  Everyday activities performed by artificial assistants can potentially be
executed naively and dangerously given their lack of common sense knowledge.
This paper presents conceptual work towards obtaining prior knowledge on the
usual modality (passive or active) of any given entity, and their affordance
estimates, by extracting high-confidence ability modality semantic relations (X
can Y relationship) from non-figurative texts, by analyzing co-occurrence of
grammatical instances of subjects and verbs, and verbs and objects. The
discussion includes an outline of the concept, potential and limitations, and
possible feature and learning framework adoption.
