Triple

T17127586
Position Surface form Disambiguated ID Type / Status
Subject Nürnberg-Steinbühl station E415637 entity
Predicate operator P179 FINISHED
Object DB Station&Service E54321 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: DB Station&Service | Statement: [Nürnberg-Steinbühl station, operator, DB Station&Service]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DB Station&Service
Context triple: [Nürnberg-Steinbühl station, operator, DB Station&Service]
  • A. DB Station&Service chosen
    DB Station&Service is a subsidiary of Deutsche Bahn responsible for managing and operating railway stations across Germany.
  • B. NS Stations
    NS Stations is a Dutch company responsible for managing and developing railway stations and related facilities across the Netherlands.
  • C. Central station
    Central station is a major railway hub providing key train connections for travelers to and from Cambridge city center.
  • D. Central station
    Central station is a key Massachusetts Bay Transportation Authority (MBTA) subway stop on the Red Line located in Cambridge, Massachusetts, serving the Central Square area.
  • E. Kiest station
    Kiest station is a Dallas Area Rapid Transit (DART) light rail stop on the Green Line serving the Kiest Boulevard area in Dallas, Texas.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f027a3d081908fc1134b50db3d45 completed April 18, 2026, 8:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a145e7481909242aab69baeb7a0 completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:36 a.m.