The default decision boundary for this tagging task is 0.5 posterior probability (more likely than not), and tagging performance at that threshold is good (around 97% accuracy, as mentioned previously).
since this is a pre-processing step, we may want to reduce possible cascading errors by allowing more words into the sets B and E. In other words, we may want more precision in our set exclusion constraints.