code: def visualize_strings(texts, language_code, select=None, colors=None):
      """
      Takes in a list of strings and a language code (Stanza defines these, ex: 'en' for English) to visualize all
      of the strings' named entities.
  
      The strings are processed by the Stanza pipeline and the named entities are displayed. Each text is separated by a delimiting line.
  
      Optionally, the 'select' argument may be configured to only visualize given named entities (ex: select=['ORG', 'PERSON']).
  
      The optional colors argument is formatted as a dictionary of NER tags with their corresponding colors, which can be
      represented as a string (ex: "blue"), a color hex value (ex: #aa9cfc), or as a linear gradient of color
      values (ex: "linear-gradient(90deg, #aa9cfc, #fc9ce7)").
      """
      lang_pipe = stanza.Pipeline(
          language_code, processors="tokenize,ner"
      )
  
      for text in texts:
          visualize_ner_str(
              text, lang_pipe, select=select, colors=colors
          )
  
file_path: stanza/stanza/utils/visualization/ner_visualization.py
imports: from spacy import displacy
  from spacy.tokens import Doc
  from spacy.tokens import Span
  from stanza.models.common.constant import is_right_to_left
  import stanza
  import spacy
  import copy
label_desc: Use image node_id 3 for calling a global function with example usage: visualize_strings(texts, language_code, select, colors) without return types