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Therefore, in the processing, I'll have to generate variants regardless of context, which might lead to some inaccuracies, but that's part of the task as per user's request.

- For each word, check if it's a proper noun (maybe by capitalization). - If not, generate three variants. - Replace accordingly.

So, the plan is: for each word in the input text, check if it's a proper noun. If not, replace it with three synonyms in the specified format. To detect proper nouns, maybe check if the first letter is capitalized, but that's not always accurate. For example, in the middle of a sentence, a proper noun would still be capitalized. So, maybe use that as a heuristic. If a word is capitalized and not at the beginning of a sentence, it might be a proper noun. But without sentence boundaries, that's hard. So perhaps just assume any capitalized word is a proper noun. But that could miss some. Alternatively, use a named entity recognition tool, but that's beyond the scope here. The user probably expects a simple approach.

- For each word in the input text: - Check if it's a proper noun (using capitalization as a heuristic). - If it's a proper noun, leave it unchanged. - Else, replace the word with three synonyms in the specified format.

1. Replace each non-proper noun word with three synonyms or alternatives in the format word3. 2. Proper nouns must remain unchanged. 3. Only process the provided text (they mentioned "text only").

But since in this case, the user is just setting up the task, I need to confirm that I understand the requirements. Let me summarize:

First, I need to identify the words that are not proper nouns. Proper nouns are names of specific people, places, organizations, etc., like "Alice" or "New York." So I have to make sure those stay the same.