five

Data, Materials, and Appendix

收藏
Figshare2024-05-25 更新2026-04-08 收录
下载链接:
https://figshare.com/articles/dataset/Data_Materials_and_Appendix/25902124
下载链接
链接失效反馈
官方服务:
资源简介:
Sentence comprehension involves both semantic and syntactic processing. Previous evidence has demonstrated the relatively weaker role of syntax compared with semantics in sentence comprehension. This study further identifies syntax’s weaker role: its underutilization, which diminishes the cognitive synergy during comprehension. In this current study, an empirical experiment comprising six paired questions with statistical analysis is conducted. The experiment demonstrates that subjects show inferior comprehension performance on semantically ambiguous but syntactically unambiguous sentences compared to their paired semantically and syntactically unambiguous sentences. The results reveal that Chinese speakers underutilize syntactic processing when comprehending English sentences. This study then elucidates three categories of parsing methods: syntactic-clue-based parsing, semantical trial-and-error-based parsing, and syntactic trial-and-error-based parsing. Additionally, it identifies two categories of parsing underutilization for sentence interpretation: partial underutilization and complete underutilization of syntactic processing in sentence comprehension. Further exploration of the reasons behind partial and complete underutilization led to the identification of trial and error as a contributing factor. Consequently, this study provides empirical evidence for the weaker role of syntactic processing compared to semantic processing in sentence comprehension. Moreover, it lays a strong foundation for the development of an innovative parsing method designed to fully integrate syntactic processing into sentence comprehension, thereby enhancing cognitive synergy and the level of English sentence comprehension for Chinese speakers.
提供机构:
Xu, Jiapeng
创建时间:
2024-05-25
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作