文本蘊涵辨識，是由兩個文本片段透過系統的處理來決定這個假設片段與另一個文本片段所代表的意義是否有蘊涵關係。雖然過去有相當多的文本蘊涵辨識相關研究，但是並未對語言現象分析用於文本推論的辨識作深入探討。本研究目的為針對語言現象用於文本推論辨識的完整分析。本研究主要透過使用NTCIR-11 RITE-VAL系統驗證子任務所提供的開發資料集與標準資料集，提出辨識語言現象分析用於文本推論辨識的模型與分析。實驗結果顯示，良好的語言現象類別有助於提升文本蘊涵系統的正確率。 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.
