Structured event graphs from legal documents improve reasoning tasks like classification and QA, but only when you already have the right documents—they don't help with initial retrieval.
ARGUS builds structured Event Knowledge Graphs from employment-discrimination legal complaints using a 5W1H schema and LLMs. The system extracts facts, organizes events with temporal and causal relationships, and merges them into document-level graphs. Testing shows these graphs improve claim classification and help answer legal questions when relevant documents are already retrieved.