Triple

T10272043
Position Surface form Disambiguated ID Type / Status
Subject Bückeburg palace chapel E240860 entity
Predicate locatedIn P40 FINISHED
Object Bückeburg E380040 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: Bückeburg | Statement: [Bückeburg palace chapel, locatedIn, Bückeburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bückeburg
Context triple: [Bückeburg palace chapel, locatedIn, Bückeburg]
  • A. Bückeburg chosen
    Bückeburg is a historic town in Lower Saxony, Germany, known for its former role as the residence of the Counts and Princes of Schaumburg-Lippe and its well-preserved Renaissance castle.
  • B. Nordhausen
    Nordhausen is a historic town in central Germany known for its medieval architecture, former role as a key trading center, and association with the nearby Mittelbau-Dora concentration camp site.
  • C. Hildesheim
    Hildesheim is a historic city in northern Germany renowned for its medieval architecture and UNESCO-listed Romanesque churches.
  • D. Braunschweig
    Braunschweig is a historic city in northern Germany known for its medieval architecture, cultural institutions, and role as an important economic and scientific center.
  • E. Staßfurt
    Staßfurt is a town in Saxony-Anhalt, Germany, historically known for its salt mining and chemical industry.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2872830819080fdfa816167d04c completed April 7, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69de8413f30c8190aebe1504e213b6cc completed April 14, 2026, 6:14 p.m.
Created at: April 6, 2026, 11:36 a.m.