frett/Text2DistBench huggingface dataset:
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Project Hail Mary
    - Release Date: 2026-03-20
    - Cast: Ryan Gosling, James Ortiz, Sandra Hüller, Lionel Boyce, Milana Vayntrub
    - Summary: S c i e n c e   t e a c h e r   R y l a n d   G r a c e   w a k e s   u p   o n   a   s p a c e s h i p   l i g h t   y e a r s   f r o m   h o m e   w i t h   n o   r e c o l l e c t i o n   o f   w h o   h e   i s   o r   h o w   h e   g o t   t h e r e .   A s   h i s   m e m o r y   r e t u r n s ,   h e   b e g i n s   t o   u n c o v e r   h i s   m i s s i o n :   s o l v e   t h e   r i d d l e   o f   t h e   m y s t e r i o u s   s u b s t a n c e   c a u s i n g   t h e   s u n   t o   d i e   o u t .   H e   m u s t   c a l l   o n   h i s   s c i e n t i f i c   k n o w l e d g e   a n d   u n o r t h o d o x   i d e a s   t o   s a v e   e v e r y t h i n g   o n   E a r t h   f r o m   e x t i n c t i o n …   b u t   a n   u n e x p e c t e d   f r i e n d s h i p   m e a n s   h e   m a y   n o t   h a v e   t o   d o   i t   a l o n e .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 32
positive: 68
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: undertone
    - Release Date: 2026-03-13
    - Cast: Nina Kiri, Adam DiMarco, Michèle Duquet, Keana Bastidas, Jeff Yung
    - Summary: T h e   h o s t   o f   a   p o p u l a r   p a r a n o r m a l   p o d c a s t   b e c o m e s   h a u n t e d   b y   t e r r i f y i n g   r e c o r d i n g s   m y s t e r i o u s l y   s e n t   h e r   w a y .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 84
positive: 16
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Hoppers
    - Release Date: 2026-03-06
    - Cast: Piper Curda, Bobby Moynihan, Jon Hamm, Kathy Najimy, Dave Franco
    - Summary: S c i e n t i s t s   h a v e   d i s c o v e r e d   h o w   t o   ' h o p '   h u m a n   c o n s c i o u s n e s s   i n t o   l i f e l i k e   r o b o t i c   a n i m a l s ,   a l l o w i n g   p e o p l e   t o   c o m m u n i c a t e   w i t h   a n i m a l s   a s   a n i m a l s .   A n i m a l   l o v e r   M a b e l   s e i z e s   a n   o p p o r t u n i t y   t o   u s e   t h e   t e c h n o l o g y ,   u n c o v e r i n g   m y s t e r i e s   w i t h i n   t h e   a n i m a l   w o r l d   b e y o n d   a n y t h i n g   s h e   c o u l d   h a v e   i m a g i n e d .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 60.46511627906976
positive: 39.53488372093023
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Dhurandhar_ The Revenge
    - Release Date: 2026-03-18
    - Cast: Ranveer Singh, Arjun Rampal, R. Madhavan, Sanjay Dutt, Sara Arjun
    - Summary: A s   r i v a l   g a n g s ,   c o r r u p t   o f f i c i a l s   a n d   a   r u t h l e s s   M a j o r   I q b a l   c l o s e   i n ,   H a m z a ' s   m i s s i o n   f o r   h i s   c o u n t r y   s p i r a l s   i n t o   a   b l o o d y   p e r s o n a l   w a r   w h e r e   t h e   l i n e   b e t w e e n   p a t r i o t   a n d   m o n s t e r   d i s a p p e a r s   i n   t h e   s t r e e t s   o f   L y a r i .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 62.903225806451616
positive: 37.096774193548384
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Forbidden Fruits
    - Release Date: 2026-03-27
    - Cast: Lili Reinhart, Lola Tung, Victoria Pedretti, Alexandra Shipp, Emma Chamberlain
    - Summary: F r e e   E d e n   e m p l o y e e   A p p l e   s e c r e t l y   r u n s   a   w i t c h y   f e m m e   c u l t   i n   t h e   b a s e m e n t   o f   t h e   m a l l   s t o r e   a f t e r   h o u r s   –   w i t h   f e l l o w   f r u i t s   C h e r r y   a n d   F i g .   B u t ,   w h e n   n e w   h i r e   P u m p k i n   c h a l l e n g e s   t h e i r   p e r f o r m a t i v e   s i s t e r h o o d ,   t h e   w o m e n   a r e   f o r c e d   t o   f a c e   t h e i r   o w n   p o i s o n s   o r   s u c c u m b   t o   a   b l o o d y   f a t e .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 24
positive: 76
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Good Luck_ Have Fun_ Don_t Die
    - Release Date: 2026-02-13
    - Cast: Sam Rockwell, Juno Temple, Haley Lu Richardson, Michael Peña, Zazie Beetz
    - Summary: A   ' M a n   f r o m   t h e   F u t u r e '   a r r i v e s   a t   a n   L A   d i n e r   w h e r e   h e   m u s t   r e c r u i t   t h e   p r e c i s e   c o m b i n a t i o n   o f   d i s g r u n t l e d   p a t r o n s   t o   j o i n   h i m   o n   a   o n e - n i g h t   q u e s t   t o   s a v e   t h e   w o r l d   f r o m   t h e   t e r m i n a l   t h r e a t   o f   a   r o g u e   a r t i f i c i a l   i n t e l l i g e n c e .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 62
positive: 38
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: EPiC_ Elvis Presley in Concert
    - Release Date: 2026-02-27
    - Cast: Elvis Presley, James Burton, John Wilkinson, Charlie Hodge, Jerry Scheff
    - Summary: L o n g - l o s t   f o o t a g e   f r o m   E l v i s   P r e s l e y ' s   l e g e n d a r y   L a s   V e g a s   r e s i d e n c y   i n   t h e   1 9 7 0 s   w o v e n   t o g e t h e r   w i t h   r a r e   1 6 m m   f o o t a g e   f r o m   E l v i s   o n   T o u r ,   a n d   8 m m   f r o m   t h e   G r a c e l a n d   a r c h i v e ,   p l u s   r e c o r d i n g s   o f   E l v i s   t e l l i n g   " h i s   s i d e   o f   t h e   s t o r y "   r e d i s c o v e r e d   d u r i n g   B a z   L u h r m a n n ' s   r e s e a r c h   f o r   h i s   2 0 2 2   f i l m ,   E l v i s .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 20.253164556962027
positive: 79.74683544303798
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Crime 101
    - Release Date: 2026-02-13
    - Cast: Chris Hemsworth, Mark Ruffalo, Halle Berry, Barry Keoghan, Monica Barbaro
    - Summary: W h e n   a n   e l u s i v e   t h i e f   w h o s e   h i g h - s t a k e s   h e i s t s   u n f o l d   a l o n g   t h e   i c o n i c   1 0 1   f r e e w a y   i n   L o s   A n g e l e s   e y e s   t h e   s c o r e   o f   a   l i f e t i m e ,   w i t h   h o p e s   o f   t h i s   b e i n g   h i s   f i n a l   j o b ,   h i s   p a t h   c o l l i d e s   w i t h   a   d i s i l l u s i o n e d   i n s u r a n c e   b r o k e r   w h o   i s   f a c i n g   h e r   o w n   c r o s s r o a d s .   D e t e r m i n e d   t o   c r a c k   t h e   c a s e ,   a   r e l e n t l e s s   d e t e c t i v e   c l o s e s   i n   o n   t h e   o p e r a t i o n ,   r a i s i n g   t h e   s t a k e s   e v e n   h i g h e r .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 34
positive: 66
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: They Will Kill You
    - Release Date: 2026-03-27
    - Cast: Zazie Beetz, Patricia Arquette, Myha'la, Paterson Joseph, Tom Felton
    - Summary: A   w o m a n   a n s w e r s   a   h e l p   w a n t e d   a d   t o   b e   a   h o u s e k e e p e r   i n   a   m y s t e r i o u s   N e w   Y o r k   C i t y   h i g h - r i s e ,   u n a w a r e   t h a t   s h e   i s   e n t e r i n g   a   c o m m u n i t y   t h a t   h a s   s e e n   a   n u m b e r   o f   d i s a p p e a r a n c e s   o v e r   t h e   y e a r s   a n d   m a y   b e   u n d e r   t h e   g r i p   o f   a   S a t a n i c   c u l t .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 53.84615384615385
positive: 46.15384615384615
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Border 2
    - Release Date: 2026-01-23
    - Cast: Sunny Deol, Varun Dhawan, Diljit Dosanjh, Ahan Shetty, Mona Singh
    - Summary: T h r e e   i d e a l i s t i c   s o l d i e r s   i n   t h e   I n d i a n   a r m y ,   n a v y   a n d   a i r   f o r c e   f a c e   g r u e l i n g   c o m b a t   c o n d i t i o n s   i n   t h i s   f i l m   s e t   d u r i n g   t h e   1 9 7 1   I n d o - P a k   w a r .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 55.00000000000001
positive: 45
You will be given information about a movie.

    Based on this information, consider how viewers are likely to react to the movie and what aspects they are likely to talk about.

    When thinking about viewer opinions, keep in mind two dimensions:
    - Stance: whether viewers are likely to express a positive or negative attitude.
    - Topic: which aspect of the movie viewers are likely to focus on.

    Stance categories:
    - positive: expressing approval, enjoyment, or praise.
    - negative: expressing criticism, dissatisfaction, or disappointment.

    Topic categories:
    - Actor: acting performance, casting, chemistry, emotional expression.
    - Storyline: plot, narrative, pacing, themes, dialogue, character development.
    - Visual: cinematography, animation, lighting, color, visual effects, production design.
    - Audio: soundtrack, music, sound effects, or audio quality.

    Read the movie information carefully.
    Then answer the question based on this information.

    Movie Information:
    
    - Movie Title: Ready or Not_ Here I Come
    - Release Date: 2026-03-20
    - Cast: Samara Weaving, Kathryn Newton, Elijah Wood, Sarah Michelle Gellar, Shawn Hatosy
    - Summary: M o m e n t s   a f t e r   s u r v i v i n g   a n   a l l - o u t   a t t a c k   f r o m   t h e   L e   D o m a s   f a m i l y ,   G r a c e   d i s c o v e r s   s h e ’ s   r e a c h e d   t h e   n e x t   l e v e l   o f   t h e   n i g h t m a r i s h   g a m e   —   a n d   t h i s   t i m e   w i t h   h e r   e s t r a n g e d   s i s t e r   F a i t h   a t   h e r   s i d e .   G r a c e   h a s   o n e   c h a n c e   t o   s u r v i v e ,   k e e p   h e r   s i s t e r   a l i v e ,   a n d   c l a i m   t h e   H i g h   S e a t   o f   t h e   C o u n c i l   t h a t   c o n t r o l s   t h e   w o r l d .   F o u r   r i v a l   f a m i l i e s   a r e   h u n t i n g   h e r   f o r   t h e   t h r o n e ,   a n d   w h o e v e r   w i n s   r u l e s   i t   a l l .
    - Synopsis:

Question:
Read the movie information.
How are viewers likely to feel overall about the movie?
Predict how common each attitude is expected to be.
Ensure the percentages sum to 100 and use integers only.

Output your prediction in the following JSON format:
{{
    "percentages": {{
        "positive": "<int>%",
        "negative": "<int>%"
    }}
}}

Answer:


Answer: negative: 41
positive: 59