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 is a cheaper Japanese venue however its rating by customers is low.
Example Output: name[Browns Cambridge], food[Japanese], priceRange[less than £20], customer rating[low]

Example Input: In the riverside area near the Crown Plaza Hotel is Browns Cambridge. It is a kid friendly coffee shop, that has Japanese food, and it's rated 1-5.
Example Output: name[Browns Cambridge], eatType[coffee shop], food[Japanese], customer rating[1 out of 5], area[riverside], familyFriendly[yes], near[Crowne Plaza Hotel]

Example Input: The Midsummer House sells Indian food near All Bar One.  The customer rating is high and the price more than £30.
Example Output:
name[Midsummer House], food[Indian], priceRange[more than £30], customer rating[high], near[All Bar One]