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ETD - Dept. of Chinese, Translation and Linguistics >
CTL - Doctor of Philosophy >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/2031/6508
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| Title: | An ontology-based approach to quantifying metaphor-making potential |
| Other Titles: | Ji yu ben ti zhi shi de yin yu sheng cheng qian neng liang hua yan jiu 基於本體知識的隱喻生成潛能量化研究 |
| Authors: | Chen, Zili ( 陳自力) |
| Department: | Department of Chinese, Translation and Linguistics |
| Degree: | Doctor of Philosophy |
| Issue Date: | 2011 |
| Publisher: | City University of Hong Kong |
| Subjects: | Metaphor. |
| Notes: | CityU Call Number: P301.5.M48 C53 2011 viii, 137 leaves : ill. 30 cm. Thesis (Ph.D.)--City University of Hong Kong, 2011. Includes bibliographical references (leaves 130-137) |
| Type: | thesis |
| Abstract: | The Conceptual Metaphor Theory argues that metaphor enacts cognition in a
manner of crossing domains (Lakoff and Johnson, 1980), which has prompted
various investigations into metaphor, particularly relating to its behavior and
function in different environments. The paper aims to extend the research scope on
metaphor by proposing an intrinsic perspective on metaphor - based on the notion
that words possess a Metaphor Making Potential. Specifically, I aim at aspects
associated with a word's meta metaphorical mechanism, a typical cognitive process
of metaphor which depends first and foremost on a word's ability to cross domains.
The upper level ontology, Suggested Upper Merged Ontology (SUMO), with
its well developed hierarchy of domain terms that represent world knowledge,
assists in revealing the inherent metaphorical property of a word. The lexical
ontology, WordNet, decomposes a word's lexical meanings into senses in terms of
synsets", which in turn can be mapped to the conceptual ontology SUMO. In this
study, WordNet serves as a parser of a word's semantic senses, and SUMO
identifies the domains, in which these senses belong.
Experiments with English verbs under the framework of WordNet and SUMO
ontology have been carried out. Eight sets of data were first drawn from the 400
million-word Corpus of Contemporary American English (COCA). The first set
consists of 1000 most frequent English verbs in the general corpus. Each of the
additional five sets consists of 1000 most frequent verbs respectively from such
registers as "Academic", "Fiction", "Magazine", "Newspaper", and "Spoken". Two
additional registers form the last two sets, i.e., "Science and Technology" under "Academic" and "Scientific Fiction and Fantasy" under "Fiction".
In seeking ways to operationalize the measurement of an English verb's MMP,
two novel domain-based algorithms have been designed along with another
conventional depth-based metric. Results from these three algorithms were
compared. A program called "MMPCalculator" was built to incorporate WordNet
3.0 and SUMO Merge 1.47. This program performs three algorithms in parallel to
generate MMP values of eight groups of verbs.
One hypothesis, which is based on Lakoff's view that metaphor is the result of
our constant interaction with our physical and cultural environments", was
established to determine whether higher frequency verbs show greater MMP values
and if so, to what extent they are correlated with each other. Another hypothesis is
based on the human intuitive judgment that texts of different genres bear different
amount of metaphorical usage of words due to different stylistic features, which
was supported by the statistical analysis of the data drawn from a survey. Given that
this judgment is true, the second hypothesis was established to determine whether
texts of different genres reveal different amount of MMP values. As a study which
is both theory- and application-oriented, this paper also tries to show that an
ontology-based approach to metaphor evaluation is de facto more objective and
operable than an intuitive-based approach in providing insights into a word's
metaphorical properties. |
| Online Catalog Link: | http://lib.cityu.edu.hk/record=b4086058 |
| Appears in Collections: | CTL - Doctor of Philosophy
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