Meta-learning has recently been proposed to learn models and algorithms that can generalize from a handful of examples. However, applications to structured prediction and textual tasks pose challenges for meta-learning algorithms. In this paper, we apply two metalearning algorithms, Prototypical Networks and Reptile, to few-shot Named Entity recognition (NER), including a method for incorporating language