Z is a probability normalization factor in order to model well defined probability distribution: herec n−1 andc n are the concepts hypothesized for the previous and current words, ).
the CRF model used for the Attribute-Value Extraction phase learns in the same way the conditional probability we use attributes-words concatenations on the source side and attribute values on the target side.