import re
text = 'INC-102301 resolved on 2026-04-06 after payment failure for order ORD-99182.'
patterns = {
'incident_id': r'INC-[0-9]{6}',
'order_id': r'ORD-[0-9]{5}',
'date': r'\b\d{4}-\d{2}-\d{2}\b',
}
extracted = {name: re.findall(pattern, text) for name, pattern in patterns.items()}
print(extracted)
Regex is not glamorous, but it remains one of the fastest ways to turn messy text into useful structured fields. I use it for IDs, dates, codes, and log fragments before reaching for heavier NLP. The important part is making patterns specific enough to avoid silent false positives.