Triple

T514253
Position Surface form Disambiguated ID Type / Status
Subject BMW E10671 entity
Predicate subsidiary P258 FINISHED
Object BMW Motorrad E10671 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: BMW Motorrad | Statement: [BMW, subsidiary, BMW Motorrad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BMW Motorrad
Context triple: [BMW, subsidiary, BMW Motorrad]
  • A. BMW chosen
    BMW is a German luxury automobile and motorcycle manufacturer renowned for its performance-oriented vehicles and engineering.
  • B. Harley-Davidson
    Harley-Davidson is an iconic American motorcycle manufacturer renowned for its heavyweight cruiser bikes, distinctive V-twin engines, and strong biker subculture.
  • C. Ducati
    Ducati is an Italian motorcycle manufacturer renowned for its high-performance sport bikes, racing heritage, and distinctive design.
  • D. Kawasaki
    Kawasaki is a major industrial and residential city in Kanagawa Prefecture, Japan, located between Tokyo and Yokohama along the Tama River.
  • E. BMW 132
    The BMW 132 was a German nine-cylinder air-cooled radial aircraft engine widely used in Luftwaffe bombers and transport aircraft during the 1930s and World War II.
  • 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_69a2e84a0d08819087e01863fcd9abf1 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1824a248190808591ab3ece7dff completed Feb. 28, 2026, 1:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4b23bf69481908db3a0f3de8c2bf1 completed March 1, 2026, 9:40 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.