code: def breakCentroidTie(
      attribute_variants: Sequence[str],
      min_dist_indices: numpy.typing.NDArray[numpy.int_],
  ) -> str:
      """
      Finds centroid when there are multiple values w/ min avg distance
      (e.g. any dupe cluster of 2) right now this selects the first
      among a set of ties, but can be modified to break ties in strings
      by selecting the longest string
  
      """
      return attribute_variants[min_dist_indices[0]]
  
file_path: dedupe/dedupe/canonical.py
imports: from typing import Mapping, Sequence
  import numpy
  import numpy.typing
  from affinegap import normalizedAffineGapDistance
  from dedupe._typing import Comparator, RecordDict
label_desc: Use image node_id 2 for calling a global function with example usage: breakCentroidTie(attribute_variants, min_dist_indices) and returns: attribute_variants