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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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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2
{"Finding Nemo": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ…", "๐Ÿต", "๐Ÿ˜"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿฆด", "๐Ÿ•ท๏ธ", "๐Ÿ”ฅ"],
  "The Godfather": ["๐Ÿ”ซ", "๐Ÿ’ฐ", "๐ŸŽ", "๐Ÿ‘”", "๐Ÿท"],
  "The Matrix": ["๐Ÿค–", "๐Ÿ’Š", "โš”๏ธ", "๐Ÿ•ถ๏ธ", "๐Ÿ•ณ๏ธ"],
  "Casablanca": ["โœˆ๏ธ", "๐ŸŒน", "๐Ÿฅƒ", "๐ŸŽป", "๐Ÿ•ฐ๏ธ"],
  "Raiders of the Lost Ark": ["๐Ÿ‘’", "๐Ÿ—ฟ", "๐Ÿ", "โ˜ ๏ธ", "๐Ÿ’Ž"],
  "V for Vendetta": ["๐Ÿ”ฅ", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ•Š๏ธ"],
  "The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿ—ก๏ธ", "๐Ÿง™โ€โ™‚๏ธ", "๐Ÿ€", "๐Ÿ’˜"],
  "Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ“–", "๐Ÿ•ฐ๏ธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿชฑ", "๐Ÿช–", "๐Ÿ—ก๏ธ", "๐ŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ…", "๐Ÿต", "๐Ÿ˜"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿฆด", "๐Ÿ•ท๏ธ", "๐Ÿ”ฅ"],
  "The Godfather": ["๐Ÿ”ซ", "๐Ÿ’ฐ", "๐ŸŽ", "๐Ÿ‘”", "๐Ÿท"],
  "The Matrix": ["๐Ÿค–", "๐Ÿ’Š", "โš”๏ธ", "๐Ÿ•ถ๏ธ", "๐Ÿ•ณ๏ธ"],
  "Casablanca": ["โœˆ๏ธ", "๐ŸŒน", "๐Ÿฅƒ", "๐ŸŽป", "๐Ÿ•ฐ๏ธ"],
  "Raiders of the Lost Ark": ["๐Ÿ‘’", "๐Ÿ—ฟ", "๐Ÿ", "โ˜ ๏ธ", "๐Ÿ’Ž"],
  "V for Vendetta": ["๐Ÿ”ฅ", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ•Š๏ธ"],
  "The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿ—ก๏ธ", "๐Ÿง™โ€โ™‚๏ธ", "๐Ÿ€", "๐Ÿ’˜"],
  "Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ“–", "๐Ÿ•ฐ๏ธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿชฑ", "๐Ÿช–", "๐Ÿ—ก๏ธ", "๐ŸŒŒ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ…', '๐Ÿต', '๐Ÿ˜'], ['๐ŸŽƒ', '๐Ÿ’€', '๐Ÿฆด', '๐Ÿ•ท๏ธ', '๐Ÿ”ฅ'], ['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐ŸŽ', '๐Ÿ‘”', '๐Ÿท'], ['๐Ÿค–', '๐Ÿ’Š', 'โš”๏ธ', '๐Ÿ•ถ๏ธ', '๐Ÿ•ณ๏ธ'], ['โœˆ๏ธ', '๐ŸŒน', '๐Ÿฅƒ', '๐ŸŽป', '๐Ÿ•ฐ๏ธ'], ['๐Ÿ‘’', '๐Ÿ—ฟ', '๐Ÿ', 'โ˜ ๏ธ', '๐Ÿ’Ž'], ['๐Ÿ”ฅ', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ•Š๏ธ'], ['๐Ÿ‘ธ', '๐Ÿ—ก๏ธ', '๐Ÿ€', '๐Ÿ’˜'], ['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ“–', '๐Ÿ•ฐ๏ธ'], ['๐Ÿœ๏ธ', '๐Ÿชฑ', '๐Ÿช–', '๐Ÿ—ก๏ธ', '๐ŸŒŒ']]

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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['๐ŸŽƒ', '๐Ÿ’€', '๐Ÿฆด', '๐Ÿ•ท๏ธ', '๐Ÿ”ฅ'],
['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐ŸŽ', '๐Ÿ‘”', '๐Ÿท'],
['๐Ÿค–', '๐Ÿ’Š', 'โš”๏ธ', '๐Ÿ•ถ๏ธ', '๐Ÿ•ณ๏ธ'],
['โœˆ๏ธ', '๐ŸŒน', '๐Ÿฅƒ', '๐ŸŽป', '๐Ÿ•ฐ๏ธ'],
['๐Ÿ‘’', '๐Ÿ—ฟ', '๐Ÿ', 'โ˜ ๏ธ', '๐Ÿ’Ž'],
['๐Ÿ”ฅ', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ•Š๏ธ'],
['๐Ÿ‘ธ', '๐Ÿ—ก๏ธ', '๐Ÿ€', '๐Ÿ’˜'],
['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ“–', '๐Ÿ•ฐ๏ธ'],
['๐Ÿœ๏ธ', '๐Ÿชฑ', '๐Ÿช–', '๐Ÿ—ก๏ธ', '๐ŸŒŒ']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "Nightmare Before Christmas",
  "The Untouchables",
  "The Matrix",
  "Casablanca",
  "Raiders of the Lost Ark",
  "Les Miserables",
  "Cinderella",
  "Back to the Future",
  "Dune"
]

Extract Json

I extracted the following JSON from that output: 

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[
  "The Lion King",
  "Nightmare Before Christmas",
  "The Untouchables",
  "The Matrix",
  "Casablanca",
  "Raiders of the Lost Ark",
  "Les Miserables",
  "Cinderella",
  "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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐Ÿต", "๐Ÿ—"],
"The Nightmare Before Christmas": ["๐ŸŽƒ", "โ˜ ๏ธ", "๐ŸŽ„", "๐Ÿ‘ป", "๐Ÿ•ท๏ธ"],
"The Godfather": ["๐Ÿ”ซ", "๐Ÿท", "๐Ÿ•ด๏ธ", "๐Ÿ—ฝ", "๐ŸŒน"],
"The Matrix": ["๐Ÿ’ป", "๐Ÿ•ถ๏ธ", "โš”๏ธ", "๐Ÿ”ซ", "๐Ÿ’Š"],
"Casablanca": ["๐Ÿ•ฐ๏ธ", "๐ŸŽป", "๐Ÿฅƒ", "โœˆ๏ธ", "๐ŸŒน"],
"Raiders of the Lost Ark": ["๐Ÿ’Ž", "๐Ÿงญ", "๐Ÿ", "๐Ÿ—ก๏ธ", "๐Ÿบ"],
"V for Vendetta": ["๐Ÿ”ต", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ“œ"],
"The Princess Bride": ["๐Ÿคบ", "๐Ÿฐ", "๐Ÿ’˜", "โš”๏ธ", "๐Ÿงšโ€โ™€๏ธ"],
"Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿค–", "๐Ÿ“ฝ๏ธ"],
"Dune": ["๐ŸŒ", "๐ŸŒ€", "๐Ÿ›", "๐Ÿœ๏ธ", "๐Ÿ—ก๏ธ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
"The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐Ÿต", "๐Ÿ—"],
"The Nightmare Before Christmas": ["๐ŸŽƒ", "โ˜ ๏ธ", "๐ŸŽ„", "๐Ÿ‘ป", "๐Ÿ•ท๏ธ"],
"The Godfather": ["๐Ÿ”ซ", "๐Ÿท", "๐Ÿ•ด๏ธ", "๐Ÿ—ฝ", "๐ŸŒน"],
"The Matrix": ["๐Ÿ’ป", "๐Ÿ•ถ๏ธ", "โš”๏ธ", "๐Ÿ”ซ", "๐Ÿ’Š"],
"Casablanca": ["๐Ÿ•ฐ๏ธ", "๐ŸŽป", "๐Ÿฅƒ", "โœˆ๏ธ", "๐ŸŒน"],
"Raiders of the Lost Ark": ["๐Ÿ’Ž", "๐Ÿงญ", "๐Ÿ", "๐Ÿ—ก๏ธ", "๐Ÿบ"],
"V for Vendetta": ["๐Ÿ”ต", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ“œ"],
"The Princess Bride": ["๐Ÿคบ", "๐Ÿฐ", "๐Ÿ’˜", "โš”๏ธ", "๐Ÿงšโ€โ™€๏ธ"],
"Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿค–", "๐Ÿ“ฝ๏ธ"],
"Dune": ["๐ŸŒ", "๐ŸŒ€", "๐Ÿ›", "๐Ÿœ๏ธ", "๐Ÿ—ก๏ธ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ„', '๐Ÿต', '๐Ÿ—'], ['๐ŸŽƒ', 'โ˜ ๏ธ', '๐ŸŽ„', '๐Ÿ‘ป', '๐Ÿ•ท๏ธ'], ['๐Ÿ”ซ', '๐Ÿท', '๐Ÿ•ด๏ธ', '๐Ÿ—ฝ', '๐ŸŒน'], ['๐Ÿ’ป', '๐Ÿ•ถ๏ธ', 'โš”๏ธ', '๐Ÿ”ซ', '๐Ÿ’Š'], ['๐Ÿ•ฐ๏ธ', '๐ŸŽป', '๐Ÿฅƒ', 'โœˆ๏ธ', '๐ŸŒน'], ['๐Ÿ’Ž', '๐Ÿงญ', '๐Ÿ', '๐Ÿ—ก๏ธ', '๐Ÿบ'], ['๐Ÿ”ต', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ“œ'], ['๐Ÿคบ', '๐Ÿฐ', '๐Ÿ’˜', 'โš”๏ธ'], ['โŒš', '๐Ÿš—', 'โšก', '๐Ÿค–', '๐Ÿ“ฝ๏ธ'], ['๐ŸŒ', '๐ŸŒ€', '๐Ÿ›', '๐Ÿœ๏ธ', '๐Ÿ—ก๏ธ']]

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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['๐ŸŽƒ', 'โ˜ ๏ธ', '๐ŸŽ„', '๐Ÿ‘ป', '๐Ÿ•ท๏ธ'],
['๐Ÿ”ซ', '๐Ÿท', '๐Ÿ•ด๏ธ', '๐Ÿ—ฝ', '๐ŸŒน'],
['๐Ÿ’ป', '๐Ÿ•ถ๏ธ', 'โš”๏ธ', '๐Ÿ”ซ', '๐Ÿ’Š'],
['๐Ÿ•ฐ๏ธ', '๐ŸŽป', '๐Ÿฅƒ', 'โœˆ๏ธ', '๐ŸŒน'],
['๐Ÿ’Ž', '๐Ÿงญ', '๐Ÿ', '๐Ÿ—ก๏ธ', '๐Ÿบ'],
['๐Ÿ”ต', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ“œ'],
['๐Ÿคบ', '๐Ÿฐ', '๐Ÿ’˜', 'โš”๏ธ'],
['โŒš', '๐Ÿš—', 'โšก', '๐Ÿค–', '๐Ÿ“ฝ๏ธ'],
['๐ŸŒ', '๐ŸŒ€', '๐Ÿ›', '๐Ÿœ๏ธ', '๐Ÿ—ก๏ธ']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Thomas Crown Affair",
  "The Matrix",
  "Casablanca",
  "Indiana Jones and the Raiders of the Lost Ark",
  "The Smurfs",
  "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 Thomas Crown Affair",
  "The Matrix",
  "Casablanca",
  "Indiana Jones and the Raiders of the Lost Ark",
  "The Smurfs",
  "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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿฆ", "๐Ÿต", "๐Ÿ˜", "๐ŸŒ…", "๐Ÿ‘‘"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿ•ท๏ธ", "๐Ÿฆด", "๐ŸŒœ"],
  "The Godfather": ["๐Ÿคต", "๐Ÿ”ซ", "๐Ÿ", "๐ŸŒน", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ•ถ๏ธ", "โŒ›", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’Š"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "๐Ÿ’‹", "๐Ÿ—บ๏ธ", "๐ŸŽป"],
  "Raiders of the Lost Ark": ["๐ŸŽฉ", "๐Ÿ’ฃ", "๐Ÿ", "๐Ÿ’", "โ˜„๏ธ"],
  "V for Vendetta": ["๐Ÿ‘บ", "๐Ÿ—ก๏ธ", "๐Ÿ“œ", "๐ŸŒน", "๐Ÿ‡ฌ๐Ÿ‡ง"],
  "The Princess Bride": ["๐Ÿ‘ธ", "โš”๏ธ", "๐Ÿ€", "๐Ÿง™", "๐ŸŒ‰"],
  "Back to the Future": ["โŒš", "๐Ÿ“†", "๐Ÿš—", "โšก", "๐Ÿค–"],
  "Dune": ["๐ŸŒ", "๐Ÿ›", "๐Ÿœ๏ธ", "โŒ›", "๐Ÿ—ก๏ธ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿต", "๐Ÿ˜", "๐ŸŒ…", "๐Ÿ‘‘"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿ•ท๏ธ", "๐Ÿฆด", "๐ŸŒœ"],
  "The Godfather": ["๐Ÿคต", "๐Ÿ”ซ", "๐Ÿ", "๐ŸŒน", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ•ถ๏ธ", "โŒ›", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’Š"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "๐Ÿ’‹", "๐Ÿ—บ๏ธ", "๐ŸŽป"],
  "Raiders of the Lost Ark": ["๐ŸŽฉ", "๐Ÿ’ฃ", "๐Ÿ", "๐Ÿ’", "โ˜„๏ธ"],
  "V for Vendetta": ["๐Ÿ‘บ", "๐Ÿ—ก๏ธ", "๐Ÿ“œ", "๐ŸŒน", "๐Ÿ‡ฌ๐Ÿ‡ง"],
  "The Princess Bride": ["๐Ÿ‘ธ", "โš”๏ธ", "๐Ÿ€", "๐Ÿง™", "๐ŸŒ‰"],
  "Back to the Future": ["โŒš", "๐Ÿ“†", "๐Ÿš—", "โšก", "๐Ÿค–"],
  "Dune": ["๐ŸŒ", "๐Ÿ›", "๐Ÿœ๏ธ", "โŒ›", "๐Ÿ—ก๏ธ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿต', '๐Ÿ˜', '๐ŸŒ…', '๐Ÿ‘‘'], ['๐ŸŽƒ', '๐Ÿ’€', '๐Ÿ•ท๏ธ', '๐Ÿฆด', '๐ŸŒœ'], ['๐Ÿคต', '๐Ÿ”ซ', '๐Ÿ', '๐ŸŒน', '๐Ÿ’ฐ'], ['๐Ÿ•ถ๏ธ', 'โŒ›', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’Š'], ['โœˆ๏ธ', '๐Ÿธ', '๐Ÿ’‹', '๐Ÿ—บ๏ธ', '๐ŸŽป'], ['๐ŸŽฉ', '๐Ÿ’ฃ', '๐Ÿ', '๐Ÿ’', 'โ˜„๏ธ'], ['๐Ÿ‘บ', '๐Ÿ—ก๏ธ', '๐Ÿ“œ', '๐ŸŒน', '๐Ÿ‡ฌ๐Ÿ‡ง'], ['๐Ÿ‘ธ', 'โš”๏ธ', '๐Ÿ€', '๐Ÿง™', '๐ŸŒ‰'], ['โŒš', '๐Ÿ“†', '๐Ÿš—', 'โšก', '๐Ÿค–'], ['๐ŸŒ', '๐Ÿ›', '๐Ÿœ๏ธ', 'โŒ›', '๐Ÿ—ก๏ธ']]

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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['๐ŸŽƒ', '๐Ÿ’€', '๐Ÿ•ท๏ธ', '๐Ÿฆด', '๐ŸŒœ'],
['๐Ÿคต', '๐Ÿ”ซ', '๐Ÿ', '๐ŸŒน', '๐Ÿ’ฐ'],
['๐Ÿ•ถ๏ธ', 'โŒ›', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’Š'],
['โœˆ๏ธ', '๐Ÿธ', '๐Ÿ’‹', '๐Ÿ—บ๏ธ', '๐ŸŽป'],
['๐ŸŽฉ', '๐Ÿ’ฃ', '๐Ÿ', '๐Ÿ’', 'โ˜„๏ธ'],
['๐Ÿ‘บ', '๐Ÿ—ก๏ธ', '๐Ÿ“œ', '๐ŸŒน', '๐Ÿ‡ฌ๐Ÿ‡ง'],
['๐Ÿ‘ธ', 'โš”๏ธ', '๐Ÿ€', '๐Ÿง™', '๐ŸŒ‰'],
['โŒš', '๐Ÿ“†', '๐Ÿš—', 'โšก', '๐Ÿค–'],
['๐ŸŒ', '๐Ÿ›', '๐Ÿœ๏ธ', 'โŒ›', '๐Ÿ—ก๏ธ']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Casablanca",
  "Raiders of the Lost Ark",
  "Mulan",
  "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",
  "Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Casablanca",
  "Raiders of the Lost Ark",
  "Mulan",
  "The Princess Bride",
  "Back to the Future",
  "Dune"
]

PyFunc

OK Resulting in output: True

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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿฆ", "๐Ÿ‘‘", "๐Ÿต", "๐Ÿ—", "๐ŸŒ„"],
"The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿง™โ€โ™‚๏ธ", "๐ŸŽ„", "๐Ÿฆด"],
"The Godfather": ["๐Ÿ•ด๏ธ", "๐Ÿ’ฐ", "๐Ÿ”ซ", "๐Ÿ", "๐Ÿ‡ฎ๐Ÿ‡น"],
"The Matrix": ["๐Ÿค–", "๐Ÿ’Š", "๐Ÿฅ‹", "๐Ÿ•ถ๏ธ", "๐ŸŒ"],
"Casablanca": ["๐Ÿ•ฐ๏ธ", "โœˆ๏ธ", "๐Ÿฅ‚", "๐ŸŒน", "๐Ÿ‡ฒ๐Ÿ‡ฆ"],
"Raiders of the Lost Ark": ["๐Ÿ‘ฃ", "๐Ÿงญ", "๐Ÿ’Ž", "โ˜„๏ธ", "๐Ÿ"],
"V for Vendetta": ["โญ", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ”ฅ"],
"The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿ—ก๏ธ", "๐Ÿคบ", "๐Ÿ’˜", "๐Ÿงšโ€โ™€๏ธ"],
"Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ•ฐ๏ธ", "๐Ÿค–"],
"Dune": ["๐Ÿœ๏ธ", "๐Ÿชฑ", "โŒ›", "๐Ÿ—ก๏ธ", "๐Ÿ›ธ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
"The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐Ÿต", "๐Ÿ—", "๐ŸŒ„"],
"The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ’€", "๐Ÿง™โ€โ™‚๏ธ", "๐ŸŽ„", "๐Ÿฆด"],
"The Godfather": ["๐Ÿ•ด๏ธ", "๐Ÿ’ฐ", "๐Ÿ”ซ", "๐Ÿ", "๐Ÿ‡ฎ๐Ÿ‡น"],
"The Matrix": ["๐Ÿค–", "๐Ÿ’Š", "๐Ÿฅ‹", "๐Ÿ•ถ๏ธ", "๐ŸŒ"],
"Casablanca": ["๐Ÿ•ฐ๏ธ", "โœˆ๏ธ", "๐Ÿฅ‚", "๐ŸŒน", "๐Ÿ‡ฒ๐Ÿ‡ฆ"],
"Raiders of the Lost Ark": ["๐Ÿ‘ฃ", "๐Ÿงญ", "๐Ÿ’Ž", "โ˜„๏ธ", "๐Ÿ"],
"V for Vendetta": ["โญ", "๐ŸŽญ", "โœŠ", "๐Ÿ—ฝ", "๐Ÿ”ฅ"],
"The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿ—ก๏ธ", "๐Ÿคบ", "๐Ÿ’˜", "๐Ÿงšโ€โ™€๏ธ"],
"Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ•ฐ๏ธ", "๐Ÿค–"],
"Dune": ["๐Ÿœ๏ธ", "๐Ÿชฑ", "โŒ›", "๐Ÿ—ก๏ธ", "๐Ÿ›ธ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐Ÿต', '๐Ÿ—', '๐ŸŒ„'], ['๐ŸŽƒ', '๐Ÿ’€', '๐ŸŽ„', '๐Ÿฆด'], ['๐Ÿ•ด๏ธ', '๐Ÿ’ฐ', '๐Ÿ”ซ', '๐Ÿ', '๐Ÿ‡ฎ๐Ÿ‡น'], ['๐Ÿค–', '๐Ÿ’Š', '๐Ÿฅ‹', '๐Ÿ•ถ๏ธ', '๐ŸŒ'], ['๐Ÿ•ฐ๏ธ', 'โœˆ๏ธ', '๐Ÿฅ‚', '๐ŸŒน', '๐Ÿ‡ฒ๐Ÿ‡ฆ'], ['๐Ÿ‘ฃ', '๐Ÿงญ', '๐Ÿ’Ž', 'โ˜„๏ธ', '๐Ÿ'], ['โญ', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ”ฅ'], ['๐Ÿ‘ธ', '๐Ÿ—ก๏ธ', '๐Ÿคบ', '๐Ÿ’˜'], ['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ•ฐ๏ธ', '๐Ÿค–'], ['๐Ÿœ๏ธ', '๐Ÿชฑ', 'โŒ›', '๐Ÿ—ก๏ธ', '๐Ÿ›ธ']]

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
4
5
6
7
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9
['๐ŸŽƒ', '๐Ÿ’€', '๐ŸŽ„', '๐Ÿฆด'],
['๐Ÿ•ด๏ธ', '๐Ÿ’ฐ', '๐Ÿ”ซ', '๐Ÿ', '๐Ÿ‡ฎ๐Ÿ‡น'],
['๐Ÿค–', '๐Ÿ’Š', '๐Ÿฅ‹', '๐Ÿ•ถ๏ธ', '๐ŸŒ'],
['๐Ÿ•ฐ๏ธ', 'โœˆ๏ธ', '๐Ÿฅ‚', '๐ŸŒน', '๐Ÿ‡ฒ๐Ÿ‡ฆ'],
['๐Ÿ‘ฃ', '๐Ÿงญ', '๐Ÿ’Ž', 'โ˜„๏ธ', '๐Ÿ'],
['โญ', '๐ŸŽญ', 'โœŠ', '๐Ÿ—ฝ', '๐Ÿ”ฅ'],
['๐Ÿ‘ธ', '๐Ÿ—ก๏ธ', '๐Ÿคบ', '๐Ÿ’˜'],
['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ•ฐ๏ธ', '๐Ÿค–'],
['๐Ÿœ๏ธ', '๐Ÿชฑ', 'โŒ›', '๐Ÿ—ก๏ธ', '๐Ÿ›ธ']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Casablanca",
  "Indiana Jones and the Raiders of the Lost Ark",
  "Rocky",
  "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",
  "Indiana Jones and the Raiders of the Lost Ark",
  "Rocky",
  "The Princess Bride",
  "Back to the Future",
  "Dune"
]

PyFunc

OK Resulting in output: True

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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿ ", "๐ŸŸ", "๐Ÿก", "๐Ÿฌ", "๐Ÿณ"],
"Toy Story": ["๐Ÿš€", "โš”๏ธ,", "๐Ÿค–", "๐Ÿ‘ฝ", "๐ŸŒŒ"]}
. 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": ["๐Ÿฆ", "๐Ÿญ", "๐ŸŒ„", "๐Ÿ‘‘", "๐Ÿ˜ญ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿฆด", "๐ŸŒœ", "๐ŸŽ…", "๐ŸŽ„"],
  "The Godfather": ["๐Ÿ”ซ", "๐Ÿคก", "๐Ÿ‘”", "๐Ÿ", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ•ถ๏ธ", "โš”๏ธ", "๐Ÿค–", "๐Ÿ”ด"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿฅƒ", "๐Ÿ’‹", "๐ŸŒน", "๐Ÿ‡ฒ๐Ÿ‡ฆ"],
  "Raiders of the Lost Ark": ["๐Ÿ‘’", "๐Ÿ—ฟ", "๐Ÿค ", "๐Ÿ", "๐Ÿ’Ž"],
  "V for Vendetta": ["๐ŸŽญ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ—ฝ", "๐Ÿ”ฅ"],
  "The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿคบ", "๐Ÿงโ€โ™‚๏ธ", "๐Ÿ€", "๐Ÿ‰"],
  "Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ“˜", "๐Ÿ•ฐ๏ธ"],
  "Dune": ["๐ŸŒ", "๐Ÿœ๏ธ", "๐Ÿชฑ", "๐Ÿ”ถ", "โ˜„๏ธ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿญ", "๐ŸŒ„", "๐Ÿ‘‘", "๐Ÿ˜ญ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿฆด", "๐ŸŒœ", "๐ŸŽ…", "๐ŸŽ„"],
  "The Godfather": ["๐Ÿ”ซ", "๐Ÿคก", "๐Ÿ‘”", "๐Ÿ", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ•ถ๏ธ", "โš”๏ธ", "๐Ÿค–", "๐Ÿ”ด"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿฅƒ", "๐Ÿ’‹", "๐ŸŒน", "๐Ÿ‡ฒ๐Ÿ‡ฆ"],
  "Raiders of the Lost Ark": ["๐Ÿ‘’", "๐Ÿ—ฟ", "๐Ÿค ", "๐Ÿ", "๐Ÿ’Ž"],
  "V for Vendetta": ["๐ŸŽญ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ—ฝ", "๐Ÿ”ฅ"],
  "The Princess Bride": ["๐Ÿ‘ธ", "๐Ÿคบ", "๐Ÿงโ€โ™‚๏ธ", "๐Ÿ€", "๐Ÿ‰"],
  "Back to the Future": ["โŒš", "๐Ÿš—", "โšก", "๐Ÿ“˜", "๐Ÿ•ฐ๏ธ"],
  "Dune": ["๐ŸŒ", "๐Ÿœ๏ธ", "๐Ÿชฑ", "๐Ÿ”ถ", "โ˜„๏ธ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿญ', '๐ŸŒ„', '๐Ÿ‘‘', '๐Ÿ˜ญ'], ['๐ŸŽƒ', '๐Ÿฆด', '๐ŸŒœ', '๐ŸŽ…', '๐ŸŽ„'], ['๐Ÿ”ซ', '๐Ÿคก', '๐Ÿ‘”', '๐Ÿ', '๐Ÿ‡ฎ๐Ÿ‡น'], ['๐Ÿ’Š', '๐Ÿ•ถ๏ธ', 'โš”๏ธ', '๐Ÿค–', '๐Ÿ”ด'], ['โœˆ๏ธ', '๐Ÿฅƒ', '๐Ÿ’‹', '๐ŸŒน', '๐Ÿ‡ฒ๐Ÿ‡ฆ'], ['๐Ÿ‘’', '๐Ÿ—ฟ', '๐Ÿค ', '๐Ÿ', '๐Ÿ’Ž'], ['๐ŸŽญ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ—ฝ', '๐Ÿ”ฅ'], ['๐Ÿ‘ธ', '๐Ÿคบ', '๐Ÿ€', '๐Ÿ‰'], ['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ“˜', '๐Ÿ•ฐ๏ธ'], ['๐ŸŒ', '๐Ÿœ๏ธ', '๐Ÿชฑ', '๐Ÿ”ถ', 'โ˜„๏ธ']]

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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3
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5
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['๐ŸŽƒ', '๐Ÿฆด', '๐ŸŒœ', '๐ŸŽ…', '๐ŸŽ„'],
['๐Ÿ”ซ', '๐Ÿคก', '๐Ÿ‘”', '๐Ÿ', '๐Ÿ‡ฎ๐Ÿ‡น'],
['๐Ÿ’Š', '๐Ÿ•ถ๏ธ', 'โš”๏ธ', '๐Ÿค–', '๐Ÿ”ด'],
['โœˆ๏ธ', '๐Ÿฅƒ', '๐Ÿ’‹', '๐ŸŒน', '๐Ÿ‡ฒ๐Ÿ‡ฆ'],
['๐Ÿ‘’', '๐Ÿ—ฟ', '๐Ÿค ', '๐Ÿ', '๐Ÿ’Ž'],
['๐ŸŽญ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ—ฝ', '๐Ÿ”ฅ'],
['๐Ÿ‘ธ', '๐Ÿคบ', '๐Ÿ€', '๐Ÿ‰'],
['โŒš', '๐Ÿš—', 'โšก', '๐Ÿ“˜', '๐Ÿ•ฐ๏ธ'],
['๐ŸŒ', '๐Ÿœ๏ธ', '๐Ÿชฑ', '๐Ÿ”ถ', 'โ˜„๏ธ']]
What are the names of the movie titles?

Output

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[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Casablanca",
  "Raiders of the Lost Ark",
  "Les Misรฉrables",
  "The Princess Bride",
  "Back to the Future",
  "The Fifth Element"
]

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",
  "Les Misรฉrables",
  "The Princess Bride",
  "Back to the Future",
  "The Fifth Element"
]

PyFunc

OK Resulting in output: True