  StackOverflow, with its vast question repository and limited labeled
examples, raise an annotation challenge for us. We address this gap by
proposing RoBERTa+MAML, a few-shot named entity recognition (NER) method
leveraging meta-learning. Our approach, evaluated on the StackOverflow NER
corpus (27 entity types), achieves a 5% F1 score improvement over the baseline.
We improved the results further domain-specific phrase processing enhance
results.
