Study for Cognitive Model and Context Understanding System for Situation Dependency of Natural Language

本研究的目的是建立一个认知模型和自然语言理解系统，以处理语言现象中包含的多义和歧义。将认知语义学、认知心理学和自然语言处理三种方法相结合，可以消除语言情境依赖的歧义。在认知语义学中，一种描述动词、名词和形容词多义词产生原理的方法。明确了多义现象中各范畴的功能作用。其次，通过设置对象和内容两个层次的理解，在句子层面上解决了语义建构在话语应用中的多义词问题。在认知心理学中，词义歧义分为语言学歧义和概念认知歧义。后者是通过实验来确定的，实验显示了这种歧义何时发生。其次，构建认知过程模型来消除人类语言理解过程中的认知歧义。在自然语言处理中，构建了一个在线关联实验系统，并通过对一组基本名词的关联实验提取出一些有用的特征。将近一千个概念被系统化，并利用这些特征在一个测量空间中表示出来。事物概念（名词）、行为概念（动词）和表现其所处环境的情景概念被提取并表示在被测空间上。这些空间上的概念对于语义消歧和构建自然语言理解系统非常有用。

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.