• Language and Information
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• v.18 no.1
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• pp.33-52
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• 2014

This paper proposes a unified structural account of some instances of the English Modals and Semi-auxiliaries. The classification and the syntactic/structural description of the English Modal auxiliary verbs and verb-related elements have long been the center for many proposals in the history of generative syntax. According to van Gelderen (1993) and Lightfoot (2002), it was sometime around 1380 that the Tense-node (T) appeared in the phrasal structures of the English language, and the T-node is under which the English Modal auxiliaries occupy. Closely related is the existing evidence that English Modals were used as main verbs up to the early sixteenth century (Lightfoot 1991, Han 2000). This paper argues for a bi-clausal approach to English Modal auxiliaries with the infinitival particle 'to' such as 'ought to' 'used to' and 'dare (to)' 'need (to)', etc. and Semi-auxiliaries including 'be to' and 'have to'. More specifically, 'ought' in 'ought to' constructions, for instance, undergoes V-to-T movement within the matrix clause, just like 'HAVEAux' and all instances of 'BE', whereas 'to' occupies the T position of the embedded complement clause. By proposing the bi-clausal account, Radford's (2004, 2009) problems can be solved. Further, the historical motivation for the account takes a stance along with Norde (2009) and Brinton & Traugott (2005) in that Radford's (2004, 2009) syncretization of the two positions of the infinitival particle 'to' is no different from the 'boundary loss' in the process of Grammariticalization. This line of argument supports Krug's (2011), and in turn Bolinger's(1980) generalization on Auxiliaryhood, while providing a novel insight into Head movement of V-to-T in Present Day English.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.95-126
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• 2010

This study proposes a bottom-up and inductive manual mapping methodology for integrating two heterogenous fine-grained ontologies which were built by a top-down and deductive methodology, namely the Sejong semantic classes (SJSC) and the upper nodes in KorLexNoun 1.5 (KLN), for HLP applications. It also discusses various problematics in the mapping processes of two language resources caused by their heterogeneity and proposes the solutions. The mapping methodology of heterogeneous fine-grained ontologies uses terminal nodes of SJSC and Least Upper Bounds (LUB) of KLN as basic mapping units. Mapping procedures are as follows: first, the mapping candidate groups are decided by the lexfollocorrelation between the synsets of KLN and the noun senses of Sejong Noun Dfotionaeci(SJND) which are classified according to SJSC. Secondly, the meanings of the candidate groups are precisely disambiguated by linguistic information provided by the two ontologies, i.e. the hierarchicllostructures, the definitions, and the exae les. Thirdly, the level of LUB is determined by applying the appropriate predicates and definitions of SJSC to the upper-lower and sister nodes of the candidate LUB. Fourthly, the mapping possibility ic inthe terminal node of SJSC is judged by che aring hierarchicllorelations of the two ontologies. Finally, the ituorrect synsets of KLN and terminologiollocandidate groups are excluded in the mapping. This study positively uses various language information described in each ontology for establishing the mapping criteria, and it is indeed the advantage of the fine-grained manual mapping. The result using the proposed methodology shows that 6,487 LUBs are mapped with 474 terminal and non-terminal nodes of SJSC, excluding the multiple mapped nodes, and that 88,255 nodes of KLN are mapped including all lower-level nodes of the mapped LUBs. The total mapping coverage is 97.91% of KLN synsets. This result can be applied in many elaborate syntactic and semantic analyses for Korean language processing.

• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.466-475
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• 2003

To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

• Korean Journal of Cognitive Science
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• v.9 no.1
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• pp.47-60
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• 1998

The study was designed to investigate implicit and explicit memory effec representations of bilinguals. Hierarchical model of bilingual information processing word naming and translation tasks in the context of semantically categorized or rar Experiments 1 and 2, bilinguals first viewed stimulus words and performed naming or tr then implicit and explicit memory tasks. In experiment I, word recognition times(exp were significantly faster for semantic category condition than random category condi naming task and lexical decision taskOmplicit memory task)showed no difference in e experiment 2, naming task and exlicit memory task showed categorization effect but fOWE a and implcit memory task showed no categorization effect. These findings support the which posits that memory representations of bilinguals are composed of two independer a and one common conceptual store.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.685-692
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• 2001

This paper describes how to disambiguate the aspectual meaning of Japanese expression "-te iru" in Japanese-Korean machine translation Due to grammatical similarities of both languages, almost all Japanese- Korean MT systems have been developed under the direct MT strategy, in which the lexical disambiguation is essential to high-quality translation. Japanese has a progressive aspectual marker “-te iru" which is difficult to translate into Korean equivalents because in Korean there are two different progressive aspectual markers: "-ko issta" for "action progressive" and "-e issta" for "state progressive". Moreover, the aspectual system of both languages does not quite coincide with each other, so the Korean progressive aspect could not be determined by Japanese meaning of " te iru" alone. The progressive aspectural meaning may be parially determined by the meaning of predicates and also the semantic meaning of predicates may be partially reshicted by adverbials, so all Japanese predicates are classified into five classes : the 1nd verb is used only for "action progrssive",2nd verb generally for "action progressive" but occasionally for "state progressive", the 3rd verb only for "state progressive", the 4th verb generally for "state progressive", but occasIonally for "action progressive", and the 5th verb for the others. Some heuristic rules are defined for disambiguation of the 2nd and 4th verbs on the basis of adverbs and abverbial phrases. In an experimental evaluation using more than 15,000 sentances from "Asahi newspapers", the proposed method improved the translation quality by about 5%, which proves that it is effective in disambiguating "-te iru" for Japanese-Korean machine translation.translation quality by about 5%, which proves that it is effective in disambiguating "-te iru" for Japanese-Korean machine translation.anslation.