Lots-of-LoRAs/task957_e2e_nlg_text_generation_generate huggingface dataset:
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[Zizzi], eatType[pub], food[English], customer rating[5 out of 5], familyFriendly[yes]
Output: 


Output: Zizzi is an English food pub with a 5 out of 5 customer rating and is family friendly
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[Green Man], food[Japanese], priceRange[moderate], area[riverside], familyFriendly[yes], near[All Bar One]
Output: 


Output: Green Man is a kids friendly Japanese restaurant in the moderate price range. It is located near All Bar One in riverside.
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[Cotto], food[Italian], customer rating[5 out of 5], familyFriendly[yes], near[Ranch]
Output: 


Output: Cotto is a family friendly Italian restaurant located near the Ranch. It has a customer rating of 5 out of 5.
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[Wildwood], eatType[pub], food[Fast food], priceRange[more than £30], customer rating[high]
Output: 


Output: I love the food at Wildwood pub. They have the best burgers.
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[The Golden Curry], food[Indian], customer rating[5 out of 5], familyFriendly[no]
Output: 


Output: There is a restaurant called The Golden Curry which provides Indian food, it has a 5 out of 5 rating but is not family friendly.
Definition: In this task, we ask you convert a data table of restaurant descriptions into fluent natural-sounding English sentences. The input is a string of key-value pairs; the output should be a natural and grammatical English sentence containing all the information from the input.

Positive Example 1 -
Input: name[Aromi], eatType[restaurant], food[English], area[city centre]
Output: Aromi is an English restaurant in the city centre.

Positive Example 2 -
Input: name[The Rice Boat], food[Indian], priceRange[cheap], customer rating[5 out of 5], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: The Rice Boat is a cheap Indian restaurant in the center of the city near Express by Holiday Inn. It is family friendly and has the highest customer rating.

Negative Example 1 -
Input: name[Blue Spice], eatType[coffee shop], priceRange[more than £30], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Avalon]
Output: Blue Spice is a Colombian coffee shop located by the riverside, near Avalon in Boston. Its prices are over £30. Its customer ratings are 5 out of 5.

Negative Example 2 -
Input: name[The Mill], eatType[restaurant], area[riverside], near[The Rice Boat]
Output: A restaurant The Mill, can find near the riverside next to The Rice Boat.

Now complete the following example -
Input: name[The Waterman], food[Fast food], priceRange[moderate], customer rating[1 out of 5], area[city centre], familyFriendly[yes]
Output: 


Output: There is a kids friendly restaurant located in city centre called The Waterman.