We test the efficacy of this method in the context of Chinese word segmentation and part-of-speech tagging, where no segmentation and POS tagging standards are widely accepted due to the lack of morphology in Chinese.

To test the efficacy of our method we choose Chinese word segmentation and part-of-speech tagging, where the problem of incompatible annotation standards is one of the most evident: so far no segmentation standard is widely accepted due to the lack of a clear definition of Chinese words, and the (almost complete) lack of morphology results in much bigger ambiguities and heavy debates in tagging philosophies for Chinese parts-of-speech.

Xue and Shen (2003) describe for the first time the character classification approach for Chinese word segmentation , Where each character is given a boundary tag denoting its relative position in a word.

It is an online training algorithm and has been successfully used in many NLP tasks, such as POS tagging (Collins, 2002), parsing (Collins and Roark, 2004), Chinese word segmentation (Zhang and Clark, 2007; J iang et al., 2008), and so on.

In this paper, we present a discriminative word-character hybrid model for joint Chinese word segmentation and POS tagging.

In this paper, we presented a discriminative word-character hybrid model for joint Chinese word segmentation and POS tagging.

Previous studies on joint Chinese word segmentation and POS tagging have used Penn Chinese Treebank (CTB) (Xia et al., 2000) in experiments.

For example, a perceptron algorithm is used for joint Chinese word segmentation and POS tagging (Zhang and Clark, 2008; Jiang et al., 2008a; Jiang et al., 2008b).