Triple

T433587
Position Surface form Disambiguated ID Type / Status
Subject Ford Blue E9764 entity
Predicate brand P1500 FINISHED
Object Ford E1133 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: Ford | Statement: [Ford Blue, brand, Ford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ford
Context triple: [Ford Blue, brand, Ford]
  • A. Ford Motor Company chosen
    Ford Motor Company is a major American automobile manufacturer, founded by Henry Ford, known for pioneering assembly-line mass production and producing iconic vehicles like the Model T and F-Series trucks.
  • B. General Motors
    General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
  • C. Chevrolet
    Chevrolet is a major American automobile marque known for producing a wide range of affordable cars, trucks, and SUVs.
  • D. Buick
    Buick is an American automobile marque known for producing upscale, comfort-oriented vehicles positioned between mainstream and luxury brands.
  • E. Ford Blue
    Ford Blue is a Ford Motor Company division focused on traditional internal-combustion and hybrid vehicles, emphasizing the brand’s legacy nameplates and mainstream models.
  • 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_69a2ef084840819080653004b674cba8 completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a47d2668348190a654c9e0c7bf10a1 completed March 1, 2026, 5:53 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.