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 coffee shop providing Indian food in the moderate price range. It is near Café Sicilia. Its customer rating is 1 out of 5.
Example Output: name[The Punter], eatType[coffee shop], food[Indian], priceRange[moderate], customer rating[1 out of 5], familyFriendly[yes], near[Café Sicilia]

Example Input: There is an expensive pub near the Café Brazil called The Cambridge Blue that sell wines and spirits.
Example Output: name[The Cambridge Blue], eatType[pub], food[French], priceRange[more than £30], near[Café Brazil]

Example Input: In the city centre you'll find an Italian restaurant called The Phoenix which as a price range of £20-25 and a high customer rating.
Example Output:
name[The Phoenix], food[Italian], priceRange[£20-25], customer rating[high], area[city centre]