Triple

T4039641
Position Surface form Disambiguated ID Type / Status
Subject Borsigwalde E83913 entity
Predicate adjacentTo P224 FINISHED
Object Märkisches Viertel E392708 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: Märkisches Viertel | Statement: [Borsigwalde, adjacentTo, Märkisches Viertel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Märkisches Viertel
Context triple: [Borsigwalde, adjacentTo, Märkisches Viertel]
  • A. Märkisches Viertel chosen
    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.
  • B. Dorotheenstadt
    Dorotheenstadt is a historic district in central Berlin, Germany, known for its cultural significance and notable institutions.
  • C. Kreuzberg
    Kreuzberg is a vibrant, historically working-class district in central Berlin known for its multicultural community, alternative culture, and lively arts and nightlife scenes.
  • D. Bayerisches Viertel
    Bayerisches Viertel is a historic residential neighborhood in Berlin known for its early 20th-century architecture and its significant Jewish cultural and memorial heritage.
  • E. Bahnhofsviertel
    Bahnhofsviertel is a central Frankfurt district known for its mix of historic Wilhelminian architecture, nightlife, red-light area, and growing creative and gastronomic scene.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb37e24c81908d6357ab8ba5388d completed March 9, 2026, 4:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b4d2cb081908dbca3bee5610cda completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:37 p.m.