Triple

T16366927
Position Surface form Disambiguated ID Type / Status
Subject Jozias van Aartsen E397459 entity
Predicate familyName P18 FINISHED
Object van Aartsen E397460 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 Aartsen | Statement: [Jozias van Aartsen, familyName, van Aartsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: van Aartsen
Context triple: [Jozias van Aartsen, familyName, van Aartsen]
  • A. van Aartsen chosen
    Van Aartsen is a Dutch surname most prominently associated with Jozias van Aartsen, a notable Dutch politician and former mayor of The Hague.
  • B. 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.
  • C. van Wijnbergen
    Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
  • D. van der Meer
    Van der Meer is a Dutch surname borne by several notable individuals, including Nobel Prize–winning physicist Simon van der Meer.
  • E. van den Bergh
    Van den Bergh is a Dutch-origin surname borne by various notable individuals across fields such as politics, science, and the arts.
  • 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_69d87f2778dc8190aa95c7572db127e6 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2ff3de3d88190a42cd708746c8bd0 completed April 18, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a002dc29f088190ba5d69ff3c12a251 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:08 a.m.