Construction and Statistical Analysis of Discourse Cohesive Components in Modern Chinese

In discourse semantic analysis, the primary focus lies on cohesive elements that maintain discourse coherence. Additionally, attention is given to referring components and topic description structures that facilitate articulation. Various terms are used to refer to these cohesive elements, such as connecting components, logical connectives, relational words and cohesive components. However, there is a lack of unified terminology. The concept of cohesive components has been proposed before. In prior research, it primarily encompassed connectives, discourse markers and tone words, all of which contribute to discourse coherence. However, these definitions were relatively imprecise, and previous studies did not systematically categorize discourse cohesive components based on specific semantic functions. Consequently, they were inadequate for chapter-level semantic analysis. This paper extends the definition and scope of cohesive components based on existing research. It categorizes cohesive components according to both their formal characteristics and semantic functions. We extract cohesive components from the BLCU-CST tree bank, filter them based on specific scope and definition, and summarize a total of 247 logical connectives, 118 discourse connective markers and six types of numerical sequence connectives. In terms of semantic function, we analyze the distribution of 14 different logical-semantic relations that cohesive components indicate within discourse. This analysis not only enriches the understanding of discourse semantics for natural language comprehension but also offers valuable insights for linguistic ontology research.