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Prediction-Ready Entity Reconciliation
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Prediction-Ready Entity Reconciliation

HardPython

Problem

Write up a prediction-ready entity reconciliation system for us on your personal computer.

Implement reconcile_entities(records, threshold). Each record is a dictionary containing record_id, name, email, and phone, where values may be empty strings. Return sorted dictionaries with canonical_id, sorted members, and a confidence score. Normalize text case-insensitively and remove non-alphanumeric characters. Use candidate blocking, weighted comparison, and transitive clustering. Two records may be compared only when they share a normalized email, phone, or first-four-character name block. Their score is 0.5 for equal nonempty emails, 0.3 for equal nonempty phones, and 0.2 * SequenceMatcher name similarity. Join records when the score meets threshold, unless two populated identifiers conflict. The canonical record has the most populated fields, with record_id as the tie-breaker.

Constraints

  • 1 <= len(records) <= 2000
  • Each record contains record_id, name, email, and phone
  • Field values are strings and may be empty
  • 0.0 <= threshold <= 1.0
  • record_id values are unique
  • A populated email or phone conflicts when both records contain different normalized values

Function Signature

def reconcile_entities(records, threshold):
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