Triple

T4211713
Position Surface form Disambiguated ID Type / Status
Subject Chinthe E93915 entity
Predicate hasGenderVariation P20413 FINISHED
Object male depictions 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 depictions | Statement: [Chinthe, hasGenderVariation, male depictions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasGenderVariation
Context triple: [Chinthe, hasGenderVariation, male depictions]
  • A. hasGenderVariant
    Indicates that one entity is a gender-specific form or variant of another entity.
  • B. hasNumberOfGenders
    Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
  • C. hasGenderDistinction
    Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
  • D. hasGenderInSomeTraditions chosen
    Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
  • E. hasGenderNeutrality
    Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular 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_69b3451743608190808f41d17ccf2650 completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34e098da881909a0cc339cc186627 completed March 12, 2026, 11:36 p.m.
PD Predicate disambiguation batch_69b347efd9b08190bb50f82e4e7fe06d completed March 12, 2026, 11:10 p.m.
Created at: March 12, 2026, 11:04 p.m.