针对介词短语右边界存在多种错误识别的问题，提出了一种基于最大熵的汉语介词短语自动识别方法。该方法结合了汉语介词短语左右边界词语的依存语法知识，先由最大熵模型对介词短语进行识别，然后利用依存树库中介词短语的左右边界词语的依存语法知识，对介词短语右边界的错误识别进行校正，提高了介词短语的识别率。%We propose a maximum entropy-based method for automatic identification of prepositional phrase, which focuses on multiple error identification problems on the right boundary of prepositional phrase. It combines the dependency grammar knowledge of prepositional phrase boundary. In the process of recognition, firstly, we apply maximum entropy to identify prepositional phrase, then fine-tune the results with dependency grammar knowledge generated by dependency treebank. It improves the recognition rate of prepositional phrase.
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