n8n

Detect hallucinations using specialised Ollama model bespoke-minicheck

Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify…

Use case
Document Extraction
Difficulty
intermediate
Author
Guido Zockoll
Updated
Jun 7, 2026

Required custom nodes

  • code
  • executeWorkflowTrigger
  • manualTrigger
  • filter
  • chainLlm
  • lmChatOllama
  • lmOllama
  • aggregate

Detect hallucinations using specialised Ollama model bespoke-minicheck

A working n8n automation that runs against a local model via Ollama - 2,483 views on the n8n template library. Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify…

What it does

Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify… It chains 12 nodes, integrating code, executeWorkflowTrigger, manualTrigger, filter.

Requirements

  • n8n (self-hosted, free) to run the workflow
  • Ollama serving a local model
  • A GPU with enough VRAM for your chosen model (see best model per GPU)

Import it

Open the workflow on the n8n template library and click Use workflow to import it into your self-hosted n8n, then point its model node at your local Ollama endpoint (http://localhost:11434).

Use it with

n8n · Ollama


Workflow by Guido Zockoll on the n8n template library. We link to the original to import; credit and the workflow JSON belong to its author.