nlp_architect.data.cdc_resources.relations.referent_dict_relation_extraction.ReferentDictRelationExtraction

class nlp_architect.data.cdc_resources.relations.referent_dict_relation_extraction.ReferentDictRelationExtraction(method: nlp_architect.data.cdc_resources.relations.relation_types_enums.OnlineOROfflineMethod = <OnlineOROfflineMethod.ONLINE: 'online'>, ref_dict: str = None)[source]
__init__(method: nlp_architect.data.cdc_resources.relations.relation_types_enums.OnlineOROfflineMethod = <OnlineOROfflineMethod.ONLINE: 'online'>, ref_dict: str = None)[source]

Extract Relation between two mentions according to Referent Dictionary knowledge

Parameters:
  • method (optional) – OnlineOROfflineMethod.{ONLINE/OFFLINE} run against full referent dictionary or a sub-set of (default = ONLINE)
  • ref_dict (required) – str Location of referent dictionary file to work with

Methods

__init__(method, ref_dict) Extract Relation between two mentions according to Referent Dictionary knowledge
extract_all_relations(mention_x, mention_y)
extract_relation(mention_x, mention_y, relation) Base Class Check if Sub class support given relation before executing the sub class
extract_sub_relations(mention_x, mention_y, …) Check if input mentions has the given relation between them
get_supported_relations() Return all supported relations by this class
is_referent_dict(mention_x, mention_y) Check if input mentions has referent dictionary relation between them
load_reference_dict(dict_fname) Method to load referent dictionary to memory
extract_all_relations(mention_x: nlp_architect.common.cdc.mention_data.MentionDataLight, mention_y: nlp_architect.common.cdc.mention_data.MentionDataLight) → Set[nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType][source]
extract_relation(mention_x: nlp_architect.common.cdc.mention_data.MentionDataLight, mention_y: nlp_architect.common.cdc.mention_data.MentionDataLight, relation: nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType) → nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType

Base Class Check if Sub class support given relation before executing the sub class

Parameters:
  • mention_x – MentionDataLight
  • mention_y – MentionDataLight
  • relation – RelationType
Returns:

relation in case mentions has given relation and

RelationType.NO_RELATION_FOUND otherwise

Return type:

RelationType

extract_sub_relations(mention_x: nlp_architect.common.cdc.mention_data.MentionDataLight, mention_y: nlp_architect.common.cdc.mention_data.MentionDataLight, relation: nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType) → nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType[source]

Check if input mentions has the given relation between them

Parameters:
  • mention_x – MentionDataLight
  • mention_y – MentionDataLight
  • relation – RelationType
Returns:

relation in case mentions has given relation or

RelationType.NO_RELATION_FOUND otherwise

Return type:

RelationType

static get_supported_relations()[source]

Return all supported relations by this class

Returns:List[RelationType]
is_referent_dict(mention_x: nlp_architect.common.cdc.mention_data.MentionDataLight, mention_y: nlp_architect.common.cdc.mention_data.MentionDataLight) → bool[source]

Check if input mentions has referent dictionary relation between them

Parameters:
  • mention_x – MentionDataLight
  • mention_y – MentionDataLight
Returns:

bool

static load_reference_dict(dict_fname: str) → Dict[str, List[str]][source]

Method to load referent dictionary to memory

Returns:List[RelationType]