Triple

T9749717
Position Surface form Disambiguated ID Type / Status
Subject Rhine-Ruhr S-Bahn E236408 entity
Predicate primaryHub P394 FINISHED
Object Dortmund Hauptbahnhof E635884 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: Dortmund Hauptbahnhof | Statement: [Rhine-Ruhr S-Bahn, primaryHub, Dortmund Hauptbahnhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dortmund Hauptbahnhof
Context triple: [Rhine-Ruhr S-Bahn, primaryHub, Dortmund Hauptbahnhof]
  • A. Dortmund Hauptbahnhof chosen
    Dortmund Hauptbahnhof is the main railway station and central transportation hub of the city of Dortmund in Germany.
  • B. Düsseldorf Hauptbahnhof
    Düsseldorf Hauptbahnhof is the main railway station of Düsseldorf and a major regional and long-distance transport hub in western Germany.
  • C. Duisburg Hauptbahnhof
    Duisburg Hauptbahnhof is the central railway station and major transportation hub serving the city of Duisburg in western Germany.
  • D. Wuppertal Hauptbahnhof
    Wuppertal Hauptbahnhof is the main railway station and central transport hub of the city of Wuppertal in western Germany.
  • E. Bonn Hauptbahnhof
    Bonn Hauptbahnhof is the central railway station of Bonn, Germany, serving as a key regional and long-distance transport hub with extensive connections across the Rhine-Ruhr area and beyond.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f6a2f8c8190a6f6af6587ee90b8 completed April 1, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c40da67c8190b9a0193e9b04fedd completed April 5, 2026, 2:08 a.m.
Created at: March 30, 2026, 8:24 p.m.