The language model behind my Graph RAG pipeline did something worse than getting a fact wrong. It fabricated the evidence. Each relation it extracted carried a quote that was supposed to come straight from the source article, and many of those quotes had never been written. They read perfectly. They did not exist.
What does fabricated evidence mean in a knowledge graph?
I am building the seed knowledge graph for 2asy.ai, a causal-chain intelligence system over trade and tariff news. Every relation and event in the graph carries an evidence field: the exact sentence from the source document that justifies it. That evidence is the whole point. It is what lets me, or a reader, trace a claim back to where it came from instead of trusting the model on faith.
The problem is that I was asking a language model to produce that evidence by quoting the source. And a language model is a text generator, not a copier. When I checked the evidence against the original articles, a large share of the quotes were not verbatim. They were fluent, on-topic, and invented.
The ellipsis was the tell
