Triple

T10132195
Position Surface form Disambiguated ID Type / Status
Subject South Holland E226364 entity
Predicate containsCity P294 FINISHED
Object Pijnacker-Nootdorp E187151 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: Pijnacker-Nootdorp | Statement: [South Holland, containsCity, Pijnacker-Nootdorp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pijnacker-Nootdorp
Context triple: [South Holland, containsCity, Pijnacker-Nootdorp]
  • A. Pijnacker-Nootdorp chosen
    Pijnacker-Nootdorp is a Dutch municipality in the western Netherlands, situated between The Hague and Rotterdam.
  • B. Noordwijkerhout
    Noordwijkerhout is a town in South Holland, Netherlands, known for its bulb flower fields and role in the Dutch "Dune and Bulb Region."
  • C. Voorhout
    Voorhout is a village in South Holland, Netherlands, that forms part of the municipality of Teylingen.
  • 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. 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_69ca843057b48190a86730167f5d6b98 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cdd336cbf48190b647c69675d0b06f completed April 2, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f03e00c819091ae5273aa10fe4b completed May 3, 2026, 10:10 a.m.
Created at: March 30, 2026, 9:06 p.m.