Triple

T13569245
Position Surface form Disambiguated ID Type / Status
Subject Dorotheenstadt parish E324114 entity
Predicate locatedInQuarter P40 FINISHED
Object Dorotheenstadt E339957 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: Dorotheenstadt | Statement: [Dorotheenstadt parish, locatedInQuarter, Dorotheenstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dorotheenstadt
Context triple: [Dorotheenstadt parish, locatedInQuarter, Dorotheenstadt]
  • A. Dorotheenstadt chosen
    Dorotheenstadt is a historic district in central Berlin, Germany, known for its cultural significance and notable institutions.
  • B. Oststadt
    Oststadt is a central district of Hanover, Germany, known for its urban residential areas, cultural venues, and proximity to the city’s main commercial and administrative centers.
  • C. Märkisches Viertel
    Märkisches Viertel is a large post-war housing estate and residential district in the Reinickendorf borough of Berlin, known for its high-rise apartment blocks and dense urban layout.
  • D. Brandenburgisches Viertel
    Brandenburgisches Viertel is a residential district of the town of Eberswalde in the German state of Brandenburg.
  • E. Bohnenviertel
    Bohnenviertel is a historic quarter in central Stuttgart known for its narrow streets, traditional houses, and vibrant mix of small shops, bars, and restaurants.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00e0188819094fde44f85adb69c completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6f931048190ad5182a8c2ebecb6 completed May 3, 2026, 10:06 p.m.
Created at: April 9, 2026, 9:48 p.m.