Triple

T11967939
Position Surface form Disambiguated ID Type / Status
Subject AFAS Live E284836 entity
Predicate cityDistrict P2709 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: [AFAS Live, cityDistrict, Bijlmermeer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bijlmermeer
Context triple: [AFAS Live, cityDistrict, 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9037adf5881908abe1a4e64a71f20 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459691ff0819099282172933d2d81 completed May 1, 2026, 7:42 a.m.
Created at: April 8, 2026, 9:46 p.m.