Triple

T5313366
Position Surface form Disambiguated ID Type / Status
Subject S-Bahn E119085 entity
Predicate hasSystem P730 FINISHED
Object Rhine-Ruhr S-Bahn E236408 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: Rhine-Ruhr S-Bahn | Statement: [S-Bahn, hasSystem, Rhine-Ruhr S-Bahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rhine-Ruhr S-Bahn
Context triple: [S-Bahn, hasSystem, Rhine-Ruhr S-Bahn]
  • A. Rhine-Ruhr S-Bahn chosen
    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.
  • B. Rhine-Main S-Bahn
    The Rhine-Main S-Bahn is a suburban rapid transit network serving the Frankfurt Rhine-Main metropolitan region in Germany, connecting Frankfurt with its surrounding cities and suburbs.
  • C. Hamburg S-Bahn
    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.
  • D. S-Bahn
    The S-Bahn is a German urban and suburban rapid transit rail system that connects city centers with surrounding metropolitan regions.
  • E. S-Bahn Nuremberg
    S-Bahn Nuremberg is a regional suburban rail network serving Nuremberg and its surrounding metropolitan area 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8536c06c81908ef8ba8c39b4fa30 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4114c120819098c2fcc7d1357441 completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 1:54 p.m.