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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

Give ONLY a JSON output. Nothing else.

Output

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸ’", "ðŸ¦“"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "ðŸ•¯ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ™ï¸"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ”«", "ðŸ–¥ï¸", "âš”ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ”", "âš”ï¸", "ðŸŒ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ—¡ï¸", "ðŸ“œ", "ðŸ•¶ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "ðŸ’”", "ðŸ´"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸŒŒ", "ðŸ•¶ï¸"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "âš”ï¸", "ðŸ›", "ðŸ‘‘"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸ’", "ðŸ¦“"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "ðŸ•¯ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ™ï¸"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ”«", "ðŸ–¥ï¸", "âš”ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ”", "âš”ï¸", "ðŸŒ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ—¡ï¸", "ðŸ“œ", "ðŸ•¶ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "ðŸ’”", "ðŸ´"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸŒŒ", "ðŸ•¶ï¸"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "âš”ï¸", "ðŸ›", "ðŸ‘‘"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ’', 'ðŸ¦“'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'ðŸ•¯ï¸'], ['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ™ï¸'], ['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ”«', 'ðŸ–¥ï¸', 'âš”ï¸'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ·'], ['ðŸ—ºï¸', 'ðŸº', 'ðŸ”', 'âš”ï¸', 'ðŸŒ'], ['ðŸŽ', 'ðŸ’£', 'ðŸ—¡ï¸', 'ðŸ“œ', 'ðŸ•¶ï¸'], ['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'ðŸ’”', 'ðŸ´'], ['ðŸš—', 'â°', 'âš¡', 'ðŸŒŒ', 'ðŸ•¶ï¸'], ['ðŸœï¸', 'ðŸŒŒ', 'âš”ï¸', 'ðŸ›', 'ðŸ‘‘']]

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

You might answer

["Finding Nemo", "Toy Story"]]

. Now give me answers for these movies:

['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'ðŸ•¯ï¸'],
['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ™ï¸'],
['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ”«', 'ðŸ–¥ï¸', 'âš”ï¸'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ·'],
['ðŸ—ºï¸', 'ðŸº', 'ðŸ”', 'âš”ï¸', 'ðŸŒ'],
['ðŸŽ­', 'ðŸ’£', 'ðŸ—¡ï¸', 'ðŸ“œ', 'ðŸ•¶ï¸'],
['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'ðŸ’”', 'ðŸ´'],
['ðŸš—', 'â°', 'âš¡', 'ðŸŒŒ', 'ðŸ•¶ï¸'],
['ðŸœï¸', 'ðŸŒŒ', 'âš”ï¸', 'ðŸ›', 'ðŸ‘‘']]

What are the names of the movie titles?

Output

["The Lion King", "Hocus Pocus", "Pulp Fiction", "The Matrix", "La La Land", "Indiana Jones", "Kingsman: The Secret Service", "The Princess Bride", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output:

["The Lion King", "Hocus Pocus", "Pulp Fiction", "The Matrix", "La La Land", "Indiana Jones", "Kingsman: The Secret Service", "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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

Give ONLY a JSON output. Nothing else.

Output

{
  "The Lion King": ["ðŸ¦", "ðŸ‘‘", "ðŸŒ…", "ðŸ’", "ðŸ—"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŽ„", "ðŸŒ™"],
  "The Godfather": ["ðŸ", "ðŸ”«", "ðŸ‘¨â€ðŸ‘¦", "ðŸ’¼", "ðŸ•¶ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ”«", "ðŸ’»", "ðŸ•°ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ’”"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ§­", "ðŸ¥¾", "ðŸ”«"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ”¥", "ðŸ›¡ï¸", "âš–ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "ðŸ´", "ðŸŒ¹"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ•°ï¸", "ðŸ‘¨â€ðŸ”¬"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "ðŸ›", "âš”ï¸", "ðŸ‘‘"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸ‘‘", "ðŸŒ…", "ðŸ’", "ðŸ—"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŽ„", "ðŸŒ™"],
  "The Godfather": ["ðŸ", "ðŸ”«", "ðŸ‘¨â€ðŸ‘¦", "ðŸ’¼", "ðŸ•¶ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ”«", "ðŸ’»", "ðŸ•°ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ’”"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ§­", "ðŸ¥¾", "ðŸ”«"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ”¥", "ðŸ›¡ï¸", "âš–ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "ðŸ´", "ðŸŒ¹"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ•°ï¸", "ðŸ‘¨â€ðŸ”¬"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "ðŸ›", "âš”ï¸", "ðŸ‘‘"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸ‘‘', 'ðŸŒ…', 'ðŸ’', 'ðŸ—'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŽ„', 'ðŸŒ™'], ['ðŸ', 'ðŸ”«', 'ðŸ’¼', 'ðŸ•¶ï¸'], ['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸ’»', 'ðŸ•°ï¸'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ’”'], ['ðŸ—ºï¸', 'ðŸº', 'ðŸ§', 'ðŸ¥¾', 'ðŸ”«'], ['ðŸŽ', 'ðŸ—¡ï¸', 'ðŸ”¥', 'ðŸ›¡ï¸', 'âš–ï¸'], ['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'ðŸ´', 'ðŸŒ¹'], ['ðŸš—', 'â³', 'âš¡', 'ðŸ•°ï¸'], ['ðŸœï¸', 'ðŸŒŒ', 'ðŸ›', 'âš”ï¸', 'ðŸ‘‘']]

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

You might answer

["Finding Nemo", "Toy Story"]]

. Now give me answers for these movies:

['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŽ„', 'ðŸŒ™'],
['ðŸ', 'ðŸ”«', 'ðŸ’¼', 'ðŸ•¶ï¸'],
['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸ’»', 'ðŸ•°ï¸'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ’”'],
['ðŸ—ºï¸', 'ðŸº', 'ðŸ§­', 'ðŸ¥¾', 'ðŸ”«'],
['ðŸŽ­', 'ðŸ—¡ï¸', 'ðŸ”¥', 'ðŸ›¡ï¸', 'âš–ï¸'],
['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'ðŸ´', 'ðŸŒ¹'],
['ðŸš—', 'â³', 'âš¡', 'ðŸ•°ï¸'],
['ðŸœï¸', 'ðŸŒŒ', 'ðŸ›', 'âš”ï¸', 'ðŸ‘‘']]

What are the names of the movie titles?

Output

["The Lion King", "The Nightmare Before Christmas", "Luca", "The Matrix", "La La Land", "Indiana Jones", "Gladiator", "The Princess Bride", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output:

["The Lion King", "The Nightmare Before Christmas", "Luca", "The Matrix", "La La Land", "Indiana Jones", "Gladiator", "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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

Give ONLY a JSON output. Nothing else.

Output

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸ¾", "ðŸŒ"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "ðŸŽ„"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ”«", "ðŸ’¼", "ðŸ·", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ”«", "ðŸ–¥ï¸", "ðŸŒŒ"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸ§³", "ðŸ”", "ðŸº", "âš”ï¸"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ•µï¸â€â™‚ï¸", "ðŸ“œ", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["ðŸ‘‘", "ðŸ’”", "âš”ï¸", "ðŸ§™â€â™‚ï¸", "ðŸ´"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ‘¨â€ðŸ”¬", "ðŸŒŒ"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "ðŸ¤´", "ðŸ", "ðŸ”«"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸ¾", "ðŸŒ"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "ðŸŽ„"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ”«", "ðŸ’¼", "ðŸ·", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ”«", "ðŸ–¥ï¸", "ðŸŒŒ"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸ§³", "ðŸ”", "ðŸº", "âš”ï¸"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ•µï¸â€â™‚ï¸", "ðŸ“œ", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["ðŸ‘‘", "ðŸ’”", "âš”ï¸", "ðŸ§™â€â™‚ï¸", "ðŸ´"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ‘¨â€ðŸ”¬", "ðŸŒŒ"],
  "Dune": ["ðŸœï¸", "ðŸŒŒ", "ðŸ¤´", "ðŸ", "ðŸ”«"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ¾', 'ðŸŒ'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'ðŸŽ„'], ['ðŸ”«', 'ðŸ’¼', 'ðŸ·', 'ðŸ‡®ðŸ‡¹'], ['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸ–¥ï¸', 'ðŸŒŒ'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ·'], ['ðŸ—ºï¸', 'ðŸ§³', 'ðŸ”', 'ðŸº', 'âš”ï¸'], ['ðŸŽ', 'ðŸ—¡ï¸', 'ðŸ“œ', 'ðŸ‡¬ðŸ‡§'], ['ðŸ‘‘', 'ðŸ’”', 'âš”ï¸', 'ðŸ´'], ['ðŸš—', 'â³', 'âš¡', 'ðŸŒŒ'], ['ðŸœï¸', 'ðŸŒŒ', 'ðŸ¤´', 'ðŸ', 'ðŸ”«']]

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

You might answer

["Finding Nemo", "Toy Story"]]

. Now give me answers for these movies:

['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'ðŸŽ„'],
['ðŸ”«', 'ðŸ’¼', 'ðŸ·', 'ðŸ‡®ðŸ‡¹'],
['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸ–¥ï¸', 'ðŸŒŒ'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ·'],
['ðŸ—ºï¸', 'ðŸ§³', 'ðŸ”', 'ðŸº', 'âš”ï¸'],
['ðŸŽ­', 'ðŸ—¡ï¸', 'ðŸ“œ', 'ðŸ‡¬ðŸ‡§'],
['ðŸ‘‘', 'ðŸ’”', 'âš”ï¸', 'ðŸ´'],
['ðŸš—', 'â³', 'âš¡', 'ðŸŒŒ'],
['ðŸœï¸', 'ðŸŒŒ', 'ðŸ¤´', 'ðŸ', 'ðŸ”«']]

What are the names of the movie titles?

Output

["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "La La Land", "Indiana Jones and the Raiders of the Lost Ark", "Shakespeare in Love", "Braveheart", "Back to the Future", "Indiana Jones and the Last Crusade"]

Extract Json

I extracted the following JSON from that output:

["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "La La Land", "Indiana Jones and the Raiders of the Lost Ark", "Shakespeare in Love", "Braveheart", "Back to the Future", "Indiana Jones and the Last Crusade"]

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

Give ONLY a JSON output. Nothing else.

Output

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸŒ", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "â„ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ™ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ’»", "âš”ï¸", "ðŸ”«"],
  "Casablanca": ["âœˆï¸", "â¤ï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ’”"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "âš”ï¸", "ðŸ§³", "ðŸ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ‡¬ðŸ‡§", "ðŸ“°", "ðŸ”¥"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ’”", "âš”ï¸", "ðŸ§™"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ•¶ï¸", "ðŸŒŒ"],
  "Dune": ["ðŸŒµ", "ðŸ‘‘", "ðŸš€", "âš”ï¸", "ðŸ’§"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸŒ", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŒ™", "â„ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘§", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ™ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ’»", "âš”ï¸", "ðŸ”«"],
  "Casablanca": ["âœˆï¸", "â¤ï¸", "ðŸŽ¶", "ðŸŒ†", "ðŸ’”"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "âš”ï¸", "ðŸ§³", "ðŸ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ—¡ï¸", "ðŸ‡¬ðŸ‡§", "ðŸ“°", "ðŸ”¥"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ’”", "âš”ï¸", "ðŸ§™"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ•¶ï¸", "ðŸŒŒ"],
  "Dune": ["ðŸŒµ", "ðŸ‘‘", "ðŸš€", "âš”ï¸", "ðŸ’§"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸŒ', 'ðŸ’'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'â„ï¸'], ['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ™ï¸'], ['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ’»', 'âš”ï¸', 'ðŸ”«'], ['âœˆï¸', 'â¤ï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ’”'], ['ðŸ—ºï¸', 'ðŸº', 'âš”ï¸', 'ðŸ§³', 'ðŸ'], ['ðŸŽ', 'ðŸ—¡ï¸', 'ðŸ‡¬ðŸ‡§', 'ðŸ“°', 'ðŸ”¥'], ['ðŸ‘¸', 'ðŸ¤´', 'ðŸ’”', 'âš”ï¸', 'ðŸ§™'], ['ðŸš—', 'â°', 'âš¡', 'ðŸ•¶ï¸', 'ðŸŒŒ'], ['ðŸŒµ', 'ðŸ‘‘', 'ðŸš€', 'âš”ï¸', 'ðŸ’§']]

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

You might answer

["Finding Nemo", "Toy Story"]]

. Now give me answers for these movies:

['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŒ™', 'â„ï¸'],
['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ™ï¸'],
['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ’»', 'âš”ï¸', 'ðŸ”«'],
['âœˆï¸', 'â¤ï¸', 'ðŸŽ¶', 'ðŸŒ†', 'ðŸ’”'],
['ðŸ—ºï¸', 'ðŸº', 'âš”ï¸', 'ðŸ§³', 'ðŸ'],
['ðŸŽ­', 'ðŸ—¡ï¸', 'ðŸ‡¬ðŸ‡§', 'ðŸ“°', 'ðŸ”¥'],
['ðŸ‘¸', 'ðŸ¤´', 'ðŸ’”', 'âš”ï¸', 'ðŸ§™'],
['ðŸš—', 'â°', 'âš¡', 'ðŸ•¶ï¸', 'ðŸŒŒ'],
['ðŸŒµ', 'ðŸ‘‘', 'ðŸš€', 'âš”ï¸', 'ðŸ’§']]

What are the names of the movie titles?

Output

["The Lion King", "Hocus Pocus", "Pulp Fiction", "The Matrix", "La La Land", "Indiana Jones", "V for Vendetta", "The Princess Bride", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output:

["The Lion King", "Hocus Pocus", "Pulp Fiction", "The Matrix", "La La Land", "Indiana Jones", "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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

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

you might might answer

{"Finding Nemo": ["ðŸ ", "ðŸŸ", "ðŸ¡", "ðŸ¬", "ðŸ³"],
"Toy Story": ["ðŸš€", "âš”ï¸,", "ðŸ¤–", "ðŸ‘½", "ðŸŒŒ"]}

. 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:

Give ONLY a JSON output. Nothing else.

Output

{
  "The Lion King": ["ðŸ¦", "ðŸ‘‘", "ðŸŒ…", "ðŸ’", "ðŸ—"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŽ„", "ðŸŒ™"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘¦", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ’Š", "ðŸ‘¨â€ðŸ’»", "ðŸ”«", "ðŸ•¶ï¸", "ðŸ•³ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸ‡²ðŸ‡¦", "ðŸŽ¶", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ”«", "ðŸŒ", "â›ï¸"],
  "V for Vendetta": ["ðŸ˜·", "ðŸŽ­", "ðŸ’¥", "ðŸ‡¬ðŸ‡§", "ðŸ“œ"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ—¡ï¸", "ðŸ´", "ðŸ’–", "ðŸ§™â€â™‚ï¸"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ•¶ï¸", "ðŸ§‘â€ðŸ”¬"],
  "Dune": ["ðŸœï¸", "ðŸª", "âš”ï¸", "ðŸ›", "ðŸš€"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸ‘‘", "ðŸŒ…", "ðŸ’", "ðŸ—"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸŽ¶", "ðŸŽ„", "ðŸŒ™"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘¦", "ðŸ’¼", "ðŸ”«", "ðŸ·", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ’Š", "ðŸ‘¨â€ðŸ’»", "ðŸ”«", "ðŸ•¶ï¸", "ðŸ•³ï¸"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸ‡²ðŸ‡¦", "ðŸŽ¶", "ðŸ·"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸº", "ðŸ”«", "ðŸŒ", "â›ï¸"],
  "V for Vendetta": ["ðŸ˜·", "ðŸŽ­", "ðŸ’¥", "ðŸ‡¬ðŸ‡§", "ðŸ“œ"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ—¡ï¸", "ðŸ´", "ðŸ’–", "ðŸ§™â€â™‚ï¸"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸ•¶ï¸", "ðŸ§‘â€ðŸ”¬"],
  "Dune": ["ðŸœï¸", "ðŸª", "âš”ï¸", "ðŸ›", "ðŸš€"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸ‘‘', 'ðŸŒ…', 'ðŸ’', 'ðŸ—'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŽ„', 'ðŸŒ™'], ['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ‡®ðŸ‡¹'], ['ðŸ’Š', 'ðŸ”«', 'ðŸ•¶ï¸', 'ðŸ•³ï¸'], ['â¤ï¸', 'âœˆï¸', 'ðŸ‡²ðŸ‡¦', 'ðŸŽ¶', 'ðŸ·'], ['ðŸ—ºï¸', 'ðŸº', 'ðŸ”«', 'ðŸŒ', 'â›ï¸'], ['ðŸ˜·', 'ðŸŽ', 'ðŸ’¥', 'ðŸ‡¬ðŸ‡§', 'ðŸ“œ'], ['ðŸ‘¸', 'ðŸ—¡ï¸', 'ðŸ´', 'ðŸ’–'], ['ðŸš—', 'â³', 'âš¡', 'ðŸ•¶ï¸'], ['ðŸœï¸', 'ðŸª', 'âš”ï¸', 'ðŸ›', 'ðŸš€']]

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

You might answer

["Finding Nemo", "Toy Story"]]

. Now give me answers for these movies:

['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ¶', 'ðŸŽ„', 'ðŸŒ™'],
['ðŸ’¼', 'ðŸ”«', 'ðŸ·', 'ðŸ‡®ðŸ‡¹'],
['ðŸ’Š', 'ðŸ”«', 'ðŸ•¶ï¸', 'ðŸ•³ï¸'],
['â¤ï¸', 'âœˆï¸', 'ðŸ‡²ðŸ‡¦', 'ðŸŽ¶', 'ðŸ·'],
['ðŸ—ºï¸', 'ðŸº', 'ðŸ”«', 'ðŸŒ', 'â›ï¸'],
['ðŸ˜·', 'ðŸŽ­', 'ðŸ’¥', 'ðŸ‡¬ðŸ‡§', 'ðŸ“œ'],
['ðŸ‘¸', 'ðŸ—¡ï¸', 'ðŸ´', 'ðŸ’–'],
['ðŸš—', 'â³', 'âš¡', 'ðŸ•¶ï¸'],
['ðŸœï¸', 'ðŸª', 'âš”ï¸', 'ðŸ›', 'ðŸš€']]

What are the names of the movie titles?

Output

["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Indiana Jones", "V for Vendetta", "Braveheart", "Back to the Future", "Dune"]

Extract Json

I extracted the following JSON from that output:

["The Lion King", "The Nightmare Before Christmas", "The Godfather", "The Matrix", "Casablanca", "Indiana Jones", "V for Vendetta", "Braveheart", "Back to the Future", "Dune"]

PyFunc

OK Resulting in output: True