This paper aims to further probe into the problems of ambiguities for automatic identification of determinative-measure compounds (DMs) in Chinese and to develop sets of rules to identify DMs and their parts of speech. It is known that Chinese DMs are identifiable by regular expressions. DM rule matching helps one solve word segmentation ambiguities, and parts of speech help one improve sense recognition and part-of-speech tagging. In this paper, a deep analysis based on
corpus data was studied. With analyses of error identification and disambiguation of DM compounds, the authors classified three types of ambiguities, i.e. word segmentation, sense, and pos ambiguities. DM rules are necessary complements to dictionaries and helpful to resolve word segmentation ambiguities by applying resolution principles and segmentation models. Sense and pos ambiguities are also expected to be resolved by different approaches during postprocessing.