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[The Golden Curry], food[English], customer rating[low], area[city centre], familyFriendly[yes], near[Café Rouge]
Output: 


Output: The Golden Curry serves English food and is family-friendly, and conveniently located in the center of town near the Café Rouge, but it has a low customer rating.
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[Midsummer House], food[Indian], customer rating[low], near[Café Rouge]
Output: 


Output: Located near Café Rouge Midsummer House is an Indian restaurant with a poor customer rating.
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[Blue Spice], food[Italian], priceRange[moderate], area[riverside]
Output: 


Output: Blue Spice is an Italian restaurant that is moderately priced in the riverside area.
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[Loch Fyne], food[French], customer rating[average], area[riverside], near[The Rice Boat]
Output: 


Output: The Loch Fyne in the riverside area near The Rice Boat serves French food and has an average customer rating.
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[Fitzbillies], food[French], priceRange[cheap], near[The Six Bells]
Output: 


Output: There is a cheap French establishment called Fitzbillies located by The Six Bells.
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[Blue Spice], food[Fast food], priceRange[high], area[riverside]
Output: 


Output: Blue Spice is an expensive fast food establishment on the 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[The Punter], food[Italian], priceRange[£20-25]
Output: 


Output: price Range is £20-25, name The Punter, food is Italian
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[English], near[Café Rouge]
Output: 


Output: Next to Café Rouge is a British restaurant called Cotto.
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 Wrestlers], food[French], priceRange[moderate], customer rating[1 out of 5], familyFriendly[yes]
Output: 


Output: The Wrestlers, has great food and drinks at low prices, everyday.
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 Punter], food[Japanese], priceRange[high]
Output: 


Output: The Punter sells Japanese food and is high in price range
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 Eagle], eatType[coffee shop], food[Italian], priceRange[moderate], customer rating[3 out of 5], area[riverside], familyFriendly[yes], near[Burger King]
Output: 


Output: There is a kid friendly river side Italian coffee shop near Burger King named The Eagle with a 3 out of 5 rating and a moderate price rating.
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[Blue Spice], priceRange[less than £20], customer rating[low], area[riverside], familyFriendly[no]
Output: 


Output: Near the river, there is an inexpensive adult restaurant called Blue Spice.
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 Rice Boat], food[Chinese], priceRange[high], customer rating[average], area[city centre], familyFriendly[yes], near[Express by Holiday Inn]
Output: 


Output: The Rice Boat Chinese restaurant is near Express by Holiday Inn in the city centre.  It is children friendly with a high price range.  It has an average customer rating.
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 Phoenix], food[Fast food], customer rating[low], area[city centre]
Output: 


Output: The Phoenix is a fast food restaurant in Luton offering budget food.
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[Cocum], eatType[coffee shop], food[Fast food], priceRange[less than £20], customer rating[low], familyFriendly[yes]
Output: 


Output: Cocum coffee shop has a low customer rating. It is low cost and family friendly.