Triple

T12483404
Position Surface form Disambiguated ID Type / Status
Subject American Photographs E298370 entity
Predicate numberOfPhotographs P62360 FINISHED
Object 87 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: 87 | Statement: [American Photographs, numberOfPhotographs, 87]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: numberOfPhotographs
Context triple: [American Photographs, numberOfPhotographs, 87]
  • A. numberOfImagesTaken
    Indicates the quantity of images that have been captured or recorded in relation to a given subject or event.
  • B. hasPhotographs
    Indicates that one entity possesses, contains, or is associated with one or more photographs of another entity or subject.
  • C. numberOfStills chosen
    Indicates the quantity of still images associated with or contained in a given entity or context.
  • D. numberOfImagesReturned
    Indicates the total count of images that are produced or provided as the result of a query, request, or operation.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94e8a706c8190873623eab7db607d completed April 10, 2026, 7:24 p.m.
PD Predicate disambiguation batch_69d94d41f3cc8190a3331fb9a895306f completed April 10, 2026, 7:19 p.m.
Created at: April 8, 2026, 9:56 p.m.