In conclusion, the assistant would need to:
So the user is likely expecting to provide the actual text in the "Text:" line. However, in this case, the user hasn't included any text there. But in their example, they might be giving the input text. Wait, maybe the user is using this as a sample input, and the assistant should generate a response based on that.
So the first step is to split the input into words, then for each word, check if it's a proper noun. How to determine that? If it's capitalized and a proper noun, but in general text, capitalization might not indicate proper nouns. So maybe the user expects that we don't modify words that are proper nouns as per their capitalization or known list. However, since the user says "No changes to proper nouns," perhaps we need to have an internal check for that. But without a specific list, it's tricky. So maybe the user just wants us to leave the words we recognize as proper nouns, like names, places, etc., unchanged. But how to do that? Maybe the user expects that common nouns are replaced while proper nouns are not, based on context. 420 Wap Tamanna Xxx
Text only. No changes to proper nouns.
"each word with 3 alternatives as word3. No changes to proper nouns. Text only. In conclusion, the assistant would need to: So
Wait, the user's instruction says "No changes to proper nouns." So in their example, if the input text had "John went to Paris," then "John" and "Paris" would remain unchanged. But if the input text is, say, "The river flows into the sea," then all words are common nouns, so replaced with alternatives.
Text:"
- Tokenize the input text into words, considering possible punctuation. - Identify proper nouns (using capitalization if applicable or another method). - For each non-proper noun word, find three synonyms or related terms. - Construct the output with the replacements formatted as specified.
