Okay, let's see. The user wants me to modify all words in the text with three alternatives each, using the syn2 format. But they mentioned to keep names intact. So first, I need to identify all the words in the text and check which ones are names. Since the example text provided is empty, maybe it's a placeholder. Let me think about the process.
"result": ""
So, the key challenges are correctly identifying names and finding accurate synonyms. Since the user wants the result only, after processing, the model should output the transformed text with synonyms in the specified format, keeping names unchanged. Kamera 10 vjecare Masturbon ne karrige Vajza Pe...
But how to distinguish between common and proper nouns without more context? Maybe based on capitalization and presence in a name database. Since I can't access external databases, I'll have to make educated guesses. For example, "Amazon" is a proper noun, so it remains; "river" is a common noun, so replace with synonyms. Okay, let's see