code: def filter_word(text):
      """
      Take out english stopwords, punctuation, and compound endings.
      """
      text = normalize(text)
      if regex.match(r"^\p{P}+$", text):
          return True
      if text.lower() in STOPWORDS:
          return True
      return False
  
file_path: ParlAI/parlai/agents/tfidf_retriever/utils.py
imports: import regex
  import unicodedata
  import numpy
  import scipy.sparse
  from sklearn.utils import murmurhash3_32
label_desc: Use image node_id 5 for calling a global function with example usage: filter_word(text) and returns: False, True, True