Triple

T17013701
Position Surface form Disambiguated ID Type / Status
Subject Dieren E412762 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Doesburg E172118 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: Doesburg | Statement: [Dieren, hasNearbySettlement, Doesburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doesburg
Context triple: [Dieren, hasNearbySettlement, Doesburg]
  • A. Doesburg chosen
    Doesburg is a historic city in the Dutch province of Gelderland, known for its well-preserved medieval center and location at the confluence of the IJssel and Oude IJssel rivers.
  • B. Vredenburg
    Vredenburg is a former name of the Muziekcentrum Vredenburg, a prominent concert and music venue in Utrecht, Netherlands.
  • C. Vredenburg
    Vredenburg is a town on South Africa’s West Coast that serves as a regional commercial and service hub near Saldanha Bay.
  • D. Batenburg
    Batenburg is a small historic town in the Dutch province of Gelderland, known for its medieval castle ruins and picturesque setting along the river Maas.
  • E. Dieburg
    Dieburg is a small historic town in the German state of Hesse, known for its medieval old town and regional administrative role.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47dab688190bf486bcf0b40ed4f completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4990948190861ff81f8fc3e8f2 completed May 10, 2026, 11:56 p.m.
Created at: April 10, 2026, 5:33 a.m.