class_docstr: Collects information on gold and predicted clusters across documents.
  Can be used to retrieve weighted LEA-score for them.
docstr: Returns weighted LEA for all the documents as
  (f1, precision, recall) 
docstr_tok: ["Returns","weighted","LEA","for","all","the","documents","as","(","f1",",","precision",",","recall",")"]
code: def total_lea(self):
      """Returns weighted LEA for all the documents as
      (f1, precision, recall)"""
      precision = self._p / (self._p_weight + EPSILON)
      recall = self._r / (self._r_weight + EPSILON)
      f1 = (precision * recall) / (precision + recall + EPSILON) * 2
      return f1, precision, recall
  
imports: from typing import Hashable, List, Tuple
  from stanza.models.coref.const import EPSILON
label_desc: Use image node_id 3 for calling the ClusterChecker obj's underlying member method code with example usage: obj.total_lea() and returns: f1,  precision,  recall