Large language models can achieve competitive performance in few-shot relation extraction tasks using the CoT-ER approach, which incorporates explicit evidence reasoning.
This work introduces a meta dataset for few-shot relation extraction that captures realistic real-world scenarios, and conducts a comprehensive evaluation of six recent few-shot relation extraction methods, revealing the need for substantial future research in this domain.