For example, if w i can be used as a noun or a verb, then we want the likelihood of seeing other nouns or verbs in position i of frames in cluster k. Here, we use the partial knowledge of the learned clusters.
we look over all existing clusters k , estimate the probability that w i is the head word of frames in k , then estimate the probability of using the head words from those other clusters in position i in cluster k. We refer to this category-based estimate as P cat : where P i (k |k) is the probability of finding usages from cluster k in position i given cluster k. To support this we record the categorization decisions the model has made.