Adding ‘Sense’ to Conceptual Modeling: An Interdisciplinary

Approach

Veikko Halttunen

Faculty of Information Technology, University of Jyväskylä, Mattilanniemi 2, Jyväskylä, Finland

Keywords: Conceptual Modeling, Concept, Conception, Perception, Semantics, Consistency, Possible World.

Abstract: In this paper, our aim is to widen the prevailing foundations of conceptual modeling theories and practices,

particularly in the context of information systems development. The approach shifts the focus from the link

between a model and the modelled reality to the link between human cognition and the model. Our approach

combines theoretical issues of different disciplines relevant to conceptual modeling. We shall make an explicit

distinction between individual conceptions and interpersonal concepts and show how this distinction could

be utilized to have conceptual models of a better consistency. We wish that this article could also serve as a

starting point for a profound scientific discussion on the real sources of conceptual models, i.e. the human

mind.

1 INTRODUCTION

In this paper, our aim is a step towards the unification

of thought and language (see Almog, 2005) in the

context of conceptual modeling. Practically, the

target is to improve the logical consistency of

conceptual models by ensuring that the individual

interpretations of reality form a more consistent

whole.

It is widely acknowledged that conceptual

modeling (CM) is a crucial part of information

systems development (e.g. Clarke et al., 2016; Wand

& Weber, 2002). Especially, modern complex IT

applications, like big data systems, require solid CM

tools and practices (see Storey & Song, 2017).

Attempts to build a conceptual model of an enterprise

architecture, for example, may be an extremely

complex task (Halttunen et al.,2006).

While numerous models are needed before a

complex system is in action (see Wand, 1996), it can

be extremely difficult to have a shared view of what

all the models mean or even what they should

represent. So far, the researchers’ main concern has

been the accuracy and consistency of the modeling

language. Instead, human thinking and conception as

the starting point for, and the content of, a conceptual

model has gained less attention. This is surprising,

since the conflict not only between the modelers’

perceptions but also between modelers’ conceptions

is evident (see Easterbrook, 1991).

Considering conceptual modeling as semantic

modeling (e.g. Wand et al. 1999) implies that it is not

only a matter of detail-hiding or abstraction but also

of carrying meaning, or sense-making. While

formalization of conceptual models is an important

issue in the IS field (e.g. ter Hofstede & Proper,

1998), it is necessary to understand, how formalized

models could be produced from human cognition (see

Siau and Tan, 2005).

We suggest that the formalization of conceptual

models should start from the very first

communicative phases of an ISD process (e.g. see

Chen et al., 1999). Actually, there are several severe

attempts to take the social and communicative

perspectives into account, e.g. Soft Systems

Methodology by Checkland (1981), ETHICS by

Mumford (1983), speech act based methods like

SAMPO by Auramäki et al. (1988) as well as tools

and methods based on communicative genres (e.g.

Päivärinta, 2001). More philosophical discussions

can be found in Hirschheim et al. (1995), Lyytinen

(1985), and Hanseth and Monteiro (1994), for

example. Nevertheless, none of these contributions

deals thoroughly with the link between the informal

specifications and the more formal ones.

When considering the development of conceptual

modeling there are three relevant, interacting worlds:

the physical world, the individual world(s) and the

248

Halttunen, V.

Adding ‘Sense’ to Conceptual Modeling: An Interdisciplinary Approach.

DOI: 10.5220/0008069702480255

In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019), pages 248-255

ISBN: 978-989-758-382-7

interpersonal world(s). To describe and clarify the

three worlds and the linkages between them we shall

utilize both philosophy and linguistics. Especially, we

make use of the theories of meaning. We combine

semantics of ordinary language (e.g. Lyons, 1971)

with a more formal approach called possible worlds

semantics (e.g. see Copeland, 2002).

The rest of the paper is organized as follows. We

start by describing the problem. Next, we shall

provide the foundational concepts upon which we

build our approach. In Chapter 4, we consider human

consciousness as a philosophical-linguistic concern.

In Chapter 5, we present a simple conceptualization

model. In Chapter 6, we provide preliminary ideas

how traditional conceptual models can be extended

by features that help to link thinking and talking about

a domain to more formal specifications. Finally, we

sum up the ideas of the paper.

2 SEARCHING FOR THE

BUILDING BLOCKS OF THE

BRIDGE

In order to get semantically rich, yet logically

consistent models of a domain, the modeling process

should ensure (1) that the sense of the concepts is

understood and agreed by the relevant parties of the

domain, and (2) that the agreement is conceptually

consistent. Our assumption is that the easiness and

the quality of interpersonal target-oriented

communication is dependent on how consistent and

reasonable the individuals’ interpretations are. When

the worlds of individual conceptions are not logically

consistent, it is not possible to build a consistent

whole, while a consistent and inclusive individual

world can correct and complete other individual

worlds. Consider the following example.

Let there be four persons A, B, C, and D. Let there

also be two things with attributes: a red car and a

green book. One of the persons, say D, suffers from

red green color blindness. While perceptions of red

light for A, B and C are mapped to their conceptions

in a way that there is a correspondence between the

perceptions and the concept of ’red’, for D the

concept of ’red’ is purely abstract having no

particular content of perception. This is because he

cannot say, for example, whether the car is red or

green, what the color of the book is or, how the colors

differ from each other. This knowledge must be

communicated to him. However, D knows through

language that there are red and green things and that

these colors can be used, for example, to define other

concepts. Thus, he can build even a large conceptual

net in which part of the concepts has no

correspondence to his experiential world. In this case,

the shared concept of ‘red’ has referent in the real

world, while the conception of ‘red’ for D does not

have. The D’s conception of ‘red’ is based on the

others’ descriptions of ‘red’, and has the reference

only in the interpersonal mental world.

Even when the world of individual conceptions

has a direct link to the world we can hear, see, and

feel ─ physical world ─ the individual world is more

or less ambiguous, since it is based on (1) physical

phenomena, (2) internal cognition, and (3) social

construction. The last viewpoint is extremely

important (e.g. von Braun et al., 2000). The social

construction means that our internal mental states are

strongly affected by communicating and

compromising the individual conceptions of fellow

creatures.

3 FOUNDATIONAL CONCEPTS

Communication among human beings is a result of a

sequence of cognitive and linguistic actions.

Falkenberg et al. (1998) and von Braun et al. (2000)

talk about perceptions, conceptions, and

representations. Perceptions can be seen as patterns of

visual, auditory or other sensations of one’s mind,

whereas conception is a result from the process

through which a human actor interprets a perception

in his mind. In order to communicate these

conceptions one needs communicative constructions

(representations).

Our foundational concepts in this paper include

perception, conception, concept, meaning, and sense.

In the rest of the article, we use them in the following

way.

Perception is a product of human mind that is

limited to a single event or, more strictly, to a physical

phenomenon that can be realized by human senses.

Observation could be used as a synonym for

perception.

Conception is a product of human mind that could

also be called an idea or a thought that has conceptual

content. When a perception starts to be

communicative, it “turns into” a conception in the

human cognitive system.

While a conception is a mental thing that can be

communicated with other people, it can be

distinguished from a concept (see Macià, 1998).

Whereas a concept can be seen as a carrier of shared

meaning for a group, a conception is a carrier of

meaning of this particular concept for an individual.

Adding ‘Sense’ to Conceptual Modeling: An Interdisciplinary Approach

249

Thus, a conception can also be called an individual

interpretation of a concept, and, vice versa, a concept

can be seen as a consensus on individual conceptions

at a certain point of time. Both conceptions and

concepts are “named things”. They are referred to by

their names, which we call words. The meaning and

the name together form a sign that is used in

communication (see Lyons, 1971).

The difference between a conception and a

concept is in the meaning of the sign. Hereafter, when

we refer to the meaning at individual level, we use the

word meaning. Instead, when we talk about meaning

at the interpersonal level, we use the word sense.

Getting closer to the meaning helps us to get more

stable, accurate and consistent sense for concepts, and

thus, conceptual models of a higher quality. The

better quality could benefit ontology engineering, for

example, since ontologies can be seen as explicit and

formal specification of shared conceptualization

(Studer et al., 1998).

Like abilities to perceive are dependent on the

observer’s senses, “interpreting abilities” are

dependent on the interpreter’s whole history as an

intellectual being. Therefore, conceptions cannot be

considered static but sensible to all chances in

circumstances.

4 HUMAN CONSCIOUSNESS – A

PHILOSOPHICAL-LINGUISTIC

PROBLEM

People differ from other creatures in that we are

aware communicators implying that can use symbols

to discuss symbols (Stacks et al. 1991). Furthermore,

we can refer to different things that are far from the

situation: we can talk about what happened in the past

or what would possibly happen in the future, we can

talk about abstract things that nobody has ever

observed, we can talk about meanings or meanings of

meanings etc. People have the ability of thinking not

anchored to a particular perceptual context

(Katzafanas, 2005, p. 9).

Indeed, language is a core feature of humankind.

As Brand (2004, p. 317) puts it: “Language

interpenetrates the human; it is not distinct from

either thought or world, but it is thanks to language

we have on one hand a subject capable of thought, and

on the other, a meaningful world.”

Popper’s thesis of three worlds provide a useful

tool for our purpose. The three worlds are: (1) the

physical world or the world of physical states, (2) the

mental world or the world of mental states, and (3)

the world of intelligibles or of ideas in the objective

sense (Popper 1972, p. 154). The last one is what

Popper calls the third world, which he also describes

as “world of possible objects of thought”.

The physical world is very much what we, in

ordinary speaking, call reality. The second world is

subjective. It consists of individual consciousness.

The third world is populated by human products,

which are purified by critical argumentation. Popper

(1972, p. 107) says that “…inmates of this world are

critical arguments, and what may be called… the state

of a discussion…” The first and the third worlds

cannot interact directly but only through the second

world.

In the following, we consider human

communication from the viewpoint of semantics, in

general, and possible worlds semantics, in particular.

4.1 Theories of Meaning

Meaning as a linguistic issue has interested both

philosophers and linguists. In linguistics, it is

primarily seen as a matter of semantics, but also

pragmatics deals with meanings (Hudson 1984, p. 4).

Semantics as a term is quite new. It can be traced

back to the late 19th century (Lyons 1971, p. 400).

Around that time a German philosopher and

mathematician Gottlob Frege made remarkable

philosophical work (Frege, 1892) that helped to

consider ‘meaning’ as both an ontological and a

linguistic issue. His aim was to unify language and

thought, but it is not clear how four-square he

believed in his own ideal (Almog, 2005)

In short, Frege (1982) made the well-known

distinction between reference (Bedeutung) and sense

(Sinn). Frege talks about references and senses of

signs (i.e. names, combinations of words, letters). The

reference of a sign is the thing the sign refers to.

Defining the sense of a sign is a more complex task.

The easiest way may be to make use of the notion of

‘idea’ (Vorstellung). Frege says that the idea is an

internal image of the reference. It is always

subjective. According to Frege the sense is something

that is between an idea and the reference: it is not

subjective like the idea, but it is not the object of the

sign (= the reference) itself either.

It is obvious that without a notion similar to

Frege’s ‘idea’, “the human factor” of information

systems design is limited to, and by, lingual elements

that can be identified and (pre-)defined (those that

carry senses). Although CM is about modeling the

senses of concepts of a domain, and we therefore need

pre-defined concepts, a high quality model of a non-

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trivial domain require good understanding of

individual conceptions on the domain.

Lyons (1971, p. 427) says that “by the sense of a

word we mean its place in a system of relationships

which it contracts with other words in the

vocabulary” (also see May, 2006). This way of

thinking, in turn, means that since the relationships

are between the vocabulary-items, there are no

presuppositions about the existence of objects or

properties outside the vocabulary of the language.

This makes it possible to discuss abstract things to the

extent of the coverage of the vocabulary. The

vocabulary is, however, changing all the time and, as

an artifact, it is totally dependent on (1) individual

cognitive processes, and (2) communicative

processes between individuals (see Katzafanas,

2005).

So far, we have discussed the meanings/senses of

single signs or symbols, which in an ordinary

language are written or uttered words. Pragmatics is

a branch of semiotics that deals with the relation of

signs to interpreters (Levinson, 1983). Its emphasis is

on language usage (Levinson, 1983, p. 5). Utterances

and speaker’s intentions are important notions in

pragmatics. Communication is seen as “a complex

kind of intention that is achieved and satisfied just by

being recognized” (Levinson 1983, p. 16).

Pragmatics goes further from knowing the

meanings of words. In doing so, pragmatics can be

seen as complement to semantics as a theory of

meaning. As Lehrer (1980, p. 6) puts it, “[T]he

meaning of the words is one thing and their use

another.” Furthermore, ”understanding an utterance

involves the making of inferences that will connect

what is said to what is mutually assumed or what has

been said before.” (Levinson 1983, p. 21)

Based on the views of Wittgenstein and Dewey,

Medina (2004) state, that “the meaning of words is

not whatever is agreed upon their users”, and, “[t]he

relation between meaning and agreement is more

indirect: agreement is the background condition for

the emergence of meaning.” In other words, while

agreement cannot change the facts around us, they are

a necessary means to human interpretations on the

facts. This idea is very important when trying to

bridge the conceptual gap discussed before.

Higginbotham (1998) distinguishes three levels

of meaning (of a word):

(1) merely possessing a word, or having it in

one’s repertoire, and so being able to use it with

its meaning,

(2) knowing the meaning of the word, and

(3) having an adequate conscious view of its

meaning.

In terms of our thinking, all these levels consider the

meaning at the individual level.

Higginbotham (1998) talks conceptual

competence, which can be seen as a result of a gradual

process in which the grasp of a concept one already

possesses can be perfected. Thinking in this way

makes it necessary to distinguish the concept itself

and the conception of the things that fall under the

concept. According to Martí (1998) the significance

of this distinction may be very radical, if it is

interpreted that there are “concepts which are such

that no one possessing them will ever be in position

to obtain an adequate conception of the kind of things

the concept applies to”.

Since concepts are essential to, and characteristic

of, communication and since they live in

communications, they have to be considered as being

partly outside individuals (e.g. Higginbotham, 1998).

Instead, as the meaning of an utterance is at least

slightly different to the sender and the receiver of a

message (see Levinson, 1983), it is reasonable to say

that both communicators have their own conceptions

of the concept. Concept are, thus, communicative

entities that are tied to language on one side (sense

carrying words defined by theirs relations in

vocabularies) and to mental states of individuals

(conceptions of concepts).

In the following sub-chapter we provide a brief

introduction to possible worlds semantics that could

help in building the bridge between informal and

(semi-)formal descriptions of a domain.

4.2 Possible Worlds Semantics

Possible worlds is an interesting notion that can be

used to describe different kinds of imaginary systems.

A possible world is a world with internal consistency

that makes it possible in logical sense (see Girle,

2014). Our reality, the physical world around us, is

one of the possible worlds, since it exists and is,

therefore, most obviously possible. According to

Hintikka (1982, p. 87) the basic idea of the notion

‘possible worlds’ is that it covers “everything” that is

possible.

Let us symbolize a real world domain, which is to

be modeled conceptually, by D, and the conceptual

model of D by M. Taken that D is one of the possible

worlds, in order to build a good model of D, we

should set the same requirement for M, too. In other

words, when M is logically consistent (a possible

world), it is possible that it is an exact model of D. If

M was not possible, how could it be a candidate for a

good model of D?

Adding ‘Sense’ to Conceptual Modeling: An Interdisciplinary Approach

251

Hintikka (1982) interprets that Frege’s ‘sense’

(Sinn) is a function the value of which is the

reference. He also argues (p. 86-87) that the

arguments of such functions of meaning are the

possible worlds. Concepts (their senses) are, thus,

functions from possible worlds to references (objects

the concepts refer to).

Since the world of individual conceptions may not

form a possible world, the world of concepts for a

group of individuals would remain more or less

ambiguous. However, the conceptions can be refined

to be more consistent, leading to more consistent use

of the corresponding concepts. This would make it

possible to have strict definitions for the concepts of

a domain.

If the meaning/sense of a particular lingual

element (concept/conception) is dependent on

individual interpretation, how much formality can be

applied, when trying to catch the meaning/sense?

Taken that so-called intentional concepts are

functions whose arguments the possible worlds are

(Hintikka, 1982, p. 20), an individual conception, in

fact, can be seen as a function that have “conceptual

state of things” as its arguments. In the first case, the

function returns the reference (the object in the

possible world referred to by the intentional concept)

as its value, whereas in the second case, the function

returns the concept as its value (the concept in a

conceptual network that is referred to by the

conception). In different conceptual states of things,

this function returns a different value.

When the conceptual state of things (i.e. how

conceptions are related to each other) is inconsistent,

it cannot represent reality that is consistent (possible)

by its nature. Therefore, the first step should be to

check and ensure that the individual worlds (of

modelers modeling the domain) are consistent. In

following, we shall provide a model dealing with the

issue.

5 A SIMPLE

CONCEPTUALIZATION

MODEL

According to Katzafanas (2005, p. 6) the shift from

an unconscious state to a conscious state is the

process of conceptualization. In other words, a state

becomes conscious once its content has been

conceptualized.

In the following, we present a simple

conceptualization model which consists of three

worlds: (1) the world of real entities which the

concepts refer to (in ordinary speaking: reality), (2)

the world of concepts that we call the interpersonal

world, and (3) the world of conceptions that we call

individual world.

To go further we make three basic assumptions:

Assumption 1: There is an objective world W

independent of the observer. This is the world of real

entities.

Assumption 2: The observer (individual) can gain

information about W directly through his/her senses

(perceptions) or indirectly though communication

with other people.

2.1. Information about W is always limited to

and/or biased by perceptual and cognitive abilities.

Therefore, part of information (theoretically)

available is lost during observation.

2.2. Concepts (words and their senses for capturing

perceived or abstract things), which are needed for

communication, are interpreted by individuals and

they relate to individual conceptions. When an

individual conception is “externalized” through

communication, part of its meaning remains

hidden. Similarly, when a concept is “internalized”

by an individual, part of its sense may not be

conceived by the individual.

Assumption 3: In interaction with each other, all the

three worlds change continuously.

On the basis of the above assumptions, we present

a simple model (Figure 1). There are three worlds in

the model: The Objective World, The Interpersonal

World and The Individual World. In terms of Frege’s

meaning concepts these worlds correspond to

reference (Bedeutung), sense (Sinn), and

idea/internal image (Vorstellung).

The interacting yet separate three worlds consist

of different things. The Objective World consists of

real entities. The Interpersonal World consists of

concepts. By concepts we do not mean only words

and their senses but also, and particularly, all complex

structures that are built upon them: ontologies,

taxonomies, vocabularies etc. And finally, the

Individual World consists of perceptions, conceptions

and tacit knowledge. Although tacit knowledge is out

of our scope, we have included it in our model to

remind that besides observations about the Objective

World (i.e. perceptions) and conceptions, there are

also third kinds of cognitive things of human mind.

They, on one hand, carry more complicated

information than perceptions do, but, as contrast to

conceptions, they remain unconscious to an

individual. For example, when an individual can

accomplish a complex procedure but cannot explain

KEOD 2019 - 11th International Conference on Knowledge Engineering and Ontology Development

252

(conceptualize) how she has done it, we talk about

tacit knowledge (e.g. see Nonaka et al., 1996).

Communications

Tacit knowledge

Concepts

Individual World

Interpersonal

World

Objective World

Conceptions

Perceptions

Figure 1: A conceptualization model.

Typically, conceptual modeling has dealt with

elements that fall into the categories of concepts and

their references. They are things that are named, often

rather well-defined, and purified from conflicting

material. Excluding a few exceptions, conceptual

modeling seems to ignore the fuzziest area of

modeling, human conceptions.

We argue that what needs to be done in

conceptual modeling is to build a bridge between

conceptions and concepts. An easy way to build such

a bridge is to combine informal elements and formal

elements in one picture. A good starting point could

be typical ER modeling. Modifications that need to be

done include:

1. The concepts must not be considered as symbols

for real world entities but rather as carriers of senses

that are linked to the individual conceptions (meaning

of concept to an individual). E (entity) in ER

modeling is replaced by C (concept) resulting in

Concept Relationship modeling (CR modeling).

2. According to (1), we are not interested in the

properties of real entities (i.e. attributes attached to

entities) at this stage but rather in properties of the

conceptions. We call these attributes conceptual

attribute.

3. Attributes attached to concepts need to clarify

individual conceptions on the concepts being

discussed. The most important one of such attributes

is definition (for expressing personal definition for a

concept, i.e. how the concept would relate to other

concepts in the individual’s mind).

4. Relationships between concepts are not those

that are observed, but those that are expressed by an

individual modeler (through the definitions of

concepts). In other words, a concept is related to

another concept, if someone says so. This is what

personal conceptions are all about. Inconsistencies

are identified and removed later.

A CR model combines two levels of formality in

one picture. On one hand, there are normal language

expressions (conceptual attributes), and on the other

hand, there are graphical expressions that follow a

certain formality (concepts and relationships). In the

next chapter, we present a modest example how a

modeling effort could proceed.

6 MODELLING

CONCEPTS/CONCEPTIONS IN

PRACTICE

Traditionally, there have been three phases in concept

modeling of a domain: (1) to find entities (concepts)

that cover the domain, (2) to analyze the relationships

between the entities, and (3) to add attributes to the

entities. This works fine when one aims at a model for

implementation. However, the procedure may not

work very well when trying to form a consistent

picture of the concepts that individuals use to describe

a domain (conceptions and their relationships). We

believe that the best way is to talk about the individual

views and conceptions. This, in turn, requires that we

can use natural language and that the natural language

is smoothly tied to a more formal representation like

a graphical model. In this part, we shall describe how

traditional ER modeling can be enhanced by a new

modeling level.

Conceptual models, like ER models, refer to the

real world domain, which they represent (Figure 2).

Thus, the concept CAR in an ER model refers to the

class of cars in the real world and the concept

PERSON refers to the class of persons in the real

world. The entities relate to each other through

relationships. Furthermore, attributes are attached to

entities. When we talk about attributes attached to

CAR, we actually talk about the properties that are

shared by the entities of the class of cars. Some key

attributes may explicitly identify an entity within the

class of similar entities.

But, what if we are primarily interested in the

consistency of the domain model? Who says that the

concepts CAR and PERSON are relevant concepts is

that domain? And further, if they are, how can we be

sure that everyone modeling the domain understand

the concepts CAR and PERSON in a similar way?

Adding ‘Sense’ to Conceptual Modeling: An Interdisciplinary Approach

253

Figure 2: A typical ER model.

In this simple case, it is obvious that no

misunderstandings will happen, but what if the

domain was a complex one, like an enterprise

architecture, or a model of climate change? While

such a modeling task would require several models

produced from different viewpoints, how can we be

sure they form a model, which would be both

covering, non-redundant and consistent at the same

time?

In Figure 3 we describe, how “CR” modeling

differs from ER modeling. When modeling a real

world domain, a modeler uses the concepts just like

in ER modeling. However, she does not define the

concept through the attributes of the entities referred

by the concept, but through the definition in which the

concept relates to other concepts. Each modeler has

finally her/his own view of the relevant concepts of

the domain. Before the individual models are

integrated into a common model (external

consistency), their internal consistency must be

checked by the rules of logics (e.g. possible world

logics). If the world of individual conceptions form a

possible world, it is a candidate for representing the

real world domain being modelled. It should be

reminded, however, that a consistent individual world

in not necessary a good model of the domain. This

must be evaluated in the later phases of conceptual

modeling.

Figure 3: A simple example of CR modeling.

7 CONCLUSIONS

In this article, we have provided a conceptual

modeling approach that puts emphasis on individual

conceptions and how they relate to interpersonal

concepts. The presented approach differs from the

prevailing conceptual modeling in a remarkable way,

since it sees concepts not only as abstractions of real

world entities, i.e. symbols that refer to the entities of

the domain being modelled, but also as references of

individual conceptions. Thus, the new approach

builds a bridge between individual thinking and

formal models of a domain, and helps to get the

models more consistent.

A main part of the article consisted of presenting

theoretical constituents of several disciplines relevant

to conceptual modeling. Based on these constituents,

we have built a conceptualization model, and

presented a modest application of it. We acknowledge

that the work is just at the beginning and that the

usefulness of the model and of the CR modeling is

still very much on a theoretical basis. Hence, a lot of

further work is required to show how the approach

works in practice.

Nevertheless, we are quite sure that the new

solutions for bridging the conceptual gap between

human thinking and formal modeling should be

searched for in the direction we have described in this

article. It is obvious that since the applications of

artificial intelligence improve as rapidly as they do

today, the “conceptual attributes”, especially the

definitions of concepts, can be quite easily analyzed

automatically. If the individual conceptions of

concepts could be presented in an ordinary language,

and their consistency checked automatically, utilizing

possible world semantics, for example, we would

have taken a big step towards higher quality

conceptual modeling.

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