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題名:A Corpus-Driven Approach to Source Domain Determination
作者:鍾曉芳 引用關係
作者(外文):Chung, Siaw-fong
出版日期:2007
出版項:臺北市:中央研究院語言學研究所
ISBN:978-986-02-0590-9
主題關鍵詞:源域概念隱喻由上而下的方式由下而上的方式知識本體搭配詞組Source domainsConceptual metaphorsTop-down approachBottom-up approachOntologyCollocation
學門:語言學
資料類型:專書
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  • 點閱點閱:148
一般來說,領域訊息在隱喻形成的時候會產生互換的情形,而在概念隱喻裡(Lakoff & Johnson 1980, Lakoff 1993),互換的兩個領域訊息分別為源域與目標域。源域通常比目標域較為具體,所以源域提供的訊息對於理解目標域的概念來說是十分關鍵的要素。因此,在過去曾經有相關的研究嘗試定義源域,可是這些研究通常會遇到以下兩個問題:第一,對源域定義的差異、第二,對源域界定的主觀程度不一致。
本研究為了克服這些困難,使用了兩個面向的方式將隱喻之源域做系統化的界定:一是由上而下、二則為由下而上。一般來說,由上而下的方式通常會假設一個上層的概念,而源域就是這些概念裡的一部分。唯有當源域已決定之後,才會把各種的隱喻例子歸類到不同的源域。而隱喻概念這個理論 (Lakoff & Johnson 1980, Lakoff 1993) 用的就是這一種方式,例如:在 LOVE IS JOURNEY的隱喻概念裡,當決定 JOURNEY 為源域之後,一些相關的例子才會接著分類到該源域內。相反地,由下而上的方式則會先累積人類的用語,而這些資訊會構成較上層的知識。此種方式通常會以頻率為基礎,如:Labov (1973)、Rosch & Mervis (1975) 所舉出的典型模範 (prototype) 指的就是共現度高的搭配詞組。在隱喻相關研究中,這兩種方式都曾有學者使用過,但是,在文獻中卻少有研究對這兩種方式做全面性的比較。本研究使用了 WordNet、SUMO (Suggested Upper Merged Ontology)(知識本體)與Chinese Sketch Engine(中文詞彙特性速描系統)等計算語言學的工具來界定源域,是第一個整合從由上而下及由下而上兩種方式來比較領域訊息的研究。並且,我們透過計算語言學工具來驗證領域界定的理論架構,得到的結果有助於我們進一步了解人類對事物的歸類。而更重要的是,本研究結合了計算語言學、語言學理論及心理語言學的知識來界定領域概念,因此其成果將具有跨領域的貢獻。
The present book provides a detailed investigation of metaphors in Mandarin Chinese based on the premise that different knowledge domains are mapped in the formulation of metaphors. In conceptual metaphors (Lakoff & Johnson 1980, Lakoff 1993), the two mapped domains include the target domain, which is usually more abstract, and the source domain, which is usually more concrete, providing key information to understand the concepts of the target domain. Due to the importance of source domains, studies attempting to define operationally how source domains are involved with conceptual metaphors have been undertaken in the past. However, these studies have encountered difficulties due to two main reasons: (a) the variation in the specificity of the source domains; and (b) the subjectivity of individuals when determining source domains.
This book overcomes these difficulties by employing both top-down and bottom-up approaches to determine the source domain of a conceptual metaphor. A top-down approach to source domain determination usually sorts metaphorical instances according to pre-determined source domains that come from a conceptual knowledge system (such as an ontology). Alternatively, a bottom-up approach accumulates knowledge about the source domain through language use (or collocation). Both approaches, top-down and bottom-up, have been used to identify source domains in metaphor studies; however, the precision of these two approaches has not previously been compared. The present book intends to fill the gap between these two approaches by comparing the approaches using computational tools, such as WordNet, SUMO (Suggested Upper Merged Ontology), and Sketch Engine.
The outcome of this study provides a comprehensive comparison of the top-down and bottom-up approaches regarding the determination of source domains. Based on the combined results of the two approaches, this study proposes a hierarchical model for source domain definition. This model facilitates automatic identification of metaphors and explains why certain domains overlap in conceptualization. By using computational tools with a linguistic framework of domain identification that contribute to computational linguistics, this study finds further support through psycholinguistic experiments, thus enhancing the ability to define source domains. This, in turn, makes a substantial contribution to understanding the human categorization of concepts through linguistic evidence.
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