Triple

T18195017
Position Surface form Disambiguated ID Type / Status
Subject Hasselblad Center E435637 entity
Predicate namedAfter P63 FINISHED
Object Hasselblad NE NERFINISHED

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: Hasselblad | Statement: [Hasselblad Center, namedAfter, Hasselblad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hasselblad
Context triple: [Hasselblad Center, namedAfter, Hasselblad]
  • A. Hasselblad (camera manufacturer) chosen
    Hasselblad is a renowned Swedish manufacturer of high-end medium format cameras and lenses, celebrated for their use in professional photography and on NASA space missions.
  • B. Leica Camera AG
    Leica Camera AG is a renowned German manufacturer of premium cameras and sport optics, celebrated for its precision engineering and iconic photographic equipment.
  • C. Nikon
    Nikon was a 17th-century Patriarch of Moscow and All Russia known for initiating major liturgical reforms that led to the Raskol (schism) in the Russian Orthodox Church.
  • D. Nikon
    Nikon is a figure associated with the Telchines, a group of mythical craftsmen and sorcerers from ancient Greek mythology.
  • E. Fujifilm
    Fujifilm is a Japanese multinational company best known for its photographic film, digital imaging products, and diversified technologies in healthcare and printing.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e0d1eb1c81908c20b6d15e9c4e8e completed April 19, 2026, 2:04 p.m.
Created at: April 10, 2026, 10:31 a.m.