Triple

T632071
Position Surface form Disambiguated ID Type / Status
Subject Islamic world E15944 entity
Predicate hasCulturalContribution P2008 FINISHED
Object Islamic architecture 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: Islamic architecture | Statement: [Islamic world, hasCulturalContribution, Islamic architecture]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCulturalContribution
Context triple: [Islamic world, hasCulturalContribution, Islamic architecture]
  • A. hasCulturalRole
    Indicates that an entity fulfills or is assigned a specific function, position, or significance within a cultural, social, or traditional context.
  • B. hasCulturalSignificance
    Indicates that something holds notable meaning, value, or importance within a particular culture or cultural context.
  • C. hasCulturalExpression
    Indicates that an entity embodies, manifests, or is associated with a particular cultural form, practice, or expression.
  • D. hasCulturalImpact chosen
    Indicates that one entity has influenced, shaped, or significantly affected the culture, values, practices, or artistic expressions of another.
  • E. hasCulturalFeature
    Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
  • 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_69a4935c131c8190a5378c6bf101e8cc completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49ec2a4c08190bc5c6ce8a10b0967 completed March 1, 2026, 8:17 p.m.
PD Predicate disambiguation batch_69a49d030c648190ba1a02301b45f694 completed March 1, 2026, 8:09 p.m.
Created at: March 1, 2026, 7:35 p.m.