In this task, you are given books product reviews in English language. The goal is to classify the review as "POS" if the overall sentiment of the review is positive or as "NEG" if the overall sentiment of the review is negative.
Example: Hopeful for those who seek harmony in the world . I wouldn't recommend this to anyone who thinks that religious wars, repression of individual spirits or rape of the earth are good things. Those who seek peace, harmony, celebration of each of us and respect for our earth will find this hopeful
Example solution: POS
Example explanation: The overall sentiment of the review is positive as the reviewer mentions positive expressions such as 'hopeful', 'will find this helpful' etc.. Hence, the label is 'POS'.

Problem: Not a good enough reference to be worth the money . This is a tremendously expensive reference that one should expect to be trustworthy. But it isn't. Nor is it as definitive as should be expected, though it does have some fascinating entries, such as the role of dogs in the history of food. For the price, there should be line drawings for some of the more unusual fruits and veg, because as it is, the verbal descriptions would lead a reader to think that something looked quite different than it does. So I use these two volumes with caution, referencing further anything said here before I take it as a given. Although some other reviewers here have criticized the dryness of style, that is what I want in this sort of thing, so I have no complaints there. Of far more importance is the slant that many of the articles have, which clearly have a political agenda that the information is wrapped around. So, while the bibliographies for same are useful, they also are selectively chosen. Given the guides to food now, and the many histories, I would think that a few books judiciously chosen are better value than this one reference, though if you are monied, this is an interesting addition to your library, to be read with a grain of salt in every 'Oh, my! I didn't know that.'
Solution: NEG