A corpus-based analysis of Vietnamese 'classifiers' con and cái.

Abstract

The purpose of this study is to examine the use of two common Vietnamese 'classifiers,' con (animacy) and cái (inanimacy) using language corpora data of over one million words. This information may contribute to an ongoing debate of whether Vietnamese 'classifiers' are a distinct word class or a subclass of nouns. Frequency and distributions were calculated using computer software. Lexical-semantic functions were manually analyzed for each occurrence. Findings indicated that con and cái were highly frequent and distributed across text genres. However, neither form consistently demonstrated a classifying function: con indicated animacy less than 24% of the time, and cái indicated inanimacy less than 65% of the time. Corpus-based analysis is a useful tool to make comparisons between prototypical and 'real-life' language use. If Vietnamese 'classifiers' are not consistently used as such, considering this group of words a subclass of nouns rather than a distinct word class may be more parsimonious.