功能字之翻譯策略:以英文介詞為例｜國立臺灣科技大學博碩士論文系統

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研究生：	王貞尹 Zhen-yin Wang
論文名稱：	功能字之翻譯策略:以英文介詞為例 Function Word Translation: A Case Study on English Prepositions
指導教授：	陳献忠 Shian-jung Chen
口試委員:	姜葳 William Jiang 鄧慧君 Huei-Chun Teng
學位類別：	碩士 Master
系所名稱：	人文社會學院 - 應用外語系 Department of Applied Foreign Languages
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	182
中文關鍵詞：	功能字翻譯、英文介系詞、比較分析、機器翻譯、介系詞依附問題
外文關鍵詞：	function word translation, L2 learning; English prepositions, machine translation, English parsing, PP attachment
相關次數：	點閱：512 下載：11
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上一筆

對於學生而言，英翻中的過程中，最難處理的部分包含介系詞。隨然國內外已有不少相關研究，但這些研究只有分類翻譯現象以及提供翻譯建議，並未對翻譯本身做深入探討。本研究從功能字角度探討英文介系詞翻譯，希望能夠找出翻譯過程中所忽略的語言現象。本研究以光華雜誌與各種文體的語料作為研究對象，目的在於探討機器和人工翻譯時，功能字處理上有沒有對等的現象。分析光華語料的結果顯示，要能處理好介系詞的翻譯，譯者必須具備有靈活的翻譯技巧與語言知識，該雜誌的翻譯品質因此遠高於一般的翻譯。本研究另外以自然語言剖析器分析英文，對照機器翻譯的介系詞處理方式，結果發現根據介系詞的關係語意功能處理介系詞依附問題(PP attachment)的英文剖析器，比起谷歌機譯的正確率高出許多。綜合光華雜誌翻譯專家的處理趨勢以英文剖析器的語言處理方法，本文提出英文介系詞的翻譯策略，對於日後翻譯教學的理論，以及機器翻譯的程式設計上，能提供參考之用。

Students doing English-to-Chinese translation often find it very difficult to translate prepositions correctly. Most studies in Taiwan on the same topic either mainly focus on collecting and classifying the problematic renditions or on giving specific suggestions about how to avoid mistakes. This study aims to trace down what have been missing in most studies and to offer a better strategy about how to deal with English prepositions in translation as well as foreign language learning.
Prepositions are function words, which are language specific. They serve as relational markers that link between objects and the referents that PPs modify. The use of any preposition in one language is very unlikely to find a corresponding counterpart in another language. The common practice trying to translate an English preposition into a preposition in Chinese or any other language is simply a product of habitual thinking or intuition, which is obviously inadequate.
Analysis of professional translators’ work from a Taiwan Panorama corpus and that of an MT corpus shows an amazing contrast between a good strategy for translating prepositions and a preposition-to-preposition machine endeavor. Poor MT results also have a domino effect on misinterpretation and phrase reordering. Our literature review shows that the study of preposition translation or the translation of function words is not properly addressed. This study is expected to shed new light to a better understanding of language processing in translation and how to narrow the gaps created by language specifics in L2 learning. An important stance on translation studies, i.e., function words are language specific and a totally different strategy is needed to deal with them in translation, is recommended and this study will provide ample evidence for this position. To prove how this would help, the same MT corpus is fed to an English parser designed to make use of full context in deciding whether a
PP is an NP-modifier or a VP modifier based on the relation between the object NP and the NP or VP it modifies. The parser's much better performance in PP attachment against Google Translate shows the importance of treating prepositions as function words and different strategies are needed in translating function words.

Table of Contents
Chapter One Introduction	1
1.1 Background and Motivation	1
1.2 Purpose of the Study	2
1.3 Research Questions	3
1.4 Significance of the Study	6
1.5 Terminologies	7
1.6 Structure of the Study	8

Chapter Two Literature Review	9
2.1 Case Grammar	9
2.2 Content words and function words	11
2.3 Prepositional phrases	12
2.3.1 Functions performed by English prepositions	13
2.3.2 Structure of prepositional phrases	18
2.3.3 Prepositional phrases and Machine Translation	22
2.4 Scholars at Macquarie University	33
2.5 Research done by scholars in Taiwan	35
2.6 Knowledge of prepositions useful to language learners and translators	36
2.7 Translation Strategies of English Prepositions	39
2.8 Language and thought	41
2.9 Insights on pedagogy	42
2.10 Summary	44

Chapter Three Methodology	45
3.1 Sample Texts	45
3.1.1 Taiwan Panorama	45
3.1.2 Wen Shin’s New English-Chinese Dictionary	50
3.1.3 Miscellaneous texts	50
3.1.4 Corpus of human translations	51
3.2. Data Collection	52
3.2.1 Bilingual data from Wen Shin’s Dictionary	52
3.2.2 Using Google Translate as the MT test bed	54

3.2.3 Corpus from Taiwan Panorama	54
3.3 Data Analysis	56
3.3.1 Linguistic analysis of the corpora for different uses of prepositions and the like in English and Chinese	56
3.3.2 Comparing translation strategies proposed by researchers	56
3.4 The Parser used in this study	59
3.4.1 Context clues used by the Parser to do PP attachment	61
3.4.2 The Parser's decision tree and related lexical features	61
3.4.3 How to evaluate the parser's performance in PP attachment	63
3.5 Evaluation of the parser's PP attachment and Google MT's PP      translation	65
3.5.1 Evaluating the parser's PP attachment	65
3.5.2  Evaluating Google MT's PP attachment	67

Chapter Four Results and Discussion	71
4.1 Language specificity of prepositions, postpositions and the like	71
4.2 The English parser's performance in PP attachment	73
4.3 Google MT's performance in PP attachment	78
4.3.1 Overview of Prepositional Errors in Machine Translation	82
4.3.2 Prepositions in Machine Translation	84
4.3.2.1 Preposition 1: about	84
4.3.2.2 Preposition 2: against	85
4.3.2.3 Preposition 3: across	87
4.3.2.4 Preposition 4: as	88
4.3.2.5 Preposition 5: at	89
4.3.2.6 Preposition 6: between	91
4.3.2.7 Preposition 7: by	92
4.3.2.8 Preposition 8: during	92
4.3.2.9 Preposition 9: for	93
4.3.2.10 Preposition 10: from	94
4.3.2.11 Preposition 11: in	96
4.3.2.12 Preposition 12: into	97
4.3.2.13 Preposition 13: of	98
4.3.2.14 Preposition 14: on	99
4.3.2.15 Preposition 15: over	101
4.3.2.16 Preposition 16: through	102
4.3.2.17 Preposition 17: to	103

4.3.2.18 Preposition 18: with	104
4.3.2.19 Preposition 19: within	105
4.4 Translation strategies learned from Taiwan Panorama translations	106
4.4.1 Overview of prepositions in Taiwan Panorama	108
4.4.2 Prepositions in Taiwan Panorama	109
4.4.2.1 Preposition 1: by	109
4.4.2.2 Preposition 2: for	110
4.4.2.3 Preposition 3: from	112
4.4.2.4 Preposition 4: in	113
4.4.2.5 Preposition 5: on	114
4.4.2.6 Preposition 6: at	115
4.4.2.7 Preposition 7: of	116
4.4.2.8 Preposition 8: to	117
4.4.2.9 Preposition 9: with	118
4.4.2.10 Preposition 10: over	119
4.5 What happens if the relational meaning is missed?	120

Chapter Five Conclusion	122
5.1 Reflections on the Study	122
5.2 Limitations of the Study	125
5.3 Suggestions for Future Research	126
5.4 Concluding Remarks	126

References	127
Appendix A: Archives of Taiwan Panorama	142
Appendix B: Parsing and Google Annotation for NBA news	153
Appendix C: Parsing and Google Annotation for Cloud Computing	165
List of Tables

Table 2.1  Yang’s (2006) definition and examples of content words	11
Table 2.2  Yang’s (2006) definition and examples of function words	11
Table 2.3  Yang’s (2006) difference between content words and function words	12
Table 2.4  Coordinating conjunctions, subordinating conjunctions, and transitions	14
Table 2.5  Function Words in Chinese and English	19
Table 2.6  Yoshihisa’s (2007) static usage of “at”	27
Table 2.7  Using illustration in the case of learning preposition by Kiyoko (2005), Ozaki (2012), and Satoh (2002)	28
Table 2.8  Get in and get on by Bunton (1989)	29
Table 2.9  In and inside by Platt (1991)	30
Table 2.10  Unnecessary usage of up by Berry (1971)	30
Table 2.11  Common mistakes of the preposition for by Turton & Heaton (2000)	31
Table 2.12  Chinese-English translation of function words by Huang (2008)	37
Table 2.13  Ho’s (2009 ) five translation strategies for English prepositions in Technology Translation	38
Table 2.14  Zhang’s (2008) transforming English prepositions into other parts of speech	40
Table 2.15  Lindstrmberg’s (1991) demonstration of prepositions in and inside, on, and at	43
Table 2.16  German prepositions taught with pictures and examples by Zhang (2011)	43
Table 3.1   Fifteen categories of the archive on the official website of Taiwan Panorama	46
Table 3.2  Miscellaneous texts as input documents for the parsing	51

Table 3.3  Categorization of Collected Archives in Taiwan Panorama	55
Table 3.4  The parser's NP representation table	64
Table 3.5  Manual annotation done on the parser's PP attachment	66
Table 3.6  Manual annotation done on Google MT's PP attachment	69
Table 3.7  Parser for Calculation for Taiwan Panorama	107
Table 4.1  Comparison between English and Chinese	72
Table 4.2  NP-modifier as Branching in NP presentation	74
Table 4.3  The parser's PP attachment annotation	77
Table 4.4  The parser's PP attachment performance	78
Table 4.5  Google MT translation and evaluation	79
Table 4.6  Interface of Google translation tool	83
Table 4.7  Distribution of prepositions in Taiwan Panorama	108


List of Figures

Figure 2.1. McCrae’s (2007) proposed context integration mechanism	24
Figure 2.2 Geometric concept of in, at, and on by Kranjec et al (2010)	26
Figure 3.1. Illustration of Txt Format in Taiwan Panorama	54
Figure 3.2. Two kinds of PP attachment	60
Figure 3.3 Google Translate prompting for input	67
Figure 3.4. Google MT results	68
Figure 3.5. The process of data analysis	107
Figure 4.1. Frequency distribution of translation strategies in Taiwan Panorama	109
Figure 4.2. Strategy use in the case of by	110
Figure 4.3. Strategy use in the case of for	111
Figure 4.4. Strategy use in the case of from	112
Figure 4.5. Strategy use in the case of in	113
Figure 4.6. Strategy use in the case of on	114
Figure 4.7. Strategy use in the case of at	115
Figure 4.8. Strategy use in the case of of	116
Figure 4.9. Strategy use in the case of to	117
Figure 4.10. Strategy use in the case of with	118
Figure 4.11. Strategy use in the case of over	119

                                

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