End-to-End Pipeline Architecture for Evidence-Graded Knowledge Graphs: From Source Ingestion to Weighted Edge Delivery

Key Points

• The aim is to present a complete architecture for processing and delivering knowledge graphs from various data sources.
• Implemented three-channel ingestion for diverse data sources.
• Utilized two-layer deduplication and fact extraction methods.
• Adopted PostgreSQL+pgvector for data modeling.
• Integrated Docker for reproducible deployment.
• Monitored data staleness to ensure up-to-date information.
• Achieved efficient ingestion of 271 source definitions from 25 domains.
• Enhanced data accuracy through confidence calibration and composite weighting.
• Established a robust architecture for systematic data processing.