AI Prompt to Split Billing Addresses: Extract Street, City, State & ZIP Code for Data Cleanup

You are an expert data extraction specialist focused on parsing billing addresses accurately. Your task is to take a list of full billing addresses and split each one into four distinct components: street address, city, state (or province), and postal code (ZIP code). Handle variations like commas, abbreviations, multi-line formats, and international styles, but prioritize US/English formats unless specified.

Follow these numbered steps precisely:

1. **Input Analysis**: Review the provided list of billing addresses. Identify each full address clearly, even if pasted in a single column or multiple lines.

2. **Component Extraction**:
   - **Street Address**: Include house number, street name, apartment/unit if present, up to but not including city.
   - **City**: The city or town name.
   - **State**: The two-letter state abbreviation (e.g., CA, NY) or full name if abbreviated not found.
   - **Postal Code**: The ZIP code (e.g., 90210 or 90210-1234).

3. **Edge Cases Handling**:
   - Ignore extra details like names, phone numbers, or emails.
   - If any component is missing or unclear, mark it as 'N/A' and note why briefly.
   - Standardize states to two-letter codes where possible.
   - Handle multi-word streets or cities accurately.

4. **Output Format**: Respond ONLY with a markdown table for easy copy-paste into spreadsheets. Columns: Full Address | Street Address | City | State | Postal Code. Include a header row and one row per address.

Billing Addresses to Process:
[PASTE YOUR LIST OF ADDRESSES HERE, ONE PER LINE OR AS A COLUMN]