Triple

T12191785
Position Surface form Disambiguated ID Type / Status
Subject Eidelstedt station E290480 entity
Predicate operator P179 FINISHED
Object S-Bahn Hamburg GmbH E511257 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 Hamburg GmbH | Statement: [Eidelstedt station, operator, S-Bahn Hamburg GmbH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S-Bahn Hamburg GmbH
Context triple: [Eidelstedt station, operator, S-Bahn Hamburg GmbH]
  • A. S-Bahn Hamburg GmbH chosen
    S-Bahn Hamburg GmbH is the company that operates Hamburg’s suburban rapid transit rail network within the German railway system.
  • B. Üstra Hannoversche Verkehrsbetriebe
    Üstra Hannoversche Verkehrsbetriebe is the main public transport company in Hanover, Germany, operating the city’s trams and buses.
  • C. S-Bahn Berlin GmbH
    S-Bahn Berlin GmbH is the company responsible for operating Berlin’s urban rapid transit S-Bahn rail network.
  • D. Hamburg S-Bahn
    The Hamburg S-Bahn is a rapid transit and commuter rail network serving the city of Hamburg and its surrounding metropolitan region in northern Germany.
  • E. Abellio Rail Mitteldeutschland
    Abellio Rail Mitteldeutschland is a German regional railway operator providing passenger train services in the central Germany area.
  • 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_69d6ab64de5881908d56eb7a75c6cc69 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c54a4648190ad0f84c229534155 completed April 10, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a8d24508190b0a60ca76d775b1e completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:50 p.m.