Few-shot Name Entity Recognition on StackOverflow
Xinwei Chen Kun Li Tianyou Song Jiangjian Guo
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.