📅 2025-05-04 — Session: Refined Schema and Parser Design for AI Message Annotation

🕒 17:20–18:25
🏷️ Labels: Schema Design, Ai Parsing, Message Annotation, Workflow Improvement, Parser Enhancements
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to refine the schema and parser design for AI message annotation, focusing on enhancing the structure and classification of parsed messages to improve workflow efficiency and message reusability.

Key Activities

  • Discussed strategies for reviewing AI interactions to improve workflows.
  • Outlined an initial parser plan for AI message annotation, including preprocessing, classification, and tagging phases.
  • Proposed enhancements for parser design by identifying additional dimensions such as response category and technical depth.
  • Finalized the schema for Phase 1 Parser, detailing structure and classification of parsed messages.
  • Developed a schema refinement plan based on new samples, suggesting hierarchical tagging and additional fields.
  • Worked on schema for classifying technical messages generated by ChatGPT.
  • Proposed a version 2 of the ParsedMessage schema to capture message diversity and richness.
  • Explained the content_medium field for content categorization in software development.
  • Provided a specification for structural fields in message parsing.
  • Defined a refined schema for ParsedMessage to facilitate retrieval and classification.

Achievements

  • Established a comprehensive plan for refining and enhancing the AI message annotation schema and parser design.
  • Created detailed specifications and templates for various aspects of the parser design.

Pending Tasks

  • Implement the refined schema and parser enhancements in the actual system.
  • Test the new schema and parser design with real-world data to validate improvements.