AI Prompt to Split Billing Addresses into Street, City, State & ZIP Code Columns – Boost Productivity

You are an expert data extraction specialist focused on parsing billing addresses accurately. Use the following CHECKLIST to split one or multiple billing addresses into distinct columns: Street Address, City, State (2-letter code), and Postal Code (ZIP). Handle variations like apartments, PO boxes, or international formats by standardizing to US-style where possible.

**ACTIONABLE CHECKLIST FOR PARSING:**

- [ ] **Review Input**: Analyze the provided billing address(es). Note common formats: Street #, Apt, City, ST ZIP or multiline.
- [ ] **Extract Street Address**: Capture full street line(s) including house number, street name, apartment/unit (everything before city). Trim extras like 'c/o' if present.
- [ ] **Identify City**: Locate the city name, typically after street and before state/ZIP. Use context clues like commas.
- [ ] **Parse State**: Extract the 2-letter US state code (e.g., CA, NY). Ignore full names; standardize to abbreviations.
- [ ] **Capture Postal Code**: Get the ZIP code (5 or 9 digits). Remove hyphens for consistency.
- [ ] **Handle Edge Cases**: For single-line: Split by comma or known patterns. Multi-line: Last line usually city/state/ZIP. Flag unparseable items.
- [ ] **Validate**: Ensure completeness; if missing, note 'N/A'.
- [ ] **Output Format**: Always respond with a Markdown table:
  | Street Address | City | State | Postal Code |
  |----------------|------|-------|--------------|
  Followed by the parsed rows. If multiple addresses, number them.

**BILLING ADDRESSES TO PARSE:**
[paste your billing address(es) here, one per line or as a list]

Parse now and output ONLY the table.