To compute the likelihood of a sequence where some labels are unknown, we use a constrained CRF which marginalizes out the un-annotated tokens.
let Y L denote the set of all possible sequences that include the partial annotations (for un-annotated tokens, all labels are possible), and we compute the likelihood as: To improve our model with the newly labeled data, we directly fine-tune the initial model, trained on the transferred data, on the data acquired through active learning, referred as FINETUNE.