Triple

T2610951
Position Surface form Disambiguated ID Type / Status
Subject County of Holland E58770 entity
Predicate contains P35 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: [County of Holland, contains, Alkmaar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alkmaar
Context triple: [County of Holland, contains, 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd87b24e48190ad1d4ce7e63c0f3e completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69c8e55a6d848190856460c45374c629 completed March 29, 2026, 8:39 a.m.
Created at: March 6, 2026, 9:50 p.m.