• Language and Information
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• v.18 no.2
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• pp.169-199
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• 2014

This study was performed to assume the Sematic role of the obligatory argument of the predicate in a Korean sentence, and to accomplish the task to attach the assumed thematic role to the real corpus. With this study, the maximum of the Sematic role was determined and the Criterion of the Sematic role was set. The maximum of the Sematic role was determined 22. This study arranged the Sematic role of case marker and attached the Sematic role to the predicate of the sentence within The standard Korean Dictionary. The program to attach the thematic role was developed(UTagger-SR). The Sematic role of case marker and Case frame dictionary was equipped in this program. By attaching the Sematic role, it was found that the most important the Sematic role in the korean sentence is the theme of the predicate and the next is the subject of the predicate.

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.1-21
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• 2002

In this paper, a persistent L1 influence on L2 argument structure acquisition is observed in terms of complement and adjunct PPs. Since the distinction between these two PPs in L1 seems not as sharp as in L2, overgeneralization is anticipated in the L2 acquisition due to L1 transfer. Result of an experimental study shows that Korean learners of English do not successfully acquire L2 verb meanings as to which locative PP is obligatory and which is not. Generally, learners transfer the L1 properties when asked to judge grammaticality. Some possible source of constraints in L2 acquisition, such as input frequency and noticing ability is proposed as possible explanations of data. Finally, pedagogical implications in language classroom for vocabulary acquisition are discussed.

• Journal of Korean Philosophical Society
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• v.146
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• pp.1-24
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• 2018

The purpose of this paper is to explore the meaning of theoretical ethics regarding bioethics. First, I explore the meanings and limitations of the bioethics domain for 'the principle of equal consideration of interests' and the 'preference utilitarianism' concepts Singer presents. Secondly, I emphasize the significance of Kant's ethics in the domain of bioethics. Lastly, I suggest that Aristotle's virtue ethics should be realized in the domain of bioethics. Furthermore, I would like to suggest the meaning of human life through this. Singer's argument brings up a new topic about the meaning of evolved life not considered in the history of traditional ethics. He presented undeniable opinions about human dignity that he took for granted. In addition, it is assessed that the scope extension for the life respect target has been reasonably achieved. Contrary to this, Kant's ethics explains the meaning of human dignity based on its metaphysical meaning. Furthermore, it provides an appropriate orientation for human life. Embracing their claims is not sufficient to explain the meaning of Good Life. The meaning of Good Life is likely to be resolved through the application of Aristotle's virtue ethics. The meaning of a being of substance is living and furthermore, it is inherent to being itself.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.131-150
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• 2015

Omission of noun phrases for obligatory cases is a common phenomenon in sentences of Korean and Japanese, which is not observed in English. When an argument of a predicate can be filled with a noun phrase co-referential with the title, the argument is more easily omitted in Encyclopedia texts. The omitted noun phrase is called a zero anaphor or zero pronoun. Encyclopedias like Wikipedia are major source for information extraction by intelligent application systems such as information retrieval and question answering systems. However, omission of noun phrases makes the quality of information extraction poor. This paper deals with the problem of developing a system that can restore omitted noun phrases in encyclopedia documents. The problem that our system deals with is almost similar to zero anaphora resolution which is one of the important problems in natural language processing. A noun phrase existing in the text that can be used for restoration is called an antecedent. An antecedent must be co-referential with the zero anaphor. While the candidates for the antecedent are only noun phrases in the same text in case of zero anaphora resolution, the title is also a candidate in our problem. In our system, the first stage is in charge of detecting the zero anaphor. In the second stage, antecedent search is carried out by considering the candidates. If antecedent search fails, an attempt made, in the third stage, to use the title as the antecedent. The main characteristic of our system is to make use of a structural SVM for finding the antecedent. The noun phrases in the text that appear before the position of zero anaphor comprise the search space. The main technique used in the methods proposed in previous research works is to perform binary classification for all the noun phrases in the search space. The noun phrase classified to be an antecedent with highest confidence is selected as the antecedent. However, we propose in this paper that antecedent search is viewed as the problem of assigning the antecedent indicator labels to a sequence of noun phrases. In other words, sequence labeling is employed in antecedent search in the text. We are the first to suggest this idea. To perform sequence labeling, we suggest to use a structural SVM which receives a sequence of noun phrases as input and returns the sequence of labels as output. An output label takes one of two values: one indicating that the corresponding noun phrase is the antecedent and the other indicating that it is not. The structural SVM we used is based on the modified Pegasos algorithm which exploits a subgradient descent methodology used for optimization problems. To train and test our system we selected a set of Wikipedia texts and constructed the annotated corpus in which gold-standard answers are provided such as zero anaphors and their possible antecedents. Training examples are prepared using the annotated corpus and used to train the SVMs and test the system. For zero anaphor detection, sentences are parsed by a syntactic analyzer and subject or object cases omitted are identified. Thus performance of our system is dependent on that of the syntactic analyzer, which is a limitation of our system. When an antecedent is not found in the text, our system tries to use the title to restore the zero anaphor. This is based on binary classification using the regular SVM. The experiment showed that our system's performance is F1 = 68.58%. This means that state-of-the-art system can be developed with our technique. It is expected that future work that enables the system to utilize semantic information can lead to a significant performance improvement.