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 

1
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…", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ”ช", "๐Ÿ‡ฎ๐Ÿ‡น", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ’ป", "๐Ÿ•ถ๏ธ", "๐Ÿ”ซ", "๐Ÿค–"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿ€", "๐Ÿฐ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘ฆโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ…", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ”ช", "๐Ÿ‡ฎ๐Ÿ‡น", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ’ป", "๐Ÿ•ถ๏ธ", "๐Ÿ”ซ", "๐Ÿค–"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿ€", "๐Ÿฐ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘ฆโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ…', '๐ŸŽถ', '๐Ÿฆ'], ['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'], ['๐Ÿ”ซ', '๐Ÿ”ช', '๐Ÿ‡ฎ๐Ÿ‡น', '๐Ÿ’ฐ'], ['๐Ÿ’Š', '๐Ÿ’ป', '๐Ÿ•ถ๏ธ', '๐Ÿ”ซ', '๐Ÿค–'], ['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'], ['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'], ['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'], ['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿ€', '๐Ÿฐ'], ['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'], ['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏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‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'],
['๐Ÿ”ซ', '๐Ÿ”ช', '๐Ÿ‡ฎ๐Ÿ‡น', '๐Ÿ’ฐ'],
['๐Ÿ’Š', '๐Ÿ’ป', '๐Ÿ•ถ๏ธ', '๐Ÿ”ซ', '๐Ÿค–'],
['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'],
['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'],
['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'],
['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿ€', '๐Ÿฐ'],
['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'],
['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐ŸŒŒ']]
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", "V for Vendetta", "Cinderella", "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", "Cinderella", "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 
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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„", "๐ŸŽถ", "๐Ÿ’”"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ’ฐ", "๐Ÿ‡ฎ๐Ÿ‡น", "๐ŸŒน"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ˜Ž", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’ป"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "๐Ÿ’”", "๐ŸŽน", "๐Ÿ•ต๏ธโ€โ™‚๏ธ"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "๐Ÿญ", "๐Ÿ’‹", "๐Ÿฐ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐ŸŽธ", "๐Ÿ‘จโ€๐Ÿ‘ฆ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐Ÿš€"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿ’”"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ’ฐ", "๐Ÿ‡ฎ๐Ÿ‡น", "๐ŸŒน"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ˜Ž", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’ป"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "๐Ÿ’”", "๐ŸŽน", "๐Ÿ•ต๏ธโ€โ™‚๏ธ"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "๐Ÿญ", "๐Ÿ’‹", "๐Ÿฐ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐ŸŽธ", "๐Ÿ‘จโ€๐Ÿ‘ฆ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐Ÿš€"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ„', '๐ŸŽถ', '๐Ÿ’”'], ['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'], ['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐Ÿ‡ฎ๐Ÿ‡น', '๐ŸŒน'], ['๐Ÿ’Š', '๐Ÿ˜Ž', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’ป'], ['โœˆ๏ธ', '๐Ÿธ', '๐Ÿ’”', '๐ŸŽน'], ['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'], ['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'], ['โš”๏ธ', '๐Ÿ‘ธ', '๐Ÿญ', '๐Ÿ’‹', '๐Ÿฐ'], ['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'], ['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐Ÿš€']]

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', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'],
['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐Ÿ‡ฎ๐Ÿ‡น', '๐ŸŒน'],
['๐Ÿ’Š', '๐Ÿ˜Ž', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’ป'],
['โœˆ๏ธ', '๐Ÿธ', '๐Ÿ’”', '๐ŸŽน'],
['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'],
['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'],
['โš”๏ธ', '๐Ÿ‘ธ', '๐Ÿญ', '๐Ÿ’‹', '๐Ÿฐ'],
['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'],
['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐Ÿš€']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Sleeping Beauty", "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 Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Sleeping Beauty", "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‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ’ฐ", "๐ŸŒน", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ•ถ๏ธ", "๐Ÿ”ซ", "๐Ÿค–", "โ“"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "โค๏ธ", "๐ŸŽน", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿบ", "๐Ÿƒ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฅ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ช"],
  "The Princess Bride": ["๐Ÿคบ", "๐Ÿ‘‘", "๐Ÿ€", "๐Ÿฐ", "โค๏ธ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐ŸŽธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ’ฐ", "๐ŸŒน", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ•ถ๏ธ", "๐Ÿ”ซ", "๐Ÿค–", "โ“"],
  "Casablanca": ["โœˆ๏ธ", "๐Ÿธ", "โค๏ธ", "๐ŸŽน", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿบ", "๐Ÿƒ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฅ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ช"],
  "The Princess Bride": ["๐Ÿคบ", "๐Ÿ‘‘", "๐Ÿ€", "๐Ÿฐ", "โค๏ธ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐ŸŽธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ„', '๐ŸŽถ', '๐Ÿฆ'], ['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'], ['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐ŸŒน', '๐Ÿ‡ฎ๐Ÿ‡น'], ['๐Ÿ’Š', '๐Ÿ•ถ๏ธ', '๐Ÿ”ซ', '๐Ÿค–', 'โ“'], ['โœˆ๏ธ', '๐Ÿธ', 'โค๏ธ', '๐ŸŽน', '๐Ÿ˜ข'], ['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿบ', '๐Ÿƒ'], ['๐ŸŽญ', '๐Ÿ’ฅ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ช'], ['๐Ÿคบ', '๐Ÿ‘‘', '๐Ÿ€', '๐Ÿฐ', 'โค๏ธ'], ['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'], ['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏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‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'],
['๐Ÿ”ซ', '๐Ÿ’ฐ', '๐ŸŒน', '๐Ÿ‡ฎ๐Ÿ‡น'],
['๐Ÿ’Š', '๐Ÿ•ถ๏ธ', '๐Ÿ”ซ', '๐Ÿค–', 'โ“'],
['โœˆ๏ธ', '๐Ÿธ', 'โค๏ธ', '๐ŸŽน', '๐Ÿ˜ข'],
['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿบ', '๐Ÿƒ'],
['๐ŸŽญ', '๐Ÿ’ฅ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ช'],
['๐Ÿคบ', '๐Ÿ‘‘', '๐Ÿ€', '๐Ÿฐ', 'โค๏ธ'],
['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'],
['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐ŸŒŒ']]
What are the names of the movie titles?

Output

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["The Lion King", "The Nightmare Before Christmas", "The Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "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 Italian Job", "The Matrix", "Casablanca", "Raiders of the Lost Ark", "V for Vendetta", "Cinderella", "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‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐ŸŒน", "๐Ÿ’ฐ", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ˜Ž", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’ป"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿญ", "๐Ÿคบ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿฆ"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐ŸŒน", "๐Ÿ’ฐ", "๐Ÿ‡ฎ๐Ÿ‡น"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ˜Ž", "๐Ÿค–", "๐Ÿ”ซ", "๐Ÿ’ป"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿ—ฟ", "๐Ÿ’ฅ"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฃ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ฅ"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿญ", "๐Ÿคบ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ„', '๐ŸŽถ', '๐Ÿฆ'], ['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'], ['๐Ÿ”ซ', '๐ŸŒน', '๐Ÿ’ฐ', '๐Ÿ‡ฎ๐Ÿ‡น'], ['๐Ÿ’Š', '๐Ÿ˜Ž', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’ป'], ['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'], ['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'], ['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'], ['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿญ', '๐Ÿคบ'], ['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'], ['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏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 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
1
2
3
4
5
6
7
8
9
['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'],
['๐Ÿ”ซ', '๐ŸŒน', '๐Ÿ’ฐ', '๐Ÿ‡ฎ๐Ÿ‡น'],
['๐Ÿ’Š', '๐Ÿ˜Ž', '๐Ÿค–', '๐Ÿ”ซ', '๐Ÿ’ป'],
['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'],
['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ—ฟ', '๐Ÿ’ฅ'],
['๐ŸŽญ', '๐Ÿ’ฃ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ฅ'],
['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿญ', '๐Ÿคบ'],
['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'],
['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐ŸŒŒ']]
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", "V for Vendetta", "Cinderella", "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", "Cinderella", "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‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿ’”"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ”ช", "๐Ÿ‡ฎ๐Ÿ‡น", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ’ป", "๐Ÿ˜Ž", "๐Ÿ”ซ", "๐Ÿค–"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿƒโ€โ™‚๏ธ", "๐Ÿ›•"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฅ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ช"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿ€", "ๅทจไบบ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output: 

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{
  "The Lion King": ["๐Ÿฆ", "๐Ÿ‘‘", "๐ŸŒ„", "๐ŸŽถ", "๐Ÿ’”"],
  "The Nightmare Before Christmas": ["๐ŸŽƒ", "๐Ÿ‘ป", "๐Ÿ’€", "๐ŸŽ„", "๐ŸŽถ"],
  "The Godfather": ["๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐Ÿ”ซ", "๐Ÿ”ช", "๐Ÿ‡ฎ๐Ÿ‡น", "๐Ÿ’ฐ"],
  "The Matrix": ["๐Ÿ’Š", "๐Ÿ’ป", "๐Ÿ˜Ž", "๐Ÿ”ซ", "๐Ÿค–"],
  "Casablanca": ["โœˆ๏ธ", "โค๏ธ", "๐Ÿธ", "๐Ÿ•ต๏ธโ€โ™‚๏ธ", "๐Ÿ˜ข"],
  "Raiders of the Lost Ark": ["๐Ÿค ", "๐Ÿ", "๐Ÿ—บ๏ธ", "๐Ÿƒโ€โ™‚๏ธ", "๐Ÿ›•"],
  "V for Vendetta": ["๐ŸŽญ", "๐Ÿ’ฅ", "โœŠ", "๐Ÿ‡ฌ๐Ÿ‡ง", "๐Ÿ”ช"],
  "The Princess Bride": ["โš”๏ธ", "๐Ÿ‘ธ", "โค๏ธ", "๐Ÿ€", "ๅทจไบบ"],
  "Back to the Future": ["๐Ÿš—", "โšก๏ธ", "๐Ÿ•ฐ๏ธ", "๐Ÿ‘จโ€๐Ÿ‘ฉโ€๐Ÿ‘งโ€๐Ÿ‘ฆ", "๐ŸŽธ"],
  "Dune": ["๐Ÿœ๏ธ", "๐Ÿ›", "๐Ÿ”ฎ", "โš”๏ธ", "๐ŸŒŒ"]
}

PyFunc

Resulting in output: [['๐Ÿฆ', '๐Ÿ‘‘', '๐ŸŒ„', '๐ŸŽถ', '๐Ÿ’”'], ['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'], ['๐Ÿ”ซ', '๐Ÿ”ช', '๐Ÿ‡ฎ๐Ÿ‡น', '๐Ÿ’ฐ'], ['๐Ÿ’Š', '๐Ÿ’ป', '๐Ÿ˜Ž', '๐Ÿ”ซ', '๐Ÿค–'], ['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'], ['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ›•'], ['๐ŸŽญ', '๐Ÿ’ฅ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ช'], ['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿ€', 'ๅทจไบบ'], ['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'], ['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏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 

1
You might answer 
1
["Finding Nemo", "Toy Story"]]
. Now give me answers for these movies: 
1
2
3
4
5
6
7
8
9
['๐ŸŽƒ', '๐Ÿ‘ป', '๐Ÿ’€', '๐ŸŽ„', '๐ŸŽถ'],
['๐Ÿ”ซ', '๐Ÿ”ช', '๐Ÿ‡ฎ๐Ÿ‡น', '๐Ÿ’ฐ'],
['๐Ÿ’Š', '๐Ÿ’ป', '๐Ÿ˜Ž', '๐Ÿ”ซ', '๐Ÿค–'],
['โœˆ๏ธ', 'โค๏ธ', '๐Ÿธ', '๐Ÿ˜ข'],
['๐Ÿค ', '๐Ÿ', '๐Ÿ—บ๏ธ', '๐Ÿ›•'],
['๐ŸŽญ', '๐Ÿ’ฅ', 'โœŠ', '๐Ÿ‡ฌ๐Ÿ‡ง', '๐Ÿ”ช'],
['โš”๏ธ', '๐Ÿ‘ธ', 'โค๏ธ', '๐Ÿ€', 'ๅทจไบบ'],
['๐Ÿš—', 'โšก๏ธ', '๐Ÿ•ฐ๏ธ', '๐ŸŽธ'],
['๐Ÿœ๏ธ', '๐Ÿ›', '๐Ÿ”ฎ', 'โš”๏ธ', '๐ŸŒŒ']]
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", "V for Vendetta", "Ella Enchanted", "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", "Ella Enchanted", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True