Videos

Graph data presents unique challenges in terms of organizing, labeling, and extracting meaningful information. GraphLabel is an innovative annotation tool designed specifically for graph data labeling and contextualization in Large Language Model-based Retrieval-Augmented Generation (RAG) searching. It provides a comprehensive solution by enabling efficient annotation and contextualization of graph data, enhancing its usability in various applications. In this session, Satej will demonstrate the capabilities and features of GraphLabel, including its intuitive interface and the functionalities for data labeling, entity recognition, relation extraction, and knowledge graph creation. You'll understand how this tool streamlines the process of annotating graph data, making it easier to create high-quality labeled datasets for LLM-based RAG searching. Whether you are a researcher, data scientist, or developer working with graph data, you will leave this session with a deep understanding of how you can revolutionize your graph data annotation workflow with GraphLabel, enabling you to unlock the full potential of LLM-based RAG searching.