A Chinese verb semantic feature dataset (CVFD).

Abstract

Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets have been developed in different languages such as English, Spanish, and German. However, there is still a lack of a dataset of Chinese verbs. In this study, we developed a semantic feature dataset of 1140 Chinese Mandarin verbs (CVFD) with 11 dimensions including verb familiarity, agentive subject, patient, action effector, perceptual modality, instrumentality, emotional valence, action imageability, action complexity, action intensity, and the usage scenario of action. We calculated the semantic features of each verb and the correlation between dimensions. We also compared the difference between action, mental, and other verbs and gave some examples about how to use CVFD to classify verbs according to different dimensions. Finally, we discussed the potential applications of CVFD in the fields of neuroscience, psycholinguistics, cultural differences, and artificial intelligence. All the data can be found at https://osf.io/pv29z/ .