As an example text, I turned to our old friend The Adventures of Sherlock Holmes and plugged in the first story, "A Scandal in Bohemia." A (very very small) section of my output looked like this:
0000002 080 To 00 PRP 0000002 090 Sherlock 00 NP0 0000002 100 Holmes 00 NP0 0000002 110 she 00 PNP 0000002 120 is 00 VBZ 0000002 130 always 00 AV0 0000002 140 THE 00 AT0 0000002 150 woman 00 NN1
Here is the first sentence of "Scandal," word by word, tagged by part of speech according to this tagset. So: preposition, proper noun, proper noun, personal pronoun, -s form of the verb "be", adverb, article, singular noun. This, of course, extends all the way through the end of the story.
So, what use might one find from this sort of POS-tagging? One example is that once you've tagged all your words it becomes much easier to pull them apart from one another and look at them as groups -- one could imagine, for example, a line of inquiry along the lines of how active vs. passive the verbs in a text are, or how many proper nouns are in a text as a measure of its specifity of place and person.