Acquisition of Periodic Events with Person Attributes

In this paper, we aim to acquire “periodic events” that represent significant actions that are happened by groups of people in particular seasons or timing. Recently, the importance of knowledge acquisition is increasing. Many studies about human action knowledge and temporal commonsense knowledge have been carrying out. We need a dataset to acquire periodic events. However, manually building the dataset with human attribute labels is costly. Therefore, we construct a human attribute classifier of Twitter users and create a large labeled tweets dataset automatically. Periodic events with specific human attributes are collected with our proposed method. Finally, we obtained commonsense event knowledge; e.g., “Students often go to college at 1 P.M.” and “Workers often work overtime on weekdays”.