ThinkWithPrompt by SynotticThinkWithPrompt

Build a taxonomy of a subject or field

A clear hierarchy of fields, subfields, and topics with definitions and cross-links, for study, research, tagging, or course design.

Research & SummariesFew-ShotStandardAnalyzePlanFill-in Template

The prompt

Build a taxonomy of a subject for me. Subject or field: [e.g. "machine learning", "public health", "contract law"] What I'll use it for: [e.g. "structuring a course", "tagging a content library", "mapping a literature review", "my own study plan"] Depth needed: [e.g. "3 levels", "down to individual topics"] Scope limits: [anything to include or exclude] Existing scheme to align with, if any: [e.g. "ACM Computing Classification", "our current tags"] Rules for a good taxonomy: - Each level uses one consistent organizing principle (e.g. by method, by application, by object of study) - say which one you chose and why. - Categories at the same level should not overlap; where real overlap exists, list it as a cross-link instead of duplicating the item. - Use names that practitioners actually use, and note common synonyms. - Keep sibling categories roughly comparable in breadth. Return: 1. The hierarchy as a nested outline (Field > Subfield > Topic > Subtopic), with a one-line definition for each item at the top two levels. 2. A cross-links list: items that belong to more than one branch, and interdisciplinary connections. 3. Where the field is contested or changing fast, a short note on alternative ways it is divided. 4. The same taxonomy as a flat table (ID | Name | Parent | Level | Synonyms) I can paste into a spreadsheet. If the subject is too broad for the depth I asked, tell me and propose where to split it.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • e.g. "machine learning", "public health", "contract law"
  • e.g. "3 levels", "down to individual topics"
  • anything to include or exclude
  • e.g. "ACM Computing Classification", "our current tags"

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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