Triple

T6548136
Position Surface form Disambiguated ID Type / Status
Subject Waterlooplein metro station E151061 entity
Predicate hasEntrance P6140 FINISHED
Object Waterlooplein E194082 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: Waterlooplein | Statement: [Waterlooplein metro station, hasEntrance, Waterlooplein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterlooplein
Context triple: [Waterlooplein metro station, hasEntrance, Waterlooplein]
  • A. Waterlooplein square chosen
    Waterlooplein square is a central square in Amsterdam best known for its historic daily flea market and proximity to major cultural and civic buildings.
  • B. Leidseplein
    Leidseplein is a lively square in central Amsterdam known for its theaters, nightlife, street performers, and numerous cafés and restaurants.
  • C. Luxemburgplein
    Luxemburgplein is a prominent square in Brussels, Belgium, located near the European Parliament and known as a hub for political and social gatherings.
  • D. Rembrandtplein
    Rembrandtplein is a lively central square in Amsterdam known for its vibrant nightlife, cafés, and statue of the painter Rembrandt van Rijn.
  • E. Koningsplein
    Koningsplein is a central square in Amsterdam known for its proximity to major canals, shopping streets, and the historic city center.
  • 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_69c687f3fd60819083bfa583e5bcfa71 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6adf132a88190af4553857a474ebd completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f784b8288190bf3778721fad4eb1 completed March 27, 2026, 9:32 p.m.
Created at: March 27, 2026, 1:51 p.m.