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", "ðŸŽ„", "ðŸŒ™", "ðŸ‘»", "ðŸ•¸ï¸"],
  "The Godfather": ["ðŸ‘”", "ðŸ", "ðŸ•¶ï¸", "ðŸ”«", "ðŸŽ©"],
  "The Matrix": ["ðŸ•¶ï¸", "ðŸ’Š", "ðŸ”«", "ðŸ–¥ï¸", "ðŸ•³ï¸"],
  "Casablanca": ["âœˆï¸", "â¤ï¸", "ðŸŒ†", "ðŸŽ·", "â˜•"],
  "Raiders of the Lost Ark": ["ðŸº", "ðŸ§­", "ðŸ—ºï¸", "âš”ï¸", "ðŸ—¡ï¸"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ’£", "ðŸŒ¹", "ðŸ‡¬ðŸ‡§", "ðŸ—¡ï¸"],
  "The Princess Bride": ["âš”ï¸", "ðŸ‘¸", "ðŸ’–", "ðŸ´", "ðŸŒ¹"],
  "Back to the Future": ["ðŸš—", "â°", "âš¡", "ðŸ•°ï¸", "ðŸ•¶ï¸"],
  "Dune": ["ðŸœï¸", "ðŸ›", "âœ¨", "ðŸ‘‘", "ðŸŒŒ"]
}

Extract Json

I extracted the following JSON from that output:

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

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸŒ…', 'ðŸ‘‘', 'ðŸ¾', 'ðŸŒ'], ['ðŸŽƒ', 'ðŸŽ„', 'ðŸŒ™', 'ðŸ‘»', 'ðŸ•¸ï¸'], ['ðŸ‘”', 'ðŸ', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸŽ©'], ['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ”«', 'ðŸ–¥ï¸', 'ðŸ•³ï¸'], ['âœˆï¸', 'â¤ï¸', 'ðŸŒ†', 'ðŸŽ·', 'â˜•'], ['ðŸº', 'ðŸ§', 'ðŸ—ºï¸', 'âš”ï¸', 'ðŸ—¡ï¸'], ['ðŸŽ', 'ðŸ’£', 'ðŸŒ¹', 'ðŸ‡¬ðŸ‡§', 'ðŸ—¡ï¸'], ['âš”ï¸', 'ðŸ‘¸', 'ðŸ’–', 'ðŸ´', 'ðŸŒ¹'], ['ðŸš—', 'â°', 'âš¡', 'ðŸ•°ï¸', 'ðŸ•¶ï¸'], ['ðŸœï¸', 'ðŸ›', 'âœ¨', 'ðŸ‘‘', 'ðŸŒŒ']]

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„', 'ðŸŒ™', 'ðŸ‘»', 'ðŸ•¸ï¸'],
['ðŸ‘”', 'ðŸ', 'ðŸ•¶ï¸', 'ðŸ”«', 'ðŸŽ©'],
['ðŸ•¶ï¸', 'ðŸ’Š', 'ðŸ”«', 'ðŸ–¥ï¸', 'ðŸ•³ï¸'],
['âœˆï¸', 'â¤ï¸', 'ðŸŒ†', 'ðŸŽ·', 'â˜•'],
['ðŸº', 'ðŸ§­', 'ðŸ—ºï¸', 'âš”ï¸', 'ðŸ—¡ï¸'],
['ðŸŽ­', 'ðŸ’£', 'ðŸŒ¹', 'ðŸ‡¬ðŸ‡§', 'ðŸ—¡ï¸'],
['âš”ï¸', 'ðŸ‘¸', 'ðŸ’–', 'ðŸ´', 'ðŸŒ¹'],
['ðŸš—', 'â°', 'âš¡', 'ðŸ•°ï¸', 'ðŸ•¶ï¸'],
['ðŸœï¸', 'ðŸ›', 'âœ¨', 'ðŸ‘‘', 'ðŸŒŒ']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Sleepless in Seattle",
  "Indiana Jones",
  "Shakespeare in Love",
  "Beauty and the Beast",
  "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",
  "Sleepless in Seattle",
  "Indiana Jones",
  "Shakespeare in Love",
  "Beauty and the Beast",
  "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", "ðŸŽ„", "ðŸ•·", "ðŸ‘»", "ðŸ¦‡"],
  "The Godfather": ["ðŸ", "ðŸ”«", "ðŸ’¼", "ðŸ•¶", "ðŸ‘”"],
  "The Matrix": ["ðŸ•¶", "ðŸ’Š", "ðŸŒ", "ðŸ¤–", "ðŸ•³"],
  "Casablanca": ["ðŸŽ¥", "ðŸŒ´", "âœˆ", "ðŸ’”", "ðŸ•Š"],
  "Raiders of the Lost Ark": ["ðŸ—º", "ðŸº", "ðŸ¹", "ðŸ›¡", "ðŸœ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ•¶", "ðŸ—¡", "ðŸ”¥", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["âš”", "ðŸ‘¸", "ðŸ‰", "ðŸ°", "ðŸŒ¹"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸš²", "ðŸ•°"],
  "Dune": ["ðŸœ", "ðŸ›", "ðŸ‘½", "ðŸ‘‘", "ðŸŒ€"]
}

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‘»", "ðŸ¦‡"],
  "The Godfather": ["ðŸ", "ðŸ”«", "ðŸ’¼", "ðŸ•¶", "ðŸ‘”"],
  "The Matrix": ["ðŸ•¶", "ðŸ’Š", "ðŸŒ", "ðŸ¤–", "ðŸ•³"],
  "Casablanca": ["ðŸŽ¥", "ðŸŒ´", "âœˆ", "ðŸ’”", "ðŸ•Š"],
  "Raiders of the Lost Ark": ["ðŸ—º", "ðŸº", "ðŸ¹", "ðŸ›¡", "ðŸœ"],
  "V for Vendetta": ["ðŸŽ­", "ðŸ•¶", "ðŸ—¡", "ðŸ”¥", "ðŸ‡¬ðŸ‡§"],
  "The Princess Bride": ["âš”", "ðŸ‘¸", "ðŸ‰", "ðŸ°", "ðŸŒ¹"],
  "Back to the Future": ["ðŸš—", "â³", "âš¡", "ðŸš²", "ðŸ•°"],
  "Dune": ["ðŸœ", "ðŸ›", "ðŸ‘½", "ðŸ‘‘", "ðŸŒ€"]
}

PyFunc

Resulting in output: [['ðŸ¦', 'ðŸ‘‘', 'ðŸŒ…', 'ðŸ˜', 'ðŸ¦“'], ['ðŸŽƒ', 'ðŸŽ„', 'ðŸ•·', 'ðŸ‘»', 'ðŸ¦‡'], ['ðŸ', 'ðŸ”«', 'ðŸ’¼', 'ðŸ•¶', 'ðŸ‘”'], ['ðŸ•¶', 'ðŸ’Š', 'ðŸŒ', 'ðŸ¤–', 'ðŸ•³'], ['ðŸŽ¥', 'ðŸŒ´', 'âœˆ', 'ðŸ’”', 'ðŸ•Š'], ['ðŸ—º', 'ðŸº', 'ðŸ¹', 'ðŸ›¡', 'ðŸœ'], ['ðŸŽ', 'ðŸ•¶', 'ðŸ—¡', 'ðŸ”¥', 'ðŸ‡¬ðŸ‡§'], ['âš”', 'ðŸ‘¸', 'ðŸ‰', 'ðŸ°', 'ðŸŒ¹'], ['ðŸš—', 'â³', 'âš¡', 'ðŸš²', 'ðŸ•°'], ['ðŸœ', 'ðŸ›', 'ðŸ‘½', 'ðŸ‘‘', 'ðŸŒ€']]

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‘»', 'ðŸ¦‡'],
['ðŸ', 'ðŸ”«', 'ðŸ’¼', 'ðŸ•¶', 'ðŸ‘”'],
['ðŸ•¶', 'ðŸ’Š', 'ðŸŒ', 'ðŸ¤–', 'ðŸ•³'],
['ðŸŽ¥', 'ðŸŒ´', 'âœˆ', 'ðŸ’”', 'ðŸ•Š'],
['ðŸ—º', 'ðŸº', 'ðŸ¹', 'ðŸ›¡', 'ðŸœ'],
['ðŸŽ­', 'ðŸ•¶', 'ðŸ—¡', 'ðŸ”¥', 'ðŸ‡¬ðŸ‡§'],
['âš”', 'ðŸ‘¸', 'ðŸ‰', 'ðŸ°', 'ðŸŒ¹'],
['ðŸš—', 'â³', 'âš¡', 'ðŸš²', 'ðŸ•°'],
['ðŸœ', 'ðŸ›', 'ðŸ‘½', 'ðŸ‘‘', 'ðŸŒ€']]

What are the names of the movie titles?

Output

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Up",
  "Indiana Jones: Raiders of the Lost Ark",
  "James Bond",
  "Frozen",
  "Back to the Future",
  "Star Wars"
]

Extract Json

I extracted the following JSON from that output:

[
  "The Lion King",
  "The Nightmare Before Christmas",
  "The Godfather",
  "The Matrix",
  "Up",
  "Indiana Jones: Raiders of the Lost Ark",
  "James Bond",
  "Frozen",
  "Back to the Future",
  "Star Wars"
]

PyFunc

OK Resulting in output: False