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This paper presents an exploratory data analysis in lexical acquisition for adjective classes using clustering techniques. From a theoretical point of view, this approach provides large-scale empirical evidence for a sound classification. From a computational point of view, it helps develop a reliable automatic subclassification method.Results show that the features used in theoretical work can be successfully modelled in terms of shallow cues. The resulting clusters parallel to a large extent with proposals in the literature, which indicates that automatic acquisition of adjective classes for large-scale lexicons is possible.

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