code: def eval_strategy_most_similar(s2v, keys):
      key_a = random.choice(keys)
      most_similar = s2v.most_similar(key_a, n=min(2000, len(s2v)))
      options = [
          (key, score) for key, score in most_similar if key in keys
      ]
      if len(options) < 2:
          return eval_strategy_most_similar(s2v, keys)
      key_b, sim_ab = options[len(options) // 2]
      key_c, sim_ac = options[-1]
      return key_a, key_b, key_c, sim_ab, sim_ac
  
file_path: sense2vec/sense2vec/prodigy_recipes.py
imports: import prodigy
  from prodigy.components.db import connect
  from prodigy.util import log, split_string, set_hashes, TASK_HASH_ATTR, INPUT_HASH_ATTR
  import murmurhash
  from sense2vec import Sense2Vec
  import srsly
  import spacy
  import random
  from wasabi import msg
  from collections import defaultdict, Counter
  import copy
  import catalogue
label_desc: Use image node_id 5 for calling a global function with example usage: eval_strategy_most_similar(s2v, keys) and returns: key_a,  key_b,  key_c,  sim_ab,  sim_ac, eval_strategy_most_similar