Triple

T20172926
Position Surface form Disambiguated ID Type / Status
Subject 1996 Stock E492012 entity
Predicate manufacturer P490 FINISHED
Object Metro-Cammell 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: Metro-Cammell | Statement: [1996 Stock, manufacturer, Metro-Cammell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metro-Cammell
Context triple: [1996 Stock, manufacturer, Metro-Cammell]
  • A. Metro-Cammell chosen
    Metro-Cammell was a major British railway rolling stock manufacturer, best known for producing multiple generations of diesel and electric trains for the UK rail network.
  • B. Scammell
    Scammell is an English surname borne by various notable individuals, including figures in American Revolutionary history and British industry.
  • C. D. Napier & Son
    D. Napier & Son was a British engineering company best known for producing high-performance aircraft engines and automotive components in the early to mid-20th century.
  • D. Armstrong Siddeley
    Armstrong Siddeley was a British engineering company best known for manufacturing luxury automobiles and aircraft engines in the early to mid-20th century.
  • E. Vosper Ltd
    Vosper Ltd was a British shipbuilding and marine engineering company best known for designing and constructing fast naval craft such as motor torpedo boats and patrol boats.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e66849709c81909b65b421282f9f3b completed April 20, 2026, 5:54 p.m.
Created at: April 11, 2026, 11:35 p.m.