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: The Punter is a child friendly coffee shop located near Café Sicilia. It has a high customer rating, and serves English food costing over 30 euro.
Example Output: name[The Punter], eatType[coffee shop], food[English], priceRange[more than £30], customer rating[high], familyFriendly[yes], near[Café Sicilia]

Example Input: The 5 out of 5 rated The Cricketers coffee shop is located near The Portland Arms. This shop serves French food in a child friendly atmosphere.
Example Output: name[The Cricketers], eatType[coffee shop], food[French], customer rating[5 out of 5], familyFriendly[yes], near[The Portland Arms]

Example Input: Browns Cambridge is a coffee shop that is family-friendly they serve fast food that is in City center that is near Crowne Plaza Hotel that has a low customer rating.
Example Output:
name[Browns Cambridge], eatType[coffee shop], food[Fast food], customer rating[low], area[city centre], familyFriendly[yes], near[Crowne Plaza Hotel]