Triple

T5193547
Position Surface form Disambiguated ID Type / Status
Subject Stuttgart S-Bahn E117213 entity
Predicate abbreviation P43 FINISHED
Object S-Bahn Stuttgart E117213 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: S-Bahn Stuttgart | Statement: [Stuttgart S-Bahn, abbreviation, S-Bahn Stuttgart]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S-Bahn Stuttgart
Context triple: [Stuttgart S-Bahn, abbreviation, S-Bahn Stuttgart]
  • A. Stuttgart S-Bahn chosen
    The Stuttgart S-Bahn is a rapid transit and commuter rail network serving Stuttgart and its surrounding region in the German state of Baden-Württemberg.
  • B. Stuttgart Stadtbahn
    The Stuttgart Stadtbahn is a light rail and tram system serving the city of Stuttgart and its surrounding metropolitan area in Germany.
  • 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. S-Bahn Nuremberg
    S-Bahn Nuremberg is a regional suburban rail network serving Nuremberg and its surrounding metropolitan area in Bavaria, Germany.
  • 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 (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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd79f142488190bc6c57b8ff7ef894 completed March 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee09743e08190a3a73fb410a6f124 completed March 21, 2026, 6:16 p.m.
Created at: March 20, 2026, 1:46 p.m.