摘要
本文根据汉语关系从句中指数量标记的隐现与语序,把汉语关系从句分成无标记形式MN、标记前置IMN和标记后置OMN三种类型。本文基于真实语料,从句法可及、语篇可及来探讨汉语关系从句指数量标记的分布,不仅关注单一因素的分析,而且综合各因素来揭示三种类型核心名词的可及性程度。研究发现:1)句法可及方面,MN、IMN均与主语关系从句相联系,OMN未表现出任何倾向,三种类型均倾向内置于主句宾语位置;2)语篇可及方面,MN、IMN的核心名词均表达新信息,MN核心名词距离被关系化的名词短语最近,IMN距离最远,三者在核心名词的长度和修饰语的数量方面存在一定的差异。语篇可及较之句法可及能更充分地说明指数量标记在汉语关系从句中的分布情况。
Based on the implicit/explicit characteristics and the word order of demonstrative quantitative classifier markers in Chinese relative clauses, this article distinguishes three types of Chinese relative clauses: modifier nominal (MN), inner modifier nominal ( IMN ), and outer modifier nominal ( OMN ). A corpora study is then conducted to explore the distribution of the demonstrative quantitative classifier markers from the perspective of syntax accessibility and discourse accessibility. Instead of focusing on only one single factor, this research integrates multi-factors to reveal the accessibility of the head NP in these three types. The results are as follows: 1 ) From the syntactic perspective, both MN and IMN are related to the subject relative clauses, whereas OMN does not show any preference. All the three types tend to take the object positions in the main clauses. 2) From the discourse perspective, the head nouns in MN and IMN express new information. The head nouns in MN are in the position nearest to the NP relativized, while the head nouns in IMN are in the farthest position. Some differences are found regarding the length of head nouns and the number of modifiers among the three types. Discourse accessibility are more interpretative than syntax accessibility in accounting for the distribution of the demonstrative quantitative classifier markers.
作者
张秋杭
ZHANG Qiuhang(School of Education,Shanghai International Studies University,Shanghai 201620,China)
出处
《外国语》
CSSCI
北大核心
2019年第5期62-71,共10页
Journal of Foreign Languages
基金
教育部人文社会科学研究青年基金项目“基于可及性理论的汉语关系从句研究”(17YJC740120)
关键词
可及性
句法可及
语篇可及
汉语关系从句
指数量标记
accessibility
syntax accessibility
discourse accessibility
Chinese relative clauses
demonstrative quantitative classifier markers