Triple

T6173964
Position Surface form Disambiguated ID Type / Status
Subject S-Bahn station Berlin Grunewald E137772 entity
Predicate servedBy P82 FINISHED
Object S7 line E464113 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: S7 line | Statement: [S-Bahn station Berlin Grunewald, servedBy, S7 line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S7 line
Context triple: [S-Bahn station Berlin Grunewald, servedBy, S7 line]
  • A. S7 line
    The S7 line is a suburban railway service of the Zürich S-Bahn network that connects the city of Zürich with surrounding municipalities along Lake Zürich.
  • B. S7 line chosen
    The S7 line is a Berlin S-Bahn railway service that runs east–west across the city, connecting key districts and suburbs as part of the German capital’s urban transit network.
  • C. S1 (Munich S-Bahn)
    S1 (Munich S-Bahn) is a suburban railway line in the Munich S-Bahn network that connects central Munich with Munich Airport and surrounding areas.
  • D. S6 line
    The S6 line is a suburban railway service of the Zürich S-Bahn network that connects the city of Zürich with surrounding regional areas.
  • E. S6 line
    The S6 line is a route of the Rhine-Main S-Bahn network serving the Frankfurt metropolitan area and connecting central Frankfurt with surrounding suburbs and towns.
  • 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_69c008a68c508190a8d78245c865960e completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d94c47481909745b2533926a1ca completed March 22, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141b200788190bd8d968edba53e5f completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:18 p.m.