First, I need to identify all the words in the input that are not proper nouns. Proper nouns are specific names like "John" or "Paris" which should be left unchanged. So, I'll have to make sure to exclude those.
Next, for each non-proper noun, I need to provide three synonyms or alternatives. The challenge here is finding accurate synonyms that fit the context. Maybe I can use a thesaurus API or a built-in thesaurus in my knowledge base to find appropriate alternatives. For example, if the word is "happy", the variants could be joyful. First, I need to identify all the words
Potential issues include words with no valid synonyms. For example, "over" might be tricky. In such cases, using a thesaurus might help, but sometimes there are no direct synonyms. In that case, pick the closest possible alternatives even if the context might slightly change. Next, for each non-proper noun, I need to
Let me try applying this to a sample sentence. Suppose the input is "John went to Paris and bought a new book for school." For example, if the word is "happy", the
Let me test this with an example. Suppose the input is "The quick brown fox jumps over the lazy dog." Proper nouns here are none, so all words are replaceable. For "quick", synonyms could be hasty. For "brown", maybe tan. "Fox" is a common noun, so alternatives could be coyote. "Jumps" as a verb might be hops. Continuing this process for each word.
Finally, after generating all the variants, reconstruct the text with the replaced words, maintaining the original structure but with the new variants. Make sure to skip proper nouns entirely, as instructed.