Few-Shot Relation Classification

Few-Shot Relation Classification is a specific task in the field of natural language processing that aims to classify relationships between entities using extremely limited labeled data. This task requires the model to quickly learn and accurately identify entity relationships based on only a few support instances (such as 1 or 5) during the testing phase, making it particularly valuable in scenarios where labeled data is scarce.