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: With the price range running more than £30, it's surprising that Alimentum is a children friendly site that offers Chinese food in the riverside area.
Example Output: name[Alimentum], food[Chinese], priceRange[more than £30], area[riverside], familyFriendly[yes]

Example Input: Zizzi is an expensive, non-child friendly coffee shop in the city centre with a price range exceeding £30 and has a low customer rating.
Example Output: name[Zizzi], eatType[coffee shop], priceRange[more than £30], customer rating[low], area[city centre], familyFriendly[no]

Example Input: The Dumpling Tree is a restaurant serving Indian food with prices less than £20
Example Output:
name[The Dumpling Tree], eatType[restaurant], food[Indian], priceRange[less than £20]