Title :
Analysis of identifying linguistic phenomena for recognizing inference in text
Author :
Min-Yuh Day ; Ya-Jung Wang
Author_Institution :
Dept. of Inf. Manage., Tamkang Univ., Taipei, Taiwan
Abstract :
Recognizing Textual Entailment (RTE) is a task in which 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 focus on RITE-VAL System Validation subtask and propose a model by using an analysis of identifying linguistic phenomena for Recognizing Inference in Text (RITE) using the development dataset of NTCIR-11 RITE-VAL subtask. The experimental results suggest that well identified linguistic phenomenon category could enhance the accuracy of textual entailment system.
Keywords :
inference mechanisms; natural language processing; text analysis; NTCIR-11 RITE- VAL sub-task; comprehensive analysis; identifying linguistic phenomena analysis; recognizing inference in text; recognizing textual entailment; Accuracy; Analytical models; Cognition; Pragmatics; Semantics; Syntactics; Text recognition; Knowledge-based; Linguistic Phenomena; Machine Learning; Recognizing Inference in Text; Textual Entailment;
Conference_Titel :
Information Reuse and Integration (IRI), 2014 IEEE 15th International Conference on
DOI :
10.1109/IRI.2014.7051945