Triple

T4628243
Position Surface form Disambiguated ID Type / Status
Subject Ford Field E101150 entity
Predicate sponsor P67 FINISHED
Object Ford Motor Company 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 Motor Company | Statement: [Ford Field, sponsor, Ford Motor Company]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ford Motor Company
Context triple: [Ford Field, sponsor, Ford Motor Company]
  • 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. Ford
    Ford is a town in the Metropolitan Borough of Sefton, Merseyside, England, forming part of the northern suburbs of Liverpool.
  • D. Ford
    Ford is a common English surname borne by numerous notable individuals, including U.S. President Gerald Ford.
  • E. Toyota Motor Corporation
    Toyota Motor Corporation is a Japanese multinational automaker renowned for its reliable vehicles, pioneering of lean manufacturing and the Toyota Production System, and global leadership in hybrid technology.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a2e9780819081add547c760abc9 completed March 20, 2026, 2:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c7add98819089fbff1a21a19e28 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:13 p.m.