Triple

T36801921
Position Surface form Disambiguated ID Type / Status
Subject Nebi Musa E909343 entity
Predicate hasGenderSegregationTraditionally P49314 FINISHED
Object yes 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: yes | Statement: [Nebi Musa, hasGenderSegregationTraditionally, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGenderSegregationTraditionally
Context triple: [Nebi Musa, hasGenderSegregationTraditionally, yes]
  • A. hasGenderDivisions chosen
    Indicates that something is organized, classified, or separated into groups based on gender.
  • B. hasGenderInSomeTraditions
    Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
  • C. hasFemaleDominatedSociety
    Indicates that the society is structured such that women hold primary power, authority, or dominance in social, political, or economic spheres.
  • D. patriarchalTerritoryTraditionallyIncludes
    Indicates that, by tradition, the territorial domain associated with a patriarch encompasses or includes a specified area or entity.
  • E. hasGenderDistinction
    Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
  • 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_69f76e7b98888190899b6478a82ad6ae completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fe031bc6208190860099aef72d8dcb completed May 8, 2026, 3:36 p.m.
PD Predicate disambiguation batch_69fe014c8b388190b5d4e0cb95ee2be5 completed May 8, 2026, 3:29 p.m.
Created at: May 3, 2026, 4:12 p.m.