code: def _write_prediction_results(concat_opinion_dict, out_override):
      out_dir = Path(out_override) if out_override else LEXICONS_OUT
      out_path = out_dir / "generated_opinion_lex_reranked.csv"
      with open(out_path, "w") as csv_file:
          writer = csv.writer(csv_file)
          writer.writerow(["Term", "Score", "Polarity", "isAcquired"])
          for key, value in concat_opinion_dict.items():
              writer.writerow([key, value[0], value[1], value[2]])
      print("Reranked opinion lexicon written to {}".format(out_path))
  
imports: import csv
  import pickle
  import numpy
  import tensorflow
  from os import PathLike
  from pathlib import Path
  from nlp_architect.models.absa.utils import _read_generic_lex_for_similarity
  from nlp_architect.models.absa import TRAIN_OUT, TRAIN_LEXICONS, GENERIC_OP_LEX, LEXICONS_OUT
  from scipy.spatial.distance import cosine
  from sklearn.model_selection import StratifiedKFold
  from tensorflow.keras.layers import Dense, Dropout
  from tensorflow.keras.models import Sequential, load_model
  from nlp_architect.utils.embedding import load_word_embeddings
label_desc: Use image node_id 21 for calling the RerankTerms obj's underlying member method code with example usage: obj._write_prediction_results(concat_opinion_dict, out_override) without return types