Cognitive grammar provides an analytic framework in which the semantic value of linguistic expressions is characterized relative to domains of presupposed knowledge. Cognitive metaphor theory holds that metaphorical language involves a mapping of conceptual structure from a source domain to a target domain. Containers are one such pervasive structure. This investigation proposes a detailed representation for the domain CONTAINER and applies it in the analysis of metaphorical expressions mapping CONTAINER onto target domains ARGUMENT and linguistic expression. Each source domain word is analyzed with respect to which aspects of the CONTAINER domain structure it refers, and whether it refers to a 2D or 3D bounded region. The pattern of aspects mapped suggest that spatial containment, content, and material container object comprise major aspects of the 3D CONTAINER domain. The target domains are demonstrated to be structured according this container organization. The results demonstrate that cognitive semantic analysis can reveal specific structures of commonsense knowledge which are prerequisite for language use.

We studied the role of action in a conceptual combination task by varying whether word stimuli could be physically grasped and arranged (words displayed individually on tangible cubes) or only touched and pointed to (words printed on a poster paper). Middle-school aged participants combined nouns from different taxonomic categories then described creative meanings. Descriptions contained more between-category relations (e.g., “shaped like” and “looks like” analogies) in the poster condition than when combining words using cubes. Conversely, participants produced more within-category descriptions (e.g., taxonomic declarations “it’s a X”, and metaphorically blended categories) when interacting with cubes than with a poster. These results suggest embodied explanations, and are consist with developmental studies that find categorization is differentially organized by shape and taxonomy. We propose that hardcopy and traditional keyboard-display computers which afford pointing and touching may engage categorization differently than tangible computers based on physical objects which afford grasping and arranging.