Triple

T5123686
Position Surface form Disambiguated ID Type / Status
Subject Uitgeest E115532 entity
Predicate locatedBetween P1262 FINISHED
Object Alkmaar E445674 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: Alkmaar | Statement: [Uitgeest, locatedBetween, Alkmaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alkmaar
Context triple: [Uitgeest, locatedBetween, Alkmaar]
  • A. Alkmaar chosen
    Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
  • B. Almere
    Almere is a modern planned city in the Dutch province of Flevoland, known for its rapid growth, contemporary architecture, and role as a major commuter town near Amsterdam.
  • C. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • D. Hellevoetsluis
    Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
  • E. Apeldoorn
    Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
  • 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_69bd4442ade0819087b9461f892b206b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7805c55c8190bc0540d755dc6242 completed March 20, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e8a6567f14819086134cdf3a13aa9b completed April 22, 2026, 10:43 a.m.
Created at: March 20, 2026, 1:42 p.m.