This approach seems to create many nonsensical suggestions. In this example, I was searching {hotels in new york city close} and the top suggestions are "hotels in new york city close to London", which is clearly a no sense. It seems to me that they are using some kind of frequent itemset algorithm and they notice that I have many friends in London, hence the synthetically generated nonsensical suggestion. As you see, Bing suggestions are not suffering this problem and correct locations are shown.
Another example: I am an Italian guy and for me Milan is in Italy (btw, this Milan is way more popular on the Web that the one in Tennessee). Plus, none of those Milan cities are near to London. Web suggestions are nailing the correct location "il duomo" is central area in Milan, Italy.
Here there is another example of nonsensical suggestion. I assume that there are no Google employees who work for Microsoft at the same time. However, both the companies are quite popular in my social network hence the synthetic suggestion.
Now, let's consider another class of defects. There are queries which are not directly answered and the proposed suggestions are quite unrelated. In this example, I was searching for {actors who won the oscar} and Facebook graph search suggestions are clearly unrelated since I am not interested in "actors who like Oscar wilde"
Here there is another example of unrelated suggestion. I am searching {visit the taja} and this is not related to "People named 'taja' who work at Visit Holland". In this case the semantic of the query is quite not understood.
If you try to replicate my examples, please note that you could get a different set of suggestions because those are generated by using your personal friend graph. However, it would be easy to generate similar situations once you understand the pattern.
See also my past postings: