As the number of learners of English is constantly growing, automatic error correction of ESL learners’ writing is an increasingly active area of research. However, most research has mainly focused on errors concerning articles and prepositions even though tense/aspect errors are also important. One of the main reasons why tense/aspect error correction is difficult is that the choice of tense/aspect is highly dependent on global context. Previous research on grammatical error correction typically uses pointwise prediction that performs classification on each word independently, and thus fails to capture the information of neighboring labels. In order to take global information into account, we regard the task as sequence labeling: each verb phrase in a document is labeled with tense/aspect depending on surrounding labels. Our experiments show that the global context makes a moderate contribution to tense/aspect error correction.