NSTD.7:5.1 - Generated-narrative pipeline: graph-to-text case

An AI agent receives a concept graph and produces a polished explanation. The author compares the needed dependency and example relations with the draft, evaluates consequential losses and repairs the account. The optional record below supports repetition of that comparison.

GeneratedNarrativeUseNote@GraphToTextTeaching:
  sourceMaterialRef: concept graph with dependency, example, counterexample and evidence links
  requiredRelationsOrConstraints: prerequisite chain, contrast pairs, evidence-return points
  generationMethodRef: LLM-assisted graph-to-text workflow
  contentPlanRef: selected nodes and relations
  discourseOrEventPlanRef: didactic dependency order with a contrast reveal
  generatedDraftRef: prose candidate
  sourceComparison: required relations compared with their sentences
  evaluationRef: relevant NSTD.6 questions and results
  useDecisionOrRepair: repair any missing prerequisite before the learner uses that inference
  revisitCondition: source graph, generator behavior or reader result changes

Pipeline steps:

1. Select the nodes, relations and returns the learner needs.
2. Choose an order through NSTD.2, then generate a short draft.
3. Compare the draft with the graph. If it says “B occurs because A” but the graph supports only “A precedes B”, replace the causal claim or obtain the missing causal account.
4. Use NSTD.6 to assess the repaired version for the intended reading. The draft need not have been accepted before this assessment.
5. Keep the adequate result. For repeated improvement, use E.23 with the version, changed part, protected characteristics and comparison basis.