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: Browns Cambridge serves low rated, high priced Indian food.
Example Output: name[Browns Cambridge], food[Indian], priceRange[high], customer rating[1 out of 5]

Example Input: Fitzbillies is a coffee shop that offers Fast Food with a moderate price and a customer rating 1 out of 5. It is located in the riverside and there is no kids area.
Example Output: name[Fitzbillies], eatType[coffee shop], food[Fast food], priceRange[moderate], customer rating[1 out of 5], area[riverside], familyFriendly[no]

Example Input: Café Rouge has a restaurant nearby with an average customer rating called Wildwood.
Example Output:
name[Wildwood], eatType[restaurant], customer rating[average], near[Café Rouge]