Triple

T22566884
Position Surface form Disambiguated ID Type / Status
Subject Stadthagen mausoleum E557974 entity
Predicate locatedIn P40 FINISHED
Object Stadthagen 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: Stadthagen | Statement: [Stadthagen mausoleum, locatedIn, Stadthagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stadthagen
Context triple: [Stadthagen mausoleum, locatedIn, Stadthagen]
  • A. Stadthagen chosen
    Stadthagen is a historic town in Lower Saxony, Germany, known for its Renaissance architecture and role as an administrative and cultural center of the surrounding region.
  • B. Northeim
    Northeim is a town in Lower Saxony, Germany, known for its medieval old town and location in the Leine River valley.
  • C. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • D. Lehrte
    Lehrte is a town in Lower Saxony, Germany, located east of Hanover and known historically for its railway junction and agricultural surroundings.
  • E. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • 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_69e11e5ae4ac8190b1f503457603d969 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15faaa0b081908d5aa8f3ba1e3dd3 completed April 29, 2026, 1:32 a.m.
Created at: April 16, 2026, 8:52 p.m.