How to Reduce LLM Hallucinations with Wikidata: Hands-On Fact-Checking Using MCP

​LLMs are powerful, but they still hallucinate facts, especially when asked about entities, relationships, or claims that require up-to-date or structured knowledge.

​In this hands-on workshop, we'll explore how to use Wikidata as a grounding and fact-checking layer for LLMs to reduce hallucinations and make AI systems more reliable.

​We'll start with a short introduction to Wikidata and then set up the Wikidata MCP so an LLM can retrieve and verify facts rather than relying solely on its internal memory. This already provides a practical way to ground LLM outputs in verifiable data.

​From there, we’ll go beyond LLM-only approaches and build a small experimental fact-checking pipeline. The system combines semantic retrieval, LLM-based reranking, and natural language inference (NLI) to validate claims against evidence in a more controlled and interpretable way.

​This workshop focuses on evidence-driven verification pipelines that make LLM's reasoning steps explicit and easier to inspect, debug, and improve.

​What we'll cover:

• ​Wikidata as a structured source for factual verification
• ​Setting up and querying Wikidata using MCP
• ​Verifying claims with MCP + an LLM
• ​Moving beyond pure GenAI to evidence-based fact-checking
• ​Finding relevant Wikidata statements with semantic search
• ​Ranking candidate evidence with an LLM
• ​Verifying claims using an NLI model

​​What you'll leave with
By the end of the workshop, you'll be able to:

• Ground LLM outputs in structured data to reduce hallucinations
• ​Understand when LLM-only fact-checking is not enough
• ​Build a small, transparent fact-checking pipeline you can adapt to real projects

​About the speaker:

​Philippe Saadé is the AI/ML project manager at Wikimedia Deutschland. His current work focuses on making Wikidata accessible to AI application with projects like the Wikidata vector database and the Wikidata Model Context Protocol.

**Join our Slack: https://datatalks.club/slack.html**
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​This event is sponsored by Wikimedia