Triple

T1590701
Position Surface form Disambiguated ID Type / Status
Subject Cornelis Tromp E34171 entity
Predicate givenName P17 FINISHED
Object Cornelis E103491 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: Cornelis | Statement: [Cornelis Tromp, givenName, Cornelis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cornelis
Context triple: [Cornelis Tromp, givenName, Cornelis]
  • A. Cornelis chosen
    Cornelis is a Dutch given name historically borne by notable figures such as statesman Cornelis de Witt.
  • B. Cornelis de Vos
    Cornelis de Vos was a prominent Flemish Baroque painter known for his refined portraits and religious scenes in early 17th-century Antwerp.
  • C. Nicolaes
    Nicolaes is a Dutch given name historically borne by several notable figures, including 17th-century painters and civic leaders of the Dutch Golden Age.
  • D. 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.
  • E. Dirck van Delen
    Dirck van Delen was a Dutch Golden Age painter renowned for his meticulously rendered architectural and church interior scenes.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa621526e8819097d8c5330e527ed3 completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae26e37de88190b817c24323951ea8 completed March 9, 2026, 1:48 a.m.
Created at: March 4, 2026, 7:27 p.m.