Triple

T1443353
Position Surface form Disambiguated ID Type / Status
Subject Amsterdam Metro line 53 E31122 entity
Predicate hasStation P35 FINISHED
Object Bullewijk E63536 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: Bullewijk | Statement: [Amsterdam Metro line 53, hasStation, Bullewijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bullewijk
Context triple: [Amsterdam Metro line 53, hasStation, Bullewijk]
  • A. Bullewijk chosen
    Bullewijk is a small waterway and urban canal in Amsterdam’s southeastern area, integrated into the city’s network of rivers and canals.
  • B. Bloemendaal
    Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
  • C. Nieuwendijk
    Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
  • D. Zwijndrecht
    Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
  • E. Begijnhof
    Begijnhof is a historic, secluded courtyard in central Amsterdam known for its preserved medieval houses and former beguine community.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c533a158819084d0917776edb6e5 completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf856d4d6481908b99610cf52abc76 completed March 22, 2026, 6 a.m.
Created at: March 1, 2026, 8 p.m.