Documentation

Code Builder

Turn a defined task or dataset into executable code without redefining linguistic annotation decisions.

Data source: Standalone input — current project data will not be changed

Generate research-ready code for corpus analysis, data preparation, and reproducible experiments—with implementation guidance from GPT-5.6.

COMPUTATIONAL WORKBENCH

How this research workflow processes your data

MethodAI-supported implementation
  1. 01Research TaskObjective, input, constraints, output
  2. 02Implementation SetupLanguage and experience level
  3. 03Generation RunExplicit AI-supported action
  4. 04Implementation BlueprintGenerated response preserved
  5. 05Researcher ReviewInspect before copying
  6. 06Colab HandoffExplicit transfer only
  7. 07Execution & EvaluationPerformed after researcher review

AI proposes code from the stated configuration. The researcher must review it before any execution.

Code Builder ownership

This tool owns dataset pipelines, preprocessing, model implementation, evaluation code, and technical debugging. Refine linguistic units, labels, rules, and ambiguity in NLP Builder. Never include API keys, participant identifiers, or sensitive raw data.

Include your research objective, input format, constraints, and expected output.