Who is this workflow for? This automated workflow leverages Ollama’s specialized bespoke-minicheck model to accurately detect hallucinations and verify factual statements within textual content. By integrating seamlessly with n8n, it ensures reliable fact-checking, enhancing the integrity of your data..

What does this workflow do?

1. Input

  • Trigger Methods:
  • Manual Trigger: Initiate the workflow by clicking the “Test workflow” button.
  • Automated Trigger: Activate the workflow through calls from other workflows using the “When Executed by Another Workflow” trigger.
  • Required Inputs:
  • facts: A curated list of verified facts.
  • text: The text intended for verification.

2. Text Preparation

  • Sentence Segmentation: The workflow uses a “Code” node to split the input text into individual sentences.
  • Contextual Awareness: It accounts for date specifications and list elements to maintain the integrity of the context during segmentation.

3. Fact Checking

  • Individual Verification: Each sentence is individually compared against the provided list of facts.
  • Model Utilization: The bespoke-minicheck model from Ollama is employed to verify each statement.
  • Response Handling: The model returns a simple “Yes” or “No” for each sentence, indicating its factual accuracy.

4. Filtering and Aggregation

  • Discrepancy Identification: Sentences marked as “No” (indicating potential hallucinations or inaccuracies) are filtered out.
  • Result Compilation: The workflow aggregates the filtered results for further analysis.

5. Summary

  • Comprehensive Reporting: A larger language model, Qwen2.5, generates a summary of the fact-checking results.
  • Summary Content:
  • Total number of incorrect factual statements identified.
  • A detailed list of the incorrect statements.
  • An overall assessment of the article’s accuracy.

🤖 Why Use This Automation Workflow?

  • Accuracy: Utilizes advanced AI models to ensure precise identification of factual discrepancies.
  • Efficiency: Automates the fact-checking process, saving time and reducing manual effort.
  • Integration: Easily integrates with existing systems and workflows, enhancing your current processes without extensive modifications.

👨‍💻 Who is This Workflow For?

This workflow is ideal for:

  • Content Creators: Ensuring the accuracy of articles, blog posts, and other written materials.
  • Publishers: Maintaining the credibility of published content.
  • Researchers: Verifying data and statements within research documents.
  • Editors: Streamlining the fact-checking process within editorial workflows.

🎯 Use Cases

  1. Media Verification: Automatically check news articles for factual accuracy before publication.
  2. Academic Research: Validate statements and data within research papers to ensure reliability.
  3. Content Management: Integrate into content management systems to verify information in real-time as content is created or edited.

TL;DR

This workflow offers a robust and automated solution for fact-checking textual content. By utilizing specialized AI models, it efficiently identifies inaccuracies, providing a structured summary that enhances the reliability of your information. Easily integrate this workflow into your systems to maintain high standards of factual integrity.

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A curated directory of the best n8n templates for workflow automations.