Triple

T18311111
Position Surface form Disambiguated ID Type / Status
Subject Giessenlanden E438625 entity
Predicate partOf P40 FINISHED
Object Molenlanden 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: Molenlanden | Statement: [Giessenlanden, partOf, Molenlanden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molenlanden
Context triple: [Giessenlanden, partOf, Molenlanden]
  • A. Molenlanden chosen
    Molenlanden is a municipality in the Dutch province of South Holland, known for its rural landscape, historic villages, and proximity to the Kinderdijk windmills.
  • B. Molenwaard
    Molenwaard was a former municipality in the Dutch province of South Holland that later became part of the newly formed municipality of Molenlanden.
  • C. Vierpolders
    Vierpolders is a village in the Dutch province of South Holland, known for its rural character and location near the town of Brielle.
  • D. Hoogblokland
    Hoogblokland is a small village in the Dutch province of Utrecht, known for its rural character and traditional polder landscape.
  • E. Kennemerland
    Kennemerland is a coastal historical region in the northwest of the Netherlands, known for its dunes, beaches, and old trading towns.
  • 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50219cd548190b8da5f402d5da773 completed April 19, 2026, 4:26 p.m.
Created at: April 10, 2026, 10:36 a.m.