Modeling objects using formal grammars has recently regained much attention in computer vision. Probabilistic logic programming, such as Bilattice based Logical Reasoning (BLR), is shown to produce impressive results in object detection/recognition. Although hierarchical object descriptions are preferred in high-level vision tasks for several reasons, BLR has been applied to non-hierarchical object grammars (compositional descriptions of object class). To better align logic programs (esp. BLR) with compositional object hierarchies, we provide a formal grammar, which can guide domain experts to describe objects. That is, we introduce a context-sensitive specification grammar or a meta-grammar, the language of which is the set of all possible object grammars. We show the practicality of the approach by an automatic compiler that translates example object grammars into a BLR logic program and applied it for detecting Graphical User Interface (GUI) components.