{
  "id": "analogical-prompting",
  "code": "PTL-0036",
  "term": "Analogical Prompting",
  "aliases": [],
  "category": "reasoning",
  "definition": "Analogical prompting asks the model to recall or generate relevant example problems and their solutions on its own before solving the target problem, removing the need for hand-written exemplars.",
  "description": "Inspired by how people draw on analogous past experience, the self-generated examples are tailored to each problem rather than fixed for the whole task.",
  "example": null,
  "broader": [],
  "narrower": [],
  "related": [
    "few-shot-prompting",
    "generated-knowledge-prompting"
  ],
  "introduced": 2023,
  "sources": [
    {
      "title": "Large Language Models as Analogical Reasoners",
      "authors": "Yasunaga et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2310.01714"
    }
  ],
  "url": "https://protologue.com/t/analogical-prompting/",
  "citation": "Protologue. (2026). Analogical Prompting. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0036). https://protologue.com/t/analogical-prompting/"
}