• Language and Information
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• v.11 no.1
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• pp.77-96
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• 2007

This paper investigates syntactic variations in English such as Dative Alternation, Particle Inversion, and Object Postposition (Heavy NP Shift) within the framework of Optimality Theory, and shows that the same set of morphological, informational, and processing constraints affect all these variations. In particular, it shows that the variants that used to be regarded as ungrammatical are in fact used fairly often in reality, especially when processing or informational conditions are met, and therefore, grammatical judgment may not be always categorical but sometimes gradient. It is argued that the notion of distance in constraint ranking in stochastic OT can effectively explain the gradience and variability of grammaticality in the variation phenomena.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.67-75
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• 2007

This paper presents the architectural aspects of the phrase analyzer that attempts to recognize phrases and identify the functional roles in the sentences in formal Japanese documents. Since the object of interest is a phrase, the current system, designed in an object-oriented architecture, contains the Phrase class, and makes use of the linguistic generalization about languages with Case markers that a phrase, whether a noun phrase, a verb phrase, a postposition (or preposition) phrase or a clause phrase, can be separated into the content and the function components. Without a dictionary, and drawing on the orthographic information on the words to parse, it also contains a class that identifies the types of characters, a class representing grammar, and a class playing the role of a controller. The system has a simple and intuitive structure, externally and internally, and therefore is easy to modify and extend.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.63-69
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• 2015

There are various researches which proposed an automatic instance generation from freetext on the web. Existing researches that focused on English, adopts pattern representation which is generated by simple rules and regular expression. These simple patterns achieves high performance, but it is not suitable in Korean due to differences of characteristics between Korean and English. Thus, this paper proposes a novel method for generating patterns and instances which focuses on Korean. A proposed method generates high quality patterns by taking advantages of dependency relations in a target sentences. In addition, a proposed method overcome restrictions from high degree of freedom of word order in Korean by utilizing postposition and it identifies a subject and an object more reliably. In experiment results, a proposed method shows higher precision than baseline and it is implies that proposed approache is suitable for self-knowledge learning system.