Triple

T18583497
Position Surface form Disambiguated ID Type / Status
Subject Lange Vijverberg E454178 entity
Predicate locatedNear P294 FINISHED
Object Korte Vijverberg 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: Korte Vijverberg | Statement: [Lange Vijverberg, locatedNear, Korte Vijverberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korte Vijverberg
Context triple: [Lange Vijverberg, locatedNear, Korte Vijverberg]
  • A. Lange Vijverberg chosen
    Lange Vijverberg is a historic street and promenade in the center of The Hague, Netherlands, known for its elegant townhouses and views over the Hofvijver and the Binnenhof.
  • B. De Vijverberg
    De Vijverberg is a football stadium in Doetinchem, Netherlands, best known as the home ground of the club De Graafschap.
  • C. Zandkreek
    Zandkreek is a tidal waterway and former estuary in the Dutch province of Zeeland, known for its role in regional water management and coastal protection.
  • D. Krimpenerwaard
    Krimpenerwaard is a rural municipality in the Dutch province of South Holland, known for its polder landscapes, dikes, and traditional villages between the rivers Lek and Hollandse IJssel.
  • E. Beekkant
    Beekkant is a Brussels Metro station that functions as a key interchange point in the western part of the city’s rapid transit network.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e543d200dc8190b8797d731f4e4865 completed April 19, 2026, 9:06 p.m.
Created at: April 10, 2026, 11:44 a.m.