Triple

T15730300
Position Surface form Disambiguated ID Type / Status
Subject S-Bahn line S26 E381324 entity
Predicate operator P179 FINISHED
Object S-Bahn Berlin GmbH E427342 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: S-Bahn Berlin GmbH | Statement: [S-Bahn line S26, 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: [S-Bahn line S26, 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 (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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb61cb881908b158609c1ccfa1e completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82fcb4e4819097bd0591bbcc3b71 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.