2017] compare each query token to the prototype of each entity class • compare each query token with each token of support examples and assign the label according to their distances[Fritzler+ 2019] ▪ Span-level metric-learning[Yu+ 2021] • Recently, bypass the issue of token-wise label dependency while explicitly utilizing phrasal representations 14 Snell+: Prototypical networks for few-shot learning, NIPS ‘17 Fritzler+: Few-shot classification in named entity recognition task, ACM/SIGAPP ‘19 Yu+: Few-shot intent classification and slot filling with retrieved examples, NAACL ‘21