Training Amazon Rekognition Custom Labels model on adjusted manifest with corrections

I have a set of images with bounding-box labels created using Ground Truth. Some of the labels were adjusted using job-chaining as described here:

https://aws.amazon.com/blogs/machine-learning/chaining-amazon-sagemaker-ground-truth-jobs-to-label-progressively/

the output manifest from the chained job still has the original bounding-box information in it. How does this affect training if I use this manifest to train an Amazon Rekognition Custom Labels model? If the adjustment was correcting an error in the previous labeling job is it going to cause confusion in the training that the incorrect label information is still present?

Thanks.