TASK DEFINITION: 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.
PROBLEM: Near Crowne Plaza Hotel, in the centre of the city is Browns Cambridge. It is a French coffee shop that is rated average and not family-friendly.

SOLUTION: name[Browns Cambridge], eatType[coffee shop], food[French], customer rating[average], area[city centre], familyFriendly[no], near[Crowne Plaza Hotel]

PROBLEM: The Punter, is restaurant more than £30

SOLUTION: name[The Punter], food[Italian], priceRange[more than £30]

PROBLEM: Fitzbillies is an average rated low cost French coffee shop located in the city centre.

SOLUTION:
name[Fitzbillies], eatType[coffee shop], food[French], priceRange[less than £20], customer rating[average], area[city centre], familyFriendly[no]

