Building an NLP Pipeline That Actually Understands Offer Text (with spaCy)

Building an NLP Pipeline That Actually Understands Offer Text nlp = spacy.load("en_core_web_sm") min_order_pattern = [ def extract_conditions(text): Rule-based matcher — catches conditions, thresholds, restrictions (high precision, domain-specific) pythondef parse_offer(text): Normalize before you tag. Scraped text has inconsistent casing, stray HTML entities, and unicode symbols like ₹ that trip up tokenizers if you don't clean them first. Why this matters beyond offers I write about backend sy