Triple

T17503466
Position Surface form Disambiguated ID Type / Status
Subject Hoheneggelsen E426250 entity
Predicate hasMunicipality P847 FINISHED
Object Schellerten 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: Schellerten | Statement: [Hoheneggelsen, hasMunicipality, Schellerten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schellerten
Context triple: [Hoheneggelsen, hasMunicipality, Schellerten]
  • A. Schellerten chosen
    Schellerten is a rural municipality in Lower Saxony, Germany, characterized by its agricultural landscape and small-village communities.
  • B. Belpberg
    Belpberg is a small former municipality in the canton of Bern, Switzerland, situated on a plateau above the Gürbetal valley and known for its rural, scenic landscape.
  • C. Brenkhausen
    Brenkhausen is a village and district of the town of Höxter in North Rhine-Westphalia, Germany.
  • D. Riedesel
    Riedesel is a German surname historically associated with noble families and notable figures such as military officers and diplomats.
  • E. Wiedensahl
    Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45213a0e88190ac183d87ec088e86 completed April 19, 2026, 3:54 a.m.
Created at: April 10, 2026, 5:48 a.m.