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Implement Entity Extraction

Objective: Build entity extraction using NLP models.

Description: Integrate spaCy and HuggingFace models for named entity recognition and extraction.

Dependencies: None

Details:

  • Integrate spaCy and HuggingFace for NER.
  • Test with sample documents for accuracy.
  • Ensure extensibility for future NLP models.

Status: Done

Test Strategy: Test with sample documents and verify entity extraction accuracy.

Entity Extraction Pipeline​

flowchart TD
  DOC[Input Document] --> SP[spaCy NER]
  DOC --> HF[HuggingFace NER]
  SP --> EN[Extracted Entities]
  HF --> EN
  EN --> OUT[Output for Context Enhancement]

Explanatory Notes​

  • Role: Entity extraction identifies key concepts and relationships in unstructured text, enabling downstream reasoning.
  • spaCy & HuggingFace: Provide state-of-the-art models for named entity recognition (NER).
  • Best Practices:
    • Fine-tune models for domain-specific accuracy.
    • Validate extraction results with real data.
    • Modularize pipeline for easy integration of new models.
  • Troubleshooting:
    • Check model versions and dependencies.
    • Analyze extraction errors and retrain as needed.