python 12 lines · 1 tab

Regular expressions for extracting structured entities from raw text

Dr. Elena Vasquez Apr 2026

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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)

1 file · python Explain with highlit

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.

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