Triple

T3616859
Position Surface form Disambiguated ID Type / Status
Subject Badhoevedorp E76622 entity
Predicate hasNeighbouringSettlement P4647 FINISHED
Object Lijnden E77278 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: Lijnden | Statement: [Badhoevedorp, hasNeighbouringSettlement, Lijnden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lijnden
Context triple: [Badhoevedorp, hasNeighbouringSettlement, Lijnden]
  • A. Lijnden chosen
    Lijnden is a village in the Dutch province of North Holland, situated near Amsterdam and known for its location within the reclaimed polder landscape.
  • B. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • C. Nijverdal
    Nijverdal is a town in the Dutch province of Overijssel known as a gateway to the Sallandse Heuvelrug National Park and its surrounding natural landscapes.
  • D. Scharendijke
    Scharendijke is a village in the Dutch province of Zeeland, known as a popular base for water sports and diving in the Grevelingen and North Sea area.
  • E. Papendrecht
    Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc27c98088190a493c9eddf6b206a completed March 8, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf275f49f48190ad92d5aaebaac4d0 completed April 3, 2026, 2:35 a.m.
Created at: March 8, 2026, 3:23 p.m.