Triple

T15139679
Position Surface form Disambiguated ID Type / Status
Subject Lelystad Airport E361650 entity
Predicate serves P98 FINISHED
Object Lelystad NE NERFINISHED

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: Lelystad | Statement: [Lelystad Airport, serves, Lelystad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lelystad
Context triple: [Lelystad Airport, serves, Lelystad]
  • A. Lelystad chosen
    Lelystad is a planned city in the Dutch province of Flevoland, known for being one of the largest land reclamation projects in the world and the capital of the province.
  • B. Delfzijl
    Delfzijl is a port town in the northeast of the Netherlands, known for its maritime industry and location on the Ems estuary near the German border.
  • C. Hoogeveen
    Hoogeveen is a town and municipality in the northeastern Netherlands known for its historical peat colonies and location in the province of Drenthe.
  • D. Alblasserdam
    Alblasserdam is a town and municipality in the western Netherlands, situated along the Noord River and known for its proximity to the Kinderdijk windmills.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d85a0759908190b8a051d2e2a1cbe6 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005c46a248190a2364092d40274f3 completed April 15, 2026, 9:40 p.m.
Created at: April 10, 2026, 3:07 a.m.