LDA-frames is an unsupervised approach for identifying semantic frames from semantically unlabeled text corpora, and seems to be a useful competitor for manually created databases of selectional preferences. The most limiting property of the algorithm is such that the number of frames and roles must be predefined. In this paper we present a modification of the LDA-frames algorithm allowing the number of frames and roles to be determined automatically, based on the character and size of training data.