Prominence and Differential Grammatical Marking in the Encoding of Syntactic Categories --- A Study with Special Reference to Chinese

Although case-marking and word order are the two basic means of encoding syntactic relations cross-linguistically, these two devices seem to have a limited role to play in the identification of the subject or the object of a sentence in Chinese. It is evident that Chinese does not employ morphological case-marking strategies to encode its grammatical relations, and it is also well-known that these relations cannot be simply defined on the basis of word order, though at the same time it is equally true that Chinese mainly depends on word order to express these relations. Given such a troublesome and often conflicting situation, it is understandable why identifying the subject and the object of a sentence has become a headache for Chinese grammarians for several decades. This project aims to probe into the mystery of grammatical relations in Chinese from the perspective of linguistic prominence and differential grammatical marking (DGM). It is argued that, although Chinese does not have any overt morphological case-marking, it does make use of DGM devices, which can be defined on the dimension of prominence along with sets of hierarchically ordered semantic features such as animacy, definiteness and person as well as a set of syntactic particles (such as ba and bei) marking specific grammatical functions. These grammatical functions including topic, subject, and object are best characterized as elements determined by the interaction of DGM and word order. By investigating the role that prominence plays in the marking of grammatical relations and the ordering of arguments, this project will try to find out the mechanism that regulates the distribution of topic and subject on the left part of the predicate, and the constraints placed on post-verbal elements. This project will contribute to the understanding of the tacit knowledge that governs the complex computation of human language as well as the underlying principle that Chinese uses in conveying information. The outcomes will have a significant contribution to the learning and teaching of Chinese as a second language, and it will also be applicable to information retrieval as well as other intelligent computation of human language.