Triple

T3176559
Position Surface form Disambiguated ID Type / Status
Subject Royal Arch Masonry E66477 entity
Predicate membershipGenderInMostJurisdictions P15554 FINISHED
Object male LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: male | Statement: [Royal Arch Masonry, membershipGenderInMostJurisdictions, male]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: membershipGenderInMostJurisdictions
Context triple: [Royal Arch Masonry, membershipGenderInMostJurisdictions, male]
  • A. hasGenderRequirement chosen
    Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
  • B. governsGender
    Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
  • C. hasGenderPolicy
    Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
  • D. hasGenderInSomeTraditions
    Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
  • E. hasNumberOfGenders
    Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada69b0bec8190957913b44d876079 completed March 8, 2026, 4:40 p.m.
PD Predicate disambiguation batch_69ad9e02677c8190a21d93b1259b2761 completed March 8, 2026, 4:04 p.m.
Created at: March 8, 2026, 3:06 p.m.