# Hallucinated Term Allowlist: closed-loop remediation in one click > Hallucinated Term Allowlist closes the loop — click a flagged term on the dashboard to allow-list it permanently, turning false positives into a one-time fix. **Category:** Hallucination Prevention **Author:** NeuralSeek Team · **Published:** June 9, 2026 **Canonical:** https://neuralseek.ai/ai-grounded/hallucinated-term-allowlist **Section index:** https://neuralseek.ai/ai-grounded No automated grounding check is perfect, and an honest platform admits it. Sometimes a term gets flagged as hallucinated when it's actually legitimate — an internal product name the source abbreviates differently, a domain-specific acronym, a brand spelling the checker doesn't recognize. Left unmanaged, these false positives are corrosive: teams either tolerate the recurring annoyance or, worse, loosen their controls to make the noise stop. The Hallucinated Term Allowlist turns each of these into a permanent, one-click fix. ## What it actually does When the system flags a term as ungrounded, a reviewer can click it directly on the dashboard to allow-list it permanently. From that moment on, the term is treated as known-safe, so the same legitimate word is never stripped again. The loop closes cleanly — detect, review, resolve — and it closes once. There's no recurring battle with the same false positive, and no engineering ticket required to make the fix stick. ## Why business teams care This is the control that makes the entire guardrail stack maintainable in the real world. Without a remediation path, aggressive hallucination controls become unlivable: every false positive is a fresh frustration, and the pressure to weaken the controls grows until they no longer protect anything. The allowlist resolves this tension. It lets you keep controls tight while continuously teaching the system your organization's specific vocabulary — so protection and usability rise together instead of trading off. ## How to tune it in practice Operationalize it as a lightweight review habit: when legitimate terms get flagged, allow-list them in the moment rather than batching the cleanup or relaxing the underlying check. Pair it directly with Hallucination KW Removal, which is the control most likely to over-strip domain-specific proper nouns. As the allowlist matures, removal becomes progressively sharper and less disruptive, and the whole stack converges toward aggressive protection with minimal false positives — a system that gets quieter and more accurate the more it's used. ## Common failure modes it prevents It prevents the two ways teams normally fail at hallucination control over time. The first is 'alert fatigue,' where recurring false positives train reviewers to ignore flags entirely, so real fabrications slip through unexamined. The second is 'control erosion,' where the friction of false positives drives teams to dial back protection until it's effectively off. The allowlist defuses both by making each false positive a one-time event rather than a permanent tax. ## Where it fits in the stack The allowlist is the feedback loop that sits across the whole hallucination layer, but it's most tightly coupled to Hallucination KW Removal and the proper-noun checks that occasionally over-fire. By feeding accountable human decisions back into those automated controls, it lets the deterministic checks stay strict while adapting to your reality — the human supplies judgment exactly where automation lacks context, and that judgment becomes permanent system knowledge. ## Human judgment, captured Every allow-list decision is attributable and auditable, so the system improves through accountable human judgment rather than silent rule changes that no one can later explain. Each fix is a recorded act by a named reviewer at a known time — governance that gets smarter with use while leaving a clean trail of exactly why every exception exists. > A guardrail without a remediation path doesn't get tighter over time — it gets ignored. ## The takeaway Hallucinated Term Allowlist makes hallucination prevention a closed loop: one click turns a false positive into a permanent, audited fix — keeping controls both tight and livable, and making the whole stack smarter the more it's used. --- From NeuralSeek's AI Grounded — practical, web-verified guidance on building governed, grounded enterprise AI. NeuralSeek is the model-agnostic, governed AI platform you own: any LLM (swap with no rebuild), your data in your own tenant (cloud or on-prem), 118 guardrails enforced before any action, one container that runs anywhere.