Text annotating process, quality vs quantity?
Both metods are against the nature of machine/statistical learning. Lack of data will not let you generalize well in any case. It will have different effect though. Generally speaking:


You will be able to classify more test samples, but sometimes will do
it wrong due to errors in data. 
You will have precise classification of some test samples, but will have no idea how to classify the rest of them.


So, it's up to your's classification score/quality estimation function which case is better for you.