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4.4.2.2 Homograph 4.4. LINGUISTIC ASPECTS OF MT The second type of lexical ambiguity occurs when a word can have two or more different meanings. Linguists distinguish between homographs, homophones and polysemes. Homographs are two (or more) ‘words’ with quite different meanings which have the same spelling: example, light (not dark or not heavy). Many Arabic words can have two or more overlapping meanings examples; ֓i֒lān could be announcement, advertisement, declaration or sign. Also, mrkz could be centre, position, rank or status. Moreover, mwq֒ could be position, rank, site or status. The direct approach has particular problems with homographs; the usual method of resolving homograph ambi- guities is to look at the closest words for clues. 4.4.3 Syntactic ambiguity Syntactic ambiguity arises when there is more than one way of analysing the underlying structure of a sentence according to the grammar used in the system. Example, I know a man with a dog who has fleas, is ambiguous. It could be the man or the dog who has fleas. It is the syntax not the meaning of the words which is unclear. The classical example is He saw the girl with the telescope. For the purposes of this discussion, we represent these examples in the notation of a context-tree grammar rather than in RRG notation. The two trees in Figure 4.5 and Figure 4.6 represent the two different analyses in the sense of recording two different ‘parse histories’. In linguistic terms, they correspond to the two readings of the sentence: one in which the PP is part of the NP (i.e. the girl has the telescope), and the other where the PP is the same level as the subject (i.e. the man has the telescope). For convenience, a bracketed notation for trees is sometimes used: the equivalents for the trees in Figure 4.5 and Figure 4.6 are shown in (4.1a) and (4.1b) respectively. 58
Figure 4.5: NP rule (NP –> det n pp) Figure 4.6: PP is attached at a higher level 4.4. LINGUISTIC ASPECTS OF MT 59
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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
Page 27 and 28: 1.4. THESIS ORGANIZATION 2009b). Ch
Page 29 and 30: 2.1. CHARACTERISTICS OF THE ARABIC
Page 31 and 32: 2.2 Characteristics of Arabic words
Page 33 and 34: 2.2. CHARACTERISTICS OF ARABIC WORD
Page 35 and 36: 2.3. PART OF SPEECH INVENTORY OF TH
Page 37 and 38: 2.3.4 Verbs 2.3. PART OF SPEECH INV
Page 39 and 40: 2.3.4.2 Aspect 2.3. PART OF SPEECH
Page 41 and 42: 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: 4.4.1 Non-Roman alphabet scripts 4.
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 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
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Table 7.7: Test : Verb ‘to be’
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Table 7.9: Test : Verb ‘to have
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7.2. SENTENCE TESTS Table 7.11: Tes
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7.2.6 Pro-drop Arabic Table 7.13: T
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Table 7.15: Test : Intransitive 2 A
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7.2.7.3 Ditransitive Table 7.17: Te
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Table 7.19: Test : Ditransitive wit
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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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