The existing semi-supervised approaches to SRL can largely be regarded as extensions to supervised techniques, as they use supervised learning as sub-routines in the estimation process.
a standard trick to achieve this behavior within the generative framework is to assume that with some small probability ε the true outcome is substituted with a random pick.