CHAT Processing Playbook for Editors and Analysts

Status: Current Last updated: 2026-03-24 00:01 EDT

Objective

Provide practical guidance for non-compiler users who create, edit, and validate CHAT files, with emphasis on error interpretation and correction workflow.

Who This Is For

• Transcript editors,
• corpus curators,
• QA reviewers,
• linguists using tooling outputs but not parser internals.

Core Editing Workflow

1. Open file in editor with CHAT diagnostics enabled.
2. Run validation (single file first, then batch).
3. Fix highest-severity structural issues first (headers, tier markers, unmatched delimiters).
4. Re-run validation and inspect warnings.
5. Only then address style and normalization suggestions.

Error Triage Heuristic

• Errors at file start: likely header formatting or encoding issues.
• Errors at tier prefix: likely malformed */% tier syntax.
• Errors inside words: likely symbol, marker, or annotation boundary issues.
• Repeated same error class: likely one systemic rule violation pattern.

Fast Interpretation Guide

• Error: parser/validator could not accept structure; must fix.
• Warning: valid but suspicious or non-canonical; review strongly recommended.
• Info: advisory normalization or convention hints.

Common Fix Recipes

• Header spacing problems:
  • Ensure expected separators and avoid accidental tabs/spaces drift.
• Unclear language/form markers:
  • Confirm @s usage and suffix ordering with house style guide.
• Duration/annotation confusion:
  • Verify bracketed annotation form and avoid malformed punctuation.
• Dependent tier attachment issues:
  • Ensure % tiers follow intended main tier and keep indentation consistent.

Batch Validation Workflow

1. Validate a small sample first.
2. Group failures by error code.
3. Fix by pattern, not file-by-file random order.
4. Re-run and confirm error count decreases monotonically.
5. Save run report for audit trail.

Collaboration Workflow with Developers

When reporting parsing issues, include:

• exact file path,
• minimal excerpt around failing span,
• observed diagnostic code/message,
• expected behavior (if known).

This reduces back-and-forth and speeds defect triage.

Quality Checklist Before Publishing Corpus Updates

• No unresolved error-level diagnostics.
• Warning classes reviewed and accepted or fixed.
• Participant headers and IDs internally consistent.
• Roundtrip serialization check passes for representative samples.
• Changelog note recorded for major normalization edits.

Training Recommendations

• Maintain short examples for each common error class.
• Provide editor cheat sheet for tier prefixes and marker syntax.
• Run periodic QA calibration sessions across editors.