Learning spatial prepositions is an important problem in spatial cognition. We describe a model for learning how to classify visual scenes according to what spatial preposition they depict. We use SEQL, an existing model of analogical generalization, to construct relational descriptions from stimuli input as hand-drawn sketches. We show that this model can distinguish between in, on, above, below, and left, after being trained on simple sketches exemplifying each preposition.