One possible clue as to why vision is better at predicting a concept's properties is given by the fact that it obtains better results on concepts such as PANTS or STOOL, where the only difference to very similar concepts like TROUSERS or CHAIR are visual (a STOOL has no backrest as opposed to a CHAIR).
table 2 shows some examples for each of the 10 property types as defined and annotated in MCRAE.