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: there is a cheap French coffee shop named Cotto that has 5 out of 5 customer rating near The Portland Arms in the riverside area
Example Output: name[Cotto], eatType[coffee shop], food[French], priceRange[cheap], customer rating[5 out of 5], area[riverside], near[The Portland Arms]

Example Input: There is a coffee shop in the riverside area named Zizzi.  It is not child-friendly, has a low customer rating, and possesses a price range of around £30.
Example Output: name[Zizzi], eatType[coffee shop], priceRange[more than £30], customer rating[low], area[riverside], familyFriendly[no]

Example Input: A moderately priced Chinese restaurant  near All Bar One called Midsummer House with an average rating.
Example Output:
name[Midsummer House], food[Chinese], priceRange[moderate], customer rating[3 out of 5], near[All Bar One]