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.

Ex 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.

Ex Output:
name[The Punter], eatType[coffee shop], food[Indian], priceRange[moderate], customer rating[1 out of 5], familyFriendly[yes], near[Café Sicilia]


Ex Input:
The Olive Grove is a pub selling good sushi at low prices , but not familiar. It is north of the City Centre.

Ex Output:
name[The Olive Grove], eatType[pub], food[Japanese], priceRange[less than £20], area[riverside], familyFriendly[no]


Ex Input:
The Phoenix has high priced Indian food with a one out of five star rating in the riverside area.

Ex Output:

name[The Phoenix], food[Indian], priceRange[high], customer rating[1 out of 5], area[riverside]