Given the ambiguity, perhaps the user expects us to treat any sequence that looks like an email, URL, or address as a name and leave them as-is, while generating variants for other words. So, the main task is to split the text into tokens that are either names or words.
Let me go through the example provided in the user's initial message. They had "example@example.com" and "123 Main St, Anytown, USA 12345." In "example@example.com," the first word "example" is a regular noun (a sample), but in the email context, it's part of the email address. Since the email address is a name/capitalized entity, perhaps I should leave "example" as is. Wait, emails typically aren't capitalized beyond the domain part. The username part is often lowercase. So maybe "example" is part of the username here, so it should remain unchanged. But the user said to keep names intact. Unless "example.com" is considered a name, like a domain name, but again, that might depend on context. Given the ambiguity, perhaps the user expects us
So, the approach would be:
But how to implement this without knowing specific rules for name detection? Maybe the user expects a general approach where any capitalized word is considered a name unless it's a common noun. However, this could lead to errors because some common nouns might start with a capital letter. For example, in the phrase "Apple is a fruit," "Apple" is a common noun and should have variants like "apple, orange, banana," but if it's part of a sentence where it's a company, it should stay "Apple." They had "example@example
Looking back at the example, "example@example.com" would be considered a name, so it remains unchanged. "123 Main St, Anytown, USA 12345" is an address, so that's a name. Then the rest of the words, if any, would be converted. However, in the provided example, there's no other text. The user included "example@example.com" and "123 Main St, Anytown, USA 12345" as placeholders. The username part is often lowercase
- Tokenize the input text into words or named entities. - For each token: - Check if it's a name (email, address, URL, proper noun). - If yes, leave it unchanged. - If not, generate three variants and format as v3. - Ensure that the output only contains the result, without explanations or additional text.
Wait, but the user said "convert every word with 3 variants formatted v2." So each word in the input text (excluding names) needs to be replaced by three possible variants. The challenge is identifying which words are names and which are regular words. Without specific context, it's hard to know. If the input text includes words that could be either names or common nouns, I might have to default to treating them as regular words unless they fit a pattern of names (like capitalized words, domains, addresses, etc.).