Triple

T20771966
Position Surface form Disambiguated ID Type / Status
Subject S-Bahn Hamburg GmbH E511257 entity
Predicate abbreviation P43 FINISHED
Object S-Bahn Hamburg NE NERFINISHED

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: S-Bahn Hamburg | Statement: [S-Bahn Hamburg GmbH, abbreviation, S-Bahn Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn Hamburg
Context triple: [S-Bahn Hamburg GmbH, abbreviation, S-Bahn Hamburg]
  • A. Hamburg S-Bahn chosen
    The Hamburg S-Bahn is a rapid transit and commuter rail network serving the city of Hamburg and its surrounding metropolitan region in northern Germany.
  • B. Hamburg U-Bahn
    The Hamburg U-Bahn is the rapid transit metro system serving the city of Hamburg, Germany, and its surrounding areas.
  • 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. Hanover Stadtbahn
    The Hanover Stadtbahn is a light rail and tram system serving the city of Hanover, Germany, providing high-capacity urban and suburban public transport through a network of surface and underground lines.
  • E. Rhine-Ruhr S-Bahn
    The Rhine-Ruhr S-Bahn is a regional rapid transit network serving the densely populated Rhine-Ruhr metropolitan area in western Germany, connecting major cities such as Duisburg, Düsseldorf, Essen, and Dortmund.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ca01148190ac018e57e0cab46f completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c2681ff88190bfe5938c2db6b2c4 completed April 21, 2026, 12:18 a.m.
Created at: April 16, 2026, 12:37 p.m.