Acquisition System For Arabic Noun Morphology
Acquisition System for Arabic Noun Morphology
Saleem Abuleil Khalid Alsamara Martha Evens
Information System Department Computer Science Department
Chicago State University Illinois Institute of Technology
9501 S. King Drive, Chicago, IL 60628 10 West 31 Street, Chicago IL 60616
s_abuleil@hotmail.com kalsamara@hotmail.com evens@iit.edu
all the roots in the file. Al-Shalabi reduced the
Abstract
processing, but he discussed this from point of
view of verbs not nouns. Anne Roeck and
Many papers have discussed different
Waleed Al-Fares (2000) developed a clustering
aspects of Arabic verb morphology. Some of
algorithm for Arabic words sharing the same
them used patterns; others used patterns and
verbal root. They used root-based clusters to
affixes. But very few have discussed Arabic
substitute for dictionaries in indexing for
noun morphology particularly for nouns that
information retrieval. Beesley and Karttunen
are not derived from verbs. In this paper we
(2000) described a new technique for
describe a learning system that can analyze
constructing finite-state transducers that
Arabic nouns to produce their
involves reapplying a regular-expression
morphological information and their
compiler to its own output. They implemented
paradigms with respect to both gender and
the system in an algorithm called compile-
number using a rule base that uses suffix
replace. This technique has proved useful for
analysis as well as pattern analysis. The
handling non-concatenate phenomena, and they
system utilizes user-feedback to classify the
demonstrate it on Malay full-stem reduplication
noun and identify the group that it belongs
and Arabic stem inter-digitations.
to.
Most verbs in the Arabic language
follow clear rules that define their morphology
1
Introduction
and generate their paradigms. Those nouns that
are not derived from roots do not seem to follow
A morphology system is the backbone of a
a similar set of well-defined rules. Instead there
natural language processing system. No
are groups showing family resemblances.
application in this field can survive without a
We believe that nouns in Arabic that are
good morphology system to support it. The
not derived from roots are governed not only by
Arabic language has its own features that are not
phonological rules but by lexical patterns that
found in other languages. That is why many
must be identified and stored for each
researchers have worked in this area. Al-Fedaghi
noun. Like irregular verbs in English their forms
and Al-Anzi (1989) present an algorithm to
are determined by history and etymology, not
generate the root and the pattern of a given
just phonology. Among many other examples,
Arabic word. The main concept in the algorithm
Pinker (1999) points to the survival of past
is to locate the position of the root’s letters in the
forms became for become and overcame for
pattern and examine the letters in the same
overcome, modeled on came for come, while
position in a given word to see whether the tri
succumb, with the same sound pattern, has a
graph forms a valid Arabic root or not.
regular past form succumbed. The same kinds
Al-Shalabi (1998) developed a system
of phenomena are especially apparent for proper
that removes the longest possible prefix from the
nouns in Arabic derived from Indian and Persian
word where the three letters of the root must lie
names. Pinker uses examples like this, as well as
somewhere in the first four or five characters of
emerging research in neurophysiology, to argue
the remainder. Then he generates some
for the coexistence of phonological rules and
combinations and checks each one of them with
lexical storage of English verb patterns.
We believe that further work in Arabic
instruments are derived; some are inert.
computational linguistics requires the
Example: حﺎﺘﻔﻣ key
development of a pattern bank for nouns. This
An adjective is considered to be a type
paper describes the tool that we have built for
of noun in traditional Arabic grammar. It
this purpose. While the set of patterns for
describes the state of the modified noun.
common nouns in Arabic may soon be
Example: ﻞﻴﻤﺟ beautiful ﺪﻴﺳ Mr.
established, newspapers and other dynamic
ﺮﺿﺎﺤﻣ Professor ﺮﺒﺒآ big
sources of language will always contain new
An adverb is a noun that is not derived
proper names, so we expect our tool to be a
and that indicates the place or the time of the
permanent part of our system, even though we
action. Example:
may need it less often as time goes on.
ﺮﻬﺷ Month ﺔﻨﻱﺪﻣ city لﺎﻤﺷ north
A proper noun is the name of a specific
2
Nouns in the Arabic Language
person, place, organization, thing, idea, event,
date, time, or other entity. Some of them are
A noun in Arabic is a word that indicates a
solid (inert) nouns some of them are derived
meaning by itself without being connected with
[Abuleil and Evens 1998].
the notion of time. There are two main kinds of
noun: variable and invariable. Variable nouns
3
Noun Classification
have different forms for the singular, the dual,
the plural, the diminutive, and the relative.
In this paper we focus on the following nouns:
Variable nouns are again divided into two kinds:
genus nouns, agent nouns, instrument nouns,
inert and derived. The inert noun is not derived
adjectives, proper adjectives (adjectives derived
from another word, i.e. it does not refer to a
from proper nouns), proper nouns, and adverbs.
verbal root. Inert nouns are divided into two
Some of these nouns are not derived from verbs
kinds: concrete nouns (e.g., lion), and abstract
and some are. All of these nouns use the same
nouns (e.g., love). Derived nouns are taken from
pattern when it comes to the dual form either for
another word (usually a verb) (e.g. office); they
masculine or feminine, but there are many ways
have a root to refer to. A derived noun is usually
to form the plural noun. Some of the nouns have
close to its root in meaning. It indicates, besides
both masculine and feminine forms, some of
the meaning, the concrete thing that caused its
them have just feminine forms and some have
formation (case of the agent-noun), or
just masculine forms. A few nouns use the same
underwent its action (case of the patient-noun),
format for both the plural and the dual (e.g.
or any other notions of time, place, or
ﻦﻴﺳرﺪﻣ teachers used for both dual and plural)
instrument. The following are the noun types:
For most nouns, when they end with the letter
A genus noun indicates what is
(ة), this indicates the feminine form of the noun,
common to every element of the genus without
sometimes it does not, but it changes the
being specific to any one of them. It is the word
meaning of the noun completely (e.g.
ﺐﺘﻜﻣ
naming a person, an animal, a thing or an idea.
office, ﺔﺒﺘﻜﻣ library). Sometimes the same
Example: ﻞﺟر man بﺎﺘآ book
consonant string with different vowels has
An agent noun is a derived noun
different meanings (e.g.
ﺔﺳرﺪﻣ school, ﺔﺳرﺪﻣ
indicating the actor of the verb or its behavior. It
teacher). Nouns are not like verbs in the Arabic
has several patterns according to its root.
language, there is no clear rule to define the
Example:
morphological information and generate the
سراد the person who studies
morphology paradigms for them. Instead each
A patient noun is a derived noun
group of nouns follows its own pattern.
indicating the person or thing that undergoes the
We have classified the nouns into 84
action of the verb. Patient nouns have several
groups according to their patterns for singular,
patterns depending in the verbal root. Example:
plural, masculine and feminine. We generated a
سورﺪﻣ the thing that has been studied
method for each group to be used to find the
An instrument noun is a noun
morphological information and to form its
indicating the tool of an action. Some
paradigm. Very few of these groups have a
unique pattern for plural and singular; and most
noun by running several tests: Database lookup,
of them share the same pattern with other
particle check, check on adjectives derived from
groups. Table 1 shows some examples of these
proper nouns, parse of noun phrases and verb
groups and their patterns. The digit 9 stands for
phrases, the affix check and the pattern check
the letter “ayn [ع]”, ‘ stands for “hamzh [ء]” and
This module was built by Abuleil and Evens
@ stands for “ta [ﻩ]” since there is no
(1998, 2001). We use this module in our new
corresponding letters in English for these letters.
system to find all nouns and extract them from
the text.
Table 1. Pattern Classification
S-M S-F P-M P-F
f9l X af9al X
Interface
f9l f9l@ af9la’ af9la’
X f9l@ X f9l
fa9l fa9l@ f9al/f9l@
f9al/f9l@
User-
DB
f9al X X af9l@
Feedback
Checker
mf9l X mfa9l X
fa9wl X fwa9el X
mf9el X mfa9el X
X fa9l@ X fa9lat
Noun
f9el f9el@ f9la’ f9la’
Database
Morphology
S: Singular
F: Feminine
Analyzer
P: Plural
M: Masculine
Type-
X: not available
Finder
4
Acquisition System
Suffix
Pattern
The system reads the next noun in the text,
Analyzer
Generator
isolates and analyzes the suffixes of the noun,
generates its pattern, and uses either the
Classified Noun Table, the Suffix/Pattern
Figure 1. The Acquisition System
Analysis or the User-Feedback Module to find
the group to which the noun belongs to identify
4.3
Database
the rules that applies to this group to generate all
The database includes a Classified Noun Table
morphological paradigms with respect to the
that contains each root noun (singular:
number and gender and updates the database.
masculine or feminine) and the number of the
The system consists of several modules as
group to which the noun belongs. Each time the
shown in Figure 1.
system identifies a new noun it adds its root to
the Classified Noun Table.
4.1
Interface Module
This graphical user interface allows the user
4.4
Noun Morphology Analyzer
to interact with the system and handles the
Module
input/output. This module displays a main
This is the core of the system, it calls different
menu with two main options: collect nouns
modules and performs different tasks to identify
from documents and find morphological
the noun and find its paradigm. First, it passes
information.
the noun to the suffix analyzer module to drop
the suffix. Second, it passes it to the pattern
4.2
Type-Finder Module
generator module to find the pattern. Third, it
The main function of this module is to read the
analyzes the pattern to see whether it belongs to
document and find the part of speech of the
more than one group. It checks the Classified
word: noun, verb, adjective, particle or proper
Nouns Table and then the suffix/pattern to
identify the group that the noun belongs to. If
4.7
Database Checker Module
the system cannot identify the group then it calls
This module identifies any already classified
the user-Feedback module to produce some
noun or any noun derived from it. It gets the
questions to be answered by the user to reduce
noun and its pattern from the noun morphology
the number of alternatives to one. Finally,
analyzer, finds all groups that contain the
depending on the group the noun belongs to, it
pattern, finds the singular noun (masculine or
generates the morphological paradigms for
feminine) in each group and uses it to check the
number and gender and updates the database.
Classified Noun Table. If the noun exists it gets
the group number to which it belongs and passes
4.5
Suffix Analyzer Module
it to the Noun Morphology Analyzer to generate
This module identifies the suffix, analyzes it and
the results. For example the noun (ﺐﻋﻼﻣ
produces some lexical information about the
playground) has the pattern (mfa9l). This pattern
noun like number and gender. First, it checks if
appears in three different groups. See table 2.
any pronoun is concatenated with the noun.
Second, it checks for a suffix indicating number.
Table 2. The Groups of the Noun “ ﺐﻋﻼﻣ”
Third, it checks for a suffix indicating gender.
Group# Sing. Sing
Plural
Plural
When the letter (ي) comes at the end of
Masc.
Fem.
Masc.
Fem.
the noun there are two cases: it could be a part of
1 X
mf9l@
X
Mfa9l
the noun so we should not drop it, or it could be
2
Mf9l
X
X
Mfa9l
an extra letter as in relative nouns or when the
3
mfa9l mf9l@ mf9lun/ تﺎﺒﻌﻠﻣ
pronoun is connected to the noun and it should
mf9len
be dropped in this case. When the noun ends
with the letters (ﻦﻱ), most of the time it
The nouns formed from these patterns have the
represents dual nouns but some times it
following paradigms. See table 3.
represents both plural and dual nouns as in the
following patterns: mfa9l, fa9l, mf9ull.
Table 3. The Paradigms of the Noun “ ﺐﻋﻼﻣ”
Sometimes we have to check the pattern also to
Group# Sing. Sing
Plural
Plural
help in analyzing the suffix. We will handle
Masc.
Fem.
Masc.
Fem.
1 X
ﺔﺒﻌﻠﻣ X
ﺐﻋﻼﻣ
these problems as special cases.
2
ﺐﻌﻠﻣ
X X ﺐﻋﻼﻣ
3
ﺐﻋﻼﻣ
ﺔﺒﻌﻠﻣ
نﻮﺒﻌﻠﻣ/
تﺎﺒﻌﻠﻣ
4.6
Pattern Generator Module
ﻦﻴﺒﻌﻠﻣ
We have collected 62 different patterns used for
both masculine and feminine, singular and plural
If the noun itself or any other noun derived from
after the suffix has been dropped see Appendix
it has been previously classified we will find its
A. We used these patterns to generate a set of
noun root (singular noun) in the Classified Noun
rules to build a finite-state diagram to be used to
Table. The module will find the root (singular
find the pattern for any noun. The input to this
masculine) “ﺐﻌﻠﻣ” in the table and will get its
module is a noun after its suffix has been
group number “2” and pass it to Noun
dropped in the previous step, the output is one or
Morphology Analyzer to find the noun
more patterns. If more than one pattern is found
paradigms.
we validate the string by checking the pattern
table.
4.8
User-Feedback Module
The letter (م) and the letter (ا) at the
This module gets all alternatives (groups) from
beginning of the noun are sometimes the first
the noun morphology analyzer module. It
characters of the noun, but sometimes they are
analyzes them and generates some questions to
separate words. We collected the nouns that
be answered by the user. It gets the answers,
begin with the letter (م) and the letter (ا) and
analyzes them and finds the group that the noun
saved them in a file to help us to distinguish
belongs to. The module asks questions like: Is
between these two cases.
the noun a singular? Is the noun a plural? Does
the noun have a masculine-singular format?
column name to form questions. For the “A1”
Does the noun have a feminine-singular format?
value use the following question: is the noun a
[column name]? For the “B1” use the following
Example:
question: does the noun have the [column name]
Input: The noun (ﺐﻋﻼﻣ playground)
format? Get the answer and drop invalid
Pattern: mfa9l
group(s).
Number of groups that contain the
pattern is 3.
Group# Sing.
Sing. Plural
Plural
Masc. Fem. Masc.
Fem.
Process:
1 -1
0
-1
1
Step #1: identify the groups
2 0
-1
-1
1
A = Σ1’s
0 0 0
2
Group# Sing. Sing.
Plural
Plural
B = Σ-1’s
1 1 2
0
Masc.
Fem.
Masc.
Fem.
C = Σ 0’s
1 1 0
0
1
X
mf9l@ X
mfa9l
A1 = #G – A
2
2
2
0
2
mf9l
X
X
mfa9l
B1 = #G – B
1
1
0
2
3
mfa9l mf9l@ mf9lun / mf9lat
mf9len
Step #5: Repeat step 3 and step 4 until you end
up with one group or all the values in both Row
Step #2: Replace (X) with –1, given pattern with
A1 and row B1 have the values either zero or the
1 and any thing else with 0.
number of groups left.
Group# Sing. Sing.
Plural
Plural
Step #6: if more than one group is left from step
Masc.
Fem.
Masc.
Fem.
#5 then find the largest value in the row “C”
1 -1
0
-1
1
from left to right and ask the following question:
2 0
-1
-1
1
which of the following [list all the options in that
3
1 0 0 0 column] is the [column name] of the noun?
Step #3: Add the one’s in each column and
Group
Sing.
Sing.
Plural
Plural
subtract it from number of groups. Add the (-
#
Masc. Fem.
Masc.
Fem.
1’s) in each column and subtract it from number
2 0
-1
-1
1
of groups. Add the (0’s) in each column.
A = Σ1’s
0 0 0 1
B = Σ-1’s
0 1 1 0
Group# Sing.
Sing. Plural
Plural
C = Σ 0’s
1 0 0 0
Masc. Fem. Masc.
Fem.
A1 = #G – A
1
1
1
0
1 -1
0
-1
1 B1 = #G – B
1
0
0
1
2 0
-1
-1
1
3 1
0
0
0 The questions the module generated from the
A = Σ1’s
1 0 0 2
previous example are:
B = Σ-1’s
1 1 2 0
Q1: is the noun plural feminine?
C = Σ 0’s
1 2 1 1
Answer: yes
// the system drops group#3
A1 = #G – A
2
3
3
1
Q2: does the noun have singular masculine
B1 = #G – B
2
2
1
3
format?
Answer: No // the system drops group#1
From the table above we know that: the
probability that the noun is singular masculine is
Result:
33.3% and the probability that it is a plural
Group # 2: The noun (ﺐﻋﻼﻣ playground) is a
feminine is 66.6%.
plural Feminine. The singular Masculine format
is (
ﺐﻌﻠﻣ), the singular Feminine format and
Step #4: Pick the smallest value greater than 0
plural masculine format are not available for this
from the “A1” row and the “B1” row go from
noun.
left to right and from top to bottom. Use the
5
Examples
Fifth, it generates the results: group#38 and
updates the database. Table 6 shows system
The following example shows how the system
output for some input.
works. Assume that the input is the noun ( ﻢﻬﺘﺏرﺪﻣ
their trainer), First the system calls the suffix
Table 6. System Output
analyzer module to drop the extra letter
Noun
ﺢﻴﺕﺎﻔﻣ
ةﺮﺋﺎﻃ
ﺎﻨﺕﻮﺻ
ﻦﻴﻤﻱﺮآ
(pronoun: their) at the end ( ﻢه + ﺖﺏرﺪﻣ), replace
keys
plane
Our
generous
sound
the letter (ت) with the letter (ة), generate the
Suffix
---- ---- ﺎﻥ
ﻦﻱ
noun (ﺔﺏرﺪﻣ trainer) and some lexical information
about the noun.
Pattern
ﻞﻴﻋﺎﻔﻣ
ﺔﻠﻋﺎﻓ
ﻞﻌﻓ
ﻞﻴﻌﻓ
Second, it passes the noun (ﺔﺏرﺪﻣ trainer)
mfa9el
fa9l@
f9l
f9el
to the pattern generator module to generate the
Group #
52 23 3 37
pattern (mf9l@). Third, it checks the group table
Result
Plural
Singular
Singular
Dual /
looking for this pattern (mf9l@). Fourth, if more
masc.
Feminine feminine
plural
that one group is found it uses the Database
masc.
Checker Module to check the Classified Noun
Singular
حﺎﺘﻔﻣ X تﻮﺻ
ﻢﻱﺮآ
Table. Fifth, if the noun does not exist in the
/ Masc.
Singular
X
ةﺮﺋﺎﻃ X ﺔﻤﻱﺮآ
table, it calls the User-Feedback Module to
/ Fem.
analyze the groups (all alternatives) and asks the
Plural /
X X X ءﺎﻣﺮآ /
user some questions to assist in identifying the
Masc.
ﻦﻴﻤﻱﺮآ
group see Table 4 and Table 5. The question that
Plural /
ﺢﻴﺕﺎﻔﻣ
تاﺮﺋﺎﻃ
تاﻮﺻا
تﺎﻤﻱﺮآ
the module generated is:
Fem.
Dual /
ﻦﻴﺡﺎﺘﻔﻣ
X
ﻦﻴﺕﻮﺻ
ﻦﻴﻤﻱﺮآ
Masc.
نﺎﺡﺎﺘﻔﻣ
نﺎﺕﻮﺻ
نﺎﻤﻱﺮآ
Question: Does the noun have a masculine-
Dual /
X
ﻦﻴﺕﺮﺋﺎﻃ
X
ﻦﻴﺘﻤﻱﺮآ
singular format?
Fem.
نﺎﺕﺮﺋﺎﻃ
نﺎﺘﻤﻱﺮآ
Answer: Yes
Result: drop group # 10 & group # 22
6
Results
Table 4. First Cycle to Generate Question
To test our system we used nouns obtained from
Group #
Sing.
Sing
Plural Plural
a corpus developed by Ahmad Hasnah based on
Masc. Fem.
Masc. Fem.
text given to Illinois Institute of Technology, by
10
-1 1 0 -1
the newspaper, Al-Raya, published in Qatar. We
22
-1 1 0 -1
have tested each module in our system: the
38
0 1 0 0
suffix analyzer modules, the pattern generator
A = Σ1’s
0 3 0 0
module, and the user-Feedback module. Table 7
B = Σ-1’s
2 0 0 2
shows the result of testing the system on 500
C = Σ 0’s
1 0 3 1
nouns.
A1 = #G – A
3
0
3
3
B1 = #G – B
1
3
3
1
Table 7. Suffix / Pattern / Noun Morphology
Analyzer
Table 5. Second Cycle to Generate Question
#
#
%
%
Group #
Sing.
Sing
Plural Plural
correct incorrect correct incorrect
Masc. Fem.
Masc. Fem.
Suffix
38
0 1 0 0
Analyzer
490
10
97%
3%
A = Σ1’s
0 1 0 0
Pattern
B = Σ-1’s
0 0 0 0
Analyzer
471
29
93%
8%
Noun
C = Σ 0’s
1 0 1 1
Morph
451
49
90.2%
9.8%
A1 = #G – A
1
0
1
1
analyzer
B1 = #G – B
1
1
1
1
As shown in Table 7 there were ten failure
because of incorrect suffix analysis and 29 due
to missing patterns. These missing patterns have
University of Montreal, Montreal, PQ, Canada,
now been added. The suffix analysis problem is
Aug 16 1998, pp 1-7.
hard to correct because it arises from underlying
ambiguities. If the noun has been classified
Abuleil, S. and Evens, M., 2002. Extracting an
previously the system does not have any
Arabic Lexicon from Arabic Newspaper Text.
problem to identify it and identify any noun
Computers and the Humanities, 36(2), pp. 191-
derived from it.
221.
The User-Feedback Module found most
of the nouns that the Database Checker Module
Al-Fedaghi, Sabah and Al-Anzi, Fawaz, 1989.
failed to identify. Table 8 shows a number of
“A New Algorithm to Generate Arabic Root-
nouns identified by suffix/pattern, nouns
Pattern Forms”. Proceedings of the 11th National
identified by Database Checker Module and
Computer Conference, King Fahd University of
nouns identified by User-Feedback Modules.
Petroleum & Minerals, Dhahran, Saudi Arabia.,
We believe that the more knowledge that the
pp 4-7.
system gains and the more nouns that it adds to
the Classified Noun Table the fewer questions
Al-Shalabi, R. and Evens, M., 1998. “A
have to be asked.
Computational Morphology System for Arabic”.
Workshop on Semitic Language Processing.
Table 8. Noun Classifier Methods
COLING-ACL’98, University of Montreal,
Nouns
Nouns
Nouns Identified
Montreal, PQ, Canada, Aug 16 1998. pp. 66-72.
Identified by
Identified by
by
Database
Suffix/
User-Feedback
Beesley, K. and Karttunen, L., 2000. “Finite-
Checker
Pattern
Module
State Non-Concatenative Morphotactics”.
Analysis
Proceedings of the 38th Annual Meeting of the
Association for Computational Linguistics.
144
32
289
Hong Kong, Oct 1-8, 2000. pp.191-198.
28.8%
7.1%
64.1%
Hasnah, A., 1996. Full Text Processing and
Retrieval: Weight Ranking, Text Structuring,
7
Conclusion
and Passage Retrieval For Arabic Documents.
Ph.D. Dissertation, Illinois Institute of
We have built a learning system that utilizes
Technology, Chicago, IL.
user feedback to identify the nouns in the Arabic
language, obtain their features and generate their
Roeck, A. and Al-Fares, W., 2000. “A
paradigms with respect to number and gender.
Morphologically Sensitive Clustering Algorithm
We tested the system on 500 nouns from
for Identifying Arabic Roots”. Proceedings of
newspaper text. The system identified 90.2% of
the 38th Annual Meeting of the Association for
them, 7.1% by just analyzing the suffix and the
Computational Linguistics. Hong Kong, Oct 1-8,
pattern of the noun, 28.8% by using the
2000. pp.199-206.
Database Checker Module and the Classified
Noun Table and 64.1% by using User-Feedback
Module. The system failed on 9.8% of the tested
Appendix A. Patterns
nouns.
Pattern Used
for
Example
References
f9l
sing – masc.
ﻞﻤﺟ
f9l
plural – masc.
رﺰﺟ
Abuleil, S. and Evens, M., 1998. “Discovering
f9l
plural – fem. / masc.
بﺮﻋ
Lexical Information by Tagging Arabic
f9l
plural – fem.
رﻮﺻ
Newspaper Text”, Workshop on Semitic
f9l
sing – masc.
ءﻮﺿ
Language Processing. COLING-ACL’98,
f9l@
sing. – fem.
ةرﻮﺻ
mf9al sing.
masc.
حﺎﺘﻔﻣ
Pattern Used
for
Example
Pattern Used
for
Example
f9l@
plural – masc.
ﺔﻠﺘﻗ
Mstf9l
sing. – masc.
مﺪﺨﺘﺴﻣ
aft9al
sing. – masc.
عاﺮﺘﺧا
mf9ll
sing. – masc.
ﻞﺴﻠﺴﻣ
anf9al
sing. – masc.
رﺎﺠﻔﻥا
Mstf9a sing.
fem.
ﻰﻔﺸﺘﺴﻣ
astf9al
sing. - masc.
رﺎﻤﺜﺘﺳا
mf9wl@
sing. – fem.
ﺔﻋﻮﺳﻮﻣ
af9al
plural – fem.
رﺎﺠﺷا
mf9el sing.
masc.
ﻞﻱﺪﻨﻣ
af9la’
plural – fem. / masc.
ءﺎﻴﻨﻏا
mfa9el
plural – fem.
ﻞﻱدﺎﻨﻣ
af9l@
plural – fem.
ﺔﻱودا
mf9le@
sing. – fem.
ﺔﻴﺡﺮﺴﻣ
af9el
sing. – masc.
ﻖﻱﺮﺏا
mfa9l
sing. – masc.
ﻞﺕﺎﻘﻣ
afa9el
plural – fem.
ﻖﻱرﺎﺏا
mfa9l@
sing. – fem.
ةﺮهﺎﻈﻣ
f9lawat
plural – fem.
تاواﺮﻤﺡ
mf9wl
sing. – masc.
عوﺮﺸﻣ
fwa9l
plural – fem.
ﻊﻣاﻮﺟ
mfa9el
plural – fem.
ﻊﻱرﺎﺸﻣ
fwa9el
plural – fem.
ﻦﻱزاﻮﻣ
fe9al sing-
masc.
ناﺰﻴﻣ
f9lan
plural – fem.
نﻻﺰﻏ
f9all
plural – fem.
ﻞﺏﺎﻨﻗ
tf9l@
plural – fem.
ﺔﻔﻠﻜﺕ
f9wl@ plural
–fem.
ﺔﻣﻮﻜﺡ
f9wl
sing. – masc.
دﻮﻤﻋ
f9ll@ sing-
fem.
ﺔﻠﺒﻨﻗ
f9le@
sing. – fem.
ﺔﻴﻌﻤﺟ
f9le sing.-
masc.
ﻲﻔﺤﺻ
f9el
sing – masc.
ﻢﻱﺮآ
f9el@ sing.-
fem.
ةﺮﻱﺰﺟ
f9al sing.-
masc.
رﺎﻄﻣ
f9al
plural – fem.
لﺎﻤﺟ
f9ale
plural – fem.
يرﺎﺤﺻ
fa9l
sing. – masc.
ﻢﻝﺎﻋ
fa9l@
sing. – fem.
ةﺮﺧﺎﺏ
f9al@
sing. – fem.
ةرﺎﺴﺧ
f9al
plural – masc.
دﺎﺠﺳ
f9la’
plural – masc.
ءﺎﻤﻠﻋ
f9la’
sing. – fem.
ءاﺮﻤﺡ
f9alel
plural – fem. / masc.
ﺮﻴهﺎﻤﺟ
fa9wl sing.
masc.
خورﺎﺻ
f9a’l
plural – fem.
ﺐﺋﺎﻘﺡ
tf9el
sing. – masc.
ﻦﻱﺮﻤﺕ
f9lwl
sing. – masc.
رﻮﻬﻤﺟ
tfa9el
plural – fem.
ﻦﻱرﺎﻤﺕ
fw9l@
sing. – fem.
ةﺮهﻮﺟ
f9wal
sing. – masc.
ناﻮﻨﻋ
f9awel
plural – fem.
ﻦﻱوﺎﻨﻋ
mf9l@
sing. – fem.
ةﺮﺠﻨﻣ
mfa9l
plural – fem.
ﺮﺟﺎﻨﻣ
mf9l
sing. – masc.
سرﺪﻣ
mf9l@
sing. – fem.
ﺔﺳرﺪﻣ
mf9l
sing. – masc.
ﺐﺘﻜﻣ
mf9l@
sing. – fem.
ﺔﺒﺘﻜﻣ
mft9l sing.
masc.
ﻞﻘﺘﻌﻣ
