Triple

T4008412
Position Surface form Disambiguated ID Type / Status
Subject Südkreuz station E89582 entity
Predicate fareZone P844 FINISHED
Object VBB Berlin A E312736 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: VBB Berlin A | Statement: [Südkreuz station, fareZone, VBB Berlin A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VBB Berlin A
Context triple: [Südkreuz station, fareZone, VBB Berlin A]
  • A. VBB: Berlin AB chosen
    VBB: Berlin AB is the central fare zone of Berlin’s public transport network, covering the inner city area served by buses, trams, U-Bahn, and S-Bahn.
  • B. VBB
    VBB is the public transport authority and fare network that coordinates and integrates regional and urban transit services across Berlin and the surrounding Brandenburg region.
  • C. MTU München
    MTU München was the original company from which MTU Aero Engines emerged, serving as a key German manufacturer in the aerospace and engine industry.
  • D. Hamburger SV
    Hamburger SV is a historic German football club based in Hamburg, known for its long-standing presence in the Bundesliga and passionate fan base.
  • E. Berliner Verkehrsbetriebe
    Berliner Verkehrsbetriebe is Berlin’s main public transport company, operating the city’s extensive network of U-Bahn trains, trams, and buses.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa647f80819081180eb267f1cfcc completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c6ae0ec819099c229a4cfe926f2 completed March 14, 2026, 11:54 a.m.
Created at: March 9, 2026, 3:34 p.m.