Triple

T16047913
Position Surface form Disambiguated ID Type / Status
Subject Rijnmond region E389271 entity
Predicate hasMunicipality P847 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: [Rijnmond region, hasMunicipality, Lansingerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lansingerland
Context triple: [Rijnmond region, hasMunicipality, 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. ’s-Gravenland
    ’s-Gravenland is a residential district in the Dutch city of Capelle aan den IJssel, located in the province of South Holland.
  • D. Rietlanden
    Rietlanden is a waterfront area in Amsterdam’s Eastern Docklands, known for its former industrial port functions and subsequent urban redevelopment.
  • E. Maasland
    Maasland is a historical region in the Low Countries centered along the river Meuse, known for its medieval political and cultural significance.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18360464881909fd4d3bcb4ffb7f5 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbddc25481908fca660c4f14eaff completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:56 a.m.