Triple

T10132197
Position Surface form Disambiguated ID Type / Status
Subject South Holland E226364 entity
Predicate containsCity P294 FINISHED
Object Molenlanden E97218 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: Molenlanden | Statement: [South Holland, containsCity, Molenlanden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molenlanden
Context triple: [South Holland, containsCity, 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. Kennemerland
    Kennemerland is a coastal historical region in the northwest of the Netherlands, known for its dunes, beaches, and old trading towns.
  • E. Land van Heusden
    Land van Heusden is a historic region in the northern part of the Dutch province of North Brabant, centered around the town of Heusden and known for its medieval fortifications and river landscapes.
  • 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_69d2e5ce3fcc8190b1d07dbba34d6bff completed April 5, 2026, 10:44 p.m.
Created at: March 30, 2026, 9:06 p.m.