Ask HN: How to run NER in batch with ChatGPT?

Named entity recognition (NER) is usually the basis of transforming unstructured data (text) into structured data (say, in JSON format). The current best approach for NER in ChatGPT is few-shot-learning, where we give a few examples and asks for it to solve ONE instance of the task. The problem with this approach is the cost. We need to use a lot of tokens from examples in order to predict a single instance. I'm trying to overcome this issue by giving more than one instance for prediction. Something like this:

``` <instruction> <1 - example> <2 - example> <3 - new instance> <4 - new instance>

<answer for 1> <answer for 2> ```

Wishing the generator to predict answers for instances 3 and 4.

From my experience, results are worst than predicting a single instance.

Does anyone have better results in this task?

Thanks!