Anyone who has spent time linking real records to knowledge bases learns the same lesson sooner or later: the hard cases are not the near misses, they are the empty returns. A system that finds several plausible entities can at least hand the problem back with context. A system that finds nothing has to decide whether the record is rare, malformed, too sparse, outside scope, or simply not represented in the source at all. That is where the design of an entity resolution
How MCP for Google Knowledge Graph and Wikidata Supports AI Agent Workflows
When people talk about giving AI agents access to external knowledge, the conversation often gets abstract very quickly. The practical questions are more grounded. Can the agent find the right entity without spraying out a hundred weak guesses? Can it show why it picked one record over another? Can a human inspect the evidence when the match is close but not safe? Can the workflow stay read-only, predictable, and easy to slot into existing tools? That is where MCP for go