Triple

T6548144
Position Surface form Disambiguated ID Type / Status
Subject Waterlooplein metro station E151061 entity
Predicate locatedUnder P10157 FINISHED
Object Valkenburgerstraat E607107 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: Valkenburgerstraat | Statement: [Waterlooplein metro station, locatedUnder, Valkenburgerstraat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valkenburgerstraat
Context triple: [Waterlooplein metro station, locatedUnder, Valkenburgerstraat]
  • A. Valkenburgerstraat chosen
    Valkenburgerstraat is a street in central Amsterdam, Netherlands, located near the Waterlooplein area and served by the city’s metro network.
  • B. Van Baerlestraat
    Van Baerlestraat is a major street in Amsterdam known for running alongside the Museumplein and providing access to several prominent museums and cultural institutions.
  • C. Wiertzstraat
    Wiertzstraat is a street in Brussels, Belgium, located in the European Quarter near key European Union institutions.
  • D. Vijzelstraat
    Vijzelstraat is a major street in central Amsterdam, Netherlands, running between the city’s historic canals and serving as an important traffic and commercial route.
  • E. Domstraat
    Domstraat is a historic street in the center of Utrecht, Netherlands, connecting key landmarks around the Dom Tower and cathedral.
  • 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_69c6eed5afb88190aa4fdae9cda04c54 completed March 27, 2026, 8:55 p.m.
Created at: March 27, 2026, 1:51 p.m.