以正規邏輯方法解決中文文本蘊含辨識問題

張富傑

doi:10.6342/NTU.2014.01460

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以正規邏輯方法解決中文文本蘊含辨識問題

A Formal Logic Approach to Chinese Recognizing Textual Entailment

張富傑 , Masters　　Advisor：黃鐘揚　　

英文 DOI： 10.6342/NTU.2014.01460

形式語意學；計算語意學；自然語言理解；一階邏輯；中文文本蘊含辨識； Formal Semantics ； Computational Semantics ； Natural Language Understanding ； First Order Logic ； Chinese Recognizing Textual Entailment

Abstract │ Reference (62) │ Altmetrics

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In the research of natural language processing (NLP), understanding the natural language is always a challenging problem. Traditionally, the research of NLP focuses on the semantics and logic of natural language. However, the present NLP research trend is focusing on the big data and machine learning techniques. These two methods have their own pros and cons; however, the traditional research of semantics and logic are seldom discussed in the recent works, and the existing machine learning techniques also have their limitations. Combining the traditional works on semantics with machine learning techniques is a good perspective to research.
We build a system to solve the Chinese recognizing textual entailment (RTE) problem by formal logic method. Based on the theory of formal semantics and computational semantics, first, we use the machine learning technique to convert Chinese sentences in natural language into syntax trees. Then, we propose an algorithm to convert the syntax trees into semantic representations. Also, we propose a method that solves the RTE problem by integrating external knowledge resources with the proposed semantic representations. With these semantic representations, we can use the theorem proving techniques to solve the problem of Chinese RTE. Then, we demonstrate that our approach can solve some simple cases of Chinese RTE. Also, we show the possibilities and difficulties to solve the real-world cases. Finally, we point out the strengths and weaknesses of our system, and the possibilities on future research to improve our system.

Reference ( 62 ) 〈TOP〉

[2] Ekaterina Ovchinnikova. Integration of World Knowledge for Natural Language Understanding. Atlantis Thinking Machines. Atlantis Press, 2012.
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[3] Donald Davidson. The individuation of events. In N. Resher, editor, Essays in Honor of Carl G. Hempel, page 216 – 234. Springer, 1969.
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[4] David R. Dowty. On the semantic content of the notion of ’thematic role’. In Raymond Turner Gennaro Chierchia, Barbara H. Partee, editor, Properties, Types and Meaning, pages 69–129. 1989.
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[5] Terence Parsons. Events in the Semantics of English: A Study in Subatomic Semantics. MIT Press, 1990.
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[6] Patrick Blackburn and Johan Bos. Representation and Inference for Natural Language. A First Course in Computational Semantics. CSLI, 2005.
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