A corpus-based study on semantic and cognitive features of <i>bei</i> sentences in Mandarin Chinese

Abstract Bei sentences in Mandarin Chinese with SOV word order have attracted extensive interest. However, their semantic features lacked quantitative evidence and their cognitive features received insufficient attention. Therefore, the current study aims to quantitatively investigate the semantic and cognitive features through the analysis of nine annotated factors in a corpus. The results regarding bei sentences show that (i) subjects exhibit a tendency to be definite and animate; non-adversative verbs have gained popularity over time, and intransitive verbs are capable of taking objects; (ii) subject relations tend to be long, implying heavy cognitive load, whereas the dependencies governed by subjects are often short, suggesting light cognitive load; and (iii) certain semantic factors significantly impact cognitive factors; for instance, animate subjects tend to govern shorter dependencies. Overall, our study provides empirical support for the semantic features of bei sentences and reveals their cognitive features using dependency distance.