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7.2. SENTENCE TESTS Table 7.21: Test : Limitation of UniArab 3 using non existing nonsense word Arabic h˘ āld ksr d. s. tqf˙g ¯ human-translated Khaled broke ( d. s. tqf˙g this word is not an Arabic word). ¯ Google Khalid break Dsthagafg Microsoft Khaled d. s. tqf˙g break ¯ UniArab Khaled broke d. s. t ¯ qf˙g In Table 7.21, we show how the system responds to an unknown word. We have put in a non-word in the Arabic sentence. The output of the Google and Microsoft’s translators are faulty in the verb. Microsoft’s translator put the unknown word in the wrong position. Google transliterates the word and puts it in the correct position. UniArab successfully translates the verb and puts the unknown word in the correct position. Figure 7.23 shows this sentence output in the UniArab system. Figure 7.23: Limitation of UniArab 3 124
7.3 System evaluation 7.3. SYSTEM EVALUATION UniArab supports simple sentences with one or two arguments or compounds. We have a number of sentences that were created to aid the grammar in terms of coverage of basic Arabic sentence structures. Further research should be conducted to incorporate more stages into UniArab. UniArab is based on RRG, and the logical structure of a sentence is the key piece of information for producing a translation. The system is programmed to be capable of dealing with specific structures. Once a structure is enabled within the system, the only limit on translating sentences of that structure is the coverage of the vocabulary. Hence, if a specific sentence structure exists with in UniArab, any sentence of that structure can be translated. This is a strength of being RRG-based, since the structure and vocabulary are dealt with independently, and vocabulary is more straightforward to improve. The structure is also independent of issues of gender and tense, which are only considered once a structure has been assigned, to determine who does what. As we develop UniArab, adding further structures increases the coverage by a considerable amount. However, as the number of structures increases, word ambiguity will become a bigger issue. UniArab uses an XML-formatted data-source as its lexicon. The key strength is that this data source is open, and can be used under any operating system, and accessed using different tools and languages. The search engine we use to access the data source is able to deal with Arabic words which translate into multiple-word English phrases. For example, ֓aryd in Arabic translates to I want. However, in its current state, we cannot find single entries that consist of multiple Arabic words. For example ˇsbāk ālh. ˇgz in Arabic translates to counter in English; the system cannot deal with this 125
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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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5.2. DESIGNING AN XML LEXICON ARCHI
Page 93 and 94: 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 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: 7.2. SENTENCE TESTS In a case where
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
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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