Entity Extractor

The Entity Extractor skill guides you through implementing named entity recognition (NER) systems that identify and classify entities in text. From people and organizations to domain-specific entities like products, medical terms, or financial instruments, this skill covers extraction approaches from simple pattern matching to advanced neural models.

Entity extraction is a foundational NLP task that powers applications from search engines to knowledge graphs. Getting it right requires understanding your domain, choosing appropriate techniques, and handling the inherent ambiguity in natural language.

Whether you need to extract standard entity types, define custom entities for your domain, or build relation extraction on top of entity recognition, this skill ensures your extraction pipeline is accurate and maintainable.

Core Workflows

Workflow 1: Choose Extraction Approach

1. Define target entities:
   • Standard types: PERSON, ORG, LOCATION, DATE, MONEY
   • Domain-specific: PRODUCT, SYMPTOM, GENE, CONTRACT
   • Relations: connections between entities
2. Assess available resources:
   • Labeled training data
   • Domain expertise
   • Compute constraints