Meyd-718 Bercinta Cepat Dengan Janda Sebelah Rumah Riho Fujimori - Indo18 -

Alternatively, maybe the entire email address is treated as a single entity, so each part isn't considered a separate word. The same goes for the address: "123 Main St, Anytown, USA 12345" should be kept as it is because it's an address, and each component is a proper name or location.

Wait, but the user said "convert every word with 3 variants formatted v1." 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.).

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. Alternatively, maybe the entire email address is treated

Wait, but how do I determine if a word is a name? For example, words like "Apple" could be a fruit or a company. How do I know which is which in the input text? The user hasn't provided any specific text to work with yet. They just gave an example with the placeholder "Text:" followed by "example@example.com" and "123 Main St, Anytown, USA 12345."

- 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. The challenge is identifying which words are names

Now, to apply this to the given example. Since the user provided the example of converting "hello world" to "heyuniverse", I can infer that each regular word is transformed, while names are kept. Therefore, if the input text includes names like email addresses or addresses, they remain the same, and other words get transformed.

1. Split the input text into words or tokens. 2. For each token, determine if it's a name (email, address, URL, capitalized proper nouns) or a regular word. 3. For regular words, generate three synonyms or variants. 4. For names, leave them unchanged. 5. Format the output with v2 for each regular word, keeping names as they are. Let me go through the example provided in

But then there are other words. Let's take "Hello, world!" as the example text. "Hello" should be converted to three variants. Let's think: possible synonyms for "hello" are "hi," "greetings," "hey." So it would become hi. Similarly, "world" could be replaced with "universe," "earth," or "planet." So earth.