17. A system for an expanded CRF model, comprising: a network connection that is coupled to tenants of the multi-tenant service; a processor and a computer-readable medium; an operating environment stored on the computer-readable medium and executing on the processor; and an eCRF manager operating under the control of the operating environment and operative to perform actions comprising: accessing an expanded Conditional Random Field (eCRF) model that includes modeling of labels with long-distance dependencies that is expressed by: p (Y, X) =Π t=1 T exp{Σ k=1 K λ k f k (y t ,y t-1 ,x t )+Σ l=1 L θ l g l (y t ,d t r ,x t )} where T is the length of the sequence, K is the number of feature functions, λ k is the weight for k-th feature functions f k , which model a relationship among current input feature x t , a previous output label y t-1 and a current output label y t , and where L is a number of dynamic feature functions, θ 1 is a weight for l-th feature functions g l , and d t r are a distance of the current label from/to a previous/next specific output label r; a searching lattice comprising nodes and edges using input data; extracting features using the searching lattice; computing probability of the nodes and the edges in the searching lattice; determining a label sequence using the searching lattice; and outputting the label sequence.
18. The system of claim 17 , further comprising computing forward and backward probabilities and re-estimating the weights.