  We revise contextual probability theory and the associated inverse Born
problem, solved by the Quantum-Like Representation Algorithm (QLRA) in case of
two discrete random variables. After pointing out the special feature and
limitations of QLRA for two binary random variables, we generalize the QLRA
procedure to solve the inverse Born problem to the case of three binary random
variables. We analyze the quantum spin model in the light of our results and
showed that can be easily obtained from a contextual probability model. We
furthermore study the inverse Born problem in the case of two continuous random
variables, exploiting the general idea underlying QLRA.
