Triple

T3848826
Position Surface form Disambiguated ID Type / Status
Subject Berlin-Schöneberg station E85239 entity
Predicate railwayLineServed P848 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: [Berlin-Schöneberg station, railwayLineServed, Berlin S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin S-Bahn
Context triple: [Berlin-Schöneberg station, railwayLineServed, 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 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.
  • C. S-Bahn
    The S-Bahn is a German urban and suburban rapid transit rail system that connects city centers with surrounding metropolitan regions.
  • D. Frankfurt U-Bahn
    The Frankfurt U-Bahn is the rapid transit system serving Frankfurt am Main, Germany, forming a core part of the city's public transportation network with multiple underground and surface lines.
  • E. 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.
  • 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_69aed936de1c81908f91bed80f70abb2 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeebcde86081908cf3840ae002acfa completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d03dbd348190aaaa58a352982248 completed March 14, 2026, 9:16 p.m.
Created at: March 9, 2026, 3:19 p.m.