Knowledge graph Extraction from Textual data using LLM
Oct 7, 2024 61 views 
The advent of Large Language Models (LLMs), such as ChatGPT and GPT-4, has revolutionized natural language processing, opening avenues for advanced textual understanding. This study explores the application of LLMs in developing Knowledge graphs from textual data. Knowledge graphs offer a structured representation of information, facilitating enhanced comprehension and utilization of unstructured text. We intend to construct Knowledge graphs that capture relationships and entities within diverse textual datasets by harnessing LLMs’ contextual understanding and language generation capabilities. The primary goal is to explore and understand how well LLMs can identify and extract relevant entities and relationships from textual data using prompt engineering while contributing to structured knowledge representation.