Triple

T19370946
Position Surface form Disambiguated ID Type / Status
Subject British Rail Class 365 E484533 entity
Predicate laterOperator P5677 FINISHED
Object WAGN 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: WAGN | Statement: [British Rail Class 365, laterOperator, WAGN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WAGN
Context triple: [British Rail Class 365, laterOperator, WAGN]
  • A. WAGN chosen
    WAGN (West Anglia Great Northern) was a former British train operating company that ran commuter and regional passenger rail services from London to destinations in East Anglia and the north of London before the franchise was restructured.
  • B. Wagner
    Wagner is a common Portuguese given name, notably borne by Brazilian actor and filmmaker Wagner Moura.
  • C. Wagner
    Wagner is a Federal-Mogul automotive parts brand best known for its replacement brake components and lighting products.
  • D. Wagner
    Wagner is a surname most famously associated with Honus Wagner, one of the greatest early baseball players in Major League history.
  • E. In Search of Wagner
    In Search of Wagner is a critical study by Theodor W. Adorno that offers a penetrating philosophical and sociological analysis of Richard Wagner’s music, aesthetics, and cultural legacy.
  • 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619b09ef08190a8b420316c0b8eb3 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.