Inferring Conceptual Structure from Cross-Language Data

Abstract

Semantic categories vary across languages, but this variation is constrained: many logically possible semantic categories are not attested, and similar categories often appear in unrelated languages. This pattern suggests a universal conceptual basis to the variation, such that different languages provide different snapshots of the same conceptual terrain. A semantic map is a means of capturing this idea. Formally, a semantic map is a graph in which vertices represent different semantic uses or functions, and edges connect closely related uses. It is assumed that the graph structure is universal, and that language-specific categories always pick out connected subgraphs of the universal graph. A semantic map thus compactly represents what patterns of variation one may and may not expect to find in a given semantic domain, in terms of presumptively universal conceptual structure. Semantic maps have been widely used recently (e.g. Haspelmath, 2003; Croft, 2003; Cysouw et al., 2010).


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