For the first layer, a large collection of stereotypical descriptions is harvested from the web.
for example: disease, poison, sin, crime, ideology, weapon, …} src(Hitler) = {monster, criminal, tyrant, idiot, madman, vegetarian, racist, …} Let srcTypical(T) denote the aggregation of all properties ascribable to T via metaphors in src(T): We can also use the posTypical and negTypical variants in (7) and (8) to focus only on metaphors that project positive or negative qualities onto T. In effect, (9) provides a feature representation for a topic T as viewed through the prism of metaphor.