Triple

T14186334
Position Surface form Disambiguated ID Type / Status
Subject Safety region Haaglanden E351586 entity
Predicate jurisdiction P82 FINISHED
Object Leidschendam-Voorburg 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: Leidschendam-Voorburg | Statement: [Safety region Haaglanden, jurisdiction, Leidschendam-Voorburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leidschendam-Voorburg
Context triple: [Safety region Haaglanden, jurisdiction, Leidschendam-Voorburg]
  • A. Leidschendam-Voorburg chosen
    Leidschendam-Voorburg is a municipality in the western Netherlands, near The Hague, formed by the towns of Leidschendam and Voorburg.
  • B. Hoofddorp
    Hoofddorp is the main town and administrative center of the municipality of Haarlemmermeer in the Netherlands.
  • C. Oisterwijk
    Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
  • D. Zoetermeer
    Zoetermeer is a modern, rapidly grown satellite city of The Hague in the western Netherlands, known for its residential neighborhoods and light-rail connections.
  • E. Beverwijk
    Beverwijk is a town and municipality in North Holland, Netherlands, known for its large indoor market and proximity to the North Sea coast.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61cd5778819092a03597bcdcc182 completed April 14, 2026, 3:48 p.m.
Created at: April 10, 2026, 1:03 a.m.