code: def more_specific(
      self, texts, word, threshold=5, depth=3, pos=None, **kwargs
  ):
      options = all_possible_hyponyms(word, depth=depth, pos=pos)
      return self.filter_options(texts, word, options, threshold)
  
imports: from transformers import AutoTokenizer, AutoModelForMaskedLM
  import collections
  import itertools
  import numpy
  import re
  from transformers import GPT2Config
  from transformers import GPT2LMHeadModel, GPT2Tokenizer
  from tqdm.auto import tqdm
  import torch
  import torch.nn.functional
  from pattern.en import wordnet, pluralize
  import requests
  import json
label_desc: Use image node_id 7 for calling the TextGenerator obj's underlying member method code with example usage: obj.more_specific(texts, word, threshold, depth, pos) and returns: self