code: def evaluate_conll_file(fileIterator):
      true_seqs, pred_seqs = [], []
  
      for line in fileIterator:
          cols = line.strip().split()
          # each non-empty line must contain >= 3 columns
          if not cols:
              true_seqs.append("O")
              pred_seqs.append("O")
          elif len(cols) < 3:
              raise IOError(
                  "conlleval: too few columns in line %s\n" % line
              )
          else:
              # extract tags from last 2 columns
              true_seqs.append(cols[-2])
              pred_seqs.append(cols[-1])
      return evaluate(true_seqs, pred_seqs)
  
file_path: graph4nlp/examples/pytorch/name_entity_recognition/conlleval.py
imports: from __future__ import division, print_function, unicode_literals
  import sys
  from collections import defaultdict
label_desc: Use image node_id 8 for calling a global function with example usage: evaluate_conll_file(fileIterator) and returns: evaluate