Step-by-step Code for Knowledge Graph Construction with Hybrid Approach
In this episode of TwoSetAI, Angelina and Mehdi provide a step-by-step walkthrough for constructing a basic Knowledge Graph (KG) for a Retrieval-Augmented Generation (RAG) system. They contrast the traditional approach for building a KG with the new approach using large language models (LLMs) to extract entities and relationships from data. They also explain why they chose a hybrid approach for constructing this example KG and demonstrate the process using a Jupyter Notebook.
The video covers the following key points:
1. **Introduction to Knowledge Graphs (KGs)**: Explanation of what a KG is, its importance, and its applications in search engines, recommendations, and question answering.
2. **Traditional Approach vs. LLM Approach**: Comparison of traditional methods (like rule-based approaches, machine learning models, and pre-trained models) with the newer LLM-based methods for entity and relationship extraction.
3. **Advantages and Disadvantages**: Discussion of the pros and cons of both approaches. Traditional methods are precise, transparent, and efficient but less scalable and adaptable. LLMs are powerful and adaptable but resource-intensive and less transparent.
4. **Use Cases**: Suitable scenarios for each approach, with traditional methods being ideal for domain-specific applications requiring high precision, and LLMs being useful for rapid prototyping and general-purpose applications.
5. **Code Walkthrough**: Detailed explanation of the code used to construct a KG using both methods. They demonstrate extracting entities and relationships from Tom Hanks’ Wikipedia page using a pre-trained model and an LLM. The hybrid approach combines the strengths of both methods for better results.
6. **Visualization**: Construction and visualization of the KG, highlighting different types of entities (like persons, locations, movies) with color-coded nodes.
The video provides practical insights into building KGs, offering a balanced view of the methodologies and their real-world applications. It emphasizes the importance of choosing the right approach based on the specific needs and constraints of the project.