18. The computer system of claim 17 , wherein the instructions further include instructions that, when executed by the at least one processor, cause the computer system to: re-estimate the support scores of the context model after generating the labels; determine whether the re-estimated support scores converge with the support scores of the model; and perform the re-training and repeat generating the labels when the re-estimated support scores do not converge with the support scores of the model.
18. The computer system of claim 17 , wherein the instructions further include instructions that, when executed by the at least one processor, cause the computer system to: re-estimate the support scores of the context model after generating the labels; determine whether the re-estimated support scores converge with the support scores of the model; and perform the re-training and repeat generating the labels when the re-estimated support scores do not converge with the support scores of the model. 19. The computer system of claim 18 , wherein re-estimating the support scores of the context model after iteration u is performed according to the equation of r f , e ( u ) = ∑ i ∈ L ⋃ U ⁢ b i , f ⁢ q i , e ( u ) ∑ i ∈ L ⋃ U ⁢ b i , f , where r is the support score of feature f for entity e, i is the entity mention from the set of labeled data L and the set of unlabeled data U, b is the phrase vector for mention i and q is a context posterior from generating the labels in iteration u.