Triple

T22415189
Position Surface form Disambiguated ID Type / Status
Subject Lennisheuvel E554102 entity
Predicate nearbySettlement P350 FINISHED
Object Liempde NE NERFINISHED

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: Liempde | Statement: [Lennisheuvel, nearbySettlement, Liempde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Liempde
Context triple: [Lennisheuvel, nearbySettlement, Liempde]
  • A. Liempde chosen
    Liempde is a village in the Dutch province of North Brabant, known for its rural character and traditional cultural landscape.
  • B. Poitzen
    Poitzen is a small village in Lower Saxony, Germany, that forms part of the municipality of Faßberg.
  • C. Leeming
    Leeming is a residential suburb in the southern part of Perth, Western Australia, known for its family-friendly environment and proximity to major transport routes and amenities.
  • D. Laak
    Laak is an urban district of The Hague in the Netherlands, known for its dense residential areas, canals, and diverse population.
  • E. Hudde
    Hudde is a Dutch surname most notably associated with Johannes Hudde, a 17th-century mathematician and mayor of Amsterdam known for his contributions to algebra and optics.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1594615f881909688b02548ee83eb completed April 29, 2026, 1:05 a.m.
Created at: April 16, 2026, 8:46 p.m.