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I am learning about probabilistic graphical models and I was wondering if there is an example explaining the math behind *conditional random fields*. Looking solely on the formula, I have no idea what we actually do. I found a lot of examples for the *hidden Markov model*. There is a part speech-tag task where we have to find the tags for the sentence "flies like a flower". On these slides (slide 8) Ambiguity Resolution: Statistical Method-Prof. Ahmed Rafea, an HMM is used to find the correct tags. How would I transform this model into a CRF and how would I apply the math?