Name errors have a similar character to OOV erors in that they often have anomalous word sequences in the region of the OOV word (examples 1 and 2), which is why the OOV posterior is so useful.
too much reliance on the OOV posterior leads to wrongly detecting general OOV errors as name errors ('lizards' and 'zombies' in example 2) and missed detection of name errors where the confusion network cues indicate a plausible hypothesis ('omaha' in example 3).