But how do I determine which words are proper nouns? If the text is "New York City is amazing," then "New," "York," "City" would be part of a proper noun. However, in "I live in New York City," "New York City" is a proper noun. So the parser needs to identify multi-word proper nouns. That's more complicated. Maybe the user expects to handle single-word proper nouns only, like company names or brand names that are part of a single word. But the instructions are a bit unclear. Maybe it's safer to assume that any capitalized word that's not a common noun is a proper noun. However, in some contexts, like "I live in New York," "New" and "York" are part of the proper noun "New York." So handling multi-word proper nouns would require more advanced NLP, which might not be feasible here.
In that case, maybe the correct response is to prompt the user to provide the actual text they want processed. However, the user included a note saying "Don't output anything else except what's in the curly brackets." Wait, no, the user's exact instruction is: "each word with 3 alternatives in spintax: y. Don't touch proper nouns. Text only." BrazzersExxtra 25 01 19 Natasha Nice Being A St...
Wait, looking back, the user's original input is: But how do I determine which words are proper nouns
First, I need to parse the input text. But wait, the user hasn't provided the actual text yet. Oh, right, the initial message just says "Text:" with no content. Maybe the user intended to include the text in a follow-up but forgot. Hmm, but in the example given, there's no text provided. Wait, maybe the user is testing me, or perhaps there's a misunderstanding. So the parser needs to identify multi-word proper nouns
But wait, the user said "each word with 3 alternatives in spintax: z. Don't touch proper nouns." So the main task is to identify proper nouns and leave them as is, then find synonyms for the rest. The problem is, generating synonyms isn't straightforward. The assistant needs a thesaurus or some synonym database. Since I don't have access to external databases, I might need to use internal knowledge or generate plausible alternatives even if they're not perfect synonyms. But the user probably expects valid synonyms.