Research based on treebanks is active for many natural language applications. However, the work to build a large-scale treebank is laborious and tedious. This paper proposes two versions of probabilistic chunkers to help the development of a bracketed corpus. The basic version partitions part-of-speech sequences into chunk sequences which form a partially bracketed corpus. Applying the chunking actions recursively, the recursive version generates a fully bracketed corpus. Rather than using a treebank as a training corpus, a corpus which is tagged with part-of-speech information only is used. The experimental results show that the probabilistic chunker has more than 92% correct rate in producing a partially bracketed corpus, and also gives very encouraging results in generating a fully bracketed corpus. Besides, this simple but effective design can be extended to other applications.