Triple

T11625612
Position Surface form Disambiguated ID Type / Status
Subject Domplein Utrecht E276260 entity
Predicate hasLandmark P105 FINISHED
Object Domkerk E302219 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: Domkerk | Statement: [Domplein Utrecht, hasLandmark, Domkerk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Domkerk
Context triple: [Domplein Utrecht, hasLandmark, Domkerk]
  • A. Domkerk chosen
    Domkerk is the historic Gothic cathedral in Utrecht that once served as the seat of the bishop and remains one of the city's most prominent landmarks.
  • B. Ouderkerk
    Ouderkerk was a former Dutch municipality in the province of South Holland that later became part of the municipality of Krimpenerwaard.
  • C. Hoedekenskerke
    Hoedekenskerke is a small village in the Dutch province of Zeeland, known for its rural character and location along the Western Scheldt.
  • D. Leegkerk
    Leegkerk is a small village in the province of Groningen in the Netherlands, known for its historic rural character and proximity to the city of Groningen.
  • E. Grijpskerk
    Grijpskerk is a village in the Dutch province of Groningen, known historically as a local agricultural and railway hub.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a12416908190ac2dcd7f7ebb308f completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87845d588190bfa4197e7ab600a7 completed April 26, 2026, 9:45 p.m.
Created at: April 8, 2026, 9:39 p.m.