Triple

T2597112
Position Surface form Disambiguated ID Type / Status
Subject Pete Kuyper E58256 entity
Predicate hasNameInEnglish P3437 FINISHED
Object Pete Kuyper E58256 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: Pete Kuyper | Statement: [Pete Kuyper, hasNameInEnglish, Pete Kuyper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pete Kuyper
Context triple: [Pete Kuyper, hasNameInEnglish, Pete Kuyper]
  • A. Pete Kuyper chosen
    Pete Kuyper was an American entrepreneur best known for establishing the window and door manufacturer that became Pella Corporation.
  • B. Ben Louw
    Ben Louw is an individual notable enough to be specifically cited as a prominent bearer of the surname Louw.
  • C. Fred J. Koenekamp
    Fred J. Koenekamp was an American cinematographer renowned for his work on major films of the 1970s and 1980s, earning an Academy Award and multiple nominations for his visually striking photography.
  • D. Herman Louw
    Herman Louw is an individual notable enough to be recognized as a prominent bearer of the surname Louw.
  • E. Martin Louw
    Martin Louw is a person bearing the surname Louw, which is associated with several notable individuals, though specific widely recognized achievements for this particular bearer are not clearly documented.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd42b3cd4819093b2cab78de1f66c completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf429ca8819091ed4737653f6023 completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:49 p.m.