@@ -82,7 +82,6 @@ def _(mo):
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2. **Process:**
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2. **Process:**
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* The LLM analyzes each transcript segment-by-segment.
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* The LLM analyzes each transcript segment-by-segment.
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* It extracts specific quotes that match a Theme Definition.
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* It extracts specific quotes that match a Theme Definition.
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* **Multi-Theme Handling:** If a quote applies to multiple themes, it is tagged with *all* relevant themes. In the dataset, this creates multiple entries (one per theme) so the quote informs the synthesis of each relevant topic.
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* **Granular Sentiment Analysis:** For each quote, the model identifies:
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* **Granular Sentiment Analysis:** For each quote, the model identifies:
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* **Subject:** The specific topic/object being discussed (e.g., "Login Flow", "Brand Tone").
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* **Subject:** The specific topic/object being discussed (e.g., "Login Flow", "Brand Tone").
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* **Sentiment:** Positive / Neutral / Negative.
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* **Sentiment:** Positive / Neutral / Negative.
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