Triple

T1752536
Position Surface form Disambiguated ID Type / Status
Subject George William, Duke of Brunswick-Lüneburg E38475 entity
Predicate regionRuled P15936 FINISHED
Object Celle E30373 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: Celle | Statement: [George William, Duke of Brunswick-Lüneburg, regionRuled, Celle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Celle
Context triple: [George William, Duke of Brunswick-Lüneburg, regionRuled, Celle]
  • A. Celle chosen
    Celle is a historic town in northern Germany renowned for its well-preserved half-timbered old town and ducal palace.
  • B. Cellese
    Cellese is a regional dialect of the Franco-Provençal language traditionally spoken in a specific area of the Franco-Provençal linguistic region.
  • C. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • D. Agria
    Agria is a coastal town in the Magnesia regional unit of Thessaly, Greece, near the city of Volos.
  • E. Rednitz
    The Rednitz is a river in Bavaria, Germany, that flows through cities such as Fürth and joins with the Pegnitz to form the Regnitz.
  • 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa641432d88190ab4254cb4c3ad402 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e625c48190a0fbda31010bdc5f completed March 8, 2026, 4:16 p.m.
Created at: March 4, 2026, 7:31 p.m.