This groundbreaking research presents a specialized system for extracting structured knowledge from unstructured data about mass-shooting incidents, supporting security and legal professionals.

• Creates the first dataset specifically designed for knowledge acquisition on mass-shooting events
• Applies named entity recognition techniques to extract critical information from complex narratives
• Provides a framework for AI-assisted investigation that can process large volumes of unstructured text
• Bridges the gap between raw data and actionable security intelligence

This research matters because it directly addresses public safety challenges by transforming overwhelming volumes of unstructured information into organized knowledge that can support timely investigations and evidence-based policy decisions.

Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice