Triple

T6725699
Position Surface form Disambiguated ID Type / Status
Subject Brandenburger Tor S-Bahn station E153510 entity
Predicate partOf P40 FINISHED
Object Berlin S-Bahn E26713 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: Berlin S-Bahn | Statement: [Brandenburger Tor S-Bahn station, partOf, Berlin S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin S-Bahn
Context triple: [Brandenburger Tor S-Bahn station, partOf, Berlin S-Bahn]
  • A. Berlin S-Bahn chosen
    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.
  • B. Berlin Stadtbahn
    Berlin Stadtbahn is a major elevated east–west railway corridor in Berlin that carries S-Bahn and regional trains through the city’s central districts.
  • C. Berlin U-Bahn
    The Berlin U-Bahn is the German capital’s extensive underground rapid transit system, forming a core part of its public transportation network.
  • D. S-Bahn Ringbahn
    The S-Bahn Ringbahn is Berlin’s circular urban rail line that loops around the inner city, connecting numerous districts and major transport hubs.
  • 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_69c6880afb988190ad88011b48ecfcba completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d15131f08190aba6c00943c51331 completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c845cc4f748190a666ab40b183cb3a completed March 28, 2026, 9:19 p.m.
Created at: March 27, 2026, 2:08 p.m.