Citation Needed: Structured data extraction workflows

In the previous article we explored how to generate and use structured data in a workflow. Now, let's take it a step further. We'll build a workflow that checks whether an article provides evidence to support its claims (but not whether the evidence itself is valid). Rather than using this to fact check articles in the wild, this might be useful for critiquing your own writing before submission or checking generated text for hallucinations. This task is impractical to automate without generative language models. Natural language processing pipelines might be able to extract or categorize entities and phrases from a text, but this task requires a degree of reading comprehension not available without larger language models. Furthermore, while many language models are capable of performing individual steps, the overall process requires more rigor and discipline than they are trained for. Frontier models might handle moderately complex tasks, but verifying that they haven't hallucinated th