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7.4 Summary 7.4. SUMMARY In this chapter we subjected the UniArab System to a series of tests in a wide range of sentence categories. For each test we compared the results obtained through UniArab to those obtained when using translation engines from Google and Microsoft. We also presented a human-translated equivalent to each. In contrast, the Google and Microsoft translators gave mixed results. In many cases, sentence meaning was lacking, and even some basic constructs could not be translated. Perhaps this is due to their focus on translating long sentences and paragraphs. We highlighted this by comparing them to UniArab for longer compound sentences and found that they did indeed convey more of the meaning. These results suggest that RRG is a promising candidate for Arabic to English Machine translation, and as the grammar is developed, the system should begin to cope with more complicated sentences. For simplex sentences (intransitive, transitive and ditransitive) it clearly outperforms existing systems. 128
Now is not the end. It is not the beginning of the end. It is perhaps, the end of the beginning. Winston Churchill 8 Conclusion In this thesis we have presented an Arabic to English machine translation system called UniArab, which is based on the Role and Reference Grammar model. We detailed the design of the system and how it was built to accommodate specifics of the Arabic lan- guage and the generation of English translations. We started with the goal of designing a machine translation system that could show whether we can extract logical structure from Arabic sentences using RRG, and use this to produce high quality translations into English. We believe the results shown in Chap- ter 7 show that our system has proved this, and that our method is more robust for these cases, than other MT systems. There are still a number of areas which need to be developed for UniArab to achieve more coverage, and we believe that we can build on the work we have done so far. Since the logical structure is separate from the vocabulary, when we focus on giving 129
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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
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3.2. FORMAL REPRESENTATION OF LAYER
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3.3. NOUN PHRASE STRUCTURE appropri
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3.4. LEXICAL REPRESENTATIONS FOR VE
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3.5. WHY WE USE RRG AS THE LINGUIST
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3.5. WHY WE USE RRG AS THE LINGUIST
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3.6. SUMMARY there will be more com
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4.1. ADVANTAGES OF MACHINE TRANSLAT
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4.2.3 Lexical databases 4.2. COMPUT
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4.3.2 Direct translation 4.3. BASIC
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4.3. BASIC MACHINE TRANSLATION STRA
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would also be needed for an interli
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4.4.1 Non-Roman alphabet scripts 4.
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Figure 4.5: NP rule (NP -> det n pp
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4.5. CHALLENGES OF ARABIC TO ENGLIS
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Figure 4.7: Direct MT system 4.6.2
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4.7 Summary Figure 4.9: Structure t
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5 Design of Arabic to English machi
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5.2. DESIGNING AN XML LEXICON ARCHI
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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 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
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
Page 141 and 142: Table 7.19: Test : Ditransitive wit
Page 143 and 144: 7.2. SENTENCE TESTS In a case where
Page 145 and 146: 7.3 System evaluation 7.3. SYSTEM E
Page 147: 7.3. SYSTEM EVALUATION search engin
Page 151 and 152: 8.1. THESIS SUMMARY and so we hope
Page 153 and 154: and proving the suitability of the
Page 155 and 156: References Abn-Aqeal, 2007. sharah
Page 157 and 158: REFERENCES Salem, Y., Hensman, A.,
Page 159 and 160: Appendix 139
Page 161 and 162: • Yasser Salem and Brian Nolan. 2
Page 163 and 164: Arabic Letter and Phonetic Value Le
Page 165 and 166: C List of translatable sentences I
Page 167 and 168: she is an engineer. Zaid loves Fati
Page 169 and 170: Jack is eating with the spoon.
Page 171 and 172: Ayah tore the page. ֓āyh
Page 173 and 174: Eman saw Sarah. r֓at ֓iymā
Page 175 and 176: Carl is brushing his hair. ym
Page 177 and 178: I want a book. ֓aryd ktāb
Page 179 and 180: Omar gave the book to Khalid.
Page 181 and 182: D Verbs in lexicon Verbs in Arabic
Page 183 and 184: Arabic Example Logical Structure
Page 185 and 186: Arabic Example Logical Structure
Page 187 and 188: Arabic ys. rs. r Example the wheel
Page 189 and 190: Arabic ֓adrs Example I am teach
Page 191 and 192: Package: Name of Class Class Summar
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