Triple

T10520759
Position Surface form Disambiguated ID Type / Status
Subject Gilze en Rijen E248162 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Dongen E686703 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: Dongen | Statement: [Gilze en Rijen, neighboringMunicipality, Dongen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dongen
Context triple: [Gilze en Rijen, neighboringMunicipality, Dongen]
  • A. Dongen chosen
    Dongen is a municipality and town in the province of North Brabant in the southern Netherlands.
  • B. Veenendaal
    Veenendaal is a Dutch town and municipality in the central Netherlands, known for its location between Utrecht and the Veluwe and its mix of residential, commercial, and light industrial areas.
  • C. Rozenburg
    Rozenburg is a town in the western Netherlands that forms part of the heavily industrialized and port-dominated region of South Holland.
  • D. Rozenburg
    Rozenburg is a village in the municipality of Haarlemmermeer in the province of North Holland, Netherlands.
  • E. Zwanenburg
    Zwanenburg is a village in North Holland, Netherlands, situated near Amsterdam and known as a suburban residential community within the Haarlemmermeer municipality.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509dec25881909bc748640f26a416 completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d933f2d9e48190a4c5d5d5bdc0d7d8 completed April 10, 2026, 5:31 p.m.
Created at: April 6, 2026, 12:28 p.m.