Triple

T5313222
Position Surface form Disambiguated ID Type / Status
Subject DB Regio E119083 entity
Predicate parentOrganization P254 FINISHED
Object Deutsche Bahn E22662 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: Deutsche Bahn | Statement: [DB Regio, parentOrganization, Deutsche Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deutsche Bahn
Context triple: [DB Regio, parentOrganization, Deutsche Bahn]
  • A. Deutsche Bahn chosen
    Deutsche Bahn is Germany's state-owned national railway company and one of the largest rail and logistics operators in Europe.
  • B. Deutsche Reichsbahn
    Deutsche Reichsbahn was the state-owned railway company of Germany for much of the 20th century, operating the national rail network before its functions were absorbed into the modern Deutsche Bahn.
  • C. ÖBB
    ÖBB is Austria’s national railway company, operating most of the country’s passenger and freight train services across domestic and international routes.
  • D. S-Bahn Berlin GmbH
    S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
  • E. Dresden Railway
    The Dresden Railway is a major German rail line connecting Berlin with Dresden, serving as an important north–south passenger and freight corridor.
  • 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8536c06c81908ef8ba8c39b4fa30 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4114c120819098c2fcc7d1357441 completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 1:54 p.m.