  We define a congruence that copes with null next-symbol probabilities that
arise when the output of a language model is constrained by some means during
text generation. We develop an algorithm for efficiently learning the quotient
with respect to this congruence and evaluate it on case studies for analyzing
statistical properties of LLM.
