Triple

T10417257
Position Surface form Disambiguated ID Type / Status
Subject Bollenstreek E245550 entity
Predicate contains P35 FINISHED
Object Noordwijkerhout E690867 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: Noordwijkerhout | Statement: [Bollenstreek, contains, Noordwijkerhout]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noordwijkerhout
Context triple: [Bollenstreek, contains, Noordwijkerhout]
  • A. Noordwijkerhout chosen
    Noordwijkerhout is a town in South Holland, Netherlands, known for its bulb flower fields and role in the Dutch "Dune and Bulb Region."
  • B. Voorhout
    Voorhout is a village in South Holland, Netherlands, that forms part of the municipality of Teylingen.
  • C. Oosterhout
    Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
  • D. Houten
    Houten is a Dutch town in the province of Utrecht, known for its bicycle-friendly urban design and as the home of the Royal Dutch Mint.
  • E. Bloemendaal
    Bloemendaal is a coastal municipality in North Holland, Netherlands, known for its beaches, dunes, and affluent residential areas.
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea1194e08190a18c3b3002147493 completed April 7, 2026, 11:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd9495b9748190905b02621939b326 completed May 8, 2026, 7:45 a.m.
Created at: April 6, 2026, 12:11 p.m.