1998 Fiscal Year Final Research Report Summary
Study for Cognitive Model and Context Understanding System for Situation Dependency of Natural Language
| Project/Area Number |
08458082
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Keio University |
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Principal Investigator |
ISHIZAKI Shun Keio Univ.Environmental Information Prof., 環境情報学部, 教授 (00245614)
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| Co-Investigator(Kenkyū-buntansha) |
IMAI Mutumi Keio Univ.Environmental Information Lecturer, 環境情報学部, 専任講師 (60255601)
TANAKA Shigenori Keio Univ.Environmental Information Prof., 環境情報学部, 教授 (50171757)
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| Project Period (FY) |
1996 – 1998
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| Keywords | natural language / context understanding / cognitive model / situation dependency / association experiment / polysemy phenomenon / spatial direction terms |
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| Research Abstract |
The objective of this study is to construct a cognitive model and a natural language understanding system which can treat with polysemy and ambiguity included in linguistic phenomena. It can be obtained by integrating the three approaches, cognitive semantics, cognitive psychology and natural language processing to disambiguate the language situation dependency.
In the cognitive semantics approach, a description method for the principle of generating polysemy in verbs, nouns and adjectives. Functional roles of each category are made clear for the polysemy phenomena. Secondly, setting two levels of understanding objects and contents, the polysemy problems at applying sense-makinq to utterances are solved at a sentence level.
In the cognitive psychology, word meaning ambiguity is classified into two, linguistic one and concept cognitive one. The latter is identified by using experiments showing when such ambiguity happens. Next, a cognitive process model is constructed to disambiguate the cognitive ambiguity in the human language understanding process.
In the natural language processing, an on-line association experiment system is constructed and by rising it, several useful features are extracted from the experiment applied to a fundamental set of nouns. Almost one thousand concepts are systematized and represented on a measured space using the features. Thing concepts(nouns), act ion concepts(verbs) and situation concepts which show their environment are extracted and represented on the measured space. Such concepts on the space are shown useful for word meaning disambiguation and for constructing natural language understanding system.
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