Statistical methods require very large corpus with high quality. But building large and faultless annotated corpus is a very difficult job. This paper proposes an efficient m e t h o d to construct part-of-speech tagged corpus. A rulebased error correction m e t h o d is proposed to find and correct errors semi-automatically by user-defined rules. We also make use of user's correction log to reflect feedback. Experiments were carried out to show the efficiency of error correction process of this workbench. The result shows that about % of tagging errors can be corrected. .
