Triple

T3694261
Position Surface form Disambiguated ID Type / Status
Subject Beinsdorp E78416 entity
Predicate locatedNear P294 FINISHED
Object Hoofddorp E76459 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: Hoofddorp | Statement: [Beinsdorp, locatedNear, Hoofddorp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hoofddorp
Context triple: [Beinsdorp, locatedNear, Hoofddorp]
  • A. Hoofddorp chosen
    Hoofddorp is the main town and administrative center of the municipality of Haarlemmermeer in the Netherlands.
  • B. Zoetermeer
    Zoetermeer is a modern, rapidly grown satellite city of The Hague in the western Netherlands, known for its residential neighborhoods and light-rail connections.
  • C. Leidschendam-Voorburg
    Leidschendam-Voorburg is a municipality in the western Netherlands, near The Hague, formed by the towns of Leidschendam and Voorburg.
  • 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. Zoeterwoude
    Zoeterwoude is a small Dutch municipality and village known for its rural character and location near Leiden in the province of South Holland.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4e9e4748190aa178692ef27e3a6 completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1a54dd08190bdaaf6772758c22f completed April 3, 2026, 1:33 p.m.
Created at: March 8, 2026, 3:26 p.m.