Three dimensional point cloud data sets are easy to acquire and manipulate, but are often too large to process directly for embedded real-time applications. The spatial information in a point cloud can be represented in a variety of reduced forms, such as voxel grids, Gaussian mixture models, or spatial semantic structures. In this article, we show how a segmented point cloud can be represented as a spatial relationship graph using bounding boxes and triangular fuzzy numbers. This model is a lightweight encoding of the relative distance and direction between objects, and can be used to describe and query for particular spatial configurations using linguistic terms in a multicriteria framework. We show how this approach can be applied on a hand-segmented subset of the NPM3D data set with several illustrative examples. The work herein has useful applications in many applied domains, such as human-robot interaction with unmanned aerial systems.