Bidirectional Sequence Classification for Part of Speech Tagging
نویسنده
چکیده
With this paper is presented a system for Part of Speech Tagging, based on the Perceptron Algorithm. In the proposed framework, the order of the inference is not forced into a monotonic behavior (left-toright), but is learned together with the parameters of the local classifier. The system tested on the task of Italian POS Tagging at EVALITA 2009 obtained the second position, with a Tagging Accuracy of 95.82%. .
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تاریخ انتشار 2009