Triple

T10947709
Position Surface form Disambiguated ID Type / Status
Subject Führerbau E258640 entity
Predicate locatedIn P40 FINISHED
Object Maxvorstadt E478074 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: Maxvorstadt | Statement: [Führerbau, locatedIn, Maxvorstadt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maxvorstadt
Context triple: [Führerbau, locatedIn, Maxvorstadt]
  • A. Maxvorstadt chosen
    Maxvorstadt is a central Munich district known for its concentration of major art museums, universities, and cultural 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. Oranienburger Vorstadt
    Oranienburger Vorstadt is a historic neighborhood in central Berlin, known for its 19th-century urban fabric, cultural sites, and proximity to key political and intellectual centers of the city.
  • D. Magniviertel
    Magniviertel is a historic quarter in Braunschweig, Germany, known for its medieval street layout, half-timbered houses, and lively cultural and nightlife scene.
  • E. Dorotheenstadt
    Dorotheenstadt is a historic district in central Berlin, Germany, known for its cultural significance and notable institutions.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770ebac3c8190849ddda3d9d37327 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c4a75688190894c83b8964509a6 completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.