Recognizing Textual Entailment (RTE) is composed by two text fragments are processed by system to determine whether the meaning of hypothesis is entailed from another text or not. Although a considerable number of studies have been made on recognizing textual entailment, little is known about the power of linguistic phenomenon for recognizing inference in text. The objective of this paper is to provide a comprehensive analysis of identifying linguistic phenomena for recognizing inference in text (RITE). In this paper, we use datasets from NTCIR-11 RITE-VAL System Validation subtask. We propose a model in System Validation subtask by using development dataset and Standard datasets on an analysis of identifying linguistic phenomena for Recognizing Inference in Text (RITE). The experimental results suggest that well identified linguistic phenomenon category could enhance the accuracy of textual entailment system.