Raw LLM Responses

Inspect the exact model output for any coded comment.

Look up by comment ID
Random samples — click to inspect
G Most people don't know their purpose, and most are unaware of all the layers of … ytc_UgxWEeaDO… G For those of us who are older enough to remember the classic Stepford Wives mov… ytc_Ugy2cVHAf… G But it sounds like poem when I did it, even though pass ai detection, periods ar… ytc_UgzTqUHw6… G You can always go back to basics - opt out of AI tech and focus on providing for… ytc_UgwQfAejP… G “Not human kids” meta ai: humans are white and the ones that are black aren’t so… ytc_Ugw8fVHpC… G "it cant be AI i know a real person when i see one. its AI yea we're cooked"… ytc_UgzeMlzsY… G Our overlords spend all their time showing us how they're complete tyrants who d… ytc_Ugy2bP90e… G That only solves the financial problem. But then what? We already have mass obes… ytr_UgwXehYcH…
Comment
On hallucination, retrieval-augmented generation (RAG) pipelines are used which add processing steps before generation to incorporate relevant context/information into the LLM's response. This is most effective in narrow, domain-specific chatbots; its pretty easy to set up a RAG pipeline to search through a given companies' terms of use and similar documents (if pre-processed, much harder if not) to create a customer service chatbot. It's more challenging to use this in generalized models, as the requisite knowledge base is far larger, but RAG is why LLMs frequently attach references to their claims now. There are risks of incorporating erroneous information into the underlying knowledge base and retrieving irrelevant information, but RAG remains an effective method of managing hallucination.
youtube AI Moral Status 2025-11-16T02:0…
Coding Result
DimensionValue
Responsibilitynone
Reasoningunclear
Policyunclear
Emotionindifference
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
[ {"id":"ytc_UgxBYclTZsCOKjvuPMt4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"}, {"id":"ytc_UgwdZZ-9k8WO7zZFk7J4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"mixed"}, {"id":"ytc_UgyxHbnWtfzT3TDCbt94AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"}, {"id":"ytc_UgwNfQ8k0NyXzuuIlcF4AaABAg","responsibility":"company","reasoning":"consequentialist","policy":"unclear","emotion":"fear"}, {"id":"ytc_UgxkUKT3mae-6MZR7ld4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"approval"}, {"id":"ytc_UgylOyQKmdf4sW81H-Z4AaABAg","responsibility":"ai_itself","reasoning":"consequentialist","policy":"none","emotion":"approval"}, {"id":"ytc_UgyFZJz845gFM8fe5-B4AaABAg","responsibility":"distributed","reasoning":"mixed","policy":"unclear","emotion":"fear"}, {"id":"ytc_UgziZ9q5yLVJqu2ds714AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"}, {"id":"ytc_UgyyiATN_IfHVFxsn514AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"indifference"}, {"id":"ytc_UgzNrBxdB_swATDSVZl4AaABAg","responsibility":"none","reasoning":"unclear","policy":"unclear","emotion":"mixed"} ]