C, Ryding, , pp. The singular words are unmarked. In addition to word forms, appropriate to the singular and to the plural, which imply more than two entities, Arabic also uses dual when the reference is to two individual entities of category Beeston, A. Some feminine nouns take a masculine sound plural, e. As for the broken plural, it is necessary to know the importance of word forms, or patterns in Arabic. The great majority of Arabic roots are trilateral, consisting of three radical letters , or consonants.
The combination of trilateral root gives a basic meaning. By modifying the root, by the addition of suffixes and prefixes, and by the vowel change, a large number of word patterns can be formed from each root. These patterns have got to be learnt along with the singular. The following are the most frequent and common patterns of broken plural: i. In addition to the above mentioned patterns, irregular plurals are also found in Arabic.
Gender is a grammatical category in Arabic. For the most part, gender is overtly marked, but there are words whose gender is covert and shows up only in agreement sequences. The gender category into which a noun falls is semantically arbitrary, except where nouns refer to human beings or other living creatures.
Gender is marked on adjectives, pronouns, and verbs, as well, but not inherent, as it is in nouns'' Karin, C. Ryding, , p.
The same feminine ending occurs in many words which have no masculine form, e. The adjective agrees with the noun it qualifies, e. But it is not always easy to recognize gender by significance.
Generally, all common and proper nouns that denote females, proper names of countries and towns , names of the body and collective nouns are feminine" Frayha, Anis, , p. The following classes of words are feminine without requiring a feminine ending: a Nouns denoting a feminine by meaning, e.
A number of words are of common gender and may be used as masculine or feminine, e. It is also used as a predicate of the nominal sentence, e. The accusative case is used for the subject of the verb, e. The governing noun comes first and loses its nunation" Tritton A. Thus, the word that governs the genitive is itself definite but never takes the article, e. All prepositions govern the genitive, e. The independent personal pronouns are used in the nominative case. The dependent or attached pronouns, on the other hand, are bound morphemes.
In addition to personal pronouns, Arabic has demonstrative, relative, and interrogative pronouns. Findings and Conclusion The contrastive analysis of the noun morphology in English and Arabic, carried out in this research, reveals the following facts: 1 Both English and Arabic share some features in their derivational structure.
Both suffixes may be added to form nouns, verbs and adjectives. Every word in Arabic may be referred to a significant root consisting of three consonants. By means of morphological processes of adding suffixes, internal vowel modification, infinite number of nouns and verbs can be derived.
Whereas, Arabic nouns have three numbers: singular, dual and plural. Gender is solely confined to personal pronouns. Whereas Arabic has only two genders: masculine and feminine.
Whereas, in Arabic, nouns are inflected for three cases, namely, nominative, accusative, and genitive. These cases are distinguished by changing the vowel ling of the final consonant. It is rather simple with regard to number, gender and case distinction. In Arabic, there is a full set of distinction for number, gender, and case. Arabic has twelve forms of independent pronouns, distinguished in number as: singular, dual, and plural.
Whereas, English has eight personal pronouns distinguished in number as: singular and plural. It does distinguish between near and far objects in number. Arabic makes distinction of gender as well as of number. Thus, it has been observed that both languages share some common features as well as several differences. In the light of such findings, the linguistic problems of the Arabic speakers learning English may be solved. In other words, through this comparison and contrast, the teacher will be aware of the structure of the two languages and the areas of difficulties of the learners at the morphological level.
It is also hoped that the analysis and results of this study would be useful both to teachers and textbooks writers of English and Arabic as foreign languages. Cambridge University, London. Block, B. Outlines of Linguistic Analysis. Linguistic Society of America. Cowan, D. An Introduction to Modern Literary Arabic.
London: Cambridge University Press. Descout, R. New York. Frayha, A. Beirut: Khayat. Fries, C. Teaching and Learning English as a Second Language. Please see chapters 7, 9 and 11 in this volume. To develop tools that enable English speakers with limited or no knowledge of Arabic deduce the gist or the general meaning of Arabic texts. To be able to extract pieces of information of interest such as person names, addresses, phone numbers, email addresses, etc.
Produce tools that can comprehend a limited set of spoken Arabic phrases and short sentences and that are capable of producing spoken short Arabic utterances on demand. Develop high quality Arabic to English machine translation systems.
Clearly, the emphasis is on developing Arabic language capabilities for non-Arabic speaking individuals. We will see below that the objectives of Arabic computational linguistics in the Arabic speaking world is quite different. Transfer of knowledge and technology to the Arab World. Most recent publica- tions in science and technology are published in the English language and are not accessible to Arab readers who have no competence in English.
For humans to translate this huge amount of material to Arabic is very costly and time consum- ing. Arabic NLP could reduce the time and cost of translating, summarizing and retrieving information in Arabic for Arab speakers.
Modernize and fertilize the Arabic language. This follows from 1 above. Trans- lating new concepts and terminology into Arabic involves coinage, arabizations and making use of lexical gaps in the Arabic language.
This will have a dramatic effect on the revitalization of the Arabic language, allowing it to fulfill essential needs for its speakers. Improve and modernize Arabic linguistics. Arabic NLP needs a more formal and precise grammar of Arabic than the current traditional grammar.
Innovation is needed while preserving the valuable heritage of traditional Arab grammarians. Make information retrieval, extraction, summarization and translation available to the Arab user. The hope is to bridge the gap between peoples of the Arab world and their peers in the advanced countries. By making information available to the Arabs in their native language, Arabic NLP tools empower the current generation of educated Arabs.
Thus Arabic NLP tools are indispensable in the struggle of Arabs to keep pace with the rest of the world. This is a matter of national security for the Arab World Farghaly, December Pioneering work on the computational morphology of Arabic focused on the retrieval of the consonantal root from fully inflected words Hlal, , through the process of decomposition and repeated matching against a dictionary of roots.
Arabic morphology poses a challenge from a theoretical point of view McCarthy, , Farghaly, , For example, McCarthy proposes a two tier notation where the elements of the consonantal root are on one tier and the vocalism is on a separate tier. Farghaly says that Arabic surface words must be analyzed at three levels: the level of the unpronounceable root, the level of the vocalism and the level of the affixes.
Farghaly suggests that the Arabic lexicon may consist of underspecified entries to represent the discontinuous nature of Arabic morphemes. The question of what constitutes entries in the Arabic lexicon has not been resolved yet. Most Arabic morphological analyzers including the most advanced treat- ment of Arabic morphology at Xerox Research Center in France embrace the view that the root is the basic entry in the Arabic lexicon Beesley, Recently, it has been shown that a stem-based approach to Arabic morphology would be more relevant for Arabic computational linguistics applications Buckwalter, , Farghaly and Senel- lart, Positing the stem as the main entry in the Arabic lexicon eliminates the step of generating stems from roots.
Stems are then associated with appropriate mor- phological, syntactic and semantic features that are needed in the syntactic analysis of Arabic. But most current morphological systems do not go beyond the strict morpholog- ical analysis of Arabic words. The morphology syntax interface is often neglected as has been noted in chapter 5 in this volume.
A verb like I. Such information is crucial for checking agreement to identify syntactic categories. Information about stems that is relevant for syntactic analysis should be included in any adequate morphological analysis of Arabic.
It is not sufficient to correctly isolate stems from all affixes. What is needed is to highlight morphological information that can be relevant in the syntactic and semantic analysis of Arabic. Consonants in an Arabic stem almost always alone carry the lexical meaning of that stem. Consider the following list: 1. Derivations of different forms do not alter the members of the root nor their order.
Instead, derivations are accomplished by modifying the vocalism. Each stem has a different vocalism while the consonants of the root remain constant. This well known and attested observation has profound implications for Arabic speech recognition and Arabic language teaching.
Arabic speakers seem to have intuitions about the role of consonants and vowels in their language. Unlike speakers of other languages, Arabic speakers can afford to pay less attention to the vowels than the consonants since only consonants carry the semantic meaning which is more crucial to understanding the message than is the grammatical information carried by the vocalism.
An Arabic speaker hearing this word by a speaker of another dialect does not need to think twice before relating what he heard to the equivalent in his dialect because they share the same consonants and differ only in the vocalism. The implications for speech recognition is that training Arabic speech recognition systems would be different from training the system for other languages.
Training for Arabic could assign more weight to consonants than to vowels. In the last ten years, there has been excellent and much needed work at the Linguistic Data Consortium of UPenn for compiling and annotating various corpora of Modern Standard Arabic and the dialects. These resources have become available to researchers and developers in academia and the industry.
The following are a few comments on the latest Arabic Treebank guidelines released in August Maamouri et al. The nominal sentence is one that consists of a subject and a predicate but lacks a verb. Both 21 and 22 have a verb, a subject and an object. However, traditional Arabic grammar considers 21 to be a nominal sentence because it begins with a noun while it regards 22 to be a verbal sentence because it begins with a verb. The ATB guidelines, correctly, regards both sentences to be verbal because both contain a verb.
Unfortunately, this is not the case. Then a trace would follow the verb with an index pointing to the TOP which is another way of saying that what has been categorized as TOP is actu- ally the subject. Actually only subjects that precede the verb would have full agreement with the verb. There is no reason to impose an imaginary deep structure order on all surface realizations. It would be more useful for Arabic computational linguistics applications to identify the subject and objects of Arabic sentences regardless of where they occur in the surface structure.
Whether the subject or object occurs before or after the verb does not change its function in the sentences. It is this function that is crucial for understanding who did what to whom. The trace is an indication that the subject was in the original place and then moved to the front. There is another case when the subject is completely dropped from the sentence as the example given on page 13 in the guideline which we present below in This sentence is a subjectless sentence.
Arabic allows the subject to drop only if the verb is inflected as the inflection on the verb provides information on the subject. Copying these features from the verb into the subject node could be of great help in MT systems. For example, The first term of such a construct is almost always indefinite. It governs the second element and assigns it genitive case. Like English, it is recursive. The whole construct acquires its gender and number from the first term while its definiteness is determined by the definiteness of the last term of the construct.
Although the noun construct is analyzed correctly in the ATB trees as a noun phrase, this construction is not marked as a possessive noun phrase or as a noun construct. The noun construct is very common in Arabic and categorizing it as a possessive NP or as an Idaafa or as a noun construct is necessary for correct translation it by machine translation systems.
This is not very informative. In the later case, it is best categorized as a aspect marker. This is the tag it should have when it comes before an imperfect verb. This is its function when it appears before a perfect verb. More detailed analysis of functional words is needed. Although the absence of the morphological tags ob- scure the syntactic analysis, one would expect at least all heads of maximal projections would be marked.
The analysis of Arabic sentences in the ATB guidelines shows verb phrases and prepositional phrases dominating verbs and prepositions, respectively. An example from the ATB guidelines is given in figure 3. No constituent in this noun phrase is marked as head. Specifying the head is particularly important when analyzing the noun construct. The head of the gender and number of the head of the noun construct is percolated to the maximal projection.
The noun construct structure is [N [NP]]. The gender and number of the headhead of the construct becomes the gender and number of the whole construct. In 25 the gender of the head of the noun construct is feminine and becomes the gender of the whole noun construct.
Thus, the verb agrees with the subject in gender and is feminine while the verb in 24 agrees in gender with the noun construct which is masculine.
The giving was to Ali. Now we expect that a parser generates two different parses of 26 and 27 with the preposition in 26 attached to the verb and the preposition in 27 attached to the noun phrase. Passing sentences 26 and 27 to the Stanford Arabic parser which was trained on the ATB annotated corpus of MSA, we get the parse trees shown in 28 and However, the structure in 27 is identical to that in 26 which signals that the parser should have detected the difference in the prepositional attachment in 26 and This is an area where the ATB could provide corpora focusing on the problematic areas in Arabic computational linguistics.
Figures 4 and 5 below show the difference in structure of 28 and Another problem that faces Arabic computational linguists is finding where a con- stituent ends. It is usually easy to learn where a syntactic constituent begins. It usually has a head and the head usually occurs in the early part of a constituent in head-initial languages.
It is difficult especially in Arabic, to define the point where a NP ends and the other begins. A speaker of Arabic would say this sentence consists of a verb followed by a subject and an object and is a regular VSO Arabic sentence. We passed the sentence to the Stanford Arabic parser.
The following is the parse tree. The higher NP node immediately dominates two NPs which are the subject and the direct object of the sentence. Assigning the subject and direct object to one node equates them as one argument. One would expect the direct object to have a sister node with the verb equal to that of the subject.
The problem here is to find out when the two noun phrases form one constituent and thus can have a higher NP node dominating them, or when they are two different arguments and should not have a common node immediately dominant.
In order for a parser to learn to differentiate the two structures, a large annotated corpora focusing on the problematic areas in Arabic computational linguistics would be extremely beneficial. The stability of the Arabic language, its inseparable ties to Islam, and its in- teresting linguistic properties raise many interesting questions for research. Furthermore, an understanding of its history, culture and linguistic properties is key to productive cultural dialog with the West. Interest in the Arabic language and culture surged in the last few years and as a result, several state-of-the-art computational tools have been developed using machine learning and engineering knowledge.
Such efforts could benefit from a fresh look at the Arabic language and its structure. Finally, we talked about computational Arabic morphology and pointed to the absence of descriptions of the morphology-syntax inter- face. We looked at the recent Arabic treebank guidelines and pointed out some possible improvements. References Abe, Shigeo. Support Vector Machines for Pattern Classification. Advances in Pattern Recognition. London: Springer Verlag.
Antonius, George. Beirut, Lebanon: Librairie du Liban. Arjomand, Said Amir. International Journal of Middle East Studies 41 4. Badawi, Al-Saeed Muhammad. Baldi, Pierre and Seren Brunak. Bioinformatics: The Machine Learning Approach. Mas- sachusetts: MIT Press, 2nd edn. Bateson, Mary Catherine. Arabic Language Handbook. Bauman, Richard. Verbal Art as Performance. Rowley, Massachusetts: Newbury House. Beesley, Kenneth.
Finite-state morphological analysis and generation of Arabic at Xerox research: Status and plans in In ACL 39th Meeting. Proceedings of the workshop on Arabic language Processing; Status and Prospects, pages 1—8. Bender, Emily. Athens, Greece. Benmamoun, Elabbas. Oxford: Oxford University Press. Biesterfeldt, Hans Hinrich. Medieval Arabic encyclopedias of science and philosophy.
Harvey, ed. Dordrecht: Kluwer Academic Publishers. Bishop, Christopher M. Pattern Recognition and Machine Learning. Information Science and Statistics. London: Springer. Bresnan, Joan. Lexical-Functional Syntax. Broadwell, George Aaron. Bergen, Norway. Buckwalter, Tim. Buckwalter Arabic morphological analyzer version 1. Cherkassky, Vladimir and Filip M. Learning from Data: Concepts, Theory and Methods.
New Jersey: John Wiley and Sons. Chomsky, Noam. Aspects of the Theory of Syntax. Cambridge, Mass. Lectures on Government and Binding. Dordrecht: Foris. New York: Praeger Publishers. The Minimalist Program. Washington, D. Eid, Mushira. Arabic grammar between the industry and on Abdel Fattah Mohamed Habib. Arabic grammar between the industry and meaning. Context and meaning - in the study of Arabic grammar methods.
Meaning in Arabic grammar - between the fulfillment of the function of language and grammatical constraints workmanship. More with book covers. Book Quotes "Arabic grammar terms and meanings".
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