Named Entity Recognition for Novel Types by Transfer LearningNamed Entity Recognition for Novel Types by Transfer LearningQu, Lizhen and Ferraro, Gabriela and Zhou, Liyuan and Hou, Weiwei and Baldwin, Timothy2016
Paper summarymarekThe authors tackle the problem of domain adaptation for NER, where the label set of the target domain is different from the source domain.
They first train a CRF model on the source domain. Next, they train a LR classifier to predict labels in the target domain, based on predicted label scores from the model. Finally, the weights from the classifier are used to initialise another CRF model, which is then fine-tuned on the target domain data.