Triple

T13489324
Position Surface form Disambiguated ID Type / Status
Subject Berlin S-Bahn fare zone B E318591 entity
Predicate appliesTo P1129 FINISHED
Object U-Bahn Berlin E144841 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: U-Bahn Berlin | Statement: [Berlin S-Bahn fare zone B, appliesTo, U-Bahn Berlin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: U-Bahn Berlin
Context triple: [Berlin S-Bahn fare zone B, appliesTo, U-Bahn Berlin]
  • A. Berlin U-Bahn chosen
    The Berlin U-Bahn is the German capital’s extensive underground rapid transit system, forming a core part of its public transportation network.
  • 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. 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.
  • D. U-Bahn
    The U-Bahn is an urban rapid transit metro system commonly found in German-speaking cities, featuring high-frequency electric trains running on dedicated tracks both underground and above ground.
  • E. Hamburg U-Bahn
    The Hamburg U-Bahn is the rapid transit metro system serving the city of Hamburg, Germany, and its surrounding areas.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf3cbe2081908c6792362c67c8f1 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7942668f481909c6d892fdfd32c02 completed May 3, 2026, 6:29 p.m.
Created at: April 9, 2026, 9:43 p.m.