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: Near the Burger King in the city centre is an Italian coffee shop called The Eagle. It is not child friendly, has an average customer rating and is in the high price range.
Example Output: name[The Eagle], eatType[coffee shop], food[Italian], priceRange[high], customer rating[average], area[city centre], familyFriendly[no], near[Burger King]

Example Input: A coffee shop that has a rating of 1 out of 5 is called The Golden Palace. They have French food for moderate prices. They recently moved to city centre.
Example Output: name[The Golden Palace], eatType[coffee shop], food[French], priceRange[moderate], customer rating[1 out of 5], area[city centre]

Example Input: Browns Cambridge is a coffee shop located near Crowne Plaza Hotel in the city centre. It serves Fast food and is not family-friendly, but has 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[no], near[Crowne Plaza Hotel]