Triple

T15196227
Position Surface form Disambiguated ID Type / Status
Subject Dirck E363143 entity
Predicate notableBearer P458 FINISHED
Object Dirck van Delen E78553 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: Dirck van Delen | Statement: [Dirck, notableBearer, Dirck van Delen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dirck van Delen
Context triple: [Dirck, notableBearer, Dirck van Delen]
  • A. Dirck van Delen chosen
    Dirck van Delen was a Dutch Golden Age painter renowned for his meticulously rendered architectural and church interior scenes.
  • B. Dirck van der Lisse
    Dirck van der Lisse was a 17th-century Dutch Golden Age painter known for his landscapes and association with the circle of Jan van Goyen.
  • C. Cornelis van der Geest
    Cornelis van der Geest was a wealthy early 17th-century Antwerp spice merchant and prominent art collector known for patronizing artists like Peter Paul Rubens and Anthony van Dyck.
  • D. Pieter Molijn
    Pieter Molijn was a Dutch Golden Age painter best known for his atmospheric landscapes and influential role in developing realistic depictions of the Dutch countryside.
  • E. Dirck van Bleyswijck
    Dirck van Bleyswijck was a 17th-century Dutch writer and city official from Delft, best known for his detailed topographical and historical description of the city.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0067fcc788190abdc083d4eadeb36 completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff755e0f2c819088293d8a55d7883a completed May 9, 2026, 5:56 p.m.
Created at: April 10, 2026, 3:10 a.m.