Raisins, Sultanas, and Currants: Lexical Classification and Abstraction via Context Priming
نویسنده
چکیده
A b s t r a c t In this paper we discuss the results of experiments which use a context, essentially an ordered set of lexical items, as the seed from which to build a network representing statistically important relationships among lexical items in some corpus. A metric is then applied to the nodes in the network in order to discover those pairs of items related by high indices of similarity. The goal of this research is to instant iate a class of items corresponding to each i tem in the priming context. We believe that this instantiat ion process is ul t imately a special case of abstract ion over the entire network; in this abstraction, similar nodes are collapsed into metanodes which may then function as if they were single lexical items.
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