Mandarin and English Event Cognitive Alignment From Corpus-Based Semantic Fusion Model Perspective - Li, Xiangling (Frontiers in Psychology, 2022)
The study explores the fusion of semantic roles and the different semantic fusion types, aiming at establishing a semantic fusion model to explain the cognitive alignment of events in Chinese and English simple sentence constructions containing two verbs. In total, 20,280 simple sentence constructions containing two verbs are collected from Chinese literary works, Peking University Chinese Corpus, and English classic literary works. The semantic fusion in the collected simple sentence constructions containing two verbs is classified into five major semantic fusion categories, which appear with different occurrence frequencies in the two languages. The semantic fusion model of event alignment is comprehensively supported by linguistic research in Chinese and English. From a cognitive linguistic perspective, it is found that the double semantic profiles of the same syntactic element N (noun) make N psychologically activated twice and enable it to enter two processes profiled by the two verbs as a participant. The two processes are combined into one event, which designates a cognitive occurrence of any degree of complexity. N’s entry into the two subevents is realized by its double semantic profiles that enable it to fuse two semantic roles into one syntactic element and explain the relationship between N’s double syntactic identities and double semantic roles. The semantic fusion model was used to explore event alignment in simple sentence constructions containing two verbs, and it was discovered that the fusion of two semantic roles is universal in languages and is a common psychological and cognitive behavior deeply rooted in the mental conceptualization of language users. The empirical discussion of simple sentence constructions containing two verbs proves that semantic fusion as an important psychological passage in event alignment has solid psychological reality and verifies the applicability of the semantic fusion model in the explanation of event alignment.