The Semantics of Topological Relations: Presenting Data from a new Elicitation Tool
In this paper, I present data from the Spatial Categorization Elicitation tool (SPACE), an inventory of contextualized video clips that attempt to exhaust spatial topological relations in a variety of languages (Thiering 2005). SPACE is generated as an offline elicitation tool based on 95 short video clips presented randomly. As a set, they are expected to exploit the imaging parameters outlined in Table 1 for a given scene and include the various manipulation of a wide range of objects in different situations including varying surfaces.
Imaging Parameters used in SPACE
1. nature of figure (shape, size, animacy, number, etc.)
2. nature of ground (medium, etc.)
3. figure/ground alignment
6. temporality (dynamic vs. static)
To elicit different constructions, I use a range of common objects in situated environments that can be realistically manipulated or interacted with by people. I filmed various situations including both animate and inanimate objects in relation to static or moving reference points.
The most frequent encoding pattern is the construction without a locative marker. My findings suggest that various semantic qualities of the figure-ground asymmetries are due to certain language-specific affordances. Thus, the data support my hypothesis that spatial topological relations are based on a speaker-dependent and language-specific set of qualitative features, i.e., several imaging parameters are mandatory cognitive operations.
If indeed objective and speaker-independent parameters exist in terms of universal mechanisms then the expressions should be fairly canonical cross-linguistically, and even manipulated situations should be construed as idealized situations. SPACE provides data supporting language-specific imaging parameters, i.e., non-universal mechanisms in the construction of spatial topological relations take over.
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