code: def semantic_distance(original: str, decompressed: str) -> float:
      doc1 = nlp(original)
      doc2 = nlp(decompressed)
  
      if decompressed.strip() == "" and original.strip() != "":
          # Recovered payload is empty
          return 1
  
      similarity = doc1.similarity(doc2)
      similarity = max(
          similarity, 0
      )  # Discard negative values, not clearly meaningful and rarely occurs
  
      dist = 1 - similarity
      return dist
  
imports: from typing import Mapping
  import jiwer
  import spacy_universal_sentence_encoder
label_desc: Use image node_id 2 for calling a global function with example usage: semantic_distance(original, decompressed) and returns: dist, int