The Universal Networking Language beyond Machne Translation

estonianmelonAI and Robotics

Oct 24, 2013 (4 years and 14 days ago)

89 views


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




1


The Universal Networking Language


beyond Machne Translation




Hiroshi Uchida, Meiying Zhu

UNDL Foundation

September

26
, 2001



1.

Introduction


The Internet has emerged as the global information infrastructure, revolutionizing access to information,
as we
ll as the speed by which it is transmitted and received. With the technology of electronic mail, for
example, people may communicate rapidly over long distances. Not all users, however, can use their
own language for communication
.

The Universal Networki
ng Language (UNL) is a
n

artificial language in the form of semantic network
for
computers to express and exchange every kind of information.

Since the advent of computers, researchers around the world have worked towards developing a
system that would over
come language barriers.

While lots of different systems have been developed by various organizations, each has their special
representation of a given language. This results in incompatibilities between systems. Then, it is
impossible to break language bar
riers in all
over
the world, even if we get together all the results in one
system.

Against this backdrop, the concept of UNL as a common language for all computer systems was born.

With the approach of UNL, the results of the past research and developmen
t can be applied to the
present development, and make the infrastructure of future research and development.



2.

UNL


What is the UNL?


The UNL consists of Universal words (UWs), Relations, Attributes, and UNL Knowledge Base. The
Universal words constitute

the vocabulary of the UNL, Relations and attribute constitutes the syntax of
the UNL and UNL Knowledge Base constitutes the semantics of the UNL.


Why the UNL is necessary?


A computer

in future
need
s

a capability to make knowledge processing.

Knowledge p
rocessing means
a computer takes over thought and judgment of human
s

using knowledge of human
s
. It is necessary to
make a processing based on contents.

Computer
s

need to have knowledge for knowledge processing.

It is necessary
for computers
to have a langu
age to have knowledge like human.

It is
also
necessary to
have a language to process contents like human.

The UNL is a language for computer
s

to do so.


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




2

The UNL can express knowledge like a natural language.

The UNL can express content
s

like a
natural langu
age.


What is different from others?


S
ystem
s

which can deal with knowledge and contents
have
already
been
developed.

But, their

representation of knowledge or contents
is

different from each other.

Moreover,
their
representations
are

language dependent.

N
amely, concept primitives used to represent knowledge
are

language
dependent.

Knowledge or contents of a system cannot be used in other system
s
.


The situation is same as machine translation.

For example, if we put all the result of research and
developme
nt of machine translation, we cannot realize multilingual machine translation system
s

which
can break language barriers.


Advantage of common language for
computer
s


The UNL greatly reduces development cost of developing knowledge or contents necessary to
make
knowledge processing by sharing knowledge and contents
. Furthermore, if every knowledge necessary
for doing something by software is described in a language for computers such as the UNL, software
only need to interpret instructions written in the lan
guage to perform it functions. And those instructions
could be shared by other software. Then we can accumulate such knowledge for computer like a
library for humans.


How the UNL express information?


The UNL represents information, i.e. meaning, sentence

by sentence. Sentence information is
represented as a

hyper
-
graph having Universal Words (UWs) as nodes and relations as arcs. This
hyper
-
graph is also represented a set of directed binary relations
, each between two of

the
UWs

present in the sentence.

Th
e UNL expresses information classifying objectivity and subjectivity. Objectivity is expressed using
UWs and relations. Subjectivity is expressed using attributes by attaching them to UWs.


A UNL document, then, will be a long list of
relations
between con
cepts
.


The following is a example of a UNL expression in graphical form and list form.



©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




3



[S:2]

{org:es}

Hace tiempo, en la ciudad de Babilonia, la gente comenzo a construir una

torre enorme, que
parecia alcanzar los cielos.

{/org}

{unl}

tim(begin(icl>do
).@entry.@past, long ago(icl>ago))

mod(city(icl>region).@def, Babylon(icl>city))

plc(begin(icl>do).@entry.@past, city (icl>region).@def)

agt(begin(icl>do).@entry.@past, people(icl>person).@def)

obj(begin(icl>do).@entry.@past, build(icl>do))

agt(build(icl>d
o), people.@def)

obj(build(icl>do), tower(icl>building).@indef)

aoj(huge(icl>big), tower(icl>building).@indef)

aoj(seem(icl>be).@past, tower(icl>building).@indef)

obj(seem(icl>be).@past, reach(icl>come).@begin.@soon)

obj(reach(icl>come).@begin
-
soon, tower(
icl>building).@indef)

gol(reach(icl>come).@begin
-
soon, heaven(icl>region).@def.@pl)

{/unl}

[/S]



3.

Universal Words


A Universal Word
represent
s

si
mple
or comp
ound

concepts.

UWs are made up of a character string

©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




4

(an English
-
language word) followed by a list
of
constraint
s.

There are three kinds of UWs. Basic
UWs, Restricted UWs and Extra UWs.


<
UW
>

::=

<
Head

Word
>

[<Constraint
List
>]

<
Head

Word
>

::=

<
character
>

=
<Constraint
List
>

::= “(“
<Constraint> [

,


<Constraint>]
… “)”
=
<Constraint>

::=
<
Relation

Labe
l
>

{
“>” | “<”

} <UW> [<Constraint List>] |

<
Relation

Label
>

{
“>” | “<”

} <UW> [<Constraint List>]

[ {
“>” | “<”

} <UW> [<Constraint List>]
]


=
<
Relation

Label
>

::= “
agt


|
and” | “aoj” | “obj” | “
icl


|
...

<
character
>

::= “
A
” | ... | “
Z


|
“a” | ...
| “z” | 0 | 1 | 2 | ... | 9
|
“_”

|




|

#


|

!


|

$


|

%


|


=


|

^




~




|




@




+




-




<




>




?









Head

Word


The Head Word

is an English word
/compound word/phrase/sentence

that is interpreted as a label for a
set of conce
pts: the set made up of all the concepts that may correspond to that in English. A Basic
UW (with no restrictions or
Constraint
List) denotes this set. Each Restricted UW denotes a subset of
this set that is defined by its
Constraint
List.

Thus, the headwo
rd serves to organize concepts and make it easier to remember which is which.


Basic U
Ws


A
Basic UW
is expressed by an English word/compound word/@hrase/sentence. The concept that a
basic UW represents is the same concept that corresponding to that in Eng
lish.


Restricted UWs


The
Constraint
List restricts the
range of the concept that
a
Basic
UW

represents.

The Basic UW “drink”, with no
Constraint
List, includes the concepts of “putting liquids in the mouth”,
“liquids that are put in the mouth”, “liquids
with alcohol”, “absorb” and others.

The Restricted UW “
drink(icl>
do(
obj>liquid
)
)
” denotes the subset of these concepts that includes
“putting liquids in the mouth”, which in turn corresponds to verbs such as “drink”, “gulp”, “chug” and
“slurp” in English.


Consider again the examples of Restricted UWs given above:

state(
icl>do(obj>thing)

is
more

specific concept

(arbitrarily associated with the English word “state”) that denotes situations

in which humans produce some information, or state something.

stat
e(
icl
>nation)

is
more

specific sense of “state” that denotes a nation.

state(icl>situation)

is
more

specific sense of “state” that denotes a kind of situation.

state(icl>government)

is
more

specific sense of “state” that denotes a kind of government.


The

information in parentheses is the
Constraint
List and it describes some conceptual restrictions, that
is why these are called Restricted UWs. Informally, the restrictions mean “restrict your attention to this
particular sense of the word”. Thus, the focu
s is clearly the idea and not the specific English word.

It often turns out that for a given language there is a wide variety of different words for these concepts
and not, coincidentally, all the same word, as in English.

Notice that by organizing these s
enses around the English words, we can simplify the task of making a
new UW/Specific Language dictionary: we can use a bilingual English/Specific Language dictionary

©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




5

and proceed from there, specifying the number different concepts necessary for each Englis
h word.

This of course does not mean that we’re translating English words; we’re just using the English
dictionary to remind us of the concepts that we will want to deal with and thus to
organize

work more
efficiently.


Extra UWs


Extra UWs denote concepts

that are not found in English and that have to be introduced as extra
categories. Foreign
-
language labels are used as Head

Words. Consider again the examples given
above:


ikebana(icl>activity, obj>flower)


“something you do with flowers”

samba(icl>dance
)



“a kind of dance”

soufflé(icl>food, pof
>
egg)


“a kind of food made with eggs”

murano(icl>glass, aoj>colorful)


“a kind of colorful glass”


To the extent that these concepts exist for English speakers, they are expressed with foreign
-
language
loanwor
ds and don’t always appear in English dictionaries. So, they simply have to be added if we are
going to be able to use these specific concepts in the UNL system. Notice that the
Constraint
List or
restrictions already give some idea of what concept is asso
ciated with these Extra UWs and the
Constraint
s binary relation this concept to other concepts already present (activity, flower, egg, food,
etc.).



4.

Relations


B
inary relations are the building blocks of UNL
sentences
. They are made up of a relation and t
wo
U
W
s
.

The relations between
UWs

in
binary relations

have different
labels

according to the different
roles

they

play
. These Relation
-
Labels are listed and defined below.


There are many factors to be considered in choosing an inventory of relations. The
principles to choose
relations as follows.


Principle 1
: Necessary Condition

When a UW has relations between more than two other UWs, each relation label should be set as to
be able to identify each relation on the premise that we have enough knowledge ab
out a concept of
each UW express.


Principle 2
: Sufficient Condition

When there are relations between UWs, each relation label, we should be set as to be able to
understand each role of each UW only by referring a relation label.



agt

Agent

a thing which

initiates an
action

and

conjunction

a
conjunctive relation between concepts

aoj

thing with attribute

a thing which is in a state or has an attribute

bas

Basis

a thing used as the basis(standard) for expressing degree

ben

Beneficiary

a not directly rel
ated beneficiary or victim of an event or state

cag

co
-
agent

a thing not in focus which
initiates an
implicit event which is done
in parallel


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




6

cao

co
-
thing with attribute

a thing not in focus is in a state in parallel

cnt

Co
ntent

an equivalent concept

c
ob

affected

co
-
thing

a thing which is directly affected by an implicit event done in
parallel or an implicit state in parallel

con

condition

a non
-
focused event or state which conditioned a focused event or
state

coo

co
-
occurrence

a co
-
occurred event or
state for a focused event or state

dur

duration

a period of time during an event occurs or a state exists

fmt

range

a range between t
wo
things

frm

origin

an origin of a thing

gol

goal/
final
state

the final state of object or the thing finally associate
d with object

of an event

ins

instrument

the instrument to carry out an event

man

manner

the way to carry out event or characteristics of a state

met

method

a means to carry out an event

mod

modification

a thing which restrict a focused thing

nam

name

a name of a thing

obj

affected

thing

a thing in focus which is directly affected by an event or state

opl

affected place

a place in focus where an event affects

or

disjunction

disjunctive relation between two concepts

per

proportion, rate

or
distribut
ion

a basis or unit of proportion, rate or distribution


plc


place

the place an event occurs or a state is true or a thing exists

plf

initial place

the place an event begins or a state becomes true

plt


final place

the place an event ends or a state be
comes false

pof

p
art
-
of

a concept of which a focused thing is a part

pos

p
ossessor


the possessor of a thing

ptn

partner

an indispensable non
-
focused initiator of an action

pur

purpose or


objective

the purpose or an objective of an agent of an event o
r a purpose
of a thing which exist

qua

quantity

a quantity of a thing or unit


Rsn

reason

a reason that an event or a state happens

Scn

scene

a virtual world
where
an event
occurs

or state is true or a thing
exists

Seq

sequence

a prior event or state o
f a focused event or state

Src

source/
initial
state

the initial state of an object or thing initially associated with the
object of an event

Tim

time

the time an event occurs or a state is true

Tmf

initial time

the time an event starts or a state become
s true

Tmt

final time

the time an event ends or a state becomes false

T
o

destination

a destination of a thing

Via

intermediate place

or
state

an intermediate place or state of an event







5.

Attributes


A
ttribute
s

of UWs are used to describe
subjectivi
ty of sentences. They show
what is said from the

©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




7

speaker’s point of view: how the speaker views what is said. This includes phenomena technically
called “speech acts”, “propositional attitudes”, “truth values”, etc. Conceptual relations and UWs are
used to

describe objectiv
ity of sentences
. Attributed of UWs enrich this description with more
information about how the speaker views these states
-
of
-
affairs and his attitudes toward them.


Time with respect to the speaker


Where does the speaker situate his des
cription in time, taking his moment of speaking as a point of
reference? A time before he spoke? After? At approximately the same time? This is the information
that defines “narrative time” as past, present or future. These Attributes are attached to the m
ain
predicate.

Although in many languages this information is signaled by tense markings on verbs, the concept is not
tense, but “time with respect to the speaker”. The clearest example is the simple present tense in
English, which is not interpreted as pr
esent time, but as “independently of specific times”.

Consider the example: The earth is round.

This sentence is true in the past, in the present and in the future, independently of speaker time, so
although the tense is “present” it is not interpreted as
present time.


@past

happened in the past

ex) He
went

there yesterday.

ex) It
was

snowing yesterday

@present

happening at present

ex) It

s 牡ining

ha牤.

@future

will happen in future

ex) He
will arrive

tomorrow


Speaker’s view of Aspect


A speaker can e
mphasize or focus on a part of an event or treat it as a whole unit. This is closely
linked to how the speaker places the event in time. These Attributes are attached to the main
predicate.

He can focus on the beginning of the event, looking forward to it
(@begin), or backward to it
(@begin).

He can also focus on the end of the event, looking forward to it (@end) or backward to it from nearby
(@end) or from farther away (@complete).

Degree of forwardness or backwardness (@soon, @just).

He can focus on the m
iddle of the event (@progress).

The speaker can choose to focus on the lasting effects or final state of the event (@state) or on the
event as a repeating unit (@repeat).

The feeling of incompleteness or not yet happen of an event with respect to the speak
er (@yet).


@begin

beginning of an event or a state

ex) It
began to

work again.


work.@begin.@past

@complete

finishing/completion of a (whole) event.

ex)
I've looked through

the script


look.@entry.@complete

@continue

continuation of an event

ex) He
went

on talking
.


talk.@continue.@past

@custom

customary or repetitious action



©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




8

ex) I used to visit [I would often go] there
when I was a boy

visit.@custom.@past

@end

end/termination of an event or a state

ex) I
have done

it.


do.@end.@present

@experienc
e

E
xperience

ex) Have you ever visited Japan?

ex) I have been there.


visit.@experience.@interrogation

visit.@exterience

@experienc
e

Experience

ex) Have you ever visited Japan?

ex) I have been there.


visit.@experience.@interrogation

visit.@exterience

@prog
ress

an event is in progress

ex) I
am working

now.


work.@progress.@present

@repeat

repetition of an event

ex) He
is jumping
.


jump.@entry.@present.@repeat

@state

final state or the existence of the object on
which an action has been taken

ex) It
is brok
en
.



break.@state


The following attributes are used to modify the attributes above.


@just

ex) He has just come.

come.@end.@just

@soon

ex) The train
is about to

leave.

leave.@begin.@soon

@yet

feeling of not yet begin or end/complete

ex) I have not yet

done it.


do.@complete.@not.@yet



Speaker's view of Reference


Whether an expression refers to a single individual, a small group or a whole set is often not clear. The
expression “the lion” is not sufficiently explicit for us to know whether the speake
r means “one
particular lion” or “all lions”. Consider the following examples:

The lion is a feline mammal.

The lion is eating an anti
-
lope.

In the first example, it seems reasonable to suppose that the speaker understood “the lion” as “all lions”,
where
as in the second example as “one particular lion”.

The following Attributes are used to make explicit what the speaker’s view of reference seems to be.



@generic

generic concept

@def

already refer
r
ed

@indef

non
-
specific class

@not

complement set

@ordi
nal

ordinal number



These Attributes are usually attached to UWs that denote things.


Speaker’s Focus



©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




9

The speaker can choose to focus or emphasize the parts of a sentence to show how important he
thinks they are in the situation described. This is ofte
n related to sentence structure.



@emphasis

Emphasis

ex)

䤠do like it


@entry

E
ntry
p
oint or
m
ain UW

of whole UNL expressions or in a hyper (scope) node

@qfocus

The focused UW of a question

@theme

I
nstantiates an object from different class

@title

Ti
tle

@topic

The topic UW of a sentence


One UW marked with "@entry" is essential to each UNL expression

or
in a Compound UW.


Speaker’s attitudes


The speaker can also express, directly or indirectly, what his attitudes or emotions are toward what is
bein
g said or who it is being said to. This includes respect and politeness toward the listener and
surprise toward what is being said.



@confirmation


Confirmation

ex)

vou won't say thatI will you?


ex⤠

sou desu ne?


⡉E gapanese)

@exclamation


Feeling of

exclamation

ex)

ki牥i na!

E

eow beauti晵l ⡩t is⤡

䥮 gapanese)

ex⤠

lhℬ look out!



佷l


@imperative



Imperative

ex)

det up
!”

ex⤠

vou will please leave the 牯om.


@interrogativ
e

Interrogation

ex)

tho is it?


@invitation


Inducement to do someth
ing

ex)

till L ton

t you have some tea?


ex)


iet

s goI shall we?


@polite


Polite feeling

ex)

C
ould you

⡰lease)
...”

ex⤠

䥦fyou could


䤠would
…”

@request


Request
ex)

please don

t 景牧et ⡀牥que
st)


@respect



Respectful feeling

ex)

o taku⡀牥spect)

E

⡹ou爩rhouse


in gapanese
)

ex⤠

dood mo牮ing⡀牥spect⤬ si爮


@vocative


Vocative

Ex)

䉯ys⡀vocative⤬ be ambitious!




qhe va物ety o映possibilities 牥晬ects deg牥es o映belie昬 emphasisI and th
e extent to which what is said
should be inte牰牥ted as a suggestion o爠o牤e爬 as well as many othe爠social 晡cto牳 such as the 牥lative
status o映the speake牳
.


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




10


Speaker's view point


The following labels are used to clarify the speaker’s viewpoint informa
tion.


@ability

a
bility, capability of doing things

ex)
He can speak English but he can't write it very well.

@admire


express speaker's admiration

@although

ex) Quit smoking but he still smoke

@apodosis
-
real

apodosis:
reality

in
the first person

ex)
We

should (would) love to go abroad if we had the chance

@apodosis
-
unrea
l

a
podosis
:
A supposed result from a supposition contrary to reality

ex)
If we had more money, we could buy a car.

@apodosis
-
cond

apodosis:
A supposed result from an assumed condition

ex)
He would smoke too much if I did not stop him

@ask
-
back

ask back

@conclusion

ex) He is her husband ; she is his wife.


doubt

have doubt

@expectation

e
xpectation to other's

ex)
He'll help you if you ask him.

Will you have another cup of coffee?

Will

you (please, kindly,

etc.) open the window?

Would you excuse me ?

@grant

t
o give consent to do

ex)
Can I smoke in here?


C o u l d I s mo k e i n h e r e ?


Yo u ma y b o r r o w my c a r i f y o u l i k e.

@g r a n t
-
n o t

t
o n o t g i v e c o n s e n t t o

e x )
Yo u {mu s t n't/a r e n o t a l l o w e
d t o/ma y n o t } b o r r o w my c a r.

@i n
d u c e

i n d u c e t o d o

@i n e v i t a b i l i t y

s
u p p o s i t i o n t h a t s o me t h i n g i s i n e v i t a b l e

e x )
T h e y s h o u l d b e h o me b y n o w.


T h e g a me w i l l (mu s t / s h o u l d ) b e f i n i s h e d b y n o w.


Oi l w i l l f l o a t (f l o a t s ) o n w a t e r.


H e'l l (a l w a y s ) t a l k
f o r h o u r s i f y o u g i v e h i m t h e c h a n c e.


T h e r e mu s t b e a mi s t a k e.


Mu s t n't t h e r e b e a n o t h e r r e a s o n f o r h i s b e h a v i o r?


T h e y o u g h t t o b e h e r e b y n o w.

@i n s i s t e n c e

s
t r o n g w i l l t o d o

e x )
Yo u s h a l l d o a s I s a y.


H e s h a l l b e p u n i s h e d.


I t's y o u r o w
n f a u l t; y o u w o u l d t a k e t h e b a b y w i t h y o u.

@i n t e n t i o n

w
i l l, i n t e n t i o n t o d o

e x )
H e s h a l l g e t t h i s mo n e y.


Yo u s h a l l d o e x a c t l y a s y o u w i s h.


I'l l w r i t e a s s o o n I a s c a n..


We w o n't s t a y l o n g e r t h a n t w o h o u r s.


H e w i l l d o i t, w h a t e v e r y o u s a
y.


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




11


H e w i l l k e e p i n t e r r u p t i n g me.

@ma y

s
u p p o s i t i o n o f a c t u a l p o s s i b i l i t y

e x )
We c o u l d g o t o t h e c o n c e r t.


T h e r o a d ma y b e b l o c k e d.


We mi g h t g o t o t h e c o n c e r t.


Wh a t y o u s a y mi g h t b e t r u e.

@o b l i g a t i o n

t
o o b l i g e s o me o n e

e x )
T h e v e n d o r s h a l l
ma i n t a i n t h e e q u i p me n t i n g o o d r e p a i r.

@o b l i g a t i o n
-
n o t

f
o r b i d t o d o

e x )
Y o u mu s t b e b a c k b y 1 0 o'c l o c k.


Y e s t e r d a y y o u h a d t o b e b a c k b y 1 0 o'c l o c k.


Y e s t e r d a y y o u s a i d y o u mu s t { h a d t o } b e b a c k b y 1 0 o'c l o c k.


Y o u { n e e d n't/d o n't h a v e t o/a r e n o t o
b l i g e d t o } b e b a c k b y 1 0 o'c l o c k.

@p o s s i b i l i t y

a
s s u me r e a s o n a b l e p o s s i b i l i t y

e x )
A n y b o d y c a n ma k e mi s t a k e s.


T h e r o a d c a n b e b l o c k e d.


T h e r o a d c o u l d b e b l o c k e d.

@p r o b a b i l i t y

a
s s u me p r o b a b i l i t y

e x )
T h a t w o u l d b e h i s mo t h e r.

@
r e g r e t


f e e
l s o r r y

@s h o u l d

t
o f e e l d u t y

e x )
Y o u s h o u l d d o a s h e s a y s.

@u n e x p e c t e d
-

p r e s u mp t i o n

p
r e s u mp t i o n c o n t r a r y t o a w i s h o r e x p e c t a t i o n

e x )
I t i s o d d t h a t y o u s h o u l d s a y t h i s t o me.


I a m s o r r y t h a t t h i s s h o u l d h a v e h a p p e n e d.

@u n e x p e c t e d
-

c o n s e q u e n c e

c o n s e q
u e n c e
c o n t r a r y t o a w i s h o r e x p e c t a t i o n

e x )
I

ma d e a d r a f t, b u t i t s t i l l n e e d s a n o t h e r w o r k.

@wi l l

w
i l l t o d o

e x )
I s h a l l n o t b e l o n g.


We s h a l l l e t y o u k n o w o u r d e c i s i o n.


We s h a l l o v e r c o me.



C o n v e n t i o n


T y p i c a l U N L s t r u c t u r e s c a n b e e x p r e s s e d b y a
t t r i b u t e, t o a v o i d t h e c o mp l e x i t y o f e n c o
n v e r t
i n g a n d
d e c o
n v e r t i n g
.
These attributes do not express speaker

s information.


@
pl

Plural

@angle_bracket

< > is used

@double_parenthesi
s

(( )) is used

@double_quotation





is used

@parenthesis

( ) is used

@single_quotation





is used

@square_bracket

[ ] is used




©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




12

6.

Knowledge Base


The UNL Knowledge Base
defines

possible binary relations between UWs (Universal Words). The
knowledge base is a set of knowledge base entries. The format of knowledge base entrie
s is as
follows.


<Knowledge Base entry>

::=

<Binary relations> "=" <degree of certainty>

<Binary Relation>

::=

<Relation Label> "(" <UW1> "," <UW2> ")"

<degree of certainty>

::=

"0" | "1" | ... | "255"


When the degree of certainty is "0", it means the

relation between two UWs is false. When the degree
of certainty is more than "1", it means the relation between two UWs is true, and the bigger the number
is, the more the credibility is.


The UW system has been introduced to
:


1)

generate a word when a conc
ept is not included in a language;

2)

reduce the number of knowledge base entries

which can be deductively inferred.


For this purpose the "
icl
" relation was introduced to make it possible to inherit properties from upper
UW's.

And each UW is categorized acco
rding to the role of concept to other concepts.


For example a knowledge "A dog can eat foods." is expressed in the following manner.


icl(dog(icl>animal), animal(icl>living thing))=1

agt (eat(icl>do(obj>thing), animal(icl>living thing))=1

obj(eat(icl>do(o
bj>thing), food(icl>functional thing))=1



7.

The UNL System


The UNL system consists of the UNL, Language Servers and basic tools.

The UNL is consists of Universal Words(UWs), relations, attributes and knowledge base.

A language server is consists of a decon
verter and an enconverter. A deconverter is a language
generation system from the UNL and consists of deconversion software, generation rules and
dictionaries for a language. An enconverter is a UNL generation system from a language and consists
of enconve
rsion software, analysis rules and dictionaries for a language.

Basic tools are UNL viewer to see UNL documents in their languages and UNL editor to make UNL
document using their languages.



©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




13



Let’s explain how UNL can be used through the Internet.
A
ny pe
rson with access to the Internet will
be able to “enconvert” text written in their own language into UNL text. And likewise, any UNL text
can be “deconverted” into a variety of native languages.


To illustrate the dual processes of “enconversion” and “de
conversion,” let’s look at a home page
developed in Arabic. Through UNL, we will be able to read this page in Spanish.

The processes of “enconversion” and “deconversion” are provided by a Language Server which
resides in the network of the Internet. The
“enconverter” and “deconverter” are responsible for
converting a particular language into UNL, and vice versa. The “enconverter” “enconverts” a
language into UNL, while the “deconverter” “deconverts” UNL into a native language.

In this example, the Arabic

Language Server and the Spanish Language Server provide the conversion
service.

When home pages are developed in Arabic, the UNL Editor recognizes the contents as Arabic and
sends a request to the Arabic Language Server to “enconvert” the text. Once the
Arabic text is
“enconverted” to UNL, the Arabic Language Server sends the results back to the UNL Editor.

Home page designers can now embed UNL into their pages.

When we read this page in Spanish, the UNL Viewer recognizes the contents as UNL and sends a
r
equest to the Spanish Language Server to “deconvert” the text. Once UNL is “deconverted” to
Spanish, the Spanish Language Server sends the results back to the UNL Editor.

As you see, the text


once converted to UNL


may be converted to many different la
nguages. For
example, home pages can be designed in one’s native language and then “enconverted” to UNL before
being uploaded. Once a home page is expressed in UNL, it can be read in a variety of languages.




©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




14

8.

Deconverter


A "deconverter" is a s
oftware that automatically deconverts UNL into native languages. It is important
to achieve a high quality and correct results. It is also important that the basic architecture of the
"deconverter" is widely shared throughout the world, in order to treat a
ll languages with the same
quality and precision standards. Technology developed for a language can be applied to other

languages
as long as the architecture is shared.


A
software for deconversion called "DeCo" which constitutes a deconverter together wit
h a word
dictionary, co
-
occurrence dictionary and conversion rules for a language. This "DeCo" is language
independent software that is applicable for any languages.

The DeCO does syntactic and
morphological generation ast the same time, and does knowledge

base
-
based word generation. It also
does co
-
occurrence
-
based word selection.


A "Deconverter", which generates natural language from UNL, plays a core role in the UNL system.
It is very significant that "deconverter" is capable of expressing UNL informati
on with very high
accuracy.



9.

Enconverter


An "enconverter" is a software that automatically or interactively enconverts natural languages text into
UNL.
A
software for enconversion called "EnCo" which constitutes an enconverter together with a
word dicti
onary,
UNL knowledge base

and conversion rules for a language. This "EnCo" is language
independent software, then it is applicable for any languages.

The EnCo performs morphological,
syntactic and semantic analysis synchronously. It also does knowledge bas
e and co
-
occurrence based
disambiguation.


An "enconverter", as it generates UNL from natural languages, enables people to make UNL
documents without any knowledge about UNL. It means that users of the UNL system do not need
learn UNL. This makes UNL quite

different from Esperanto, for instance.



10.

Dictionary


A word dictionary stores information for a language. It stores information concerning what kinds of
UWs(concepts) words of the language expresses and where those words can be used. A word
dictionary s
tores the following items:


1)

Universal words for identifying concepts

2)

Word headings for words that can express concepts

3)

Information on the syntactical behavior of words


A word dictionary provides information for computers to understand natural language, an
d express
information in natural language. A dictionary entry consists of a correspondence between a concept
and a word, and information concerning syntax properties of a word when that correspondence was
established.


The following shows the text format o
f word entries:


©

Copyright UNL Centre / UNDL Foundation. All rights reserved.




15


<word entry>

::= <word heading> <word
-
id> <
UW
> <syntax attribute>

<other> ";"

<word heading>

::= "[" <character string> "]"

<word id>

::= "{" <number> "}"

<
UW
>


::= """ <character string> """

<syntax attribute>::= "("{ <character string> "
," }... ")"

<others>

::= "<" <language
-
id> "," <frequency> "," <priority> ">:"

<language id>

::= "
A
"

| "B" | ... | "Z"

<frequency>

::= <number>

<priority>

::= <number>



11.

Conclusion


The UNL system
can be used in many ways in various locations around the wo
rld.

For example, it is
easy for us to imagine UNL being used in fields as diverse as e
-
commerce, medicine, social welfare,
business, libraries, and entertainment. In addition, UNL can expand the possibilities of other
technologies, such as voice recogniti
on and voice synthesis software, thereby enabling virtual
communication. For example, many universities have virtual university projects and UNL could become
an important technology of these. In short, we are confident that the applications of UNL will imp
rove
both access to knowledge and support distance learning throughout the world.

With the Internet serving as the global information infrastructure, UNL is the medium that facilitates
communication within this infrastructure. In this way, UNL can connect



and even improve


all
kinds of human activities.


As a more conrete applications of the UNL System, following application systems are considered.


Multilingual information Service

Information retrieval system

UNL based search engine

Machine translation

system

Expert system


UNL should be developed by all the people in the world. Universal words necessary for each language
are different from each language. The UNL is a kind of language for computer that everybody will
participate to create and bring u
p.