Another reason for the mediocre performance of the two-stage ICL approach is that only ten few-shot examples per category were provided -though arguably the most relevant. In contrast, Figure states the substantially larger number of training examples provided per category for fine-tuning. Adding more few-shot demonstrations in the prompt has been shown to improve the performance of ICL on the NER task in a general domain . Intuitively, this should be even more applicable in domain-specific settings. However, adding more context would also result in an increased number of input tokens and thus more expensive model inferences.