Triple

T2060219
Position Surface form Disambiguated ID Type / Status
Subject Old Masters E45771 entity
Predicate hasNotableExample P1259 FINISHED
Object Gerrit Dou E127620 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: Gerrit Dou | Statement: [Old Masters, hasNotableExample, Gerrit Dou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gerrit Dou
Context triple: [Old Masters, hasNotableExample, Gerrit Dou]
  • A. Gerrit Dou chosen
    Gerrit Dou was a Dutch Golden Age painter renowned for his meticulously detailed genre scenes and mastery of light as a leading figure of the Leiden fijnschilders.
  • B. Cornelis van Haarlem
    Cornelis van Haarlem was a Dutch late Renaissance painter known for his dynamic, elongated figures and complex compositions that exemplify Northern Mannerism.
  • C. Aert van der Neer
    Aert van der Neer was a Dutch Golden Age painter renowned for his atmospheric moonlit landscapes and winter scenes.
  • D. Frederik de Wit
    Frederik de Wit was a prominent 17th-century Dutch cartographer and publisher renowned for his richly decorated maps and atlases produced during the Dutch Golden Age of cartography.
  • E. Jan van Goyen
    Jan van Goyen was a prominent 17th-century Dutch landscape painter of the Golden Age, known for his tonal, atmospheric river and village 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_69a8891a19508190a12ef1e192308dcb completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9cfdac88190b8b7af1bfea6a78e completed March 7, 2026, 5:38 a.m.
NED1 Entity disambiguation (via context triple) batch_69b20f1577388190bc95b2151af55732 completed March 12, 2026, 12:55 a.m.
Created at: March 4, 2026, 7:40 p.m.