Triple

T15233662
Position Surface form Disambiguated ID Type / Status
Subject Jodenbreestraat E364067 entity
Predicate near P350 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: [Jodenbreestraat, near, Waterlooplein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waterlooplein
Context triple: [Jodenbreestraat, near, 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. Merwedeplein
    Merwedeplein is a residential square in Amsterdam best known for being the neighborhood where Anne Frank lived before going into hiding.
  • D. Luxemburgplein
    Luxemburgplein is a prominent square in Brussels, Belgium, located near the European Parliament and known as a hub for political and social gatherings.
  • E. Gelderlandplein
    Gelderlandplein is a major shopping center in Amsterdam’s Buitenveldert district, featuring a wide range of retail stores, restaurants, and services.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007d7237081908dc17900ee66b64f completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd3dd5a081909a1a7fceda648c29 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:12 a.m.