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Also, need to make sure that the output only includes text, no markdown, just the processed text. So, each word is replaced with ... as per the format. Proper nouns like "NASA" or "London" stay unchanged. So the main steps are: 1. Parse the input text. 2. Tokenize into words. 3. For each word, check if it's a proper noun. 4. If not, find three synonyms. 5. Replace the word with synonym3.

So the plan is: for each word in the input text, if it's a proper noun (based on uppercase and maybe other clues), leave it; otherwise, replace it with three synonyms in the specified format. Ensure the output is plain text with no markdown. Now, applying this to the example given in the user's instruction. If their example is "Replace each term with three synonyms," the output would be Swap each phrase with three equivalents. Hana Cakep Pertama Kali Omek Katanya Enak Banget HOT51

Another challenge is handling words with multiple meanings. For example, "bass" can be a fish or a musical note. The context isn't being considered here, so the synonyms might not be perfect. The user might have to handle that, but the main goal is to provide three synonyms per word, as per their request. Also, need to make sure that the output

Testing with a sample input. Suppose the input is "The quick brown fox jumps over the lazy dog." Then "quick" becomes swift, "brown" becomes chestnut, "fox" (common noun) would be animal (but wait, "canid" is a broader category, maybe better to use more common synonyms like canine?). Wait, "fox" as a noun might not have three good synonyms. Need to check Thesaurus.com or a thesaurus API. Alternatively, for "fox," synonyms could be vixen but the last is a family name. Hmm, maybe dog but wolf isn't a synonym for fox. This shows that sometimes it's hard to find perfect synonyms, but the user just wants three suggestions, so even if the third is a bit off is okay. Proper nouns like "NASA" or "London" stay unchanged

I think I need to proceed by using a thesaurus to find synonyms for each word, avoiding proper nouns. The user might be using this for text processing, perhaps to generate variations for content creation, SEO, or something similar. The key is to make the output usable even if not perfect, as the user can adjust later.