Triple

T6475121
Position Surface form Disambiguated ID Type / Status
Subject Berlin tram E146051 entity
Predicate operator P179 FINISHED
Object Berliner Verkehrsbetriebe E71401 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: Berliner Verkehrsbetriebe | Statement: [Berlin tram, operator, Berliner Verkehrsbetriebe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berliner Verkehrsbetriebe
Context triple: [Berlin tram, operator, Berliner Verkehrsbetriebe]
  • A. Berliner Verkehrsbetriebe chosen
    Berliner Verkehrsbetriebe is Berlin’s main public transport company, operating the city’s extensive network of U-Bahn trains, trams, and buses.
  • B. S-Bahn Berlin GmbH
    S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
  • C. Verkehrsverbund Berlin-Brandenburg
    Verkehrsverbund Berlin-Brandenburg is the integrated public transport authority that coordinates and manages fares and services across Berlin and the surrounding Brandenburg region.
  • D. Basler Verkehrs-Betriebe
    Basler Verkehrs-Betriebe is the main public transport company of Basel, Switzerland, operating the city’s tram and bus services.
  • E. 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.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a341360819082f2b5496a1a68b0 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70060c7788190aab7ca88615d6e71 completed March 27, 2026, 10:10 p.m.
Created at: March 22, 2026, 4:50 p.m.