Triple

T23363951
Position Surface form Disambiguated ID Type / Status
Subject Swart E593260 entity
Predicate hasVariant P455 FINISHED
Object Zwart NE NERFINISHED

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: Zwart | Statement: [Swart, hasVariant, Zwart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zwart
Context triple: [Swart, hasVariant, Zwart]
  • A. Swart chosen
    Swart is a surname of Afrikaans and Dutch origin, notably borne by Charles Robberts Swart, the first State President of South Africa.
  • B. Blaak
    Blaak is a central transport hub and urban square in Rotterdam, known for its metro and train station near landmarks like the Cube Houses and Markthal.
  • C. Geel-zwarten
    Geel-zwarten is a common Dutch nickname referring to the football club Vitesse, derived from the team’s yellow-and-black colors.
  • D. Rood-witten
    Rood-witten is a popular nickname for PSV Eindhoven, referring to the club’s traditional red-and-white team colors.
  • E. Blaauw
    Blaauw is a Dutch surname most notably associated with Gerrit Blaauw, a pioneering computer architect involved in the design of early IBM systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e25d2593c88190bcdf4a716a94ccb2 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1a0aac4248190a4663ed12aed6856 completed April 29, 2026, 6:09 a.m.
Created at: April 17, 2026, 5:31 p.m.