That's the whole problem. If you have tons (100s of thousands or more) of labels, then you have "structured" data, but how do you correctly classify that scraped item into the correct label?
Putting all the labels into the LLM is super expensive per call when you have millions of items to classify.
You can't reduce the number of labels becasue they are correctly organizes/structured. This class of problem exists in many different domains.
That's the whole problem. If you have tons (100s of thousands or more) of labels, then you have "structured" data, but how do you correctly classify that scraped item into the correct label?
Putting all the labels into the LLM is super expensive per call when you have millions of items to classify.
You can't reduce the number of labels becasue they are correctly organizes/structured. This class of problem exists in many different domains.