Triple

T11231930
Position Surface form Disambiguated ID Type / Status
Subject Olympiastadion S-Bahn station E265842 entity
Predicate railNetwork P522 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: [Olympiastadion S-Bahn station, railNetwork, Berlin S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin S-Bahn
Context triple: [Olympiastadion S-Bahn station, railNetwork, 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9026e1c81909456ac946bbba972 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc4c630c8190a5e43c2108dfb50d completed April 19, 2026, 12:36 p.m.
Created at: April 8, 2026, 9:30 p.m.