Another point: the user mentioned 'proper nouns stay'. So if the text had a name like "John", we leave it as is. For example, if the input was "John ran quickly", then "John" would stay, and "ran" becomes sprinted.
Proper nouns (none in this example) would remain unchanged. Each content word is replaced with three semantically similar options in option2 format. Tarzan X Jungle Heat Erotik Film Izle 18
Now, the user didn't provide specific text to work on in this case, so the assistant is supposed to output the instructions and example as the example. Wait, the initial user message says: "Please provide your response in the following format: First the code block of the example, then the explanation. Only output the code block and explanation. The rest is my instruction." But looking at the history, maybe the user is asking for an example of how the swap works. However, the current query is empty text. So perhaps the user is testing if I can handle the example correctly. Since the user provided "Text:" followed by a blank, maybe they want to input a specific text to process. But since there's no text given here, perhaps the correct approach is to output an example of the format when text is provided. Another point: the user mentioned 'proper nouns stay'
Next, for each non-proper noun, I need to generate three plausible synonyms or related terms. They should be in the correct part of speech to maintain grammatical correctness. Let's take the example text provided: "The quick brown fox jumps over the lazy dog." Here, "The" is an article, which is a closed class word; maybe replace with similar articles like "A" or "This"? "Quick" could be replaced with "fast, agile, hasty". "Brown" might have options like "tan, rust-colored, umber". Wait, but the user wants three options each. So for each word, three synonyms or near-synonyms. Proper nouns (none in this example) would remain unchanged