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Another thing is the synonyms need to be accurate and appropriate for the term. Using a thesaurus API or a synonym database would help, but as a manual process, I need to think of three suitable ones.

Now, applying this to an example input. Suppose the input is "I bought a new product from Apple." The output should be "I acquired a new item from Apple." cassandra busty anal

Yes, that makes sense. The brand name "Apple" is preserved, and other terms are replaced with synonyms. Another thing is the synonyms need to be

First, I need to process each term in the input text, replace it with three synonyms separated by vertical bars, and enclose them in curly braces. But brand names should remain unchanged. So, I need to identify which terms are brand names. However, in the example given, the input was just "product" and the output was the synonym replacements. So maybe the input will have specific brand names, and I need to leave those as they are. Suppose the input is "I bought a new product from Apple

Wait, but the user hasn't provided any actual text to process. The input text is just a line with "text:" followed by "..." and then the task description. Hmm, maybe that's a mistake. The task section says "Return text only." So perhaps in the actual scenario, the user will input some text with terms to replace, and brand names to preserve.

1. Parse the input text into individual terms. 2. For each term, determine if it's a brand name. - How? Maybe check against a predefined list of brand names. If not found, proceed to synonym replacement. 3. For non-brand terms, generate three synonyms. 4. Replace the term with synonym3. 5. Combine the processed terms back into the text, maintaining original order and punctuation.

For proper nouns like "United Nations", they remain as is.