Triple

T427800
Position Surface form Disambiguated ID Type / Status
Subject Chemnitz Hauptbahnhof E9646 entity
Predicate railwayNetwork P522 FINISHED
Object Deutsche Bahn network E22662 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: Deutsche Bahn network | Statement: [Chemnitz Hauptbahnhof, railwayNetwork, Deutsche Bahn network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deutsche Bahn network
Context triple: [Chemnitz Hauptbahnhof, railwayNetwork, Deutsche Bahn network]
  • A. Deutsche Bahn chosen
    Deutsche Bahn is Germany's state-owned national railway company and one of the largest rail and logistics operators in Europe.
  • B. Berlin S-Bahn
    The Berlin S-Bahn is a rapid transit railway network serving Berlin and its surrounding areas, integrating suburban and urban rail services across the metropolitan region.
  • C. Rhine Railway
    The Rhine Railway is a major railway line in Western Europe that connects key cities along the Rhine corridor, facilitating both international passenger and freight transport.
  • D. Thalys
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • E. RegioExpress
    RegioExpress is a category of Swiss regional express trains that provide relatively fast, limited-stop connections between major and medium-sized 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2eed7f3508190995dcd39586ed614 completed Feb. 28, 2026, 1:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69a431df41888190b643fd3cf0d20a09 completed March 1, 2026, 12:32 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.