class_docstr: Extract Relation between two mentions according to computation and rule based algorithms
class_docstr_tok: ["Extract","Relation","between","two","mentions","according","to","computation","and","rule","based","algorithms"]
docstr: Check if input mentions has fuzzy head fit relation
  
  Args:
      mention_x: MentionDataLight
      mention_y: MentionDataLight
  
  Returns:
      RelationType.FUZZY_HEAD_FIT or RelationType.NO_RELATION_FOUND
docstr_tok: ["Check","if","input","mentions","has","fuzzy","head","fit","relation","Args",":","mention_x",":","MentionDataLight","mention_y",":","MentionDataLight","Returns",":","RelationType.FUZZY_HEAD_FIT","or","RelationType.NO_RELATION_FOUND"]
code: def extract_fuzzy_head_fit(
      mention_x: MentionDataLight, mention_y: MentionDataLight
  ) -> RelationType:
      """
      Check if input mentions has fuzzy head fit relation
  
      Args:
          mention_x: MentionDataLight
          mention_y: MentionDataLight
  
      Returns:
          RelationType.FUZZY_HEAD_FIT or RelationType.NO_RELATION_FOUND
      """
      if StringUtils.is_preposition(
          mention_x.mention_head_lemma.lower()
      ) or StringUtils.is_preposition(
          mention_y.mention_head_lemma.lower()
      ):
          return RelationType.NO_RELATION_FOUND
  
      mention_y_tokens = mention_y.tokens_str.split()
      mention_x_tokens = mention_x.tokens_str.split()
      if (
          mention_x.mention_head in mention_y_tokens
          or mention_y.mention_head in mention_x_tokens
      ):
          return RelationType.FUZZY_HEAD_FIT
      return RelationType.NO_RELATION_FOUND
  
file_path: nlp-architect/nlp_architect/data/cdc_resources/relations/computed_relation_extraction.py
imports: import difflib
  import logging
  import sys
  from typing import List, 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
  from nlp_architect.utils.string_utils import StringUtils
label_desc: Use image node_id 4 for calling the ComputedRelationExtraction obj's underlying member method code with example usage: obj.extract_fuzzy_head_fit(mention_x, mention_y) and returns: RelationType, RelationType, RelationType