nlp_architect.data.cdc_resources.relations.computed_relation_extraction.ComputedRelationExtraction

class nlp_architect.data.cdc_resources.relations.computed_relation_extraction.ComputedRelationExtraction[source]

Extract Relation between two mentions according to computation and rule based algorithms

__init__()

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__()

Initialize self.

extract_all_relations(mention_x, mention_y)

Try to find if mentions has anyone or more of the relations this class support

extract_exact_string(mention_x, mention_y)

Check if input mentions has exact string relation

extract_fuzzy_fit(mention_x, mention_y)

Check if input mentions has fuzzy fit relation

extract_fuzzy_head_fit(mention_x, mention_y)

Check if input mentions has fuzzy head fit relation

extract_relation(mention_x, mention_y, relation)

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

extract_same_head_lemma(mention_x, mention_y)

Check if input mentions has same head lemma relation

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

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]

Try to find if mentions has anyone or more of the relations this class support

Parameters
  • mention_x – MentionDataLight

  • mention_y – MentionDataLight

Returns

One or more of: RelationType.EXACT_STRING, RelationType.FUZZY_FIT,

RelationType.FUZZY_HEAD_FIT, RelationType.SAME_HEAD_LEMMA, RelationType.SAME_HEAD_LEMMA_RELAX

Return type

Set[RelationType]

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

Check if input mentions has exact string relation

Parameters
  • mention_x – MentionDataLight

  • mention_y – MentionDataLight

Returns

RelationType.EXACT_STRING or RelationType.NO_RELATION_FOUND

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

Check if input mentions has fuzzy fit relation

Parameters
  • mention_x – MentionDataLight

  • mention_y – MentionDataLight

Returns

RelationType.FUZZY_FIT or RelationType.NO_RELATION_FOUND

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

Check if input mentions has fuzzy head fit relation

Parameters
  • mention_x – MentionDataLight

  • mention_y – MentionDataLight

Returns

RelationType.FUZZY_HEAD_FIT or RelationType.NO_RELATION_FOUND

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

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

Check if input mentions has same head lemma relation

Parameters
  • mention_x – MentionDataLight

  • mention_y – MentionDataLight

Returns

RelationType.SAME_HEAD_LEMMA or RelationType.NO_RELATION_FOUND

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() → List[nlp_architect.data.cdc_resources.relations.relation_types_enums.RelationType][source]

Return all supported relations by this class

Returns

List[RelationType]