Implemented NER pipeline for heterogeneous data sources

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📅 2025-08-10 — Session: Implemented NER pipeline for heterogeneous data sources

🕒 22:20–23:05
🏷️ Labels: NER, Python, Spacy, Sqlite, Data Ingestion
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to implement a Named Entity Recognition (NER) pipeline capable of processing heterogeneous data sources, including emails, websites, RSS feeds, and chat exports, with a focus on creating a minimal viable product (MVP).

Key Activities

  • Developed a detailed plan for NER implementation, outlining data sources, output schema, model choices, and processing pipelines.
  • Conducted a kickoff session to discuss architecture choices, model selection, and data ingestion strategies.
  • Created a Python script skeleton for NER ingestion, including SQLite setup and command-line interface commands.
  • Implemented a minimal viable product (MVP) for NER ingestion, supporting various document types and utilizing a SQLite database for storage.
  • Reviewed the ner_ingest.py script, covering functionality, design choices, and extension plans.
  • Planned integration of Telegram and WhatsApp data into the NER pipeline.

Achievements

  • Successfully outlined and initiated the NER pipeline with a focus on MVP development.
  • Established a foundational Python script for data ingestion and processing.
  • Integrated SQLite for data management and storage.

Pending Tasks

  • Extend the NER pipeline to include real-time data processing from Telegram and WhatsApp.
  • Further develop integration layers for enhanced automation and data handling.

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