Triple

T23125429
Position Surface form Disambiguated ID Type / Status
Subject Westkreuz station E577015 entity
Predicate operator P179 FINISHED
Object S-Bahn Berlin GmbH NE NERFINISHED

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: S-Bahn Berlin GmbH | Statement: [Westkreuz station, operator, S-Bahn Berlin GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn Berlin GmbH
Context triple: [Westkreuz station, operator, S-Bahn Berlin GmbH]
  • A. S-Bahn Berlin GmbH chosen
    S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
  • B. Berliner Verkehrsbetriebe
    Berliner Verkehrsbetriebe is Berlin’s main public transport company, operating the city’s extensive network of U-Bahn trains, trams, and buses.
  • C. S-Bahn Hamburg GmbH
    S-Bahn Hamburg GmbH is the company that operates Hamburg’s suburban rapid transit rail network within the German railway system.
  • D. Abellio Rail Mitteldeutschland
    Abellio Rail Mitteldeutschland is a German regional railway operator providing passenger train services in the central Germany area.
  • E. Berlin S-Bahn
    The Berlin S-Bahn is a rapid transit railway network serving Berlin and its surrounding areas, integrating suburban and urban rail services across the metropolitan region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f6c2e881909a228fdcfeb7c7d3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e53ac288190b27fe8064fb576c2 completed April 29, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:59 p.m.