Argumentness and Probabilistic Case Structures

This paper proposes that the argument structures be stated in a way that uses probabilities derived from a corpus to replace a Boolean-value system of subcategorization. To do this, we make a cognitive model from a situation to an utterance to explain the phenomena of arguments'ellipsis, though the traditional term ellipsis is not suitable under our new concepts. We claim that the binary distinction is neither rational nor suitable for a real syntactic analysis. To solve this problem, we propose two new concepts argumentness and probabilistic Case structures by adapting the prototype theory. We believe that these concepts are effective in the syntactic analysis of NLP.