This library helps with the generation of fingerprints for entity data. A fingerprint in this context is understood as a simplified entity identifier, derived from it's name or address and used for cross-referencing of entity across different datasets.
import fingerprints fp = fingerprints.generate('Mr. Sherlock Holmes') assert fp == 'holmes sherlock' fp = fingerprints.generate('Siemens Aktiengesellschaft') assert fp == 'ag siemens' fp = fingerprints.generate('New York, New York') assert fp == 'new york'
Company type names
A significant part of what
fingerprints does it to recognize company legal form
names. For example,
fingerprints will be able to simplify
Общество с ограниченной ответственностью to
AG. The required database
is based on two different sources:
- A Google Spreadsheet created by OCCRP.
- The ISO 20275: Entity Legal Forms Code List
Wikipedia also maintains an index of types of business entity.
- Clustering in Depth, part of the OpenRefine documentation discussing how to create collisions in data clustering.
- probablepeople, parser for western names made by the brilliant folks at datamade.us.