Triple

T6260426
Position Surface form Disambiguated ID Type / Status
Subject Spui E140281 entity
Predicate nearbySettlement P350 FINISHED
Object Spijkenisse E70497 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: Spijkenisse | Statement: [Spui, nearbySettlement, Spijkenisse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Spijkenisse
Context triple: [Spui, nearbySettlement, Spijkenisse]
  • A. Spijkenisse chosen
    Spijkenisse is a town and former municipality in the western Netherlands, now part of the municipality of Nissewaard and known as a suburban area near Rotterdam.
  • B. Sparnacien
    Sparnacien is the French demonym for an inhabitant of the town of Épernay in the Champagne region.
  • C. Winkel van Sinkel
    Winkel van Sinkel is a historic former department store and cultural landmark in the center of Utrecht, Netherlands, now used as a venue for events, dining, and nightlife.
  • D. Zesgehuchten
    Zesgehuchten was a former village and municipality in the Dutch province of North Brabant, now part of the city of Geldrop-Mierlo.
  • E. De Kwakel
    De Kwakel is a small village in the Dutch province of North Holland, known for its rural character and proximity to the town of Uithoorn.
  • 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_69c008c95c5c819084bd3dd56133d84d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063856f308190a351a661caaae5f9 completed March 22, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c24444b85c8190adf09c473b42ea9b completed March 24, 2026, 7:59 a.m.
Created at: March 22, 2026, 4:24 p.m.