Triple

T4931335
Position Surface form Disambiguated ID Type / Status
Subject University of Harderwijk E110702 entity
Predicate locatedIn P40 FINISHED
Object Harderwijk E326186 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: Harderwijk | Statement: [University of Harderwijk, locatedIn, Harderwijk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harderwijk
Context triple: [University of Harderwijk, locatedIn, Harderwijk]
  • A. Harderwijk chosen
    Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
  • B. Waalwijk
    Waalwijk is a town and municipality in the southern Netherlands known historically for its leather and shoe industry.
  • C. Steenwijk
    Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
  • D. Meerwijk
    Meerwijk is a residential neighborhood within the town of Uithoorn in the province of North Holland, Netherlands.
  • E. Cuijk
    Cuijk is a historic town in the Dutch province of North Brabant, known for its Roman-era heritage and location along the River Meuse.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd706245e48190a61d573438461c30 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3734e5e688190bbfa472547ef65e8 completed April 18, 2026, 12:04 p.m.
Created at: March 20, 2026, 1:30 p.m.