MCU at NTCIR: A Resources Limited Chinese Textual Entailment Recognition System

نویسندگان

  • Yu-Chieh Wu
  • Chung-Jung Lee
  • Yaw-Chu Chen
چکیده

Recognizing inference in text is the task of finding the textual entailment relation between the given hypothesis and text fragments. Developing a high-performance text paraphrasing system usually requires rich external knowledge such as syntactic parsing, thesaurus which is limited in Chinese since the Chinese word segmentation problem should be resolve first. In this paper, we go different line. We propose a pattern-based and support vector machine-based trainable text entailment tagging framework under the condition of part-of-speech tagging information is available. We derive two exclusive feature sets for learners. One is the operations between the text pairs, while the other adopted the traditional bag-of-words model. Finally, we train the classifier with the above features. The official results indicate the effectiveness of our method. In terms of accuracy, our method achieves 53.6% for Traditional Chinese MC task (second place) and 55.4% for Traditional Chinese BC task. After the correction, our method in BC task is 67.9% with the same setting.

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تاریخ انتشار 2011