docstr: Check if input mentions has VerbOcean relation between them
  
  Args:
      mention_x: MentionDataLight
      mention_y: MentionDataLight
  
  Returns:
      bool
docstr_tok: ["Check","if","input","mentions","has","VerbOcean","relation","between","them","Args",":","mention_x",":","MentionDataLight","mention_y",":","MentionDataLight","Returns",":","bool"]
code: def is_verbocean_relation(
      self, mention_x: MentionDataLight, mention_y: MentionDataLight
  ) -> bool:
      """
      Check if input mentions has VerbOcean relation between them
  
      Args:
          mention_x: MentionDataLight
          mention_y: MentionDataLight
  
      Returns:
          bool
      """
      x_head = mention_x.mention_head
  
      y_head = mention_y.mention_head
  
      rel = None
  
      if x_head in self.vo and y_head in self.vo[x_head]:
          rel = self.vo[x_head][y_head]
      elif y_head in self.vo and x_head in self.vo[y_head]:
          rel = self.vo[y_head][x_head]
  
      match_result = False
      if rel is not None and rel != "[unk]" and rel != "[low-vol]":
          match_result = True
  
      return match_result
  
file_path: nlp-architect/nlp_architect/data/cdc_resources/relations/verbocean_relation_extraction.py
imports: import logging
  import os
  from typing import Dict, Set
  from nlp_architect.common.cdc.mention_data import MentionDataLight
  from nlp_architect.data.cdc_resources.relations.relation_extraction import RelationExtraction
  from nlp_architect.data.cdc_resources.relations.relation_types_enums import RelationType, OnlineOROfflineMethod
  from nlp_architect.utils.io import load_json_file
  from nlp_architect.utils.string_utils import StringUtils
label_desc: Use image node_id 4 for calling the VerboceanRelationExtraction obj's underlying member method code with example usage: obj.is_verbocean_relation(mention_x, mention_y) and returns: match_result