Triple

T10738762
Position Surface form Disambiguated ID Type / Status
Subject Goldene Kamera E253263 entity
Predicate trophyShape P486 FINISHED
Object golden camera E253263 NE 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: golden camera | Statement: [Goldene Kamera, trophyShape, golden camera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: golden camera
Context triple: [Goldene Kamera, trophyShape, golden camera]
  • A. Golden Camera 300
    The Golden Camera 300 is a prestigious cinematography award recognizing outstanding achievement in the art and craft of motion picture photography.
  • B. Goldene Kamera chosen
    The Goldene Kamera is a prestigious German film and television award presented annually by the magazine Hörzu to honor outstanding achievements in entertainment.
  • C. The Camera
    The Camera is a seminal photography book by Ansel Adams that explores the technical and artistic use of cameras in creating expressive photographs.
  • D. Kwamera
    Kwamera is an Oceanic language spoken by indigenous communities on Tanna Island in Vanuatu.
  • E. Camira
    Camira is a compact family car model produced by Holden, the Australian subsidiary of General Motors, during the 1980s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710424d8c81908ee9b59d622f2af5 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de22ed6edc8190beb76bd2971c7cec completed April 14, 2026, 11:20 a.m.
Created at: April 8, 2026, 9:14 p.m.