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", "ðŸŽ„", "ðŸ‘»", "ðŸ•¸ï¸", "ðŸ’€"],
  "The Godfather": ["ðŸ’¼", "ðŸ”«", "ðŸ", "ðŸ•´ï¸", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’»", "ðŸ”‹", "ðŸ¤–", "ðŸŽ†"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸŒ", "ðŸŽ­"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸ•µï¸", "ðŸº", "ðŸ", "ðŸšª"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ”¥", "ðŸŽ‡", "ðŸ“°", "âš”ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ›¡ï¸", "ðŸ’˜"],
  "Back to the Future": ["â°", "ðŸš—", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸŒ ", "ðŸ‘‘", "ðŸª", "ðŸ¦‚"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸ‘‘", "ðŸŒ…", "ðŸ—", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸŽ„", "ðŸ‘»", "ðŸ•¸ï¸", "ðŸ’€"],
  "The Godfather": ["ðŸ’¼", "ðŸ”«", "ðŸ", "ðŸ•´ï¸", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’»", "ðŸ”‹", "ðŸ¤–", "ðŸŽ†"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸŒ", "ðŸŽ­"],
  "Raiders of the Lost Ark": ["ðŸ—ºï¸", "ðŸ•µï¸", "ðŸº", "ðŸ", "ðŸšª"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ”¥", "ðŸŽ‡", "ðŸ“°", "âš”ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ›¡ï¸", "ðŸ’˜"],
  "Back to the Future": ["â°", "ðŸš—", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸŒ ", "ðŸ‘‘", "ðŸª", "ðŸ¦‚"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸ‘‘', 'ðŸŒ…', 'ðŸ—', 'ðŸ’'], ['ðŸŽƒ', 'ðŸŽ„', 'ðŸ‘»', 'ðŸ•¸ï¸', 'ðŸ’€'], ['ðŸ’¼', 'ðŸ”«', 'ðŸ', 'ðŸ•´ï¸', 'ðŸ‡®ðŸ‡¹'], ['ðŸ•¶ï¸', 'ðŸ’»', 'ðŸ”‹', 'ðŸ¤–', 'ðŸŽ†'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸŒ', 'ðŸŽ'], ['ðŸ—ºï¸', 'ðŸ•µï¸', 'ðŸº', 'ðŸ', 'ðŸšª'], ['ðŸŽ', 'ðŸ”¥', 'ðŸŽ‡', 'ðŸ“°', 'âš”ï¸'], ['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ›¡ï¸', 'ðŸ’˜'], ['â°', 'ðŸš—', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'], ['ðŸœï¸', 'ðŸŒ ', 'ðŸ‘‘', 'ðŸª', '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', 'ðŸŽ„', 'ðŸ‘»', 'ðŸ•¸ï¸', 'ðŸ’€'],
['ðŸ’¼', 'ðŸ”«', 'ðŸ', 'ðŸ•´ï¸', 'ðŸ‡®ðŸ‡¹'],
['ðŸ•¶ï¸', 'ðŸ’»', 'ðŸ”‹', 'ðŸ¤–', 'ðŸŽ†'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸŒ', 'ðŸŽ­'],
['ðŸ—ºï¸', 'ðŸ•µï¸', 'ðŸº', 'ðŸ', 'ðŸšª'],
['ðŸŽ­', 'ðŸ”¥', 'ðŸŽ‡', 'ðŸ“°', 'âš”ï¸'],
['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ›¡ï¸', 'ðŸ’˜'],
['â°', 'ðŸš—', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'],
['ðŸœï¸', 'ðŸŒ ', 'ðŸ‘‘', 'ðŸª', 'ðŸ¦‚']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Moulin Rouge!",
  "Indiana Jones",
  "The Greatest Showman",
  "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",
  "The Godfather",
  "The Matrix",
  "Moulin Rouge!",
  "Indiana Jones",
  "The Greatest Showman",
  "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—", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ’€", "ðŸŽ„", "ðŸ‘»", "ðŸ•¸ï¸"],
  "The Godfather": ["ðŸ‘”", "ðŸ”«", "ðŸ", "ðŸ’¼", "ðŸ•´ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ’»", "ðŸ•¶ï¸", "ðŸ¤–", "ðŸšª"],
  "Casablanca": ["ðŸ—ºï¸", "â¤ï¸", "âœˆï¸", "ðŸŽ¶", "â˜•"],
  "Raiders of the Lost Ark": ["ðŸ—¿", "ðŸŒ", "ðŸº", "ðŸ§­", "ðŸ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ™ï¸", "ðŸ“º", "âš”ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ§™", "â¤ï¸"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸŒ ", "ðŸ‘‘", "ðŸª", "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„", "ðŸ‘»", "ðŸ•¸ï¸"],
  "The Godfather": ["ðŸ‘”", "ðŸ”«", "ðŸ", "ðŸ’¼", "ðŸ•´ï¸"],
  "The Matrix": ["ðŸ’Š", "ðŸ’»", "ðŸ•¶ï¸", "ðŸ¤–", "ðŸšª"],
  "Casablanca": ["ðŸ—ºï¸", "â¤ï¸", "âœˆï¸", "ðŸŽ¶", "â˜•"],
  "Raiders of the Lost Ark": ["ðŸ—¿", "ðŸŒ", "ðŸº", "ðŸ§­", "ðŸ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ™ï¸", "ðŸ“º", "âš”ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ§™", "â¤ï¸"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸŒ ", "ðŸ‘‘", "ðŸª", "ðŸ›"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ—', 'ðŸ’'], ['ðŸŽƒ', 'ðŸ’€', 'ðŸŽ„', 'ðŸ‘»', 'ðŸ•¸ï¸'], ['ðŸ‘”', 'ðŸ”«', 'ðŸ', 'ðŸ’¼', 'ðŸ•´ï¸'], ['ðŸ’Š', 'ðŸ’»', 'ðŸ•¶ï¸', 'ðŸ¤–', 'ðŸšª'], ['ðŸ—ºï¸', 'â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'â˜•'], ['ðŸ—¿', 'ðŸŒ', 'ðŸº', 'ðŸ§', 'ðŸ'], ['ðŸŽ', 'ðŸ’£', 'ðŸ™ï¸', 'ðŸ“º', 'âš”ï¸'], ['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'â¤ï¸'], ['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'], ['ðŸœï¸', 'ðŸŒ ', 'ðŸ‘‘', 'ðŸª', '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„', 'ðŸ‘»', 'ðŸ•¸ï¸'],
['ðŸ‘”', 'ðŸ”«', 'ðŸ', 'ðŸ’¼', 'ðŸ•´ï¸'],
['ðŸ’Š', 'ðŸ’»', 'ðŸ•¶ï¸', 'ðŸ¤–', 'ðŸšª'],
['ðŸ—ºï¸', 'â¤ï¸', 'âœˆï¸', 'ðŸŽ¶', 'â˜•'],
['ðŸ—¿', 'ðŸŒ', 'ðŸº', 'ðŸ§­', 'ðŸ'],
['ðŸŽ­', 'ðŸ’£', 'ðŸ™ï¸', 'ðŸ“º', 'âš”ï¸'],
['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'â¤ï¸'],
['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'],
['ðŸœï¸', 'ðŸŒ ', 'ðŸ‘‘', 'ðŸª', 'ðŸ›']]

What are the names of the movie titles?

Output

[
    "The Lion King",
    "The Nightmare Before Christmas",
    "The Godfather",
    "The Matrix",
    "Up",
    "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",
    "The Nightmare Before Christmas",
    "The Godfather",
    "The Matrix",
    "Up",
    "Indiana Jones",
    "V for Vendetta",
    "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

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„", "ðŸ’€", "ðŸ•·ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘©â€ðŸ‘§â€ðŸ‘¦", "ðŸ”«", "ðŸ", "ðŸ’¼", "ðŸš¬"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ’»", "ðŸ¤–", "ðŸ”«"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸ‡²ðŸ‡¦", "ðŸ•¶ï¸"],
  "Raiders of the Lost Ark": ["ðŸ—¿", "ðŸº", "ðŸ¦Ÿ", "ðŸ”«", "ðŸŒ´"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ”¥", "ðŸ—¡ï¸", "ðŸ“º", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "â¤ï¸", "ðŸ‘¹"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ‘Ÿ", "ðŸ“–"],
  "Dune": ["ðŸœï¸", "ðŸŒ¾", "ðŸ›", "ðŸ‘‘", "ðŸš€"]
}

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„", "ðŸ’€", "ðŸ•·ï¸"],
  "The Godfather": ["ðŸ‘¨â€ðŸ‘©â€ðŸ‘§â€ðŸ‘¦", "ðŸ”«", "ðŸ", "ðŸ’¼", "ðŸš¬"],
  "The Matrix": ["ðŸ’Š", "ðŸ•¶ï¸", "ðŸ’»", "ðŸ¤–", "ðŸ”«"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸ‡²ðŸ‡¦", "ðŸ•¶ï¸"],
  "Raiders of the Lost Ark": ["ðŸ—¿", "ðŸº", "ðŸ¦Ÿ", "ðŸ”«", "ðŸŒ´"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ”¥", "ðŸ—¡ï¸", "ðŸ“º", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "ðŸ—¡ï¸", "â¤ï¸", "ðŸ‘¹"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ‘Ÿ", "ðŸ“–"],
  "Dune": ["ðŸœï¸", "ðŸŒ¾", "ðŸ›", "ðŸ‘‘", "ðŸš€"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ—', 'ðŸ’'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸŽ„', 'ðŸ’€', 'ðŸ•·ï¸'], ['ðŸ”«', 'ðŸ', 'ðŸ’¼', 'ðŸš¬'], ['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ’»', 'ðŸ¤–', 'ðŸ”«'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸ‡²ðŸ‡¦', 'ðŸ•¶ï¸'], ['ðŸ—¿', 'ðŸº', 'ðŸ¦Ÿ', 'ðŸ”«', 'ðŸŒ´'], ['ðŸŽ', 'ðŸ”¥', 'ðŸ—¡ï¸', 'ðŸ“º', 'ðŸ‡¬ðŸ‡§'], ['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'â¤ï¸', 'ðŸ‘¹'], ['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“–'], ['ðŸœï¸', 'ðŸŒ¾', 'ðŸ›', '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„', 'ðŸ’€', 'ðŸ•·ï¸'],
['ðŸ”«', 'ðŸ', 'ðŸ’¼', 'ðŸš¬'],
['ðŸ’Š', 'ðŸ•¶ï¸', 'ðŸ’»', 'ðŸ¤–', 'ðŸ”«'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸ‡²ðŸ‡¦', 'ðŸ•¶ï¸'],
['ðŸ—¿', 'ðŸº', 'ðŸ¦Ÿ', 'ðŸ”«', 'ðŸŒ´'],
['ðŸŽ­', 'ðŸ”¥', 'ðŸ—¡ï¸', 'ðŸ“º', 'ðŸ‡¬ðŸ‡§'],
['ðŸ‘¸', 'ðŸ¤´', 'ðŸ—¡ï¸', 'â¤ï¸', 'ðŸ‘¹'],
['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“–'],
['ðŸœï¸', 'ðŸŒ¾', 'ðŸ›', 'ðŸ‘‘', 'ðŸš€']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "Pulp Fiction",
  "The Matrix",
  "Casablanca",
  "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",
  "The Nightmare Before Christmas",
  "Pulp Fiction",
  "The Matrix",
  "Casablanca",
  "Indiana Jones",
  "V for Vendetta",
  "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

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…", "ðŸŒ¿", "ðŸ—"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸ‘»", "ðŸ’€", "ðŸŽ„", "ðŸ•¸"],
  "The Godfather": ["ðŸ¤µ", "ðŸ", "ðŸ”«", "ðŸ•´ï¸", "ðŸ‡®ðŸ‡¹"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ’»", "ðŸ•´ï¸", "ðŸ”«"],
  "Casablanca": ["ðŸ•Œ", "ðŸŽ¶", "ðŸ’”", "âœˆï¸", "ðŸŒ†"],
  "Raiders of the Lost Ark": ["ðŸ§‘â€ðŸ«", "ðŸ—ºï¸", "ðŸº", "ðŸ", "âœˆï¸"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ”¥", "ðŸ‡¬ðŸ‡§", "âš”ï¸"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ§™", "ðŸŒ„"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸª", "ðŸ‘‘", "ðŸ›", "ðŸ—¡ï¸"]
}

Extract Json

I extracted the following JSON from that output:

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

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸ‘‘', 'ðŸŒ…', 'ðŸŒ¿', 'ðŸ—'], ['ðŸŽƒ', 'ðŸ‘»', 'ðŸ’€', 'ðŸŽ„', 'ðŸ•¸'], ['ðŸ¤µ', 'ðŸ', 'ðŸ”«', 'ðŸ•´ï¸', 'ðŸ‡®ðŸ‡¹'], ['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ’»', 'ðŸ•´ï¸', 'ðŸ”«'], ['ðŸ•Œ', 'ðŸŽ¶', 'ðŸ’”', 'âœˆï¸', 'ðŸŒ†'], ['ðŸ—ºï¸', 'ðŸº', 'ðŸ', 'âœˆï¸'], ['ðŸŽ', 'ðŸ’£', 'ðŸ”¥', 'ðŸ‡¬ðŸ‡§', 'âš”ï¸'], ['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'ðŸŒ„'], ['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'], ['ðŸœï¸', 'ðŸª', 'ðŸ‘‘', 'ðŸ›', 'ðŸ—¡ï¸']]

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‘»', 'ðŸ’€', 'ðŸŽ„', 'ðŸ•¸'],
['ðŸ¤µ', 'ðŸ', 'ðŸ”«', 'ðŸ•´ï¸', 'ðŸ‡®ðŸ‡¹'],
['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ’»', 'ðŸ•´ï¸', 'ðŸ”«'],
['ðŸ•Œ', 'ðŸŽ¶', 'ðŸ’”', 'âœˆï¸', 'ðŸŒ†'],
['ðŸ—ºï¸', 'ðŸº', 'ðŸ', 'âœˆï¸'],
['ðŸŽ­', 'ðŸ’£', 'ðŸ”¥', 'ðŸ‡¬ðŸ‡§', 'âš”ï¸'],
['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'ðŸŒ„'],
['ðŸš—', 'â°', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'],
['ðŸœï¸', 'ðŸª', 'ðŸ‘‘', 'ðŸ›', 'ðŸ—¡ï¸']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Aladdin",
  "Indiana Jones",
  "V for Vendetta",
  "The Lord of the Rings",
  "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",
  "Aladdin",
  "Indiana Jones",
  "V for Vendetta",
  "The Lord of the Rings",
  "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—", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸŽ„", "ðŸ‘»", "ðŸ•¸ï¸", "ðŸ’€"],
  "The Godfather": ["ðŸ•´ï¸", "ðŸ’¼", "ðŸ”«", "ðŸ", "ðŸš¬"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ’»", "ðŸ¤–", "ðŸšª"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸŒ†", "ðŸ‡²ðŸ‡¦"],
  "Raiders of the Lost Ark": ["ðŸ§³", "âš”ï¸", "ðŸ—ºï¸", "ðŸ", "ðŸº"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ”ª", "ðŸ›ï¸", "ðŸ“°"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ§™", "â¤ï¸"],
  "Back to the Future": ["â°", "ðŸš—", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸ›", "ðŸ‘‘", "ðŸŒ ", "ðŸª"]
}

Extract Json

I extracted the following JSON from that output:

{
  "The Lion King": ["ðŸ¦", "ðŸŒ…", "ðŸ‘‘", "ðŸ—", "ðŸ’"],
  "The Nightmare Before Christmas": ["ðŸŽƒ", "ðŸŽ„", "ðŸ‘»", "ðŸ•¸ï¸", "ðŸ’€"],
  "The Godfather": ["ðŸ•´ï¸", "ðŸ’¼", "ðŸ”«", "ðŸ", "ðŸš¬"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ’»", "ðŸ¤–", "ðŸšª"],
  "Casablanca": ["â¤ï¸", "âœˆï¸", "ðŸŽ¹", "ðŸŒ†", "ðŸ‡²ðŸ‡¦"],
  "Raiders of the Lost Ark": ["ðŸ§³", "âš”ï¸", "ðŸ—ºï¸", "ðŸ", "ðŸº"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸ”ª", "ðŸ›ï¸", "ðŸ“°"],
  "The Princess Bride": ["ðŸ‘¸", "ðŸ¤´", "âš”ï¸", "ðŸ§™", "â¤ï¸"],
  "Back to the Future": ["â°", "ðŸš—", "âš¡", "ðŸ‘Ÿ", "ðŸ“…"],
  "Dune": ["ðŸœï¸", "ðŸ›", "ðŸ‘‘", "ðŸŒ ", "ðŸª"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ—', 'ðŸ’'], ['ðŸŽƒ', 'ðŸŽ„', 'ðŸ‘»', 'ðŸ•¸ï¸', 'ðŸ’€'], ['ðŸ•´ï¸', 'ðŸ’¼', 'ðŸ”«', 'ðŸ', 'ðŸš¬'], ['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ’»', 'ðŸ¤–', 'ðŸšª'], ['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸŒ†', 'ðŸ‡²ðŸ‡¦'], ['ðŸ§³', 'âš”ï¸', 'ðŸ—ºï¸', 'ðŸ', 'ðŸº'], ['ðŸŽ', 'ðŸ’£', 'ðŸ”ª', 'ðŸ›ï¸', 'ðŸ“°'], ['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'â¤ï¸'], ['â°', 'ðŸš—', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'], ['ðŸœï¸', 'ðŸ›', 'ðŸ‘‘', 'ðŸŒ ', 'ðŸª']]

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', 'ðŸŽ„', 'ðŸ‘»', 'ðŸ•¸ï¸', 'ðŸ’€'],
['ðŸ•´ï¸', 'ðŸ’¼', 'ðŸ”«', 'ðŸ', 'ðŸš¬'],
['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ’»', 'ðŸ¤–', 'ðŸšª'],
['â¤ï¸', 'âœˆï¸', 'ðŸŽ¹', 'ðŸŒ†', 'ðŸ‡²ðŸ‡¦'],
['ðŸ§³', 'âš”ï¸', 'ðŸ—ºï¸', 'ðŸ', 'ðŸº'],
['ðŸŽ­', 'ðŸ’£', 'ðŸ”ª', 'ðŸ›ï¸', 'ðŸ“°'],
['ðŸ‘¸', 'ðŸ¤´', 'âš”ï¸', 'ðŸ§™', 'â¤ï¸'],
['â°', 'ðŸš—', 'âš¡', 'ðŸ‘Ÿ', 'ðŸ“…'],
['ðŸœï¸', 'ðŸ›', 'ðŸ‘‘', 'ðŸŒ ', 'ðŸª']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "Pulp Fiction",
  "The Matrix",
  "Casablanca",
  "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",
  "The Nightmare Before Christmas",
  "Pulp Fiction",
  "The Matrix",
  "Casablanca",
  "Indiana Jones",
  "V for Vendetta",
  "The Princess Bride",
  "Back to the Future",
  "Dune"
]

PyFunc

OK Resulting in output: True