Building a Financial Named Entity Recognition Pipeline for Enterprise AI

Short summary

Named Entity Recognition for enterprise financial documents requires domain-specific entity types (COMPANY, INVOICE, PAYMENT_TYPE) instead of generic linguistic categories. The workflow includes taxonomy definition, pre-labeling raw transaction narratives via regex and master data, annotation validation in Doccano, BIO-format conversion, transformer fine-tuning, and per-entity evaluation. Production systems must also implement entity resolution to map extracted entities to actual business identifiers like customer IDs and invoice numbers.

• •Define business entity taxonomies before annotation, not linguistic categories like PERSON or LOCATION
• •Use pre-labeling with regex and master data to reduce manual annotation burden significantly
• •Evaluate per-entity precision/recall metrics, not just overall accuracy for actionable feedback
• •Implement entity resolution post-processing to map predictions to actual business IDs

Generated with AI, which can make mistakes.