Triple

T6358369
Position Surface form Disambiguated ID Type / Status
Subject Berlin public transport network E143047 entity
Predicate includesMode P1393 FINISHED
Object S-Bahn E119085 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 | Statement: [Berlin public transport network, includesMode, S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn
Context triple: [Berlin public transport network, includesMode, S-Bahn]
  • A. S-Bahn chosen
    The S-Bahn is a German urban and suburban rapid transit rail system that connects city centers with surrounding metropolitan regions.
  • B. Berlin S-Bahn
    The Berlin S-Bahn is a rapid transit railway network serving Berlin and its surrounding areas, integrating suburban and urban rail services across the metropolitan region.
  • C. Rhine-Ruhr S-Bahn
    The Rhine-Ruhr S-Bahn is a regional rapid transit network serving the densely populated Rhine-Ruhr metropolitan area in western Germany, connecting major cities such as Duisburg, Düsseldorf, Essen, and Dortmund.
  • 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. Munich S-Bahn
    The Munich S-Bahn is a rapid transit and commuter rail network serving Munich and its surrounding metropolitan region in Bavaria, Germany.
  • 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_69c008d7a9c4819098d647ec47776917 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c067f5bdd481909cf9db595ddb27df completed March 22, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a5cf7008190a24ecfeab5acb583 completed March 28, 2026, 12:01 a.m.
Created at: March 22, 2026, 4:32 p.m.