Triple

T17053322
Position Surface form Disambiguated ID Type / Status
Subject Military Boekelo-Enschede E413755 entity
Predicate locatedIn P40 FINISHED
Object Boekelo E901443 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: Boekelo | Statement: [Military Boekelo-Enschede, locatedIn, Boekelo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Boekelo
Context triple: [Military Boekelo-Enschede, locatedIn, Boekelo]
  • A. Boekelo chosen
    Boekelo is a village in the Dutch province of Overijssel, known for its salt industry heritage and annual international military horse trials.
  • B. Lheebroek
    Lheebroek is a small village in the Dutch province of Drenthe, situated within the municipality of Westerveld.
  • C. Blokzijl
    Blokzijl is a historic former trading town and harbor in the Dutch province of Overijssel, known for its picturesque canals and well-preserved old center.
  • D. Boskoop
    Boskoop is a Dutch town historically renowned as a major center of tree and nursery cultivation.
  • E. Leenderbos
    Leenderbos is a large forest and nature reserve in the Dutch province of North Brabant, known for its pine woods, heathlands, and walking and cycling trails.
  • 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_69d886cde3d481908d4d01ba88ba7eb7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3daa491008190ad013ee37532aa51 completed April 18, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012343eca0819086a07511c5d22878 completed May 11, 2026, 12:31 a.m.
Created at: April 10, 2026, 5:34 a.m.