This repository contains code and data for reproducing the experiments of three papers that focus on two subtasks of table annotation, column type annotation (CTA) and column property annotation (CPA). CTA is the task of annotating table columns with semantic types from pre-defined vocabularies, while CPA is the task of annotating the relationships between two columns.

The papers are organized into the following folders:

1. CTAusingChatGPT contains code and data used in the paper: "Column Type Annotation using ChatGPT"
2. CPAusingLLMs contains code and data used in the paper: " Column Property Annotation using Large Language Models"
3. KnowledgeSelfRefinementForCTA contains code and data used in the paper: "Evaluating Knowledge Generation and Self-Refinement Strategies for LLM-based Column Type Annotation"