SOURCE-LINKED INTELLIGENCE
ARGUS: Role-Aware Event Knowledge Graphs for U.S. Employment-Discrimination Complaints
U.S. employment-discrimination complaints describe complex event sequences that are not explicitly captured by lexical or embedding-based representations alone. We present ARGUS, a source-grounded pipeline that combines a 5W1H-inspired schema, legal-domain models, and LLM-based structured generation to construct document-level Event Knowledge Graphs (EKGs) from CourtListener complaints. ARGUS extracts fact-bearing statements, builds chunk-level event graphs with participant, temporal, and causal structure, and merges them into document-level representations. We evaluate graph quality through h
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T17:29:40.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.