Triple

T1283709
Position Surface form Disambiguated ID Type / Status
Subject Cornelis Theodorus Elout E27383 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 Theodorus Elout, givenName, Cornelis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cornelis
Context triple: [Cornelis Theodorus Elout, 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c0b599ac819096fca9ada294d939 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5ac8a2481908394095e9a6edc6a completed March 8, 2026, 5:45 p.m.
Created at: March 1, 2026, 7:50 p.m.