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 Cambridge Blue is a pub that is low priced that offers wine, cheese, and grapes, and is located next to Café Brazil.
Example Output: name[The Cambridge Blue], eatType[pub], food[French], priceRange[less than £20], near[Café Brazil]

Example Input: In riverside is a coffee shop with high price range and a rating of 3 out of 5, it is near Avalon and yes is also child friendly. It is called Blue Spice.
Example Output: name[Blue Spice], eatType[coffee shop], priceRange[high], customer rating[3 out of 5], area[riverside], familyFriendly[yes], near[Avalon]

Example Input: Cotto, an Indian restaurant, has a high customer rating. This is because it is kid friendly and located near the Ranch.
Example Output:
name[Cotto], food[Indian], customer rating[high], familyFriendly[yes], near[Ranch]