How to improve Comprehend results when the model returns incorrect results?

What is the best way to improve the results I receive back from Comprehend when using Custom Entities?

I've trained the model, but the results are still falling short. I'm not sure if training the model with more annotation examples will improve my results. It would be great to be able to correct the model when it gets something wrong. What is the best way to accomplish my goal of improving the output over time?

For example, AWS returned the value of "select common flexbase" as one single "material" type. This should have been three separate "material" types (and was annotated hundreds, if not thousands, of times separately in the training annotations).

In another example from the same sample email, AWS returned the value of "Rowlett @ Bickers Drive & Westover Drive Export Trees Trash Concrete Asphalt Dirt Import Select Common Flexbase (Crushed Conc) Flexbase (Crushed Limestone)......." as one single "address" type. The address part was only "Rowlett @ Bickers Drive & Westover Drive" with the majority of the remainder being individual "material" types.

I have a lot of other examples, but it's a bit difficult explaining them without the benefit of attaching the source files and the AWS Comprehend output.