Triple

T10323495
Position Surface form Disambiguated ID Type / Status
Subject Hoyte van Hoytema E242698 entity
Predicate familyName P18 FINISHED
Object van Hoytema E242698 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: van Hoytema | Statement: [Hoyte van Hoytema, familyName, van Hoytema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: van Hoytema
Context triple: [Hoyte van Hoytema, familyName, van Hoytema]
  • A. van Hoytema chosen
    Van Hoytema is a Dutch surname most notably borne by acclaimed cinematographer Hoyte van Hoytema, known for his work on major contemporary films.
  • B. van Wijnbergen
    Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
  • C. van Amsberg
    Van Amsberg is the German-origin noble family name associated with the Dutch royal family, including members such as Prince Constantijn of the Netherlands.
  • D. van Riemsdijk
    Van Riemsdijk is a Dutch surname associated with several notable figures, including colonial administrators and scholars from the Netherlands.
  • E. van Slingelandt
    Van Slingelandt is a Dutch surname historically associated with a prominent political and administrative family in the Netherlands.
  • 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_69d381af787481908bc401325c760a88 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d6cdb6cc8190b37ca4494287128b completed April 7, 2026, 10:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71da2053481908fe5ed097b480cdd completed April 9, 2026, 3:31 a.m.
Created at: April 6, 2026, 11:50 a.m.