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/> EnglishTranslate=“read” Table 5.2: Verb 2 Arabic verb ktbt English translation wrote Logical structure [do’(x,[write’(x,(y)])] Tense past Gender f Person 3rd Number singular LogicalStructures= “” NumberVerb=“sg” P.O.S=“Verb” genderVerb=“M” personVerb=“3rd” tenseVerb=“PAST” 5.3 Design of test strategy 5.3. DESIGN OF TEST STRATEGY We will create variants of Arabic sentences that represent all possible structures of sentences that UniArab can translate. We will evaluate the result of the system output by comparing between human-translated and machine-translated versions. In Tables 5.3 to 5.9 we represent some examples of sentences that are used to test the UniArab system. For actual test examples see Appendix C. Verb-Subject one argument in deferent tenses: In Table 5.3, Verb-Subject Agreement with two arguments sentences, are sentences where UniArab should select the correct form of the verb. In particular the verb must agree with the subject. 74
5.3. DESIGN OF TEST STRATEGY Table 5.3: Test strategy: verb-subject agreement Arabic human-translated UniArab other yˇsrb ֒mr ālh. lyb Omar is drinking the milk. ? ? ˇsrb ֒mr ālh. lyb Omar drank the milk. ? ? mārk qrā ālktāb Mark read the book. ? ? syˇsrb mārk āllbn Mark will drink the milk ? ? Demonstrative Adjective-Noun: The system should place the Demonstrative Adjective-Noun Agreement that agrees in number and gender. The test sentences are shown in Table 5.4. Table 5.4: Test strategy: demonstrative adjective-noun agreement Arabic human-translated UniArab best of rest hd ¯ ā ālrˇgl This man ? ? d ¯ lk ālrˇgl That man ? ? Gender-Ambiguous proper nouns: Proper nouns can confuse MT in two different ways. The first, the MT system may not identify that the word is a proper noun and analyse it as a noun, adjective, or any other categories. The second is that it may fail to identify the gender of the noun and thus fail to provide information needed for agreement in Arabic. The test sentences are shown in Table 5.5. The UniArab system should follow the rules for agreement in number and gender. This is due to the fact that Arabic differs greatly from English in the distribution of number and gender in the pronoun system, lexical items as well as the syntactic structure. This difference results in many agreement problems during the translation process. Table 5.5: Test strategy: gender-ambiguous proper nouns Arabic human-translated UniArab best of rest qr֓a ˇgāk ālktāb Jack read the book. ? ? qr֓at māry ālktāb Mary read the book. ? ? 75
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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
Page 43 and 44: 2.4.1.1 Verb and noun 2.4. SENTENCE
Page 45 and 46: Table 2.27: verb(V), subject(S) and
Page 47 and 48: 3 Role and Reference Grammar (RRG)
Page 49 and 50: 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
Page 63 and 64: 3.5. WHY WE USE RRG AS THE LINGUIST
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 91 and 92: 5.2. DESIGNING AN XML LEXICON ARCHI
Page 93: 5.2. DESIGNING AN XML LEXICON ARCHI
Page 97 and 98: 5.4. DESIGN OF EVALUATION CRITERIA
Page 99 and 100: 6 UniArab: a proof-of-concept Arabi
Page 101 and 102: 6.1. CONCEPTUAL STRUCTURE OF THE UN
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
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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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7.3 System evaluation 7.3. SYSTEM E
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7.3. SYSTEM EVALUATION search engin
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Now is not the end. It is not the b
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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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