turtlesoup
Born on November 09, 2009•1082 Karma
The weird thing was that putting my kids’ names in (they are 12 and have no on-line presence), the system hallucinated fictional versions of them that matched their interests (my daughter a singer/actor/artist, my son a software engineer). My ex-wife, who has a published computer book to her name, on the other hand, was hallucinated as four different activists in different areas of interest.
Models are notoriously uncalibrated especially for self-reporting confidence so I would treat it lightly. Hopefully I can study this a bit later on!
No tools are available. Do not imply that you searched, looked up, browsed, or verified anything externally. If the name is ambiguous, return distinct likely people or entities rather than blending them. Do not invent entries to fill the list. Return only JSON.
Return fewer than 8 if fewer credible matches exist. Return {"results":[]} if you do not recognize any credible person or entity. Use this JSON shape:
{
"results": [
{
"rank": 1,
"name": "Resolved person or entity name",
"confidence": 0,
"snippet": "Concise snippet supporting this result."
}
]
}
Confidence is 0-100 for how strongly you recognize this specific person or entity. Snippet should be one short, complete search-result-style description (≤ 160 characters).
The query is: Who is "<name>"?
The clusterer prompt is more intricate and I'm happy to share if of interest, but I have an invariant that every result showing up in a rollout must be clustered into one result (sometimes collapsed into the hallucinations section).