execution of the LISP interpreter 
resumes. In the case of the version of DISPLAY used to display PC-WIIS 
images, the operator presupposes that the user first executes the MSDOS 
WINDOWS display management program, then executes PC-WIIS from MSDOS 
WINDOWS as required to initialize the PC-WIIS image system, and thereupon 
executes the definition-based expert system of the present invention out 
of MSDOS WINDOWS. Under these circumstances, the LISP sys:dos function 
results in the execution of the program specified in the sys:dos function 
results in the execution of the program specified in the the program 
specified in the sys:dos function simply calls a PC-WIIS routine which 
opens the image file specified in the function, calls another PC-WIIS 
routine which displays the image in the on the display, and then responds 
to a keystroke input by the user by calling a third PC-WIIS routine which 
closes the image file and then returning. Upon return, the LISP 
interpreter again resumes. In the automatic realtor application discussed 
above, the images of the houses are managed by PC-WIIS, and the DISPLAY 
"*WIIS*" operator causes the display of the images. 
16. The CALL Operator 
The CALL operator specifies a non-LISP function which is invoked when the 
term 211 defined with the operator is evaluated. The value returned by the 
function becomes the value of the term. As is apparent from the foregoing, 
the non-LISP function may either be invoked primarily for the value it 
returns or for the side effects which are produced by its execution. The 
operator has the following syntax: 
______________________________________ 
call TEXT-EXPRESSION [, using SPEC-LIST] [, returning 
NUMBER SPEC] 
______________________________________ 
When evaluated, TEXT-EXPRESSION must yield the name of the non-LISP 
function being invoked. The function may be any function which follows the 
interface standards of the C programming language. SPEC-LIST is a list of 
expressions specifying the values of the actual arguments for the non-LISP 
function being invoked. In a preferred embodiment, the expressions must 
have scalar or string values. When the non-LISP function is a mathematical 
function, the type of the value it returns may be specified using 
NUMBER-SPEC. The choices are double, float, int, long, unsigned int, and 
unsigned long. The default is int. 
In a preferred embodiment, the call operator is implemented using an 
external program interface which permits the LISP interpreter to make 
calls to non-LISP programs when no operating system intervention is 
required for the call. The external program interface includes an EPI.EXE 
file which includes executable code for all of the functions specified in 
call operators and executable code which sets up and performs the calls. 
New functions are added to the EPI.EXE file simply by using a linker to 
link their executable code into EPI.EXE. Setting up and performing a call 
in a preferred embodiment is complicated by the fact that the LISP 
interpreter runs in protected mode in extended memory, while the 
executable code in EPI.EXE execute in real mode in base memory. 
Consequently, when a term 211 defined with the call operator is evaluated, 
the processor must switch from protected to real mode and the code in 
EPI.EXE which calls the function specified in the call operator must copy 
the values of the actual arguments from extended memory to base memory, 
performing any necessary type conversions as it does so. On return, the 
reverse happens: the code in EPI.EXE must copy the values of the actual 
arguments and the returned value from base memory to extended memory, 
performing any type conversions as it does so, and on return from EPI.EXE, 
the processor must switch from real mode to protected mode. 
17. Table Terms and Values 
The definition-based expert system as described in the parent of the 
present application permitted terms 211 having Boolean, arithmetic, and 
character-string values and defined operations involving those value 
types. The improved definition-based expert system described herein 
further permits definition of terms 211 as tables and fields in tables and 
operations on table values. A table is arranged in rows and columns. Each 
column is specified by a term 211, and the values contained in one of the 
colmns serve as a key by means of which a given row may be selected. For 
example, a term 211 called CLIENTS might have columns specified by the 
terms 211 NAME, ADDRESS, nd TELEPHONE and a row for each client. The row 
for a single client might look like this: 
______________________________________ 
NAME ADDRESS PHONE 
______________________________________ 
Smith, John 
303 W. First St., New York, NY. 
301-666-5555 
______________________________________ 
If NAME served as the key, the row could be specified by means of "Smith, 
John". 
In the improved definition-based expert, a term may represent one of two 
kinds of tables. The first kind is a base table. Base tables actually 
contain data values. The data values may be specified in definition 213 of 
the base table, may be obtained from the user by means of the ASK 
operator, or may be obtained from an external file. The second kind is a 
query table. A query table is a table which is produced by a query 
operation from a base table or another query table. For instance, a table 
NEW.sub.-- YORK.sub.-- CLIENTS might be defined from CLIENTS by running a 
query operation which extracted all rows from CLIENTS in which ADDRESS 
specified New York, N.Y. 
Table operators may used with either kind of table. The operators include 
the following: 
Look-up operators for obtaining the value of a field specified by a term 
211 from a row; 
aggregate operators for obtaining values derived from all of the fields in 
a table specified by a given term 211; 
quantifying operators for obtaining Boolean values derived from all of the 
fields in a table specified by a given term 211. 
The following will first deal with the definition of base tables, then with 
the definition of query tables, and finally with the table operators. 
18. Defining Base Tables 
In a preferred embodiment, the syntax used to define a term 211 as having a 
base table as its value may define a base table which employs a numeric 
key field or one which employs a character-string key field: 
______________________________________ 
table with number key NUMBER-TERM 
table with text key TEXT-TERM 
______________________________________ 
In the case of the base table with the numeric key field, NUMBER-TERM is 
the term 211 which identifies the column of the table whose numeric values 
will be used as keys; in the case of the base table with the text key 
field, TEXT-TERM is the term 211 which identifies the column of the table 
whose text values will be used as keys. The table operator which defines 
CLIENTS looks like this: 
EQU table with text key NAME 
Terms 211 identifying columns in the table are defined by means of the 
FIELD OF operator. The syntax depends on whether the values are specified 
in definition 213 or are obtained externally. In the first case, the 
syntax is: 
EQU field of TABLE TERM, values VALUE-LIST 
The TABLE-TERM is a term 211 representing a table value; the values in 
VALUE-LIST are constants have the type required by the values contained in 
the column identified by the term 211 being defined. If the field being 
defined was specified as a key in the table definition, the number of 
values in the list determines the number of rows in the table. For 
example, in the case of CLIENTS, the field NAME might be defined like 
this: 
______________________________________ 
field of CLIENTS, values "Smith, Adam" "Smith, John" 
"Smith, David" 
______________________________________ 
defines a CLIENTS table with three rows. 
The syntax for specifying that the values for a column of a table are to be 
obtained externally is the following: 
______________________________________ 
field of TABLE-TERM, ask [QUOTED-TEXT [, for every 
TABLE-OR-QUERY-EXPRESSION]]] 
______________________________________ 
TABLE TERM is again the term 211 for the base table in which the term 211 
being defined specifies a column. "ask" indicates that the values for the 
specified column are to be obtained interactively from a user at a 
terminal. QUOTED-TEXT specifies a prompt string to be output when the user 
is asked. If nothing further is specified the definition-based expert 
system will output any prompt and the value of the key field for the row 
and wait for user input. For example, ADDRESS might be defined like this: 
EQU field of CLIENTS, ask "What is the address of" 
For each row in CLIENTS, the expert system will output the prompt followed 
by the value of NAME for that row and wait for the user to provide the 
address. As will be explained in more detail below, The inputs may be 
restricted to rows meeting specific criteria by means of the optional "for 
every TABLE-OR-QUERY-EXPRESSION". For example, ADDRESS in CLIENTS might be 
defined as follows: 
______________________________________ 
field of CLIENTS, ask "Please input the address of", for 
every CLIENTS where NAME is "Smith, John" 
______________________________________ 
This will cause the user to be asked only for John Smith's address, and 
that address will be written to the ADDRESS field of the row containing 
"Smith, John" as its NAME value. As may be seen from the foregoing, a 
given table may have columns filled using ASK and others filled using 
VALUES. If ASK is used to fill fields specified as a key in the table 
definition, the size of the table will depend on the number of fields 
filled. 
Additionally, a term 211 may be defined as a table which is stored in a 
MS-DOS file. In that case, definition 213 is as follows: 
EQU dosfile table 
The expert system shell of the present invention responds to such a 
definition with a sequence of menus which permit the developer of the 
application to specify which MS-DOS file contains the table's data and how 
the terms 211 defining columns in the table relate to fields in the MS-DOS 
file. Definitions for such tables do not contain ask operators or value 
operators. 
19. Defining Query Tables 
A query table is a query table which is defined by means of a query 
operation on a base table or another query table. The syntax of the query 
table definition is the following: 
EQU TABLE-OR-QUERY-TERM where BOOLEAN-EXPRESSION 
The TABLE-OR-QUERY-TERM specifies the base or query table from which the 
rows are selected; the BOOLEAN EXPRESSION specifies the condition under 
which a row is to be selected. For example NON.sub.-- JOHN.sub.-- 
SMITH.sub.-- TABLE could be defined as follows: 
EQU CLIENTS where NAME is not "Smith, John" 
The resulting query table will have all of the rows of CLIENTS except the 
row where NAME has the value "Smith, John". As noted above, the "where 
BOOLEAN EXPRESSION" operator may also be used to control which rows are 
selected for interactive input to a base table using the "ask" operator. 
20. Operations on Tables 
Once a table has been defined as set forth above, terms 211 may be defined 
by specifying operations on the table. The simplest operation is selecting 
a field from a specified row. The operator that does this is the OF 
operator: 
EQU FIELD-NAME-TERM of ROW-SPECIFYING-TERM 
The FIELD-NAME-TERM is the term 211 identifying a field in the row. The 
ROW-SPECIFYING-TERM is a term 211 whose definition specifies a single row. 
definition 213 may thus define a base table having only a single row or a 
query table having only a single row. For example, the query table 
JOHN.sub.-- SMITH.sub.-- TABLE might be defined as 
EQU CLIENTS where NAME is "Smith, John" 
JOHN.sub.-- SMITH.sub.-- TABLE thus consists of a single row, and an of 
operator defining a term JOHN.sub.-- SMITH.sub.-- ADDRESS would look like 
this: 
EQU ADDRESS of JOHN.sub.-- SMITH.sub.-- TABLE 
Aggregate operators are operators which produce a result based on part or 
all of the data contained in a column of a table. The operators return 
text, arithmetic, or Boolean values. The text aggregate operator is 
COLLECT, which makes a text string consisting of values from a column. A 
new line character is appended to the end of each value in the string. The 
operator has the syntax: 
______________________________________ 
collect FIELD-TERM-TEXT-EXPRESSION for every 
TABLE-OR-QUERY-EXPRESSION 
______________________________________ 
FIELD-TERM-TEXT-EXPRESSION is an expression whose definition involves a 
term 211 which identifies a column in the table specified by 
TABLE-OR-QUERY-EXPRESSION. The COLLECT operator then makes a text string 
as specified by FIELD-TERM-NAME-EXPRESSION of the values in the field. 
Here and in the following, TABLE-OR-QUERY-EXPRESSION may of course include 
a WHERE operator as described above. For instance, a term 211 NAME.sub.-- 
LIST might be defined like this: 
EQU collect NAME for every CLIENTS 
NAME.sub.-- LIST would have the character-string value 
______________________________________ 
"Smith, Adam 
Smith, John 
Smith, David" 
______________________________________ 
An important aspect of the fact that an expression involving a field name 
can be used in the COLLECT operator is that the value defined by the 
COLLECT operator may be computed from the value returned from the fields. 
The arithmetic aggregate operators include operators for obtaining the 
average of the values in the fields, the maximum of the values in the 
fields, the minimum of the values in the fields, the total of the values 
in the fields, the number of fields, and the percent of the fields meeting 
a given condition. The average operator can stand as an example for 
average, maximum, minimum, and total. The syntax is the following: 
______________________________________ 
average FIELD-TERM-NUMBER-EXPRESSION for every 
TABLE-OR-QUERY-EXPRESSION 
______________________________________ 
FIELD-TERM-NUMBER-EXPRESSION is an expression whose evaluation involves a 
term 211 specifying a number field in a base table or query table defined 
by TABLE-OR-QUERY-EXPRESSION. Again, the use of an expression involving 
the field term permits specification of computation on the result returned 
by the operator. 
The COUNT EVERY operator simply counts the number of rows in a specified 
table. The syntax is as follows: 
EQU count every TABLE-OR-QUERY-EXPRESSION 
For example, a term 211 NUMBER.sub.-- OF.sub.-- CLIENTS could be defined as 
follows: 
EQU count every CLIENTS 
With the table CLIENTS of the present example, NUMBER.sub.-- OF.sub.-- 
CLIENTS would have the value 3. 
The PERCENT WHERE operator determines what percentage of the values of a 
specified field in a table fulfill a specified condition. The operator has 
the syntax 
______________________________________ 
percent TABLE-OR-QUERY-TERM where 
FIELD-TERM-BOOLEAN-EXPRESSION 
______________________________________ 
TABLE-OR-QUERY-TERM specifies the base table or query table upon which the 
operation is being performed, and FIELD-TERM-BOOLEAN-EXPRESSION is a 
Boolean expression involving a term 211 specifying one of the fields in 
the specified table. For instance, a PERCENT.sub.-- JOHN.sub.-- SMITH term 
211 might be defined as follows: 
EQU percent CLIENTS where NAME is "Smith, John" 
PERCENT.sub.-- JOHN.sub.-- SMITH would have the value "33" because "Smith, 
John" is one of three rows in the table. 
The Boolean aggregate value operators are FOR EVERY, which determines 
whether a Boolean expression involving a term 211 which is a field name is 
true for every row of the table, and FOR SOME, which determines whether 
such a Boolean expression is true for any row of the table. The syntax of 
FOR SOME is exemplary for both: 
______________________________________ 
for some TABLE-OR-QUERY-EXPRESSION, 
FIELD-TERM-BOOLEAN-EXPRESSION 
______________________________________ 
TABLE-OR-QUERY-EXPRESSION specifies the base table or query table upon 
which the operation is being performed and the 
FIELD-TERM-BOOLEAN-EXPRESSION is a Boolean expression involving a term 211 
specifying a field in the table. An example would be a definition for a 
term IS.sub.-- JOHN.sub.-- SMITH.sub.-- THERE?, which would look like 
this: 
EQU for some CLIENTS, NAME is "Smith, John" 
As may be seen from the foregoing table values and table terms 211 
represent a major enhancement of the rule-based expert system. Terms 211 
may now represent ordered collections of data and fields within the 
collections, and operators on tables permit the definition of query tables 
and operations which for both types of tables permit retrieval of 
individual field values and computation of results depending on the values 
in an entire column. 
21. "Don't Know" Values 
A problem of the definition-based expert system as originally implemented 
was that it could not adequately handle user responses which indicated 
that the user did not know the answer to a question addressed him by the 
expert system. This problem has been overcome by permitting designers of 
the definition-based expert systems of the present invention to add a 
"don't know" value to each of the classes of scalar values used in the 
definition-based expert system and add the notion of "don't know 
dependency" for scalar values and table values which are not themselves 
"don't know" values but are dependent on "don't know" values. Where "don't 
know" values are specified, users of the system may provide "don t know" 
as a possible input to the system. Provision of the value in a preferred 
embodiment is by means of a function key or by means of selection from a 
drop-down menu. 
For example if "don't know" values are specified and the field PHONE of 
CLIENTS is defined as follows: 
EQU field of CLIENTS, ask "What is the telephone number of" 
the user can specify "Don't know". If the user so specifies, the value of 
PHONE for that field is "Don't know". Assuming that "Don't know" was the 
answer for the row for which NAME has the value "Smith, John", a term 211 
JOHN.sub.-- SMITH.sub.-- PHONE defined with 
EQU PHONE of JOHN.sub.-- SMITH.sub.-- TABLE 
would specify PHONE for that row and would have the value "Don't know". 
Further, the value of a term 211 PHONE.sub.-- LIST defined for the field 
PHONE with the COLLECT operator would be "don't know dependent" because at 
least one of the values in the column defined by PHONE is a "don't know" 
value. Assuming that only John Smith's phone was not known, the 
PHONE.sub.-- LIST definition 
EQU collect PHONE for every CLIENTS 
would yield a value like: 
______________________________________ 
"555-1111 
666-2222" 
______________________________________ 
Moreover, the definition-based expert system will associate a "don't know" 
dependency indication with the value, i.e., an indication that a "Don't 
know" value was involved in its computation. In this case, the indication 
specifies two things: the location in the value which would have been 
occupied by the "don't know" value and that one of the three fields in the 
column has a "don't know" value. 
Evaluation of a term 211 defined with almost any operator available in the 
definition-based expert system may involve evaluation of another term 211 
which has a "don't know" value. In a preferred embodiment, the general 
rules for the determination of the value of a term 211 where a "don't 
know" value is involved are the following: 
1. If the value of the result is independent of the "don't know" value, the 
result is returned without any indication of don't know dependencies. 
2. If the value of the result is dependent from the "don't know" value and 
no value can be determined without the "don't know" value, the returned 
result is "don't know" with an indication of "don't know" dependencies. 
3. If the value of the result is dependent from the "don't know" value but 
some value can be determined without the "don't know" value, the returned 
result is the value so determined with an indication of "don't know" 
dependencies Such a result is termed an estimate. 
An example for the first two rules is given by the behavior of the MULTIPLY 
operator indicated by "*" when one of its operands has a value of "don't 
know.". If the other operand has the value 0, the operator returns 0, 
since that result is independent of the value of the other operand. 
Otherwise, the MULTIPLY operator returns "don't know". An example for the 
third rule is the COLLECT operator. As shown by the example, if a field of 
the collected column has the value "don't know", COLLECT ignores that 
field when it makes the result string. 
The indication of "don't know" dependencies which is returned along with 
"don't know" or an estimate includes the term 211 from the hierarchy of 
definitions for the term 211 being evaluated whose value is directly 
dependent on "don't know" and when the value is an estimate, estimate 
information which indicates the extent to which the estimate is affected 
by "don't know" values. The content of the estimate information depends on 
the operator which produced the estimate. Generally speaking, when the 
estimate is a string value, the estimate information includes the index of 
the position in the string which the first component having a "don't know" 
value would have occupied. When the estimate is produced by an operator 
such as AVERAGE which examines the contents of all of the fields of a 
column, the estimate information includes the total number of fields of 
the column and the number of fields with "don't know" values. An operator 
such as COLLECT, which both produces a string and examines the contents of 
all of the fields of a column, has estimate information including both the 
position of the first "don't know" value in the result string and the 
total number of fields and the number of fields with "don't know" values. 
In a preferred embodiment, there are two special Boolean operators which 
permit detection of "don't know" values and estimates. The first detects 
"don't know" values and has the syntax: 
EQU TEXT-NUMBER-BOOLEAN-EXPRESSION=don't know 
The operator returns the value TRUE if the expression has the value "don't 
know" and otherwise returns false. An example of its use would be in a 
definition of DONT.sub.-- KNOW.sub.-- ABOUT.sub.-- JOHN.sub.-- 
SMITH.sub.-- PHONE which looked like this: 
EQU JOHN.sub.-- SMITH.sub.-- PHONE=don't know 
Since the value of JOHN.sub.-- SMITH.sub.-- PHONE is the value of the PHONE 
field for John Smith's row of CLIENTS, DONT.sub.-- KNOW.sub.-- 
ABOUT.sub.-- JOHN.sub.-- SMITH.sub.-- PHONE has the value TRUE. The second 
detects estimates and has the syntax: 
EQU TEXT-NUMBER-BOOLEAN-EXPRESSION=don't know estimate 
The operator returns the value TRUE if the expression is an estimate and 
otherwise returns FALSE. An example of its use would be a definition of 
PHONE.sub.-- LIST.sub.-- INCOMPLETE which looked like this: 
EQU PHONE.sub.-- LIST=don't know estimate. 
Here, PHONE.sub.-- LIST is an estimate, so PHONE.sub.-- LIST.sub.-- 
INCOMPLETE will have the value TRUE. 
22. Implementation of Don't Know Values 
As previously pointed out, operators are implemented in a preferred 
embodiment by means of LISP functions. In the preferred embodiment, the 
functions for the operators return lists. The implementation of "don't 
know" values in a preferred embodiment takes advantage of this feature and 
of a built-in LISP special symbol, NIL. The value of NIL in LISP is the 
empty list and, in contexts requiring Boolean values, the value FALSE. NIL 
is used in the preferred embodiment to represent "don't know". To 
distinguish NIL from Boolean values, the present embodiment has defined 
yes-no operations. These operations work like Boolean operations, except 
that the LISP Boolean primitive symbol T has been replaced by the symbol 
YES and the Boolean primitive symbol NIL has been replaced by the symbol 
NO. 
In the preferred embodiment, the list returned by a function always has as 
its first element the value required by the term 211 defined by means of 
the function. If there are "don't know" dependencies, the first element 
will itself be a list. The first element of that list will be the returned 
value, i.e., either NIL representing "don't know" or an estimate. The next 
element is the don't know dependency indication. If the returned value is 
NIL, the dependency indication is a list of the terms 211 whose "don't 
know" values made return of the "don't know" value necessary. If the 
returned value is an estimate, the dependency indication is a list in 
which each element is a list consisting of a term whose "don't know" 
values made the estimate necessary and the estimate information. For 
example, the required value returned by PHONE.sub.-- LIST would be a list 
of the following form: 
______________________________________ 
("555-1111 
666-2222" 9 (PHONE 1 3)) 
______________________________________ 
The text string is of course the string made by the COLLECT function; the 
value 9 is the index (counting the new line character) of the position of 
the first "don't know" value in the text string; PHONE is the field name 
for the column which COLLECT read to obtain the string; 1 3, finally, 
indicate that there was 1 "don't know" value out of three total fields. 
The advantages of a definition-based expert system with "don't know" values 
which have the properties just described are clear. Beyond making it 
possible for a user to indicate that he doesn't know, the definition-based 
expert system can determine whether the "don't know" makes a difference 
and if it does, whether an estimate is possible. Moreover, the "don't 
know" dependency information makes it possible for the definition-based 
expert system to determine which terms 211 are the sources of the 
dependency and in the case of the estimate, to determine to what extent 
the "don't know" values may affect the value for which the estimate has 
been made. 
23. A Document Generation System Employing the Definition based Expert 
System 
The definition-based expert system disclosed in sections 1-22 above becomes 
a document generation system with the addition of a single new operator. 
The operator is called the wp text operator. The following disclosure will 
first describe the wp text operator, then discuss an example document 
template, thereupon provide an overview of the implementation of the wp 
text operator in a preferred embodiment, and finally present details of 
the preferred embodiment. 
24. The WP TEXT Operator 
The wp text operator is used to define terms 211 of the text type as 
portions of a template document written using the WP+ editor produced by 
Wang Laboratories, Inc. The WP+ editor is disclosed in detail in U.S. Pat. 
No. 4,633,430, James Lee Cooper, Control Structure for a Document 
Processing System, issued 12/30/86, which is hereby incorporated by 
reference into the present disclosure. The wp text operator has the 
syntax: 
EQU wp text [if YES-NO-EXPRESSION] 
When the definition-based expert system evaluates term 211 defined by the 
operator, the term 211's value is the portion of the template document 
specified by the term's definition. When the definition-based expert 
system is being used as a document generation system, the value of term 
211 defined by the wp text operator is output to the output document being 
produced by the document generation system. When the optional 
EQU if YES-NO-EXPRESSION 
is present, the term 211 defined by the wp text operator is evaluated only 
if the YES-NO-EXPRESSION evaluates to YES; if it evaluates to NO, the term 
211 is not evaluated; if the YES-NO-EXPRESSION evaluates to a "don't know" 
value as described in section 21 above, the term 211 evaluates to the 
string "don't know". 
For example, a document generation system which generates wills defines a 
term 211 DIST-LIFE-INSURANCE ON CHILD which evaluates to the clause from 
the template document for distribution of life insurance to a child as 
follows: 
EQU wp text if TRANSFER-INS-ON-CHILD 
TRANSFER-INS-ON-CHILD is a yes-no term 211 which is defined as the user's 
response to the question, "Does the client wish to transfer interest in 
life insurance on any children to children and descendents?". When a will 
is generated using the will generation system, the person for whom the 
will is being generated answers the question. If the answer is yes, the 
template portion identified by DIST-LIFE-INSURANCE-ON-CHILD is included in 
the will; if the answer is no, it is not; if the answer is "don't know", 
the term 211's value is that string. 
As may be seen from the foregoing, a document may be defined by simply 
concatenating string terms defined with the wp text operator. For 
instance, the will generation system includes the text term GENERATE WILL, 
which is defined as follows: 
______________________________________ 
WILL-TITLE; 
REVOKE-PRIOR-WILL; 
DISTRIBUTION; 
UNDER-AGE-PROVISION; 
PAYMENT-OF-DEBT; 
CUSTODY-OF-MINORS; 
MISC-PROVISIONS; 
EXECUTORS 
______________________________________ 
The ";" is a concatenation operator, and each of the terms 211 being 
concatenated is either itself a wp text term or a concatenation of wp text 
terms. Thus, when GENERATE WILL is evaluated, its value is a concatenation 
of the template portions defined for the wp text terms. In document 
generation, that value is produced in a WP+ document. In a preferred 
embodiment, producing the value in a WP+ document involves two steps: in a 
first step, a value is produced which includes a list of the WP text terms 
in the order in which the template portions they represent are to appear 
in the output document; in a second step, the template portions on the 
list are copied from the template document to the output document in the 
order in which they appear on the list. 
In a preferred embodiment, there are two methods of defining terms 211 with 
the wp text operator. In the first method, when a user of expert system 
shell 201 defines a term 211 using the wp text operator, a component of 
expert system shell 201 automatically run the WP+ editor produced by Wang 
Laboratories, Inc. The user of shell 201 then uses the WP+ editor to add 
the text represented by the term 211 to the template document. In the 
second method, the user of shell 201 uses WP+ independently of shell 201 
to compose the template document. The names of the wp text terms 211 are 
included in the template document. When this approach is used, the user 
provides the template document name to shell 201, which then reads the 
document and asks the user whether he wishes to add the wp text terms 211 
defined in the template document to the knowledge base. If the user wishes 
to add a term, shell 201 makes a definition for the term. 
As will be described in more detail below, the text may include other terms 
211. These terms 211 are called merge terms. When definition processor 207 
adds the new wp text term 211 representing the text to term store 215, 
definition processor 207 checks the merge terms in the text to determine 
whether they have definitions in TS 215; if they do not, the user of shell 
201 is prompted to provide a definition as described at section 5 above. 
When a wp text term 211 is evaluated by inference engine 219, each merge 
term in the portion of the template which defines the wp text term is 
evaluated; when the portion of the template 1001 represented by w text 
term 211 is output to the output document, each merge term in the template 
portion is replaced by the merge term's value. If the merge term's value 
is "don't know", a string of that value replaces the merge term. In a 
preferred embodiment, a merge term may be another term 211 defined with 
the wp text type. 
25. The Template Document: FIG. 10 
FIG. 10 shows an example of a template document 1001 used in a preferred 
embodiment to define wp text terms. In a preferred embodiment, template 
document 1001 is written using the WP+ editor. In the figure, the portion 
of template document 1001 which defines a wp text term appears as a 
fragment 1002. Each fragment 1002 begins with fragment term 1003, which is 
identical with the wp text term 211 defined by the fragment and ends with 
a colon (:). The fragment term 1003 and the colon 1009 are identified by a 
fragment term attribute which the WP+ editor assigns to the text string 
representing fragment term 1003 and to colon 1009 In FIG. 10, text with 
the fragment term attribute is represented by text in upright bold face 
type. 
The text between fragment term 1003 and the colon is fragment text 1005. As 
previously indicated, fragment text 1005 may include merge terms, shown in 
FIG. 10 with the reference number 1007. A merge term 1007 is identified in 
fragment text 1005 by a merge term attribute which the WP+ editor assigns 
to the text string representing merge term 1007. In FIG. 10, text with the 
merge term attribute is represented by underlined italic bold face text. 
The merge term Client may serve as an example of merge terms 1007 
generally. Client is a text term which is defined as a field of a table 
term which contains the name of the client. When a will is produced, 
Client is replaced by the name from the table term. In a preferred 
embodiment, when the first letter of a merge term 1007 other than a wp 
text merge term 1007 is capitalized, the first letter of the value which 
replaces the merge term is also capitalized. In a preferred embodiment, 
the editor also responds to the fragment term attribute and the merge term 
attribute by altering the manner in which text strings having those 
attributes are displayed or printed. Consequently, a user of the document 
generation system can determine from a display or printed output of 
template document 1001 which text string is the fragment term 1003 being 
defined by the fragment and which included text strings are merge terms 
1007. Template document 1001 may additionally include comments, i.e., text 
which is included in template document 1001 but is not part of any 
fragment 1002. In a preferred embodiment, text which belongs to a comment 
is indicated by a comment attribute. Again, the comment attribute alters 
the manner in which text strings having the attribute are displayed or 
printed. 
26. Overview of Implementation of the wp text Operator in a Preferred 
Environment: FIG. 11 
FIG. 11 is a block diagram of the implementation of a document generation 
system 1102 based on the use of the WP text operator in the 
definition-based expert system shown in FIG. 2. FIG. 11 shows definition 
processor 207, term inference engine 219, and term store 215 from that 
figure and the additional components required for the WP text operator. 
Portions of FIG. 2 which do not appear in FIG. 11 are understood to be the 
same as in FIG. 2. As in FIG. 2, arrows show the flow of data between the 
components. The additional components are WP text operator defining 
component 1101 of definition processor 207, WP text solving component 1103 
of term inference engine 219, editor 1105, index 1106, template document 
1001, and generated document 1111. In a preferred embodiment, components 
1101 and 1103 are LISP functions executed by LISP environment 561. 
Editor 1105 is a version of the WP+ editor which has been adapted to 
operate on a microprocessor running the MS-DOS (TM) operating system 
produced by Microsoft, Inc. LISP interpreter 501 employs the sys:dos 
function to invoke editor 1105, as described at the end of section 16 
above. Other editors may be employed in the same manner as the WP+ editor. 
Editor 1105 is understood to provide not only interactive editing, but 
also an application interface which permits other application programs to 
use the editor to perform editing operations on documents. 
Template document 1001 is a document which has the template text from which 
documents will be generated by the document generation system. In a 
preferred embodiment, the WP+ editor locates fragments 1002 in template 
1001 by means of named marks, i.e., names associated with locations in 
template 1001. Generated document 1111 is a document generated by the 
definition-based expert system from the values of the fragment terms 1003 
and any merge terms contained in fragment text 1005 for the fragment terms 
1003. Index 1106 is used for quick location of fragment terms 1003 and 
merge terms 1007 from template 1001. It contains a control record 
including the name of template document 1001 and the time and date at 
which template document 1001 was last altered by the definition-based 
expert system (CTL REC 1108 and two lists: FT List 1107, which is a list 
of fragment terms 1003 and the named marks by means of which the fragments 
can be located in template 1001, and MT list 1109, which is a list of the 
merge terms 1007 contained in fragment text 1005 of each fragment 1002. In 
a preferred embodiment, both lists are implemented by means of b-trees. 
Other implementations permitting quick search are of course possible. 
The foregoing new components are employed both in the definition of 
fragment terms 1003 and in the generation of documents using the fragment 
terms. The following discussion begins with the definition of fragment 
terms 1003 and continues with the generation of documents. 
27. Definition of Fragment Terms 1003 
When definion based expert system shell 201 is performing a DEFINE 
operation involving a fragment term 1003, the DEFINE function, described 
in Section 7 above, invokes WPT DEF 1101 and provides it with fragment 
term 1003. WPT DEF 1101 first asks the person making the definition 
whether fragment term 1003 is to be included in an existing template 1001 
or a new template 1001. If the user indicates a new template 1001, WPT DEF 
1101 asks for the name of the new template 1001 and WPT DEF 1101 uses 
sys:dos to invoke editor 1105 to create the document. If the user 
indicates that he wishes to link to an existing template 1001, WPT DEF 
1101 asks for the name of that template. 
Once WPT DEF 1101 has the name of template 1001, it determines whether 
there is an index 1106 for template 1001. If there is not, WPT DEF 1101 
creates index 1106 for the new template and places the name of the 
document in CTL REC 1108. The user next indicates whether he wishes to 
edit the template. If he does, WPT DEF 1101, creates a temporary document 
using editor 1105. WPT DEF 1101 then provides access to editor 1105 to the 
person creating the definition. That person uses editor 1105 to write 
fragment text 1005 represented by fragment term 1003 in the temporary 
document. In so doing, he gives any merge terms 1007 in fragment text the 
merge term attribute. When he is done, he leaves editor 1105 and WPT DEF 
1101 resumes execution. 
Next, WPT DEF 1101 makes an entry in FT List 1107 for fragment term 1003. 
The entry relates fragment term 1003 to a named mark by means of which 
editor 1105 can locate the fragment in template 1101. WPT DEF 1107 makes 
the named mark, termed henceforth a fragment name 1113, from fragment term 
1003. Fragment term 1003 may be of any practical length (the limit is 30 
characters in a preferred embodiment), but WP+ permits a maximum length of 
10 characters for a named mark. WPT DEF 1101 begins by simply truncating 
fragment term 1003 if necessary to obtain the fragment name; it then 
searches FT list 1107 to determine whether an identical fragment name 
already exists; if one does, WPT DEF 1101 makes the new fragment name 
unique. In a preferred embodiment, WPT DEF 1101 does this by working 
through a collating sequence of characters beginning with the last 
character in the fragment name. Until a unique fragment name is obtained, 
WPT DEF 101 replaces the last character in the fragment name with the next 
character in the collating sequence and then checks to determine whether 
the fragment name is unique. If no unique name is found using that 
collating sequence, the sequence is worked through again beginning with 
the second-to-last character in the name, and so forth. Once a unique 
fragment name is obtained, WPT DEF 1101 invokes editor 1105 to add 
fragment term 1003 to the end of template 1001 and to give fragment term 
1003 the fragment term attribute, then uses editor 1105 to create a named 
mark using fragment name 1113 in template 1001. The named mark indicates 
the location of the last character in fragment term 1003. The next step is 
to use editor 1105 to copy the fragment from the temporary document to 
template 1001. After this is done, the temporary document is deleted. The 
last step is to use editor 1105 to append colon 1009 to the fragment and 
to give colon 1009 the fragment term attribute. 
When all of this is done, WPT DEF 1101 uses editor 1105 to search for merge 
terms 1007 in fragment 1002 by searching for text having the merge term 
attribute. Each time editor 1105 finds a merge term and returns it to WPT 
DEF 1101, WPT DEF 1101 adds it to the list of merge terms 1007 for the 
fragment 1002 in MT List 1109. When all of the merge terms for fragment 
1002 are on MT list 1109, definition processor 207 takes each merge term 
1007 for the fragment and determines whether the merge term 1007 has a 
definition in term store 215. If it does not, definition processor 207 
requests the user to define the merge term 1007 as described in Section 5 
above. When WPT DEF 1101 returns to the DEFINE function, the DEFINE 
function creates a TERM 211 and DEF 213 for fragment term 1003 in Term 
Store 213 as described in Section 7 above. In a preferred embodiment, DEF 
213 includes the LISP symbol representing WPT Run 1103. Each fragment term 
1003 is defined as indicated above; as the user leaves shell 201, shell 
201 indicates the time and the date in CTL REC 1108. 
As previously explained, definition-based expert system shell also includes 
a REDEFINE operation for redefining previously-defined terms 211. When the 
term 211 being redefined is a fragment term 1003, REDEFINE 101 invokes WPT 
DEF 1101, providing WPT DEF 1101 with the fragment term 1003 to be 
redefined. In this case, WPT DEF 1101 employs editor 1105 to create a 
temporary document, then uses fragment term 1003 and FT List 1107 to 
obtain fragment name 1113 corresponding to fragment term 1003, provides 
fragment name 1113 to editor 1105 to locate the fragment 1002 identified 
by fragment term 1003 in template 1001, and thereupon employs editor 1105 
to copy the text following the end of fragment term 1003 to the temporary 
document. Copying continues until WPT DEF 1101 encounters colon 1009, 
which it recognizes from the fragment term attribute. The person 
redefining the term then uses editor 1105 to edit the text in the 
temporary document as described above. When the user is finished, WPT DEF 
1101 proceeds as described above, except that it deletes old fragment text 
1001 and replaces it with the new fragment text 1002 from the temporary 
document. 
As indicated above, a template document 1001 may be edited using editor 
1105 independently of definition-based expert system shell 201. In that 
situation, the person editing template document 1001 indicates a fragment 
term 1003 by using the WP+ editor to assign the fragment term attribute to 
the text string which is the fragment term 1003 and indicates a merge term 
1007 by using the WP+ editor to assign the merge term attribute to the 
text string which is the merge term 1005, and indicates the end of the 
fragment by using the WP+ editor to place colon 1009 at that point and 
assign colon 1009 the fragment term attribute. Editor 1105 automatically 
includes the time and date of editing of template document 1001 in the 
information which it maintains concerning the document. 
To include the new fragment terms 1003 in term store 215, the user of 
expert system shell links expert system shell 201 to the template document 
1001 as indicated above. If the template document 1001 is new, or if the 
time and date of editing are later than those indicated for the template 
document in CTL REC 1108, WPT DEF 1101 verifies template document 1001. It 
begins verification by deleting index 1106 and making a new index 1106 for 
template 1101. WPT DEF 1101 then determines for each fragment term 1003 
whether the fragment term 1003 is already defined in term store 215, makes 
a list of the undefined fragment terms 1003, and asks the user whether he 
wishes to add definitions to term store 215. If he does, the definitions 
are added as indicated above. In the course of defining an undefined 
fragment term 1003, WPTDEF 1101 searches fragment text 1005 for the 
fragment term 1003 for merge terms 1007 and processes each merge term 1007 
as described above. An advantage of permitting the user to select which 
undefined fragment terms 1003 he wishes to add to his term store 215 is 
that a template 1001 may be prepared having fragment terms 1003 for 
different applications and a user can select only those fragment terms 
1003 from the template 1001 which he requires for his particular document 
generation application. 
8. Generation of Document 1111 
In a preferred embodiment, generation of a document 1111 is a two step 
process. The first step is the generation of a script which includes 
fragment terms 1003 for all of the fragments 1002 which will appear in the 
output document; the second step is the generation of the output document 
from the script. 
In the first step, a user of definition-based expert system 202 asks expert 
system 202 to solve a text term 211 which is either a fragment term 1003 
or is defined as a concatenation involving fragment terms 1003. The 
general method employed by expert system 202 to solve a term is described 
in the discussion of the WHAT function in section 7 above. When the term 
being solved is a fragment term 1003, term inferencing engine 219 employs 
WPT SOLVE function 1103. The term inferencing engine provides each 
fragment term in order to WPT SOLVE, and WPT SOLVE evaluates the fragment 
term 1003 by determining from any condition contained in fragment term 
1003's definition whether the fragment text 1005 represented by the term 
is to be included in the output document. If it is, WPT SOLVE 1103 
provides fragment term 1003, suitably delimited, to the WHAT function as 
the value of fragment term 1003. If the fragment is to be included, WPT 
SOLVE 1103 further uses fragment term 1003 to locate fragment name 1113 in 
fragment term list 1107, employs editor 1105 and fragment name 1113 to 
locate fragment text 1005 in template document 1001, uses editor 1105 to 
locate each merge term 1007 in fragment text 1005, and provides each merge 
term 1007 to inference engine 219 for evaluation. Inference engine 219 
evaluates the term and retains any external values needed for its 
evaluation as described in Section 7 above. 
The result of operation of the WHAT function is the script. In the script, 
The fragment terms 1003 are delimited in the text value so that they are 
distinguished from other text in the text value and appear in the order in 
which the fragment text 1005 will appear in output document 1111. As with 
the results of the WHAT function generally, the script is displayed. 
Display of the script is advantageous because it permits a developer of a 
template 1001 a set of term definitions involving template 1001 to 
determine the correctness of the term definitions without generating 
document 1111. In other embodiments, no script may be displayed, the value 
provided to the WHAT function by WPT SOLVE may contain text 1005 with any 
merge terms 1007 replaced by their values, and the value provided to the 
WHAT function may be output directly to editor 1105 for inclusion in 
generated document 1111. 
When inferencing engine 219 displays the script, it offers the user the 
option of making generated document 1111; when the user elects to do so, 
WPT SOLVE 1103 asks the user for the name of generated document 1111, uses 
editor 1105 to create generated document 1111, and then reads the script. 
For each fragment term 1003 in the script, it uses FT List 1107 to obtain 
the corresponding fragment name 1113, provides the fragment name to editor 
1105 to locate fragment text 1005, uses editor 1105 to copy fragment text 
1005 from template 1001 to generated document 1111, then uses editor 1105 
to read fragment text 1105 in generated document 1111 until a merge term 
1007 is encountered, reads the merge term 1007, obtains the value of merge 
term 1007 from inferencing engine 219, which recomputes it using the 
stored external values, determines from MT List 1109 whether the merge 
term's value is to be capitalized, and uses editor 1105 to replace merge 
term 1007 with the stored value, capitalizing the first letter if MT List 
1109 so indicates. If the merge term 1007 is a fragment term 1003, WPT 
SOLVE 1103 proceeds as just indicated for the fragment 1002 represented by 
that fragment term 1003. 
29. Implementation Details of Template 1001 and Index 1106: FIGS. 12-14 
The documents employed in the preferred embodiment are all represented by 
means of the document structure used by the WP+ editor. FIGS. 12-13 show 
those aspects of the document structure which are relevant to the present 
invention. A further description of the document structure may be found in 
U.S. Pat. No. 4,751,740, T. Wright, Apparatus, Method, and Structure for 
Translating a Document Having One Structure into a Document Having Another 
Structure, issued 6/14/88. The portions of the patent which are of 
particular relevance are col. 13, line 21-col. 15, line 9, and FIG. 10. 
U.S. Pat. No. 4,751,740 is hereby incorporated by reference into the 
present disclosure. As may be seen from FIG. 13, in the document structure 
employed by the WP+ editor, the document is represented by means of a set 
of blocks which are addressable by block number. The blocks are all of the 
same size, but fall into three distinct functional groups: administrative 
blocks, index blocks, and text blocks. 
The administrative blocks appear in FIG. 13 as doc info blocks 1201 and 
document table 1203. Doc info blocks 1201 contain information about the 
document represented by the structure, including a field 1209 which 
indicates the time and date at which the document was last edited. As 
previously described, this field is used in the present invention to 
determine whether a template 1001 has been edited outside of 
definition-based expert system 201. Document table 1203 contains pointers 
1205 to a number of indexes; the only one which is of interest in the 
present context is a name index pointer 1207 to a name index which relates 
names to locations of text blocks. The name index is made up of one or 
more name index blocks 1209, only one of which is shown in FIG. 12. If 
more than one is required, chains and trees of name index blocks are 
constructed. Each name index block contains name index entries 1211 
arranged in alphabetical order. The entries which are of interest for the 
present discussion relate fragment names 1113 to locations of text blocks. 
The text blocks contain the text of the document. Each text block 1211 
contains a text portion 1213, in which the characters making up the text 
are stored, and an attribute portion 1215, which contains information 
concerning locations in text portion 1213. In a template 1001, the 
attribute portion contains the information which indicates that a sequence 
of characters in text portion 1213 is a fragment term 1003 or a merge term 
1007. The text blocks are organized into a doubly linked text block chain 
1217. In a template 1001, text block chain 1217 represents the fragments 
1002; two such fragments are shown in chain 1217. The beginning of each 
fragment 1002 may be located by means of the name index; fragment name 113 
is used to located name index entry 1211 for that name 113 and the block 
pointer is followed to the block which begins the chain When Editor 1105 
establishes a named mark, it splits blocks in text chain 1217 so that the 
position indicated by the named mark is the first character in text 1213 
of a text block 1211. Editor 105 further includes special routines 
available to application programs for returning information from doc info 
blocks 1201, for reading characters and attributes from text blocks 1211, 
for writing characters and attributes to text blocks 1211, for finding 
named locations in text block chain 1217, and for copying material to and 
deleting material from text block chain 1217. 
FIG. 13 shows short display attribute word 1301, the kind of attribute word 
used in template 1001 to indicate a fragment term attribute and a merge 
term attribute. The attribute words for the text in text 1213 of a text 
block 1211 are contained in that text block's attribute area 1215. The 
attribute words are stored in reverse order from the text, i.e., 
attributes applying to the first character in text portion 1213 are at the 
end of attribute portion 1215. As editor 1105 writes a text block 1211, it 
adds characters by working backwards from the beginning of text 1213; it 
adds attributes for the characters by working forwards from the end of 
attributes 1215; when there is no empty space between the end of text 1213 
and the end of attributes 1215, the block is full. When editor 1105 reads 
text from text 1213, it simultaneously reads the attributes in attributes 
1215 and provides codes indicating which attributes apply to the character 
currently being read. There are four fields in attribute word 1301: a type 
field, which indicates what kind of attribute the word represents, an 
auxiliary type field 1305 which offers additional information concerning 
the type, a start field, which indicates the position in text 1213 of the 
first character in a sequence of characters to which the attribute 
applies, and an end field 1309 which indicates the position in text 1213 
of the last character of the sequence. In a preferred embodiment, the 
fragment term attribute and the merge term attribute are indicated by 
different values in type field 1303. Using the information from attribute 
words 1301 for the fragment term and merge term attributes, WPTDEF 1101 
and WPTSOLVE 1103 are able to determine whether a sequence of characters 
in a fragment 1002 is a fragment term or a merge term and are able to 
identify the end of a fragment. 
FIG. 14 is a detail of entries in the components of index 1106. There is a 
single control record 1108 in index 1106 for a given template 1001. Two 
items of information are included: template name 1401, which is the name 
of template document 1001 to which index 1106 belongs, and last time 
edited 1403, which indicates the last time that WPT DEF 1101 changed 
template document 1101 to which index 1106 belongs. There is a fragment 
term list entry 1405 for each fragment in template 1001. As previously 
mentioned, the list is organized as a b-tree permitting rapid access of 
fragment term list entries 1405 by fragment term 1003. Each fragment term 
list entry 1405 contains a fragment term 1002 and fragment name 113 for 
the fragment 1002 identified by fragment term 1003. Finally, there is a 
merge term list entry 1407 for each merge term 1007 in each fragment 1002 
of template 1001. Again, the merge term list is organized as a b-tree 
permitting rapid access of merge term list entries 1407 for a fragment 
1002 by fragment term 1003 for the fragment 1002. Each merge term list 
entry 1407 contains fragment term 1003 for the fragment 1002 to which the 
merge term 1007 belongs, the merge term 1007 and a capitalization flag 
1409 which is set by WPT DEF 1101 to indicate that the first letter of the 
value which replaces the merge term 1007 when the merge term 1007 is 
solved is to be capitalized As previously indicated, the user of 
definition-based expert system shell 1201 indicates that the value should 
be capitalized by capitalizing the first letter of the merge term. The 
merge term entries 1407 for a given fragment term 1003 are arranged in MT 
List 1109 alphabetically by merge term 1007. 
The foregoing additional disclosure has shown how a document generation 
system may be developed using the definition-based expert system disclosed 
in sections 1-22 above, the WP+ editor, and a template document 1001 
produced by the WP+ editor. While definition-based expert system 201, the 
WP+ editor, and the document structure used by the WP+ editor are all 
particularly well-suited for implementing the invention, the invention may 
also be implemented using other types of expert systems, other editors, 
and other document structures. In particular, techniques other than those 
disclosed herein may be used to identify fragment terms and merge terms in 
template 1001, to permit location of fragments in template 1001, and to 
determine whether a fragment term or a merge term has already been 
defined. Further, in some embodiments, the step of producing a script may 
be omitted and the solve operation may result in the immediate output of 
the generated document. This being the case, the disclosed embodiments are 
to be considered in all respects as illustrative and not restrictive, the 
scope of the invention being indicated by the appended claims rather than 
the foregoing description, and all changes which come within the meaning 
and range of equivalency of the claims are intended to be embraced 
therein.