Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
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2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "🦓", "🐗", "🐒", "🐦"],
  "The Nightmare Before Christmas": ["👻", "🎃", "💀", "🎄", "🕯️"],
  "The Godfather": ["👨‍💼", "🔫", "💣", "💼", "💰"],
  "The Matrix": ["💊", "🕶️", "💻", "🤖", "🐇"],
  "Casablanca": ["✈️", "💔", "🍷", "🐪", "🌆"],
  "Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "💀", "✈️"],
  "V for Vendetta": ["🎭", "🎩", "⚔️", "💣", "✊"],
  "The Princess Bride": ["👸", "🏰", "⚔️", "🐀", "🎭"],
  "Back to the Future": ["🚗", "⏰", "🔬", "⚡️", "🎸"],
  "Dune": ["🏜️", "🐛", "⚔️", "🕶️", "🔮"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "🦓", "🐗", "🐒", "🐦"],
  "The Nightmare Before Christmas": ["👻", "🎃", "💀", "🎄", "🕯️"],
  "The Godfather": ["👨‍💼", "🔫", "💣", "💼", "💰"],
  "The Matrix": ["💊", "🕶️", "💻", "🤖", "🐇"],
  "Casablanca": ["✈️", "💔", "🍷", "🐪", "🌆"],
  "Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "💀", "✈️"],
  "V for Vendetta": ["🎭", "🎩", "⚔️", "💣", "✊"],
  "The Princess Bride": ["👸", "🏰", "⚔️", "🐀", "🎭"],
  "Back to the Future": ["🚗", "⏰", "🔬", "⚡️", "🎸"],
  "Dune": ["🏜️", "🐛", "⚔️", "🕶️", "🔮"]
}

PyFunc

Resulting in output: [['🦁', '🦓', '🐗', '🐒', '🐦'], ['👻', '🎃', '💀', '🎄', '🕯️'], ['🔫', '💣', '💼', '💰'], ['💊', '🕶️', '💻', '🤖', '🐇'], ['✈️', '💔', '🍷', '🐪', '🌆'], ['🗺️', '🔫', '🐍', '💀', '✈️'], ['🎭', '🎩', '⚔️', '💣', '✊'], ['👸', '🏰', '⚔️', '🐀', '🎭'], ['🚗', '⏰', '🔬', '⚡️', '🎸'], ['🏜️', '🐛', '⚔️', '🕶️', '🔮']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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['👻', '🎃', '💀', '🎄', '🕯️'],
['🔫', '💣', '💼', '💰'],
['💊', '🕶️', '💻', '🤖', '🐇'],
['✈️', '💔', '🍷', '🐪', '🌆'],
['🗺️', '🔫', '🐍', '💀', '✈️'],
['🎭', '🎩', '⚔️', '💣', '✊'],
['👸', '🏰', '⚔️', '🐀', '🎭'],
['🚗', '⏰', '🔬', '⚡️', '🎸'],
['🏜️', '🐛', '⚔️', '🕶️', '🔮']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Money Heist",
  "The Matrix",
  "Lost in Translation",
  "Snakes on a Plane",
  "Hamilton",
  "Hamlet",
  "Back to the Future",
  "Dune"
]

Extract Json

I extracted the following JSON from that output: 

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[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Money Heist",
  "The Matrix",
  "Lost in Translation",
  "Snakes on a Plane",
  "Hamilton",
  "Hamlet",
  "Back to the Future",
  "Dune"
]

PyFunc

OK Resulting in output: False

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
"The Lion King": ["🦁", "🦓", "🐘", "🦒", "🎶"],
"The Nightmare Before Christmas": ["🎃", "💀", "👻", "🎄", "🕷️"],
"The Godfather": ["🔫", "💰", "🤵‍♂️", "🩸", "🚬"],
"The Matrix": ["🤖", "🕶️", "💻", "💊", "🏃‍♂️"],
"Casablanca": ["✈️", "🥃", "🚬", "🕵️‍♂️", "💔"],
"Raiders of the Lost Ark": ["🔫", "🗺️", "🐍", "💀", "✈️"],
"V for Vendetta": ["🎭", "🎩", "💣", "✊", "🌹"],
"The Princess Bride": ["⚔️", "👸", "🧙‍♂️", "🏰", "❤️"],
"Back to the Future": ["🚗", "🕒", "🎸", "⚡️", "🚀"],
"Dune": ["🪱", "🏜️", "🚀", "🪐", "⚔️"]
}

Extract Json

I extracted the following JSON from that output: 

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{
"The Lion King": ["🦁", "🦓", "🐘", "🦒", "🎶"],
"The Nightmare Before Christmas": ["🎃", "💀", "👻", "🎄", "🕷️"],
"The Godfather": ["🔫", "💰", "🤵‍♂️", "🩸", "🚬"],
"The Matrix": ["🤖", "🕶️", "💻", "💊", "🏃‍♂️"],
"Casablanca": ["✈️", "🥃", "🚬", "🕵️‍♂️", "💔"],
"Raiders of the Lost Ark": ["🔫", "🗺️", "🐍", "💀", "✈️"],
"V for Vendetta": ["🎭", "🎩", "💣", "✊", "🌹"],
"The Princess Bride": ["⚔️", "👸", "🧙‍♂️", "🏰", "❤️"],
"Back to the Future": ["🚗", "🕒", "🎸", "⚡️", "🚀"],
"Dune": ["🪱", "🏜️", "🚀", "🪐", "⚔️"]
}

PyFunc

Resulting in output: [['🦁', '🦓', '🐘', '🦒', '🎶'], ['🎃', '💀', '👻', '🎄', '🕷️'], ['🔫', '💰', '🩸', '🚬'], ['🤖', '🕶️', '💻', '💊'], ['✈️', '🥃', '🚬', '💔'], ['🔫', '🗺️', '🐍', '💀', '✈️'], ['🎭', '🎩', '💣', '✊', '🌹'], ['⚔️', '👸', '🏰', '❤️'], ['🚗', '🕒', '🎸', '⚡️', '🚀'], ['🪱', '🏜️', '🚀', '🪐', '⚔️']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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['🎃', '💀', '👻', '🎄', '🕷️'],
['🔫', '💰', '🩸', '🚬'],
['🤖', '🕶️', '💻', '💊'],
['✈️', '🥃', '🚬', '💔'],
['🔫', '🗺️', '🐍', '💀', '✈️'],
['🎭', '🎩', '💣', '✊', '🌹'],
['⚔️', '👸', '🏰', '❤️'],
['🚗', '🕒', '🎸', '⚡️', '🚀'],
['🪱', '🏜️', '🚀', '🪐', '⚔️']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "Halloweentown",
  "Scarface",
  "The Matrix",
  "Casablanca",
  "Red Eye",
  "V for Vendetta",
  "The Princess Bride",
  "Back to the Future",
  "Dune"
]

Extract Json

I extracted the following JSON from that output: 

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[
  "The Lion King",
  "Halloweentown",
  "Scarface",
  "The Matrix",
  "Casablanca",
  "Red Eye",
  "V for Vendetta",
  "The Princess Bride",
  "Back to the Future",
  "Dune"
]

PyFunc

OK Resulting in output: False

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
"The Lion King": ["🦁", "🦓", "🐘", "🦒", "🌳"],
"The Nightmare Before Christmas": ["💀", "🎃", "👻", "🦇", "🎄"],
"The Godfather": ["🔫", "💰", "🩸", "🚬", "🕴️"],
"The Matrix": ["💾", "💻", "💊", "🕶️", "🤖"],
"Casablanca": ["✈️", "🌃", "🎩", "🥃", "🚬"],
"Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "✈️", "🕌"],
"V for Vendetta": ["🎭", "🎩", "💣", "✊", "💂"],
"The Princess Bride": ["👸", "⚔️", "🧙", "🐎", "🏰"],
"Back to the Future": ["🚗", "🕒", "⚡️", "🏫", "🎸"],
"Dune": ["🏜️", "🪱", "🛡️", "🔮", "🦅"]
}

Extract Json

I extracted the following JSON from that output: 

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{
"The Lion King": ["🦁", "🦓", "🐘", "🦒", "🌳"],
"The Nightmare Before Christmas": ["💀", "🎃", "👻", "🦇", "🎄"],
"The Godfather": ["🔫", "💰", "🩸", "🚬", "🕴️"],
"The Matrix": ["💾", "💻", "💊", "🕶️", "🤖"],
"Casablanca": ["✈️", "🌃", "🎩", "🥃", "🚬"],
"Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "✈️", "🕌"],
"V for Vendetta": ["🎭", "🎩", "💣", "✊", "💂"],
"The Princess Bride": ["👸", "⚔️", "🧙", "🐎", "🏰"],
"Back to the Future": ["🚗", "🕒", "⚡️", "🏫", "🎸"],
"Dune": ["🏜️", "🪱", "🛡️", "🔮", "🦅"]
}

PyFunc

Resulting in output: [['🦁', '🦓', '🐘', '🦒', '🌳'], ['💀', '🎃', '👻', '🦇', '🎄'], ['🔫', '💰', '🩸', '🚬', '🕴️'], ['💾', '💻', '💊', '🕶️', '🤖'], ['✈️', '🌃', '🎩', '🥃', '🚬'], ['🗺️', '🔫', '🐍', '✈️', '🕌'], ['🎭', '🎩', '💣', '✊', '💂'], ['👸', '⚔️', '🧙', '🐎', '🏰'], ['🚗', '🕒', '⚡️', '🏫', '🎸'], ['🏜️', '🪱', '🛡️', '🔮', '🦅']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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2
3
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5
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9
['💀', '🎃', '👻', '🦇', '🎄'],
['🔫', '💰', '🩸', '🚬', '🕴️'],
['💾', '💻', '💊', '🕶️', '🤖'],
['✈️', '🌃', '🎩', '🥃', '🚬'],
['🗺️', '🔫', '🐍', '✈️', '🕌'],
['🎭', '🎩', '💣', '✊', '💂'],
['👸', '⚔️', '🧙', '🐎', '🏰'],
['🚗', '🕒', '⚡️', '🏫', '🎸'],
['🏜️', '🪱', '🛡️', '🔮', '🦅']]
What are the names of the movie titles?

Output

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["The Lion King", "Halloween", "Scarface", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "King Arthur", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King", "Halloween", "Scarface", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "King Arthur", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: False

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

1
you might might answer 
1
2
{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
1
Give ONLY a JSON output. Nothing else.

Output

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{
  "The Lion King": ["🦁", "🦓", "🐗", "🐘", "🐒"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🦇", "🕷️"],
  "The Godfather": ["🔫", "🩸", "💼", "🕶️", "🚬"],
  "The Matrix": ["💊", "💻", "🕶️", "🤖", "🔫"],
  "Casablanca": ["✈️", "🧥", "🥃", "🚬", "🗺️"],
  "Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "🎭", "✈️"],
  "V for Vendetta": ["🎭", "🎩", "💣", "🩸", "👁️"],
  "The Princess Bride": ["🏰", "⚔️", "🐎", "🐀", "💍"],
  "Back to the Future": ["⚡️", "🚗", "🕒", "🎸", "🏫"],
  "Dune": ["🏜️", "🪱", "🦅", "⚔️", "🪐"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["🦁", "🦓", "🐗", "🐘", "🐒"],
  "The Nightmare Before Christmas": ["🎃", "👻", "💀", "🦇", "🕷️"],
  "The Godfather": ["🔫", "🩸", "💼", "🕶️", "🚬"],
  "The Matrix": ["💊", "💻", "🕶️", "🤖", "🔫"],
  "Casablanca": ["✈️", "🧥", "🥃", "🚬", "🗺️"],
  "Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "🎭", "✈️"],
  "V for Vendetta": ["🎭", "🎩", "💣", "🩸", "👁️"],
  "The Princess Bride": ["🏰", "⚔️", "🐎", "🐀", "💍"],
  "Back to the Future": ["⚡️", "🚗", "🕒", "🎸", "🏫"],
  "Dune": ["🏜️", "🪱", "🦅", "⚔️", "🪐"]
}

PyFunc

Resulting in output: [['🦁', '🦓', '🐗', '🐘', '🐒'], ['🎃', '👻', '💀', '🦇', '🕷️'], ['🔫', '🩸', '💼', '🕶️', '🚬'], ['💊', '💻', '🕶️', '🤖', '🔫'], ['✈️', '🧥', '🥃', '🚬', '🗺️'], ['🗺️', '🔫', '🐍', '🎭', '✈️'], ['🎭', '🎩', '💣', '🩸', '👁️'], ['🏰', '⚔️', '🐎', '🐀', '💍'], ['⚡️', '🚗', '🕒', '🎸', '🏫'], ['🏜️', '🪱', '🦅', '⚔️', '🪐']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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2
3
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9
['🎃', '👻', '💀', '🦇', '🕷️'],
['🔫', '🩸', '💼', '🕶️', '🚬'],
['💊', '💻', '🕶️', '🤖', '🔫'],
['✈️', '🧥', '🥃', '🚬', '🗺️'],
['🗺️', '🔫', '🐍', '🎭', '✈️'],
['🎭', '🎩', '💣', '🩸', '👁️'],
['🏰', '⚔️', '🐎', '🐀', '💍'],
['⚡️', '🚗', '🕒', '🎸', '🏫'],
['🏜️', '🪱', '🦅', '⚔️', '🪐']]
What are the names of the movie titles?

Output

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["The Lion King",
 "Halloween",
 "John Wick",
 "The Matrix",
 "Casablanca",
 "Raiders of the Lost Ark",
 "The Prestige",
 "The Lord of the Rings: The Fellowship of the Ring",
 "Back to the Future",
 "Dune"]

Extract Json

I extracted the following JSON from that output: 

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["The Lion King",
 "Halloween",
 "John Wick",
 "The Matrix",
 "Casablanca",
 "Raiders of the Lost Ark",
 "The Prestige",
 "The Lord of the Rings: The Fellowship of the Ring",
 "Back to the Future",
 "Dune"]

PyFunc

OK Resulting in output: False

Initial Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
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Give ONLY a JSON output. Nothing else.

LLM Generation

Query

For each of the following ten movies give at most 5 emoji that would best describe the movie. Give your answer as a JSON array. So If I asked for 

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you might might answer 
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{"Finding Nemo": ["🐠", "🐟", "🐡", "🐬", "🐳"],
"Toy Story": ["🚀", "⚔️,", "🤖", "👽", "🌌"]}
. Each emoji must be a single utf8 character. ABSOLUTELY NO ZERO WIDTH JOINING. (So, max(len(emoji) for movie in result.values() for emoji in movie) == 1) Now give me answers for these movies: 
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Give ONLY a JSON output. Nothing else.

Output

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{
"The Lion King": ["🦁", "🐘", "🐒", "🦓", "🦒"],
"The Nightmare Before Christmas": ["💀", "🎃", "🦇", "🕷️", "🕸️"],
"The Godfather": ["🔫", "💰", "🤵", "🍷", "🚬"],
"The Matrix": ["🕶️", "💻", "💊", "🤖", "🔫"],
"Casablanca": ["✈️", "🥃", "🚬", "🧥", "🎩"],
"Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "🎩", "✈️"],
"V for Vendetta": ["🎭", "💣", "🎩", "🩸", "✊"],
"The Princess Bride": ["👸", "👰", "⚔️", "🏰", "🐎"],
"Back to the Future": ["🚗", "⏰", "🎸", "🕶️", "🛹"],
"Dune": ["🪱", "🏜️", "⚔️", "🌌", "🛡️"]
}

Extract Json

I extracted the following JSON from that output: 

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{
"The Lion King": ["🦁", "🐘", "🐒", "🦓", "🦒"],
"The Nightmare Before Christmas": ["💀", "🎃", "🦇", "🕷️", "🕸️"],
"The Godfather": ["🔫", "💰", "🤵", "🍷", "🚬"],
"The Matrix": ["🕶️", "💻", "💊", "🤖", "🔫"],
"Casablanca": ["✈️", "🥃", "🚬", "🧥", "🎩"],
"Raiders of the Lost Ark": ["🗺️", "🔫", "🐍", "🎩", "✈️"],
"V for Vendetta": ["🎭", "💣", "🎩", "🩸", "✊"],
"The Princess Bride": ["👸", "👰", "⚔️", "🏰", "🐎"],
"Back to the Future": ["🚗", "⏰", "🎸", "🕶️", "🛹"],
"Dune": ["🪱", "🏜️", "⚔️", "🌌", "🛡️"]
}

PyFunc

Resulting in output: [['🦁', '🐘', '🐒', '🦓', '🦒'], ['💀', '🎃', '🦇', '🕷️', '🕸️'], ['🔫', '💰', '🤵', '🍷', '🚬'], ['🕶️', '💻', '💊', '🤖', '🔫'], ['✈️', '🥃', '🚬', '🧥', '🎩'], ['🗺️', '🔫', '🐍', '🎩', '✈️'], ['🎭', '💣', '🎩', '🩸', '✊'], ['👸', '👰', '⚔️', '🏰', '🐎'], ['🚗', '⏰', '🎸', '🕶️', '🛹'], ['🪱', '🏜️', '⚔️', '🌌', '🛡️']]

LLM Generation

Query

For each of the following ten movies described by 5 emoji, give the movie title that best matches. Give your answer as a JSON list. So If I asked for 

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You might answer 
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["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
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['💀', '🎃', '🦇', '🕷️', '🕸️'],
['🔫', '💰', '🤵', '🍷', '🚬'],
['🕶️', '💻', '💊', '🤖', '🔫'],
['✈️', '🥃', '🚬', '🧥', '🎩'],
['🗺️', '🔫', '🐍', '🎩', '✈️'],
['🎭', '💣', '🎩', '🩸', '✊'],
['👸', '👰', '⚔️', '🏰', '🐎'],
['🚗', '⏰', '🎸', '🕶️', '🛹'],
['🪱', '🏜️', '⚔️', '🌌', '🛡️']]
What are the names of the movie titles?

Output

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[
"The Lion King",
"Halloween",
"James Bond",
"The Matrix",
"Casablanca",
"Indiana Jones",
"Fight Club",
"Braveheart",
"Back to the Future",
"Dune"
]

Extract Json

I extracted the following JSON from that output: 

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[
"The Lion King",
"Halloween",
"James Bond",
"The Matrix",
"Casablanca",
"Indiana Jones",
"Fight Club",
"Braveheart",
"Back to the Future",
"Dune"
]

PyFunc

OK Resulting in output: False