In this webinar session, we will unveil how Hume leverages GPT and LLMs to expedite intelligence analysis on extensive unstructured datasets, with a specific focus on law enforcement.
Our live demonstration will centre on the public judicial reports detailing a vast web of state corruption in South Africa, commonly known as the "state capture" or the Gupta Leaks. By employing OpenAI’s GPT (Generative Pre-trained Transformers), we will showcase how the model facilitates Named Entity Recognition (NER) and Relation Extraction (RE) to extract pertinent knowledge from these texts.
You will learn:
Prompt Engineering Excellence
Use GPT to identify key elements crucial for Knowledge Graph creation, including entities and the relationships between them.
LLMs in Action
Explore the use of Large Language Models (LLMs) for building Knowledge Graphs, including data cleaning and normalization processes
Investigate the central questions surrounding the Gupta Leaks:
- How did the Guptas sustain corruption on this scale for an extended period without arousing suspicion?
- What were the complicit organizations linked to the Guptas?
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