Given the data that we've already annotated, we can simulate this process by iterating through  our labeled data and collecting annotated product names that are sufficiently common.
we take all (lowercased, stemmed) product tokens and keep those occurring at least 4 times in the training dataset (recall that these datasets are ≈ 700 posts).