docstr: Returns parsed `word` and `status` as bool.
  `status` will be `False` if word wasn't handled, `True` otherwise.
docstr_tok: ["Returns","parsed","`","word","`","and","`","status","`","as","bool",".","`","status","`","will","be","`","False","`","if","word","was","n't","handled",",","`","True","`","otherwise","."]
code: def parse_one_word(self, word: str):
      """
      Returns parsed `word` and `status` as bool.
      `status` will be `False` if word wasn't handled, `True` otherwise.
      """
  
      if (
          self.phoneme_probability is not None
          and self._rng.random() > self.phoneme_probability
      ):
          return word, True
  
      # punctuation or whitespace.
      if re.search(r"[a-zA-ZÀ-ÿ\d]", word) is None:
          return list(word), True
  
      # heteronyms
      if self.heteronyms is not None and word in self.heteronyms:
          return word, True
  
      # `'s` suffix
      if (
          len(word) > 2
          and word.endswith("'s")
          and (word not in self.phoneme_dict)
          and (word[:-2] in self.phoneme_dict)
          and (
              not self.ignore_ambiguous_words
              or self.is_unique_in_phoneme_dict(word[:-2])
          )
      ):
          return self.phoneme_dict[word[:-2]][0] + ["Z"], True
  
      # `s` suffix
      if (
          len(word) > 1
          and word.endswith("s")
          and (word not in self.phoneme_dict)
          and (word[:-1] in self.phoneme_dict)
          and (
              not self.ignore_ambiguous_words
              or self.is_unique_in_phoneme_dict(word[:-1])
          )
      ):
          return self.phoneme_dict[word[:-1]][0] + ["Z"], True
  
      # phoneme dict
      if word in self.phoneme_dict and (
          not self.ignore_ambiguous_words
          or self.is_unique_in_phoneme_dict(word)
      ):
          return self.phoneme_dict[word][0], True
  
      if self.apply_to_oov_word is not None:
          return self.apply_to_oov_word(word), True
      else:
          return word, False
  
file_path: NeMo/nemo/collections/tts/g2p/models/en_us_arpabet.py
imports: import pathlib
  import random
  import re
  import time
  from typing import Optional
  import nltk
  import torch
  from nemo.collections.common.tokenizers.text_to_speech.tokenizer_utils import english_word_tokenize
  from nemo.collections.tts.g2p.models.base import BaseG2p
  from nemo.utils import logging
  from nemo.utils.get_rank import is_global_rank_zero
label_desc: Use image node_id 5 for calling the EnglishG2p obj's underlying member method code with example usage: obj.parse_one_word(word) and returns: word,  True, list,  True, word,  True, unknown,  True, unknown,  True, self,  True, self,  True, word,  False