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.

Example Input: Zizzi is an expensive, non-child friendly coffee shop in the city centre with a price range exceeding £30 and has a low customer rating.
Example Output: name[Zizzi], eatType[coffee shop], priceRange[more than £30], customer rating[low], area[city centre], familyFriendly[no]

Example Input: Browns Cambridge in the city centre near Crowne Plaza Hotel is a family-friendly, fast food and coffee shop with a customer rating of 5 out of 5.
Example Output: name[Browns Cambridge], eatType[coffee shop], food[Fast food], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Crowne Plaza Hotel]

Example Input: Cocum is a coffee shop that serves Italian food. They are kid friendly and their price range is high.
Example Output:
name[Cocum], eatType[coffee shop], food[Italian], priceRange[high], customer rating[average], familyFriendly[yes]