Triple

T22594618
Position Surface form Disambiguated ID Type / Status
Subject IJsselmeer water system E574640 entity
Predicate hasPart P35 FINISHED
Object Randmeren NE NERFINISHED

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: Randmeren | Statement: [IJsselmeer water system, hasPart, Randmeren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Randmeren
Context triple: [IJsselmeer water system, hasPart, Randmeren]
  • A. Randmeren chosen
    Randmeren is a chain of shallow border lakes in the central Netherlands that separates the former island of Flevoland from the older mainland provinces.
  • B. Heenweg
    Heenweg is a small village in the Dutch municipality of Westland in the province of South Holland, Netherlands.
  • C. Heemraadlaan
    Heemraadlaan is a metro station in Spijkenisse, Netherlands, serving as part of the Rotterdam Metro network.
  • D. Renkum
    Renkum is a municipality and town in the province of Gelderland in the eastern Netherlands, known for its riverside landscapes and proximity to the city of Arnhem.
  • E. Twekkelervaart
    Twekkelervaart is a canal in the eastern Netherlands that serves as a waterway in and around the city of Almelo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f16164d690819096f7c4efb6cedad9 completed April 29, 2026, 1:39 a.m.
Created at: April 17, 2026, 2:49 p.m.