Triple

T7770685
Position Surface form Disambiguated ID Type / Status
Subject Metro Line 54 E179060 entity
Predicate serves P98 FINISHED
Object Bijlmermeer E310978 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: Bijlmermeer | Statement: [Metro Line 54, serves, Bijlmermeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bijlmermeer
Context triple: [Metro Line 54, serves, Bijlmermeer]
  • A. Bijlmermeer chosen
    Bijlmermeer is a residential neighborhood in Amsterdam, Netherlands, known for its large-scale modernist high-rise housing and diverse, multicultural population.
  • B. IJmeer
    IJmeer is a shallow lake in the Netherlands, located east of Amsterdam and forming part of the IJsselmeer lake system.
  • C. Haarlemmermeer
    Haarlemmermeer is a municipality in the province of North Holland in the Netherlands, best known for encompassing Amsterdam Airport Schiphol.
  • D. Watergraafsmeer
    Watergraafsmeer is a residential neighborhood and former polder in the eastern part of Amsterdam, known for its green spaces and relatively quiet, spacious character.
  • E. Oldambtmeer
    Oldambtmeer is an artificial lake in the municipality of Oldambt in the province of Groningen, Netherlands, created as part of a large-scale landscape and recreational development project.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70438ca2481909114b0c434717109 completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7ead45c8190847365d8549eefab completed March 29, 2026, 6:34 a.m.
Created at: March 27, 2026, 4:11 p.m.