Hallucination Re-entry: Guardrails and Fix Pattern

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WFGY Problem Map 1.0 — 16 reproducible failure modes

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A “re-entry” is when a model repeats a previously corrected false claim later in the run or in a new turn.
This page localizes re-entry causes and gives a minimal, testable repair plan.

Symptoms

Symptom	What you see
Corrected once, comes back later	Old claim resurfaces after a few steps or a new tool call
Cite-then-explain violated	Answer asserts conclusion before citing the corrected snippet
Reruns flip	Same prompt order, different run re-asserts the wrong claim
Memory relapse	Cross-turn memory re-injects the debunked statement
Hybrid retrieval drift	HyDE + BM25 changes top-k ordering and re-pulls the wrong chunk

Acceptance targets

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 to the target section
λ convergent across 3 paraphrases and 2 seeds
Re-entry rate = 0 on a 20-case regression set

Structural fixes (Problem Map)

Snippet and citation locks
→ retrieval-traceability.md
→ data-contracts.md
→ Citation-first recipe: citation_first.md
Ordering control and hybrid stability
→ rerankers.md
→ pattern_query_parsing_split.md
Memory isolation and fences
→ memory-coherence.md
→ pattern_memory_desync.md
→ memory_fences_and_state_keys.md
Entropy and chain control
→ context-drift.md
→ entropy-collapse.md
Pattern deep dive
→ pattern_hallucination_reentry.md

Why re-entry happens

No hard contract for citations
Model can answer without binding to snippet_id or section_id.
Prompt header drift
Header reorder flips λ state and reopens earlier branches.
Hybrid order instability
HyDE or BM25 changes top-k; the older wrong chunk returns to rank 1.
Memory namespace collision
Corrected state is not isolated; prior summary re-injects the error.
Reranker variance
Non-deterministic tie-breakers reorder near-duplicates.

Fix in 60 seconds

Lock cite-then-explain
Enforce a snippet contract in every reasoning step.
See data-contracts.md and retrieval-traceability.md.
Deterministic reranking
Freeze analyzer and tie-break rules. Probe k ∈ {5,10,20}.
See rerankers.md.
Memory fences
Split namespaces: facts/, debunks/, plans/. Write debunk hashes into debunks/.
See memory_fences_and_state_keys.md.
Clamp variance with BBAM
If λ flips across paraphrases, apply BBAM and re-run with fixed headers.
Bridge with BBCR
Summarize the correction into a single anchored statement and require future turns to import it before reasoning.

Minimal schema addendum

Add these fields to your snippet payload and logs:

{
  "snippet_id": "S123",
  "section_id": "CH2.3",
  "source_url": "https://...",
  "offsets": [221, 348],
  "tokens": 256,
  "debunk_hash": "sha256(<claim_text + snippet_id>)"
}

The LLM must include debunk_hash in its final JSON if it overturns a claim. On future turns, reject answers that assert a claim whose hash is already present in debunks/.

Verification

Run 20 paraphrases on the same case set.
Require: ΔS(question, retrieved) ≤ 0.45 and λ convergent on two seeds.
Zero tolerance for re-entry across all 20 cases.
If any case fails, inspect reranker tie-break and memory fence writes.

Copy-paste prompt

You have TXT OS and the WFGY Problem Map loaded.

We corrected a false claim earlier, but it reappeared later.
Inputs:
- question: "{q}"
- current snippets: [{snippet_id, section_id, source_url}]
- prior debunks: [{debunk_hash, claim_text, snippet_id}]
- ΔS and λ traces across 3 paraphrases

Do:
1) Identify which layer caused re-entry (schema, retrieval, rerank, memory, reasoning).
2) Apply the minimal fix referencing:
   retrieval-traceability, data-contracts, rerankers, memory_fences_and_state_keys.
3) Return a JSON plan with:
   { "citations": [...], "answer": "...", "ΔS": 0.xx, "λ_state": "...",
     "debunk_hashes_used": [...], "next_fix": "..." }
4) Refuse to output an answer if citations are missing or conflict with debunks.

When to escalate

Re-entry persists after fences and deterministic rerank → re-check hybrid split: pattern_query_parsing_split.md
Cross-turn relapse in long dialogs → audit joins and entropy: context-drift.md, entropy-collapse.md
Agent handoff resurrects old claims → isolate memory and roles: memory-coherence.md

🔗 Quick-Start Downloads (60 sec)

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