Formally, φ t (the word distribution for tuple t) has a Dirichlet(ω ( t) ) prior, where for each word w in the vector,ω w is a log-linear function: (1) where ω (B) is a corpus-wide precision scalar (the bias), ω w is a corpus-specific bias for word w, and ω (k) t k w is a bias parameter for word w for component t k of the kth factor.
if the b value is near 0 for a particular triple, then it will have very low prior probability.