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processing/normalize_company.py

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  1. """Company-name normalization for entity resolution and matching."""
  3. from __future__ import annotations
  5. import re
  6. import unicodedata
  8. # legal-form suffix tokens (accent-stripped, lowercase); stripped repeatedly
  9. LEGAL_SUFFIXES = {
  10. "gmbh", "ag", "sa", "sarl", "sarl", "sarl", "sasu", "sas", "srl", "spa",
  11. "ltd", "limited", "llc", "llp", "lp", "inc", "incorporated", "plc",
  12. "corp", "corporation", "bv", "nv", "ug", "se", "oy", "oyj", "ab", "as",
  13. "asa", "aps", "gk", "kg", "ohg", "gbr", "ek", "eg", "eir", "scs",
  14. "stiftung", "verein", "societe", "society", "ans", "co", "company",
  15. "holdings", "holding", "group", "gruppe", "international",
  16. "pvt", "pty", "srl", "sarl", "sl", "srls", "ooo", "zao", "kk", "pt",
  17. }
  20. def strip_accents(s: str) -> str:
  21. return "".join(c for c in unicodedata.normalize("NFKD", s) if not unicodedata.combining(c))
  24. def normalize_company_name(name: str | None) -> str | None:
  25. """'ACME Electronics GmbH' / 'Acme Electronics' / 'ACME ELECTRONICS GMBH'
  26. all -> 'acme electronics'. Preserves the original alongside; caller's job.
  27. """
  28. if not name or not isinstance(name, str):
  29. return None
  30. s = strip_accents(name).lower()
  31. s = s.replace("&", " and ")
  32. # dots removed WITHOUT introducing spaces so legal forms like
  33. # "S.A.", "s.à r.l.", "b.v." collapse to sa / sarl / bv before suffix-strip
  34. s = s.replace(".", "")
  35. s = re.sub(r"[^\w\s]", " ", s, flags=re.UNICODE)
  36. tokens = [t for t in s.split() if t]
  37. while tokens and tokens[-1] in LEGAL_SUFFIXES:
  38. tokens.pop()
  39. if tokens and tokens[0] == "the":
  40. tokens = tokens[1:]
  41. return " ".join(tokens) or None