text: import spacy
  
  from pymusas.lexicon_collection import LexiconCollection, LexiconEntry
  from pymusas.spacy_tagger import create_spacy_rule_based_tagger_component
  from pymusas.spacy_lexicon_collection import lexicon_collection
  '''
  from __future__ import annotations
  from spacy.language import Language
  from spacy.tokens import Doc
  from spacy.matcher import PhraseMatcher
  import spacy
  
  DICTIONARY = {"lol": "laughing out loud", "brb": "be right back"}
  DICTIONARY.update({value: key for key, value in DICTIONARY.items()})
  
  @Language.factory("ucrel")
  def create_spacy_rule_based_tagger_component(nlp: Language, name: str):
      return SpacyRuleBasedTagger(nlp)
  
  class SpacyRuleBasedTagger:
      def __init__(self, nlp: Language):
          pass
  '''
  # Add the component to the pipeline and configure it
  a_collection = lexicon_collection(data={'London|PROPN': ['Z2']}).data
  print(a_collection)
  nlp = spacy.load("en_core_web_sm")
  nlp.add_pipe("usas_tagger", last=True, config={'lexicon_lookup':a_collection})
  doc = nlp('London is great today')
  for token in doc:
      print(f'{token.text} {token._.usas_tags}')