Proceedings of the Korean Society for Language and Information Conference (한국언어정보학회:학술대회논문집)
Korean Society for Language and Information (KSLI)
- Annual
Domain
- Linguistics > Linguistics, General
1996.02a
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Our research goal has been the development of a domain independent natural language processing (NLP) system suitable for information retrieval. As part of that research, we have investigated ways to automatically extend the semantics of a lexicon derived from machine-readable lexical sources. This paper details the extraction of thematic roles derived from lexical patterns in a machine-readable dictionary.
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This paper treats the japanese adjective phrase forming derivational suffix -tai from a new point of view: firstly it tries to approach from a semantic standpoint by applying the proposal made in Ikeya (1991). It will be shown that adjective phrases formed by -tai fits nicely with the semantic structure proposed by Ikeya. Secondly, we attempt to 'derive' -tai sentences by adopting a basic framework of HPSG so that we can 'derive' them without having recourse to transformational operations, that is, in a monostratal way. In tackling the problem we have tried to incorporate many ideas proposed so far on this issue.
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A spontaneously spoken, natural Japanese discourse contains many instances of the so-called redundant interjections and of backchannel utterances. These expressions have not hitherto received much attention and few systematic analyses have been made. We show that these utterances are characterizable as discourse markers, and that they comprise a well-defined category, characterizable in a regular manner by their phonologico-prosodic properties. Our report is based on an experiment involving spontaneously spoken conversations, recorded in a laboratory environment and analyzed using digital devices. Prosodic patterns of discourse markers occurring in the recorded conversations have been analyzed. Several pitch patterns have been found that characterize the most frequently used Japanese discourse markers
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