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6.1. CONCEPTUAL STRUCTURE OF THE UNIARAB SYSTEM has been implemented as a set of XML documents. The use of XML has the added advantage of portability. UniArab will effectively work the same regardless of the operating system. To understand the morphology of each word, we first tokenize each sentence and determine the word relationships. Phase 5 of the system holds all attributes specific to each word of the source sentence. Phase (6) Syntactic Parser Determines the precise phrasal structure and category of the Arabic sentence. At this point, the types and attributes of all words in the sentence are known. Phase (7) Syntactic linking (RRG) We must first develop the link from syntax to semantics out of the phrasal structure created in Phase 6, if we are to create a logical structure that will generate a target language and also act as the link in the opposite direction from semantics to syntax. The system should answer the main question in this phase, who does what to whom? We use the gender of the verb to determine the actor. When the subject and object have different genders, the gender of the verb must match the subject. If they both agree with the verb, then MSA dictates that the first noun is the subject. In this case the actor is Khalid and the undergoer is the book. Phase (8) Logical Structure Creation of logical structure is the most crucial phase. An accurate representation of the logical structure of an Arabic sentence is the primary strength of UniArab. Below is a sample output from the UniArab system. The Arabic equivalent of the past tense sentence ‘Khalid read the book’ qr֓a h ˘ āld ālktāb is input as the source. ālktāb book:N h ˘ āld Khalid:MsgN qr֓a read:V The results of the parse can be seen in the following logical structure: Verb read 82
6.1. CONCEPTUAL STRUCTURE OF THE UNIARAB SYSTEM sg 3rd M PAST qr֓a where the Proper Noun is Khalid sg unspec M h ˘ āld and the Noun is, the book sg def M ālktāb Consider the following example; Omar is a student. be’(Omar,[student’]). in Arabic ֒mr tlmyd ¯ . This is a challenge since there is no verb ‘to be’ in Arabic, but this must be inferred for correct translation. Instead of saying ‘Omar is a student’, the Arabic equivalent would be ‘Omar student’. We also face the challenge of inferring the indefinite article, which does not exist in Arabic. All of the unique information for each word can thus be taken from the lexicon to aid in the creation of a logical structure of the target language. Phase (9) Semantic to Syntax Assuming we have an input and have produced a struc- tured syntactic representation of it, the grammar can map this structure from a semantic representation. In this phase the system uses a linking algorithm provided by RRG to determine actor and undergoer assignments, assign the core arguments and assign the predicate in the nucleus. The system uses semantic arguments of logical structures other than of the main verb. Phase (10) Syntax Generation This will be unique for each target language. In this phase the system uses the target language rules to generate the syntax. In this case English language rules are used. Phase (11) Generate English Morphology The system generates English morphology in an innovative way, generating the tenses not existent in Arabic but in English as well as verb ‘to be’. Figure 6.3 shows the technique used to generate the correct verb tenses, and generate verb to be. Verbs in English have a mood; e.g. indicative, subjunctive, imperative 83
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A generic framework for Arabic to E
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sentence and its linking algorithm
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Declaration I herby certify that th
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advices, but also academically and
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CONTENTS 2.3.1.2 Indefinite nouns .
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CONTENTS 4.4.1 Non-Roman alphabet s
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CONTENTS 7.2.8 Limitation of UniAra
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LIST OF FIGURES 4.4 Difference betw
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List of Tables 2.1 Dual: merely add
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LIST OF TABLES 5.9 Test strategy: p
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1 Introduction The following paragr
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high-quality translation technology
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1.3. TECHNOLOGIES ditransitive). Th
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1.4. THESIS ORGANIZATION 2009b). Ch
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2.1. CHARACTERISTICS OF THE ARABIC
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2.2 Characteristics of Arabic words
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2.2. CHARACTERISTICS OF ARABIC WORD
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2.3. PART OF SPEECH INVENTORY OF TH
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2.3.4 Verbs 2.3. PART OF SPEECH INV
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2.3.4.2 Aspect 2.3. PART OF SPEECH
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2.3. PART OF SPEECH INVENTORY OF TH
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2.4.1.1 Verb and noun 2.4. SENTENCE
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Table 2.27: verb(V), subject(S) and
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3 Role and Reference Grammar (RRG)
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3.1. ROLE AND REFERENCE GRAMMAR LIN
Page 51 and 52: 3.2. FORMAL REPRESENTATION OF LAYER
Page 57 and 58: 3.3. NOUN PHRASE STRUCTURE appropri
Page 59 and 60: 3.4. LEXICAL REPRESENTATIONS FOR VE
Page 61 and 62: 3.5. WHY WE USE RRG AS THE LINGUIST
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Page 65 and 66: 3.6. SUMMARY there will be more com
Page 67 and 68: 4.1. ADVANTAGES OF MACHINE TRANSLAT
Page 69 and 70: 4.2.3 Lexical databases 4.2. COMPUT
Page 71 and 72: 4.3.2 Direct translation 4.3. BASIC
Page 73 and 74: 4.3. BASIC MACHINE TRANSLATION STRA
Page 75 and 76: would also be needed for an interli
Page 77 and 78: 4.4.1 Non-Roman alphabet scripts 4.
Page 79 and 80: Figure 4.5: NP rule (NP -> det n pp
Page 81 and 82: 4.5. CHALLENGES OF ARABIC TO ENGLIS
Page 83 and 84: Figure 4.7: Direct MT system 4.6.2
Page 85 and 86: 4.7 Summary Figure 4.9: Structure t
Page 87 and 88: 5 Design of Arabic to English machi
Page 89 and 90: 5.2. DESIGNING AN XML LEXICON ARCHI
Page 95 and 96: 5.3. DESIGN OF TEST STRATEGY Table
Page 97 and 98: 5.4. DESIGN OF EVALUATION CRITERIA
Page 99 and 100: 6 UniArab: a proof-of-concept Arabi
Page 101: 6.1. CONCEPTUAL STRUCTURE OF THE UN
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Page 107 and 108: 6.2. UNIARAB: LEXICAL REPRESENTATIO
Page 113 and 114: 6.3. UNIARAB: GENERATION which mean
Page 115 and 116: Figure 6.11: UniArab’s GUI 1 6.4.
Page 117 and 118: 6.4.1 Lexicon interface Figure 6.13
Page 119 and 120: 6.6 Summary 6.6. SUMMARY We present
Page 121 and 122: 7.2. SENTENCE TESTS to which standa
Page 123 and 124: Table 7.2: Test : Verb-subject; agr
Page 125 and 126: Figure 7.4: Verb-subject agreement
Page 127 and 128: Table 7.5: Test : gender-ambiguous
Page 129 and 130: Table 7.7: Test : Verb ‘to be’
Page 131 and 132: Table 7.9: Test : Verb ‘to have
Page 133 and 134: 7.2. SENTENCE TESTS Table 7.11: Tes
Page 135 and 136: 7.2.6 Pro-drop Arabic Table 7.13: T
Page 137 and 138: Table 7.15: Test : Intransitive 2 A
Page 139 and 140: 7.2.7.3 Ditransitive Table 7.17: Te
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Page 143 and 144: 7.2. SENTENCE TESTS In a case where
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Page 147 and 148: 7.3. SYSTEM EVALUATION search engin
Page 149 and 150: Now is not the end. It is not the b
Page 151 and 152: 8.1. THESIS SUMMARY and so we hope
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and proving the suitability of the
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References Abn-Aqeal, 2007. sharah
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REFERENCES Salem, Y., Hensman, A.,
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Appendix 139
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• Yasser Salem and Brian Nolan. 2
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Arabic Letter and Phonetic Value Le
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C List of translatable sentences I
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she is an engineer. Zaid loves Fati
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Jack is eating with the spoon.
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Ayah tore the page. ֓āyh
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Eman saw Sarah. r֓at ֓iymā
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Carl is brushing his hair. ym
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I want a book. ֓aryd ktāb
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Omar gave the book to Khalid.
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D Verbs in lexicon Verbs in Arabic
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Arabic Example Logical Structure
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Arabic Example Logical Structure
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Arabic ys. rs. r Example the wheel
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Arabic ֓adrs Example I am teach
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Package: Name of Class Class Summar
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