Triple

T261343
Position Surface form Disambiguated ID Type / Status
Subject The Hague E5547 entity
Predicate contains P35 FINISHED
Object Kijkduin E71726 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: Kijkduin | Statement: [The Hague, contains, Kijkduin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kijkduin
Context triple: [The Hague, contains, Kijkduin]
  • A. Scheveningen chosen
    Scheveningen is a popular seaside resort district of The Hague in the Netherlands, known for its long sandy beach, pier, and promenade along the North Sea coast.
  • B. Harlem Meer
    Harlem Meer is a picturesque man-made lake and surrounding landscape located at the northeast corner of Central Park in New York City.
  • C. Bullewijk
    Bullewijk is a small waterway and urban canal in Amsterdam’s southeastern area, integrated into the city’s network of rivers and canals.
  • D. Grevelingen
    Grevelingen is a large saltwater lake and former estuary in the southwestern Netherlands, known for its nature reserves, water sports, and role in the Delta Works coastal defense system.
  • E. IJmeer
    IJmeer is a shallow lake in the Netherlands, located east of Amsterdam and forming part of the IJsselmeer lake system.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a501b9767c8190a3449503fa372c64 completed March 2, 2026, 3:19 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.