Triple

T2990219
Position Surface form Disambiguated ID Type / Status
Subject flower auction building E80730 entity
Predicate locatedIn P40 FINISHED
Object Aalsmeer E80730 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: Aalsmeer | Statement: [flower auction building, locatedIn, Aalsmeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aalsmeer
Context triple: [flower auction building, locatedIn, Aalsmeer]
  • A. Aalsmeer chosen
    Aalsmeer is a Dutch town in North Holland best known as a global center for the flower and plant trade, hosting one of the world’s largest flower auctions.
  • B. Alkmaar
    Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
  • C. Gorinchem
    Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
  • D. Purmerend
    Purmerend is a Dutch city and municipality located in the province of North Holland, known historically as a market town north of Amsterdam.
  • E. Deurne
    Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99de55208190bc56ecbe08638e5a completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69c941f469c881908e83cfd6c8191af1 completed March 29, 2026, 3:15 p.m.
Created at: March 8, 2026, 2:59 p.m.