In this task, we ask you to parse restaurant descriptions into a structured data table of key-value pairs. Here are the attributes (keys) and their examples values. You should preserve this order when creating the answer: 
 name: The Eagle,... 
 eatType: restaurant, coffee shop,... 
 food: French, Italian,... 
 priceRange: cheap, expensive,... 
 customerRating: 1 of 5 (low), 4 of 5 (high) 
 area: riverside, city center, ... 
 familyFriendly: Yes / No 
 near: Panda Express,...
 The output table may contain all or only some of the attributes but must not contain unlisted attributes. For the output to be considered correct, it also must parse all of the attributes existant in the input sentence; in other words, incomplete parsing would be considered incorrect.

Input: Consider Input: If you want Japanese food, The Cambridge Blue  is fair but has a low customer rating.

Output: name[The Cambridge Blue], eatType[restaurant], food[Japanese], customer rating[low]


Input: Consider Input: Browns Cambridge, the coffee shop, can be found near Crowne Plaza Hotel, in City Centre, but it is not family-friendly and has low ratings.

Output: name[Browns Cambridge], eatType[coffee shop], food[Italian], customer rating[low], area[city centre], familyFriendly[no], near[Crowne Plaza Hotel]


Input: Consider Input: The Golden Palace is an expensive restaurant that has an average customer rating that is a coffee shop in City center that services Italian food.


Output: name[The Golden Palace], eatType[coffee shop], food[Italian], priceRange[high], customer rating[average], area[city centre]