Chain-of-Layer: Iteratively Prompting Large Language Models for Taxonomy Induction from Limited Examples

Understand

Automatic taxonomy induction is crucial for web search, recommendation systems, and question answering.

• Manual curation of taxonomies is expensive in terms of human effort, making automatic taxonomy construction highly desirable.
• In this work, we introduce Chain-of-Layer which is an in-context learning framework designed to induct taxonomies from a given set of entities.
• Chain-of-Layer breaks down the task into selecting relevant candidate entities in each layer and gradually building the taxonomy from top to bottom.