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.

Input: Consider Input: Near Clare Hall area, price range 23, Bibimbap House, McDonalds.

Output: name[Bibimbap House], food[Fast food], priceRange[£20-25], area[riverside], near[Clare Hall]


Input: Consider 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.

Output: name[Browns Cambridge], eatType[coffee shop], food[Japanese], customer rating[1 out of 5], area[riverside], familyFriendly[yes], near[Crowne Plaza Hotel]


Input: Consider Input: Browns Cambridge is a hamburger joint that has an average rating of 3 out of 5 stars and is low priced.


Output: name[Browns Cambridge], food[Fast food], priceRange[less than £20], customer rating[average]