Triple

T6994717
Position Surface form Disambiguated ID Type / Status
Subject Zoetermeer E162179 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Lansingerland E70498 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: Lansingerland | Statement: [Zoetermeer, hasNeighbouringMunicipality, Lansingerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lansingerland
Context triple: [Zoetermeer, hasNeighbouringMunicipality, Lansingerland]
  • A. Lansingerland chosen
    Lansingerland is a Dutch municipality in the province of South Holland, known for its suburban communities and greenhouse horticulture near the city of Rotterdam.
  • B. Harlingerland
    Harlingerland is a historic coastal region in East Frisia in northwestern Germany, known for its North Sea landscape, dike systems, and traditional Frisian culture.
  • C. Rietlanden
    Rietlanden is a waterfront area in Amsterdam’s Eastern Docklands, known for its former industrial port functions and subsequent urban redevelopment.
  • D. Landsmeer
    Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
  • E. Lage Landen
    Lage Landen is the historical Low Countries region in Western Europe, roughly encompassing present-day Belgium, the Netherlands, and Luxembourg.
  • 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_69c68857ffc08190857dc62cd5253777 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dbeaa88c8190a49f8504c1793e1f completed March 27, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76a1adec88190a769ec7af0fa7b51 completed March 28, 2026, 5:41 a.m.
Created at: March 27, 2026, 2:32 p.m.