Triple

T4703417
Position Surface form Disambiguated ID Type / Status
Subject Porto Katsiki E104329 entity
Predicate isPhotoSubjectOf P9792 FINISHED
Object Greek tourism promotions 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: Greek tourism promotions | Statement: [Porto Katsiki, isPhotoSubjectOf, Greek tourism promotions]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: isPhotoSubjectOf
Context triple: [Porto Katsiki, isPhotoSubjectOf, Greek tourism promotions]
  • A. isPhotographicSubject chosen
    Indicates that an entity serves as the subject or main focus captured in a photograph taken by another entity.
  • B. evokesImageOf
    Indicates that one entity triggers or brings to mind a mental image or visual representation of another entity.
  • C. hasPhotographicSignificance
    Indicates that something holds notable importance or relevance in the context of photography, such as for documentation, artistic value, or visual record.
  • D. imagedBy
    Indicates that something is captured, recorded, or represented in an image created by a particular imaging device, method, or agent.
  • E. hasPhotograph
    Indicates that one entity possesses, includes, or is associated with a photograph depicting or representing another 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd650ad0f88190844bfcb46b3071c2 completed March 20, 2026, 3:17 p.m.
PD Predicate disambiguation batch_69bd621ba7448190a53ab1e2897acf71 completed March 20, 2026, 3:04 p.m.
Created at: March 20, 2026, 1:17 p.m.