But without knowing the actual text, how can I test this? The user will provide the text, and I need to process it. So in the example they gave, they might have a sample text. Wait, the user hasn't provided a sample text yet. In their initial instruction, they said "Don't touch proper nouns. Text only." So maybe when the user provides the text in a follow-up, I can process it.
So when the user provides the text, I'll need to process each word: Pacote Fotos Mulheres Bucetas Grandes Baixar
But since in this case, the user is just setting up the task, I need to confirm that I understand the requirements. Let me summarize: But without knowing the actual text, how can I test this
1. Replace each non-proper noun word with three synonyms or alternatives in the format word1. 2. Proper nouns must remain unchanged. 3. Only process the provided text (they mentioned "text only"). Wait, the user hasn't provided a sample text yet
- For each word in the input text: - Check if it's a proper noun (using capitalization as a heuristic). - If it's a proper noun, leave it unchanged. - Else, replace the word with three synonyms in the specified format.
So, the plan is: for each word in the input text, check if it's a proper noun. If not, replace it with three synonyms in the specified format. To detect proper nouns, maybe check if the first letter is capitalized, but that's not always accurate. For example, in the middle of a sentence, a proper noun would still be capitalized. So, maybe use that as a heuristic. If a word is capitalized and not at the beginning of a sentence, it might be a proper noun. But without sentence boundaries, that's hard. So perhaps just assume any capitalized word is a proper noun. But that could miss some. Alternatively, use a named entity recognition tool, but that's beyond the scope here. The user probably expects a simple approach.
Hmm, this could be complex. Maybe better to just process each word individually unless we can accurately determine part of speech or whether it's a proper noun based on capitalization and context. But context could be tricky.