“像”的明喻计算

汉语隐喻计算是一项难度很大的工作,明喻由于带有明显的标志(比喻词)成为计算机自动识别的基础类型。该文着力于典型的比喻词“像”的比喻义及相关比喻成分的自动识别。首先,人工标注了1 586句语料,分析了明喻句的基本特点。然后,使用最大熵模型对“像”的比喻义和非比喻义进行分类,开放测试F值达到了89%。最后,用条件随机场模型识别出比喻的本体、喻体和相似点,F值分别达到了73%、86%和83%。

Computation of Chinese Simile with "Xiang"

The computation of metaphors in Chinese is certainly a challenging issue. Simile, with an obvious mark word, is a good start for automatic processing of metaphor. This paper is focused on automatic identification of Chinese simile phrases with the word “xiang”. Altogether 1 586 sentences containing “xiang” are first retrieved from the corpus and manually tagged and analyzed. Then the Maximum Entropy Model is applied to detect the simile meaning of “xiang”resulting in a F-score of 89% in open test. Finally, Conditional Random Fields (CRFs) Model is used to identify tenor, vehicle and similarity in the simile, achieving an acceptable F-score of 73%, 86% and 83%.