Triple

T3564946
Position Surface form Disambiguated ID Type / Status
Subject Anthony Barra E75423 entity
Predicate spouseEmployer P26554 FINISHED
Object General Motors E506 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: General Motors | Statement: [Anthony Barra, spouseEmployer, General Motors]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: General Motors
Context triple: [Anthony Barra, spouseEmployer, General Motors]
  • A. General Motors chosen
    General Motors is a major American multinational automotive manufacturer known for brands such as Chevrolet, GMC, Cadillac, and Buick.
  • B. Ford Motor Company
    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.
  • C. Ford
    Ford is a common English surname borne by numerous notable individuals, including U.S. President Gerald Ford.
  • D. Chevrolet
    Chevrolet is a major American automobile marque known for producing a wide range of affordable cars, trucks, and SUVs.
  • E. American Motors Corporation
    American Motors Corporation was a major American automobile manufacturer best known for producing compact cars and later spawning the AM General division that built military and utility vehicles.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0a8f6288190928479f5bea32245 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48825d5a08190b57407b660fb5954 completed March 13, 2026, 9:56 p.m.
Created at: March 8, 2026, 3:21 p.m.