lyndonkl Map Analogy to Concept
Table of Contents
Related skills: Called by the Intuition Builder per framing, after generate-analogy-set and before stress-test-analogy. Gentner's structure-mapping theory is the theoretical spine: good analogies map relations, not just objects.
Workflow
For one framing (source → target):
- [ ] Step 1: Enumerate the source domain's key components (entities + relations)
- [ ] Step 2: For each source component, propose the target component it maps to
- [ ] Step 3: Check systematicity — do the relations carry across, or only objects?
- [ ] Step 4: Flag any source component that maps to nothing concrete (vague mapping = reject)
- [ ] Step 5: Return the mapping table
Step 3: Systematicity check
A strong analogy preserves the pattern of relations, not just object-level similarity. Example:
- Weak: "a neural network is like a brain" — both have "neurons", but the relation "neurons fire" doesn't carry over in a useful way.
- Strong: "V/D/J gene recombination in B cells maps to multi-agent diversity" — the relation "small vocabulary generates exponential combinatorial space" carries.
If the framing only matches on objects (nouns), reject or downgrade.
Step 4: Unmapped flagging
Every source component must map somewhere. "It's like a brain" fails because "brain" is unmapped to anything specific in the target (neuron? cortex? entire NS?). Flag and reject.
Mapping schema
source_domain: "library card catalog"
target_concept: "KV cache"
mapping:
- source: "library"
target: "the KV cache data structure"
relation: "contains"
- source: "drawer"
target: "cache slot"
relation: "capacity-bounded container"
- source: "card"
target: "(key, value) projection pair"
relation: "indexed entry"
- source: "lookup by drawer then card"
target: "retrieval by position in key tensor"
relation: "indexed retrieval"
- source: "eviction when drawers fill"
target: "LRU / FIFO eviction under context-length pressure"
relation: "replacement under capacity constraint"
systematicity_score: 4/5 # how well relations carry over
unmapped_source: none
unmapped_target: "the attention operation that reads this cache" # flagged — see stress-test
Worked example
Framing: "Dropout is antibody diversity for weights."
Source components:
- immune system
- antibody population
- pathogen recognition
- diversity generation (V/D/J recombination)
Target components:
- neural network
- weights under dropout
- generalization to unseen examples
- implicit ensembling via sub-networks
Mapping:
| Source | Target | Relation |
|---|---|---|
| immune system | the trained neural network | generates patterns from a small genome/parameter set |
| antibody population | ensemble of thinned sub-networks | many variants tested in parallel |
| pathogen recognition | generalization on test data | performance on unseen inputs |
| V/D/J combinatorial generation | random dropout masks produce sub-network diversity | small seed → many variants |
Systematicity: 4/5 — the relation "small number of building blocks → large functional diversity" carries across. The one break: actual biological V/D/J has selection (negative selection in thymus), which dropout doesn't do. Flag.
Guardrails
- Every source component maps to a concrete target component. No source is left unmapped.
- Rate systematicity on a 1–5 scale. Below 3 = the analogy is object-level, not relation-level; flag for downgrade.
- Do not generate the analogy itself — that's
generate-analogy-set. This skill only maps. - Flag unmapped target components as candidates for the stress-test boundary.
- Mapping output is structured (table or yaml) — don't write it as prose.
Quick reference
- Input: one framing (source + target).
- Output: structured mapping + systematicity score + unmapped flags.
- Theoretical basis: Gentner's structure-mapping; relations > objects.