Research Update: Defining Sections & Handling Redundancy in Templify Configs

As we move toward a working proof of concept (PoC) for config generation, one of the central design questions is:How do we define a “section” when no explicit titles are provided by the user?

1. Moving Beyond Over-Reliance on Headings

Traditionally, section boundaries are defined by titles or headings provided by the user. But many document types — resumes, legal contracts, scientific abstracts — often blur section boundaries or lack explicit headings altogether.

Our evolving definition:

A section = an anchor pattern + the body patterns that follow until the next anchor.

• Anchors may be user-provided titles or heuristically inferred “heading-like” patterns.

• Bodies are the paragraphs, lists, tables, or callouts that logically attach to the last anchor.

This ensures every document, with or without explicit titles, can still be broken into meaningful sections.

2. Skeleton of Patterns

We’re treating configs not as ad-hoc collections, but as a skeleton of reusable pattern classes.

• Skeleton includes:

  • H-* (Headings)

  • P-* (Paragraphs)

  • LIST-* (Lists)

  • TABLE-* (Tables)

  • CALLOUT-* (Callouts)

• DOCX intake and plaintext intake both populate this skeleton with the subset of patterns observed in a document.

This means the config remains consistent, reusable, and domain-independent, while still adapting to each document’s structure.

3. Redundancy Handling

To keep configs clean and usable, we’re implementing a multi-layered redundancy strategy:

1. Deduplication Key

   • When adding a descriptor, compute a hash from (class_, style, normalized_pattern).

   • If already present, skip it.

2. Confidence Pruning

   • If two descriptors overlap, retain the one with higher confidence.

   • Example: semantic match (0.91) overrides heuristic match (0.60).

3. Variant Collapsing (Optional)

   • For highly repetitive descriptors (e.g., multiple P-BODY), collapse into a single rule with multiple signals/examples.

   • Example:

     { "class_": "P-BODY", "signals": ["HEURISTIC", "SEMANTIC"], "examples": ["FCC Back Ends and APIs", "Software Engineer"] }

This ensures the config doesn’t balloon with duplicates, but remains compact, high-confidence, and representative.

4. Domain Pack Anchoring

To further refine relevance, we can apply domain-specific whitelisting:

• Example: In a resume domain pack, prioritize anchors like Experience, Education, and Skills.

• Noise such as arbitrary bolded phrases or decorative text is filtered out.

This provides domain-sensitive configs that are both robust and focused.

5. Roadmap Impact

Together, these principles give us a strong foundation for the PoC:

• Every document can yield usable sections (explicit or inferred).

• Configs act as a library of reusable patterns, not a grab bag of matches.

• Redundancy is controlled, ensuring clarity and maintainability.

• Domain packs offer future precision, aligning outputs with real-world use cases.

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Next Steps

• Implement incremental section naming (section1, section2, …).

• Store anchors as full PatternDescriptors, not just raw text.

• Integrate deduplication + pruning into the config pipeline.

• Explore lightweight domain pack anchoring for early use cases (e.g., resumes).

With these decisions, Templify is positioned to deliver a clean, extensible config library that can map plaintext back to DOCX with confidence — the core milestone for our PoC.