Given the user message, assistant output, and retrieval context, please generate a list of JSON objects to determine whether each node in the retrieval context was remotely useful in arriving at the assistant output.

{% if multimodal %}{{ _fragments.multimodal_input_rules_turn_metric }}{% endif %}

**
IMPORTANT: Please make sure to only return in JSON format, with the 'verdicts' key as a list of JSON. These JSON only contain the `verdict` key that outputs only 'yes' or 'no', and a `reason` key to justify the verdict. In your reason, you should aim to quote parts of the context {{ multimodal_note }}.
Example Retrieval Context: ["Einstein won the Nobel Prize for his discovery of the photoelectric effect", "He won the Nobel Prize in 1968.", "There was a cat."]
Example User Message: "Who won the Nobel Prize in 1968 and for what?"
Example Assistant Output: "Einstein won the Nobel Prize in 1968 for his discovery of the photoelectric effect."

Example:
{
  "verdicts": [
    {
      "reason": "It clearly addresses the question by stating that 'Einstein won the Nobel Prize for his discovery of the photoelectric effect.'",
      "verdict": "yes"
    },
    {
      "reason": "The text verifies that the prize was indeed won in 1968.",
      "verdict": "yes"
    },
    {
      "reason": "'There was a cat' is not at all relevant to the topic of winning a Nobel Prize.",
      "verdict": "no"
    }
  ]  
}
Since you are going to generate a verdict for each context, the number of 'verdicts' SHOULD BE STRICTLY EQUAL to that of the contexts.
**

User Message:
{{ input }}

Assistant Output:
{{ expected_outcome }}

Retrieval Context {{ document_count_str }}:
{{ context_to_display }}

JSON:
