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": ["ð ", "ð", "ðĄ", "ðŽ", "ðģ"],
"Toy Story": ["ð", "âïļ,", "ðĪ", "ð―", "ð"]}
|
.
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": ["ð ", "ð", "ðĄ", "ðŽ", "ðģ"],
"Toy Story": ["ð", "âïļ,", "ðĪ", "ð―", "ð"]}
|
.
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
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12 | {
"The Lion King": ["ðĶ", "ð", "ð
", "ðū", "ðķ"],
"The Nightmare Before Christmas": ["ð", "ðŧ", "ð", "ð", "ð"],
"The Godfather": ["ðĪ", "ðŦ", "ð", "ðĩ", "ðŽ"],
"The Matrix": ["ð", "ðķ", "ðĩ", "ðī", "ðŧ"],
"Casablanca": ["ð", "âĨ", "â", "ðķ", "ð"],
"Raiders of the Lost Ark": ["ðĻ", "ðš", "ðš", "ð", "ðĶ"],
"V for Vendetta": ["ð", "ðĢ", "ðŽ", "ðĨ", "ðģ"],
"The Princess Bride": ["ðļ", "ðĪī", "â", "âĨ", "ð"],
"Back to the Future": ["â°", "ð", "âĄ", "ðĄ", "ð°"],
"Dune": ["ð", "ðŠą", "â", "ðŦ", "ð"]
}
|
Extract Json
I extracted the following JSON from that output:
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12 | {
"The Lion King": ["ðĶ", "ð", "ð
", "ðū", "ðķ"],
"The Nightmare Before Christmas": ["ð", "ðŧ", "ð", "ð", "ð"],
"The Godfather": ["ðĪ", "ðŦ", "ð", "ðĩ", "ðŽ"],
"The Matrix": ["ð", "ðķ", "ðĩ", "ðī", "ðŧ"],
"Casablanca": ["ð", "âĨ", "â", "ðķ", "ð"],
"Raiders of the Lost Ark": ["ðĻ", "ðš", "ðš", "ð", "ðĶ"],
"V for Vendetta": ["ð", "ðĢ", "ðŽ", "ðĨ", "ðģ"],
"The Princess Bride": ["ðļ", "ðĪī", "â", "âĨ", "ð"],
"Back to the Future": ["â°", "ð", "âĄ", "ðĄ", "ð°"],
"Dune": ["ð", "ðŠą", "â", "ðŦ", "ð"]
}
|
PyFunc
Resulting in output:
[['ðĶ', 'ð', 'ð
', 'ðū', 'ðķ'],
['ð', 'ðŧ', 'ð', 'ð', 'ð'],
['ðĪ', 'ðŦ', 'ð', 'ðĩ', 'ðŽ'],
['ð', 'ðķ', 'ðĩ', 'ðī', 'ðŧ'],
['ð', 'âĨ', 'â', 'ðķ', 'ð'],
['ðĻ', 'ðš', 'ðš', 'ð', 'ðĶ'],
['ð', 'ðĢ', 'ðŽ', 'ðĨ', 'ðģ'],
['ðļ', 'ðĪī', 'â', 'âĨ', 'ð'],
['â°', 'ð', 'âĄ', 'ðĄ', 'ð°'],
['ð', 'ðŠą', 'â', 'ðŦ', 'ð']]
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:
| ['ð', 'ðŧ', 'ð', 'ð', 'ð'],
['ðĪ', 'ðŦ', 'ð', 'ðĩ', 'ðŽ'],
['ð', 'ðķ', 'ðĩ', 'ðī', 'ðŧ'],
['ð', 'âĨ', 'â', 'ðķ', 'ð'],
['ðĻ', 'ðš', 'ðš', 'ð', 'ðĶ'],
['ð', 'ðĢ', 'ðŽ', 'ðĨ', 'ðģ'],
['ðļ', 'ðĪī', 'â', 'âĨ', 'ð'],
['â°', 'ð', 'âĄ', 'ðĄ', 'ð°'],
['ð', 'ðŠą', 'â', 'ðŦ', 'ð']]
|
What are the names of the movie titles?
Output
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12 | [
"The Lion King",
"The Nightmare Before Christmas",
"The Godfather",
"The Matrix",
"La La Land",
"Raiders of the Lost Ark",
"V for Vendetta",
"The Princess Bride",
"Back to the Future",
"Dune"
]
|
Extract Json
I extracted the following JSON from that output:
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12 | [
"The Lion King",
"The Nightmare Before Christmas",
"The Godfather",
"The Matrix",
"La La Land",
"Raiders of the Lost Ark",
"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": ["ð ", "ð", "ðĄ", "ðŽ", "ðģ"],
"Toy Story": ["ð", "âïļ,", "ðĪ", "ð―", "ð"]}
|
.
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": ["ð ", "ð", "ðĄ", "ðŽ", "ðģ"],
"Toy Story": ["ð", "âïļ,", "ðĪ", "ð―", "ð"]}
|
.
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
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12 | {
"The Lion King": ["ðĶ", "ð", "ð
", "ðŋ"],
"The Nightmare Before Christmas": ["ð", "ðŧ", "ð", "ðļ", "ð·"],
"The Godfather": ["ðŦ", "ðž", "ð", "ð"],
"The Matrix": ["ð", "ðĩ", "ðķ", "ðŧ"],
"Casablanca": ["â", "âĪïļ", "â", "ð"],
"Raiders of the Lost Ark": ["ðš", "ðš", "ðĢ", "ðĶ", "ð"],
"V for Vendetta": ["ð", "ðĨ", "ðĢ", "ðĄ"],
"The Princess Bride": ["ðĪš", "âĪïļ", "â", "ð", "ð°"],
"Back to the Future": ["â", "âĄ", "ð", "âģ"],
"Dune": ["ð", "ð", "â", "ð"]
}
|
Extract Json
I extracted the following JSON from that output:
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12 | {
"The Lion King": ["ðĶ", "ð", "ð
", "ðŋ"],
"The Nightmare Before Christmas": ["ð", "ðŧ", "ð", "ðļ", "ð·"],
"The Godfather": ["ðŦ", "ðž", "ð", "ð"],
"The Matrix": ["ð", "ðĩ", "ðķ", "ðŧ"],
"Casablanca": ["â", "âĪïļ", "â", "ð"],
"Raiders of the Lost Ark": ["ðš", "ðš", "ðĢ", "ðĶ", "ð"],
"V for Vendetta": ["ð", "ðĨ", "ðĢ", "ðĄ"],
"The Princess Bride": ["ðĪš", "âĪïļ", "â", "ð", "ð°"],
"Back to the Future": ["â", "âĄ", "ð", "âģ"],
"Dune": ["ð", "ð", "â", "ð"]
}
|
PyFunc
Resulting in output:
[['ðĶ', 'ð', 'ð
', 'ðŋ'],
['ð', 'ðŧ', 'ð', 'ðļ', 'ð·'],
['ðŦ', 'ðž', 'ð', 'ð'],
['ð', 'ðĩ', 'ðķ', 'ðŧ'],
['â', 'âĪïļ', 'â', 'ð'],
['ðš', 'ðš', 'ðĢ', 'ðĶ', 'ð'],
['ð', 'ðĨ', 'ðĢ', 'ðĄ'],
['ðĪš', 'âĪïļ', 'â', 'ð', 'ð°'],
['â', 'âĄ', 'ð', 'âģ'],
['ð', 'ð', 'â', 'ð']]
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:
| ['ð', 'ðŧ', 'ð', 'ðļ', 'ð·'],
['ðŦ', 'ðž', 'ð', 'ð'],
['ð', 'ðĩ', 'ðķ', 'ðŧ'],
['â', 'âĪïļ', 'â', 'ð'],
['ðš', 'ðš', 'ðĢ', 'ðĶ', 'ð'],
['ð', 'ðĨ', 'ðĢ', 'ðĄ'],
['ðĪš', 'âĪïļ', 'â', 'ð', 'ð°'],
['â', 'âĄ', 'ð', 'âģ'],
['ð', 'ð', 'â', 'ð']]
|
What are the names of the movie titles?
Output
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12 | [
"The Lion King",
"Halloween",
"The Godfather",
"The Matrix",
"Up in the Air",
"Raiders of the Lost Ark",
"V for Vendetta",
"The Princess Bride",
"Back to the Future",
"Dune"
]
|
Extract Json
I extracted the following JSON from that output:
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12 | [
"The Lion King",
"Halloween",
"The Godfather",
"The Matrix",
"Up in the Air",
"Raiders of the Lost Ark",
"V for Vendetta",
"The Princess Bride",
"Back to the Future",
"Dune"
]
|
PyFunc
OK
Resulting in output:
True