Part 9/11:
While the technology is promising, David candidly admits hurdles—most notably, digesting lengthy opinions (sometimes 200+ pages) into a usable knowledge graph. To handle this, he proposes chunking documents into meaningful segments, maintaining critical details like dates, decisions, and reasoning, then converting each into nodes.
He also emphasizes the importance of experimentation—testing different summarization, structuring, and visualization methods. Visualization with Python tools or graph databases like Neo4j could turn raw case law into powerful research aids.