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[Clowns], eatType[coffee shop], food[French], customer rating[5 out of 5], area[riverside], near[Clare Hall]
Output: 


Output: There is a five star rated French coffee shop in the riverside area near Clare Hall named Clowns.
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[Aromi], eatType[coffee shop], food[French], customer rating[high], area[riverside], familyFriendly[yes]
Output: 


Output: Aromi, stunning coffee shop thats kid friendly.. Yes,  high customer rating.. Yes,  beautiful view.. Riverside and the very best French 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[Midsummer House], food[Italian], priceRange[high], customer rating[average], near[All Bar One]
Output: 


Output: Midsummer House is located near the All Bar One and is in the high 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[Wildwood], eatType[pub], food[Chinese], priceRange[less than £20], customer rating[low]
Output: 


Output: Wildwood is a Chinese pub that is inexpensive that 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[Browns Cambridge], eatType[coffee shop], food[Fast food], customer rating[5 out of 5], area[riverside], familyFriendly[yes], near[Crowne Plaza Hotel]
Output: 


Output: Browns Cambridge in the riverside area near the Crowne Plaza Hotel is a top notch place for a quick bit in a family friendly coffee shop style atmosphere.
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 Twenty Two], priceRange[moderate], customer rating[1 out of 5], area[riverside], familyFriendly[yes], near[The Rice Boat]
Output: 


Output: On the riverside near The Rice Boat is another location called The Twenty Two.  It's kid friendly, falls in the moderate price range, and has a customer rating of 1 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[Alimentum], food[English], priceRange[£20-25], customer rating[high], area[riverside], near[Yippee Noodle Bar]
Output: 


Output: Alimentum serves English food in the price range of £20-£25. It is near the Yippee Noodle Bar in riverside and has a high 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 Mill], eatType[pub], food[Indian], priceRange[moderate], area[riverside]
Output: 


Output: A moderately price Indian pub in riverside is called The Mill.
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[Chinese], priceRange[cheap], customer rating[average], area[city centre], familyFriendly[no]
Output: 


Output: Looking for cheap Chinese food, The Waterman is located near city centre.  The establishment 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[Travellers Rest Beefeater], priceRange[cheap], customer rating[5 out of 5], area[riverside], near[Café Adriatic]
Output: 


Output: Near the Café Adriatic, in the riverside area, there is a cheap restaurant called the Travellers Rest Beefeater 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[coffee shop], food[Italian], priceRange[moderate], customer rating[1 out of 5], near[Ranch]
Output: 


Output: Wildwood is a Italian coffee shop near Ranch the price ranges are moderate and the customer rating is a 1 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[Cocum], eatType[pub], priceRange[moderate], customer rating[3 out of 5], familyFriendly[yes]
Output: 


Output: Cocum is a kids friendly pub with a moderate price range. Customer rating is 3 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[Fitzbillies], eatType[coffee shop], food[Italian], priceRange[high], customer rating[average], area[riverside], familyFriendly[no]
Output: 


Output: For those with a larger budget, Fitzbillies is an Italian style coffee shop located 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[Cocum], eatType[coffee shop], food[Japanese], priceRange[less than £20], customer rating[low], familyFriendly[yes]
Output: 


Output: Serving Japanese food is Cocum coffee shop. Though with a low customer rating, Cocum is family friendly and the price range is under £20.
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], eatType[restaurant], food[French], priceRange[moderate], familyFriendly[no]
Output: 


Output: A French restaurant named Loch Fyne have a moderate price range, but is not welcoming towards kids