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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/101067


    Title: Analysis of Identifying Linguistic Phenomena for Recognizing Inference in Text
    Authors: Day, Min-Yuh;Wang, Ya-Jung
    Contributors: 淡江大學資訊管理學系
    Keywords: Linguistic Phenomena;Recognizing Inference in Text;Textual Entailment;Knowledge-based;Machine Learning
    Date: 2014-08-15
    Issue Date: 2015-03-26 16:34:59 (UTC+8)
    Publisher: IEEE
    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.
    Relation: Proceedings of the IEEE International Conference on Information Reuse and Integration (IEEE IRI 2014), pp.607-612
    Appears in Collections:[資訊管理學系暨研究所] 會議論文

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