Triple

T11467227
Position Surface form Disambiguated ID Type / Status
Subject Munich U-Bahn E271808 entity
Predicate hasInterchangeWith P1018 FINISHED
Object Munich S-Bahn E507939 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: Munich S-Bahn | Statement: [Munich U-Bahn, hasInterchangeWith, Munich S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Munich S-Bahn
Context triple: [Munich U-Bahn, hasInterchangeWith, Munich S-Bahn]
  • A. Munich S-Bahn chosen
    The Munich S-Bahn is a rapid transit and commuter rail network serving Munich and its surrounding metropolitan region in Bavaria, Germany.
  • B. Munich U-Bahn
    The Munich U-Bahn is the German city's rapid transit metro system, forming a core part of its public transportation network with multiple underground lines serving urban and suburban areas.
  • C. Munich S-Bahn trunk line
    The Munich S-Bahn trunk line is the central underground rail corridor that carries most S-Bahn routes through Munich’s city center, forming the backbone of the regional rapid transit network.
  • D. S-Bahn Nuremberg
    S-Bahn Nuremberg is a regional suburban rail network serving Nuremberg and its surrounding metropolitan area in Bavaria, Germany.
  • E. 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.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f74144819094479690c8151073 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e9429a308190810b485708d28617 completed April 20, 2026, 8:52 a.m.
Created at: April 8, 2026, 9:35 p.m.