Triple

T15730264
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Heiligensee station E381323 entity
Predicate operatedBy P86 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: [Berlin-Heiligensee station, operatedBy, DB Station&Service]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DB Station&Service
Context triple: [Berlin-Heiligensee station, operatedBy, 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_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.