This model, called coref, implements the first two steps of the above algorithm, but instead of extracting only mental state terms associated with event actors (last step), it considers all mentions appearing anywhere in the coreference neighborhood.
all unique sentences traversed by the relevant coreference chains are first pieced together to define a single neighborhood for a given document; then the relative joint frequencies of n-grams are computed by incrementing f once for each neighborhood that contains all terms with correct POS tags.