Triple

T13224939
Position Surface form Disambiguated ID Type / Status
Subject Portrait of a Gentleman with a Letter E314852 entity
Predicate creator P184 FINISHED
Object Jan Verkolje E80123 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: Jan Verkolje | Statement: [Portrait of a Gentleman with a Letter, creator, Jan Verkolje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jan Verkolje
Context triple: [Portrait of a Gentleman with a Letter, creator, Jan Verkolje]
  • A. Jan Verkolje chosen
    Jan Verkolje was a 17th-century Dutch painter and mezzotint engraver known for his portraits and genre scenes in the Baroque style.
  • B. Jan van der Vliet
    Jan van der Vliet was a Dutch artist associated with the Delft painters’ Guild of Saint Luke during the Dutch Golden Age.
  • C. Willem van der Vliet
    Willem van der Vliet was a Dutch Golden Age painter from Delft, known for his portraits and history paintings and as an early mentor to his nephew Hendrick Cornelisz. van Vliet.
  • D. Dani van Velthoven
    Dani van Velthoven is a Dutch singer who gained national fame after winning the popular televised talent competition The Voice of Holland.
  • 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_69d806affc688190a25b6ccc588e9c72 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d3128348190836158467e9cfbe2 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a83125d481908fe02cf85651a7bb completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:19 p.m.