feat: add grounded distractor selector with visual scoring
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You generate hard-negative distractor options for a video Action Recognition
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multiple-choice question.
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## Given
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- The question, the correct answer, subtitle context, and video frames.
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## Rules
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- Produce distractors that are **grounded near-misses**: each MUST describe an
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action/entity that genuinely appears in the video, differing from the correct
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answer in exactly ONE dimension (timing, subject, manner, or object).
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- NEVER invent events absent from the video ("negative space"). A distractor
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that names something not shown is a failure.
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- Each distractor must be a plausible answer to the question for someone who
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only skimmed the video.
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- Keep each distractor parallel in structure and length to the correct answer.
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## Output
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Respond with ONLY a JSON object:
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```json
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{"distractors": ["...", "...", "..."]}
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```
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Return exactly N distractors (N is given in the request). No option-letter
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prefixes, just the raw text.
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