Traditional Chinese text chunking approach is to identify phrases using only one model and same features. It has been shown that the limitations of using only one model are that: the use of the same types of features is not suitable for all phrases, and data sparseness may also result. In this paper, the divide-conquer model is proposed and applied in the identification of Chinese phrases. This model divides the task of chunking into several sub-tasks according to sensitive features of each phrase and identifies different phrases in parallel. Then, a two-stage decreasing conflict strategy is used to synthesize each sub-task''s answer. Through testing on Chinese Penn Treebank, F score of Chinese chunking using Multi-agent strategy achieves to 95.82%, which is higher than the best result that has been reported.
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