class_docstr: Create a doc instance of text, obtain cleaned, readable text and
  metadata from this doc.
  
  Properties:
  raw: incoming, unedited text
  language: 2-letter code for the language of the text
  is_detected_language: is the language detected or specified beforehand
  is_reliable_language: is the language specified or was it reliably detected
  hint_language: language you expect your text to be
  _spacy_nlps: nested dictionary {lang: {model_id: model}} with loaded spacy language modules
docstr: True if the language was specified or if was it reliably detected
  
  >>> from textpipe.doc import Doc
  >>> Doc('...').is_reliable_language
  False
  >>> Doc('Test', hint_language='nl').is_reliable_language
  True
docstr_tok: ["True","if","the","language","was","specified","or","if","was","it","reliably","detected",">",">",">","from","textpipe.doc","import","Doc",">",">",">","Doc","(","'","...","'",")",".is_reliable_language","False",">",">",">","Doc","(","'Test","'",",","hint_language='nl","'",")",".is_reliable_language","True"]
code: def is_reliable_language(self):
      """
      True if the language was specified or if was it reliably detected
  
      >>> from textpipe.doc import Doc
      >>> Doc('...').is_reliable_language
      False
      >>> Doc('Test', hint_language='nl').is_reliable_language
      True
      """
      if self._is_reliable_language is None:
          (
              self._is_reliable_language,
              self._language,
          ) = self.detect_language(self.hint_language)
      return self._is_reliable_language
  
imports: import functools
  import re
  import unicodedata
  from collections import Counter
  from urllib.parse import urlparse
  import cld2
  import numpy
  import spacy
  import spacy.matcher
  import textacy
  import textacy.ke
  import textacy.text_utils
  from bs4 import BeautifulSoup
  from datasketch import MinHash
  from gensim.models.keyedvectors import KeyedVectors
  from gensim.summarization.summarizer import summarize
  from textpipe.data.emoji import EMOJI_TO_UNICODE_NAME, EMOJI_TO_SENTIMENT
  from textpipe.wrappers import RedisKeyedVectors
  from textpipe.util import getattr_
label_desc: Use image node_id 3 for calling the Doc obj's underlying member method code with example usage: obj.is_reliable_language() and returns: self