Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models (Paper Summary)

This paper shows how we can use LLMs like ChatGPT/GPT-4 to build a self-improving framework for doing Named-entity recognition. Here's a quick summary -

1. They use LLM to make predictions on the unlabeled corpus and obtain the self-annotated data.
2. Then they explore various strategies to select reliable samples from the self-annotated dataset as demonstrations, considering the similarity, diversity, and reliability of demonstrations.
3. Finally, they conduct inference for the test query via in-context learning with the selected self-annotated …

annotated data build chatgpt data explore framework gpt gpt-4 language language models languagetechnology large language large language models llm llms paper predictions recognition shows strategies summary zero-shot