A Chinese verb semantic feature dataset (CVFD).

Journal: Behavior research methods
Published Date: Jan 9, 2023

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/ .

Authors

  • Yaling Deng
    Neuroscience and Intelligent Media Institute, Communication University of China, Beijing 100024, China.
  • Jiwen Li
    SINOPEC Shanghai Research Institute of Petrochemical Technology, National Key Laboratory of Green Chemical and Industrial Catalysis, Shanghai 201208, China.
  • Minglu Niu
    State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China.
  • Ye Wang
    College of Computer Science and Technology, Jilin University, Changchun 130012, China.
  • Wenlong Fu
    State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China.
  • Yanzhu Gong
    State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, 100024, China.
  • Shuo Ding
    Department of Biomedical Engineering, National University of Singapore, Singapore.
  • Wenyi Li
    Department of Orthopedics, Hebei General Hospital, No. 348 Hepingxi Road, Shijiazhuang, Hebei, China.
  • Wei He
    Department of Orthopaedics Surgery, First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
  • Lihong Cao
    State Key Laboratory of Media Convergence and Communication, Communication University of China, Beijing, China.

Keywords

External Resources

Popular Topics
Recent Journals