Triple

T4055651
Position Surface form Disambiguated ID Type / Status
Subject Adjaruli E84686 entity
Predicate genderRoleFeature P25470 FINISHED
Object emphasis on female grace 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: emphasis on female grace | Statement: [Adjaruli, genderRoleFeature, emphasis on female grace]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: genderRoleFeature
Context triple: [Adjaruli, genderRoleFeature, emphasis on female grace]
  • A. genderConfiguration
    Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
  • B. genderRule
    Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
  • C. genderCategories
    Indicates the classification of an entity into one or more gender-related categories or identities.
  • D. genderVariant
    Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
  • E. genderDivision chosen
    Indicates a relationship where roles, responsibilities, or categories are separated or distinguished based on gender.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbabec608190a35d39d3d03b928b completed March 9, 2026, 4:56 p.m.
PD Predicate disambiguation batch_69aef90249e4819095e9e043bc4aa9a6 completed March 9, 2026, 4:44 p.m.
Created at: March 9, 2026, 3:38 p.m.