Based on text chunking using HMM, transformation-based learning is made use of to improve the precision of chunk tags further. The training data and the test data are from Penn treebank 4.0, and 13 text chunks are used. Rules are learned automatically according to the rule templates. The precision is improved 4.48%. The detailed analysis that affects the text chunking is given. Different threshold, different scale of training data, different learning equation and different rule templates can affect the precision of the text chunking.