Triple

T1777890
Position Surface form Disambiguated ID Type / Status
Subject Johan Barthold Jongkind E39221 entity
Predicate influencedBy P9 FINISHED
Object Andreas Schelfhout E203733 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: Andreas Schelfhout | Statement: [Johan Barthold Jongkind, influencedBy, Andreas Schelfhout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andreas Schelfhout
Context triple: [Johan Barthold Jongkind, influencedBy, Andreas Schelfhout]
  • A. Andreas Schelfhout chosen
    Andreas Schelfhout was a prominent 19th-century Dutch landscape painter and influential teacher associated with the Romantic movement in the Netherlands.
  • B. Daniël Stalpaert
    Daniël Stalpaert was a 17th-century Dutch architect and city planner known for his influential role in shaping Amsterdam’s urban landscape.
  • C. Ben Weyts
    Ben Weyts is a Belgian politician from Flanders who has served in prominent roles within the Flemish government, particularly in areas such as education and mobility.
  • D. Johannes Uytenbogaert
    Johannes Uytenbogaert was a leading Dutch Remonstrant minister and theologian of the early 17th century, known as a chief spokesman for Arminianism in the Netherlands.
  • E. Rogier Stoffers
    Rogier Stoffers is a Dutch cinematographer known for his work on a range of international films and television productions.
  • 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_69a88630519c8190a17addd83c4a3ef4 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64b967f08190a73216361b9c2d83 completed March 6, 2026, 5:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9a14a18819090b83b3d10304c74 completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:31 p.m.