Triple

T1586490
Position Surface form Disambiguated ID Type / Status
Subject Pierre Cuypers E34076 entity
Predicate deathPlace P21 FINISHED
Object Roermond, Netherlands E214518 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: Roermond, Netherlands | Statement: [Pierre Cuypers, deathPlace, Roermond, Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roermond, Netherlands
Context triple: [Pierre Cuypers, deathPlace, Roermond, Netherlands]
  • A. Roermond, Netherlands chosen
    Roermond, Netherlands is a historic city in the southeastern province of Limburg known for its medieval architecture, riverside setting, and role as a regional commercial and cultural center.
  • B. Zundert, Netherlands
    Zundert, Netherlands is a small Dutch town in North Brabant best known as the birthplace of painter Vincent van Gogh.
  • C. Haarlem, Netherlands
    Haarlem, Netherlands is a historic Dutch city near Amsterdam known for its medieval architecture, cultural heritage, and role as the capital of North Holland.
  • D. Asten, Netherlands
    Asten is a town in the Dutch province of North Brabant known for its bell foundry and carillon manufacturing industry.
  • E. Enschede, Netherlands
    Enschede is a city in the eastern Netherlands known for its former textile industry, technical university, and location near the German border.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908f3b5f48190bd5eff3ce81c5ffb completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb90e16081908d70df182b7efb8a completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:27 p.m.