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.

Q: 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.

A: name[Zizzi], eatType[coffee shop], priceRange[more than £30], customer rating[low], area[city centre], familyFriendly[no]
****
Q: A restaurant named The Golden Curry is located near The Bakers. It has Indian food and is not kid friendly with a moderate price range

A: name[The Golden Curry], food[Indian], priceRange[moderate], familyFriendly[no], near[The Bakers]
****
Q: The Punter, which is an Indian-serving coffee shop near Café Sicilia, has a price range of £20-25, is kid friendly and has a high customer rating.

A:
name[The Punter], eatType[coffee shop], food[Indian], priceRange[£20-25], customer rating[high], familyFriendly[yes], near[Café Sicilia]
****